Post on 16-May-2022
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ACADEMIC ENTREPRENEURSHIP IN A RESOURCE
CONSTRAINED ENVIRONMENT
A thesis submitted to The University of Manchester for the degree of
Doctor of Philosophy (PhD)
in the Faculty of Humanities
2012
LASANDAHASI RANMUTHUMALIE DE SILVA
MANCHESTER BUSINESS SCHOOL
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Table of Contents List of Tables ............................................................................................................................ 7
List of Figures ........................................................................................................................... 9
List of Abbreviations ............................................................................................................. 10
Abstract ................................................................................................................................... 11
Declaration .............................................................................................................................. 12
Copyright Statement .............................................................................................................. 12
Acknowledgements ................................................................................................................. 14
The Author .............................................................................................................................. 15
Chapter 1: Introduction ........................................................................................................ 18
1.1. Specific Objectives .................................................................................................... 19
1.2. The Structure of the Thesis ....................................................................................... 21
Chapter 2: A Resource Constrained Environment ............................................................. 25
2.1. Academic Entrepreneurship in Resource Constrained Environments ...................... 25
2.2. An Overview of Sri Lankan Economy ...................................................................... 28
2.2.1. Financial Resource States in Sri Lanka .............................................................. 29
2.2.2. Human Resources in Sri Lanka .......................................................................... 31
2.2.3. Technological Resources in Sri Lanka ............................................................... 32
2.2.4. Institutional and Policy Framework in Sri Lanka ............................................... 35
2.2.5. Physical Infrastructure in Sri Lanka ................................................................... 37
2.3. Chapter Summary ...................................................................................................... 38
Chapter 3: Academic Entrepreneurship: A Review of the Literature.............................. 41
3.1. The Definition of Entrepreneurship .......................................................................... 41
3.2. The Definition of Academic Entrepreneurship ......................................................... 43
3.2.1. Defining Academic Entrepreneurship: The Focused View ................................ 43
3.2.2. A Definition of Academic Entrepreneurship: The Broader View ...................... 46
3.2.3. The Definition of Academic Entrepreneurship for this Study ............................ 48
3.3. Academic Entrepreneurial Engagement in a Resource Constrained Environment ... 50
3.4. Multiple Academic Entrepreneurial Activities carried out by Academic
Entrepreneurs .................................................................................................................... 52
3.5. Synergistic Effects of Diversifying Academic Entrepreneurial Activities................ 54
3.6. Academic Motivation ................................................................................................ 55
3.7. Multi-level Factors affecting the Nature of Academic Entrepreneurial Engagement
.......................................................................................................................................... 58
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3.7.1. Academic Entrepreneur and Academic Entrepreneurship .................................. 59
3.7.2. The Environmental Context of Academic Entrepreneur .................................... 65
3.8. The Impacts of Academic Entrepreneurship ............................................................. 70
3.9. Barriers to Academic Entrepreneurship .................................................................... 72
3.10. Chapter Summary .................................................................................................... 73
Chapter 4: Research Hypotheses .......................................................................................... 76
4.1. Investigating the ‘Plural activity’ of Academic Entrepreneurs in a Resource
Constrained Environment ................................................................................................. 76
4.2. Investigating the Motivation of Academic Entrepreneurs in a Resource Constrained
Environment ..................................................................................................................... 81
4.3. The Influence of Multilevel Factors on the ‘Plural Activity’ of Academic
Entrepreneurs in a Resource Constrained Environment ................................................... 84
4.4. The Impacts of Academic Engagement in Entrepreneurial Activities in a Resource
Constrained Environment ................................................................................................. 91
Chapter 5: Research Methodology ....................................................................................... 95
5.1. Research Philosophy ................................................................................................. 95
5.2. The Mixed Method Design ........................................................................................ 98
5.3. The Initial Data Gathering Stage ............................................................................... 99
5.4. The Survey and Qualitative Data Gathering Phase ................................................. 100
5.4.1. Sampling Strategy – The Survey and Qualitative Data Gathering Phase ......... 100
5.4.2. Data Collection and Data Analysis – The Survey and Qualitative Data gathering
Phases.......................................................................................................................... 107
5.5. The Characteristics of Respondents ........................................................................ 122
5.6. An Overview of Academic Entrepreneurial Engagement ....................................... 123
5.7. Chapter Summary .................................................................................................... 125
Chapter 6: The ‘Plural Activities’ of Academic Entrepreneurs operating in a
Resource Constrained Environment .................................................................................. 127
6.1. Academic Entrepreneurship in a Resource Constrained Environment ................... 127
6.2. Analysis: Academic Entrepreneurial Engagement in a Resource Constrained
Environment ................................................................................................................... 128
6.2.1. Teaching related Academic Entrepreneurial Activities .................................... 132
6.2.2. Research related Academic Entrepreneurial Activities .................................... 132
6.3. Analysis: ‘Plural activity’ and Synergistic Effects .................................................. 134
6.3.1. The Synergistic Effect on Social Networks ...................................................... 134
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6.3.2. Synergistic Effects on Knowledge and Skills ................................................... 137
6.3.3. Synergistic Effects and their Impacts on Input-output flows ........................... 139
6.3.4. Synergistic Effects on Physical Resources ....................................................... 139
6.4. Analysis: The ‘Plural activity’ of Academic Entrepreneurs: An Emergent Strategy to
Extract Values from Resource Constrained Environments ............................................ 142
6.5. Chapter Summary .................................................................................................... 145
Chapter 7: The Motivations of Academic Entrepreneurs operating in a Resource
Constrained Environment ................................................................................................... 147
7.1. The Motivations of Academic Entrepreneurs.......................................................... 147
7.2. Analysis: The ‘Plural Activity’ and Motivations of Academic Entrepreneurs ....... 148
7.2.1. Push Motives that have no Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs ............................................................................................. 149
7.2.2. Push Motives that have a Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs ............................................................................................. 150
7.2.3. Pull Motives that have no Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs ............................................................................................. 151
7.2.4. Pull Motives that have a Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs ............................................................................................. 153
7.3. Analysis: Dynamisms in Entrepreneurial Motivation ............................................. 155
7.3.1. Dynamism in Entrepreneurial Motivation: Single Role Academic Entrepreneurs
.................................................................................................................................... 156
7.3.2. Dynamism in Entrepreneurial Motivation: Double Role Academic
Entrepreneurs .............................................................................................................. 156
7.3.3. Dynamism in Entrepreneurial Motivation: Triple Role Academic Entrepreneurs
.................................................................................................................................... 158
7.4. Chapter Summary .................................................................................................... 161
Chapter 8: The Influence of Multilevel Factors on the ‘Plural Activities’ of Academic
Entrepreneurs operating in a Resource Constrained Environment ............................... 164
8.1. The Influence of Multilevel Factors on Academic Entrepreneurship ..................... 164
8.2. Analysis: The Relationship between the Personal Characteristics, and ‘Plural
activities’, of Academic Entrepreneurs .......................................................................... 166
8.2.1. The Relationship between the Age and Position, and ‘Plural activities’ of
Academic Entrepreneurs ............................................................................................. 166
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8.2.2. The Relationship between the Gender, and ‘Plural activities’, of Academic
Entrepreneurs .............................................................................................................. 169
8.2.3. The Relationship between the Discipline, and ‘Plural activities’, of Academic
Entrepreneurs .............................................................................................................. 171
8.2.4. The Relationship between the Educational Level, and ‘Plural activities’, of
Academic Entrepreneurs ............................................................................................. 175
8.2.5. The Relationship between the Business Management and Entrepreneurial
Knowledge and Skills, and ‘Plural activities’, of Academic Entrepreneurs ............... 176
8.2.6. The Relationship between the Social Network and Skills, and ‘Plural activities’,
of Academic Entrepreneurs ........................................................................................ 179
8.3. Analysis: The Relative Influence of Meso and Micro Level Factors on the ‘Plural
activities’ of Academic Entrepreneurs: A Multi-level Analysis .................................... 181
8.4. Analysis: The Relationship between the Perceived Quality of Universities and
‘Plural Activities’ ........................................................................................................... 182
8.5. Analysis: An Aggregated Model: Factors Affecting the ‘Plural Activities’ of
Academic Entrepreneurs ................................................................................................ 183
8.6. Analysis: University, Industry, and Government Interactions ................................ 187
8.6.1. Reasons for University Industry Interactions ................................................... 187
8.6.2. The Role of Government .................................................................................. 189
8.7. Chapter Summary .................................................................................................... 190
Chapter 9: The Impacts of Academic Entrepreneurial Engagement in a Resource
Constrained Environment ................................................................................................... 193
9.1. The Impacts of Academic Entrepreneurial Engagement ......................................... 193
9.2. Analysis: The Impacts of Academic Entrepreneurship on Normal Academics Duties
........................................................................................................................................ 195
9.3. Analysis: The Positive Impacts of Academic Entrepreneurship on Normal Academic
Duties .............................................................................................................................. 198
9.3.1. The Positive Impacts of Academic Entrepreneurship on the Normal Academic
Duties of Single Role Academic Entrepreneurs ......................................................... 198
9.3.2. The Positive Impacts of Academic Entrepreneurship on the Normal Academic
Duties of Double Role Academic Entrepreneurs ........................................................ 199
9.3.3. The Positive Impacts of Academic Entrepreneurship on Normal Academic
Duties: Triple Role Academic Entrepreneurs ............................................................. 201
9.4. Analysis: The National Economic Importance of Academic Entrepreneurship ..... 204
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9.5. Chapter Summary .................................................................................................... 208
Chapter 10: Conclusions and Recommendations ............................................................. 211
10.1. Implications for Theory ......................................................................................... 214
10.1.1. Academic Entrepreneurship: Resource Constrained Environments vs. Resource
Rich Environments ..................................................................................................... 214
10.1.2. The ‘Plural Activities’ of Academic Entrepreneurs ....................................... 218
10.2. Implications for Policy .......................................................................................... 220
10.3. Limitations of the Study and Future Research Avenues ....................................... 225
References ............................................................................................................................. 227
Appendix 5.1: Initial Data Gathering ................................................................................ 243
Appendix 5.2: Sampling ...................................................................................................... 246
Appendix 5.3: Non-Response Bias of the on-line Survey ................................................ 247
Appendix 5.4: Survey Questionnaire ................................................................................. 249
Appendix 5.5: Questionnaire-In-depth Interviews ........................................................... 256
Appendix 8.1: Parameter Estimates: Triple role academic entrepreneur in
comparison to double role academic entrepreneur........................................................... 265
Appendix 8.2: Parameter Estimates: Double role academic entrepreneur in
comparison to single role academic entrepreneur ............................................................ 266
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List of Tables
Table 2.1: National Innovative Capacity Index.................................................. 27
Table 2.2: Worldwide Governance Indicators (WGI) in 2009........................... 37
Table 3.1: The Definition of Academic Entrepreneur........................................ 45
Table 3.2: Academic Entrepreneurial Activities................................................. 47
Table 4.1: Types of Academic Entrepreneurial Activities.................................. 80
Table 4.2: The ‘Plural activities’ of Academic Entrepreneurs............................ 81
Table 4.3: The Qualities of Universities affecting Academic Entrepreneurial
Endeavour..................................................................................................................
90
Table 4.4: Research Objectives and Hypotheses................................................ 95
Table 5.1: The Types of Data needed to achieve Research Objectives.............. 97
Table 5.2: Mixed Method Sampling Techniques................................................ 103
Table 5.3: Sampling – On-line Survey................................................................ 106
Table 5.4: Basis for the Sampling of Qualitative Data Gathering Stage............. 107
Table 5.5: Objective 1- Quantitative Data Analysis............................................ 112
Table 5.6: The Motivations of Academic Entrepreneurs.................................... 113
Table 5.7: Objective 2- Quantitative Data Analysis............................................ 114
Table 5.9: Objective 3- Hypothesis - 3.1- Quantitative Data Analysis............... 116
Table 5: 10: Objective 3 – Hypothesis 3.2- Quantitative Data Analysis............... 118
Table 5.11: Objective 3- Hypothesis 3.3- Quantitative Data Analysis................ 119
Table 5.12: Aspects on Normal Academic Duties ............................................. 120
Table 5:13: Objective 4- Quantitative Data Analysis.......................................... 123
Table 5.14: The Characteristics of Respondents ................................................ 124
Table 5.15: Academic’s Engagement in Academic Entrepreneurial Activities.. 125
Table 6.1: ‘Plural Activity’ types adopted by Academic Entrepreneurs –
Results........................................................................................................................
130
Table 6.2: Extent of engagement- Teaching related academic entrepreneurial
activities.....................................................................................................................
133
Table 6.3: The Extent of engagement- research related academic
entrepreneurial activities ...........................................................................................
134
Table 7.1: A Comparison of the Motives of Academic Entrepreneurs............... 150
Table 8.1: The Age of Academics........................................................................ 168
Table 8.2: The Position of Academics.................................................................
169
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Table 8.3: Academic Entrepreneurial Activities considered in the Promotion
Scheme......................................................................................................................
170
Table 8.4: The Gender of the Academic............................................................. 172
Table 8.5: The Discipline of the Academic........................................................ 174
Table 8.6: The Level of Education of the Academic.......................................... 177
Table 8.7: The Business Management Knowledge and Skills of the Academic 178
Table 8.8: The Effect of Entrepreneurial Knowledge and Skills of the
Academic....................................................................................................................
179
Table 8.9: Test for Unidimentionality................................................................. 181
Table 8.10: The Effect of Perceived Quality of University and Department........ 184
Table 8.11: Independent and Dependent Variables: Multinomial Logistic
Regression..................................................................................................................
186
Table 8.12: Likelihood Ratio Tests...................................................................... 187
Table 9.1: The Impacts of Academic Entrepreneurship on Normal Academics
Duties..........................................................................................................................
197
Table 9.2: The ‘plural activity’ of academic entrepreneurs and impacts on
normal academic duties..............................................................................................
198
Table 9.3: The Economic Outcomes of Academic Entrepreneurial
Engagement................................................................................................................
206
Table 9.4: Perceived Economic Importance Vs. The Type of Academic
Entrepreneurs..............................................................................................................
207
Table 10.1: Results- Research Hypotheses........................................................... 214
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List of Figures
Figure 1.1: The Layout of the Thesis................................................................. 24
Figure 2.1.1: GNI per capita (current US$) Income: without High Income
Countries..................................................................................................................
30
Figure 2.1.2: GNI per capita (current US$) Income: with High Income
Countries..................................................................................................................
30
Figure 2.2: Government Expenditure on Research and Development (as a %
of GDP)....................................................................................................................
31
Figure 2.3: Government Expenditure on University as a Percentage of GDP... 31
Figure 2.4: Researchers in Research and Development (per million people).... 32
Figure 2.5.1: High-technology Exports (% of manufactured exports): without
High Income Countries............................................................................................
33
Figure 2.5.2: High-technology Exports (% of manufactured exports): with High
Income Countries.....................................................................................................
33
Figure 2.6.1: The Number of Patent Applications by Residents: without High
Income Countries.....................................................................................................
34
Figure 2.6.2: The Number of Patent Applications by Residents: with High
Income Countries.....................................................................................................
34
Figure 2.7.1: Internet Users (per 100 people): without High Income Countries... 35
Figure 2.7.2: Internet Users (per 100 people): with High Income Countries........ 35
Figure 3.1: The Effect of Multi-level Factors on Academic Entrepreneurship... 59
Figure 3.2 : The Role of Government................................................................ 70
Figure 6.1: ‘Plural activities’ of Academic Entrepreneurs.................................. 135
Figure 6.2: Academic Entrepreneurship: Strategy to Extract Values from
Resource Constrained Environments.......................................................................
145
Figure 7.1: Dynamism in Academic Entrepreneurial Motivation...................... 162
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List of Abbreviations
EU: European Union
GDP: Gross Domestic Product
GEM: Global Entrepreneurship Monitor
GNI: Gross National Income
MIT: Massachusetts Institute of Technology
MoTR: Ministry of Technology and Research
NASTEC: National Science and Technology Commission
NIS: National Innovation System
NSC: National Science Council
OECD: Organisation for Economic Co-operation and Development
R & D: Research and Development
RAE: Research Assessment Exercise
TTO: Technology Transfer Offices
UK: United Kingdom
URE: University Research Enterprise
US: United States
WGI: Worldwide Governance Indicator
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Abstract University of Manchester
Lasandahasi Ranmuthumalie de Silva, Doctor of Philosophy (PhD) Academic Entrepreneurship in a Resource Constrained Environment
11.08.2012 Expectations regarding the contributions of academics to entrepreneurial activity in addition to their primary role of carrying out teaching and research have increased in recent years. Nevertheless, research on academic entrepreneurship has, to date, been carried out mainly in developed nations and there has been little emphasis on developing countries, particularly low income ones. Developing countries, when compared with developed nations, have been reported to face relatively high levels of resource scarcity that involve shortages of skills, finance, physical infrastructure, technology, and institutions needed for innovation and entrepreneurship. This gap in our knowledge leads to the main objective of this study, which is to investigate academic entrepreneurship in a resource constrained environment. Referring to the entrepreneurship and diversification literature, the current study argues that, as a strategy to extract value from a resource constrained environment, academic entrepreneurs may diversify their entrepreneurial engagements, which is named in this research as ‘plural activity’. In order to achieve the main objective, this thesis derives four specific objectives; namely, investigating the ‘plural activities’ of academic entrepreneurs, studying the motivations of academic entrepreneurs, examining the influence of multilevel causal factors on ‘plural activities’, and investigating the impacts of academic entrepreneurship on universities and wider economy.
Sequential mixed methods were adopted in three stages; namely, an initial context specific data gathering stage, an on-line survey, and in-depth interviews. Initial context specific data were used to design two subsequent data collection phases. This approach was believed to improve the construct validity of the study. The main purpose of the on-line survey was to obtain a broad understanding of the entrepreneurial engagements of academics, while that of in-depth interviews was to obtain detailed context specific data, required to achieve research objectives. This sequential mixed method design of a survey being followed up by in-depth interviews was also considered to improve the internal validity of this research.
The results suggested that entrepreneurial activity was a means of overcoming resource barriers in a resource constrained environment as opposed to resources are a means of becoming entrepreneurial in a resource rich environment. The majority of academic entrepreneurs had overcome resource and opportunity constraints by diversifying their entrepreneurial engagements. ‘Plural activity’ was found to generate synergies between multiple academic entrepreneurial activities. Diversifying into a greater number of different activities was found to generate more synergistic effects than diversifying into a limited number of similar activities. Nevertheless, there remained synergies between those who adopted different diversification strategies. Moreover, academic entrepreneurship was found to enable the overcoming of resource barriers to university teaching and research as well as deliver positive outcomes to universities and wider economy. Furthermore, it was evident that academics were initially motivated by ‘push’ motives and over time the influence of ‘push’ factors declined, while the impact of ‘pull’ motives increased. As a result of a lack of research capabilities of industry and funding for universities, there was a higher mutual interdependence between universities and industry. However, due to the unavailability of supportive mechanisms or formal institutional infrastructure to promote academic entrepreneurship, university-industry interactions were driven by individuals, and thus, were scattered and isolated. Policy implications and future research avenues were considered in conclusion.
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Declaration
No portion of the work referred in the thesis has been submitted in support of an
application for another degree or qualification of this or any other university or other
institute of learning
Copyright Statement
i. The author of this thesis (including any appendices and/or schedules to this thesis) owns
certain copyright or related rights in it (the “Copyright”) and s/he has given The University
of Manchester certain rights to use such Copyright, including for administrative purposes.
ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy,
may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as
amended) and regulations issued under it or, where appropriate, in accordance with
licensing agreements which the University has from time to time. This page must form
part of any such copies made.
iii. The ownership of certain Copyright, patents, designs, trademarks and other intellectual
property (the “Intellectual Property”) and any reproductions of copyright works in the
thesis, for example graphs and tables (“Reproductions”), which may be described in this
thesis, may not be owned by the author and may be owned by third parties. Such
intellectual Property and Reproductions cannot and must not be made available for use
without the prior written permission of the owner(s) of the relevant Intellectual Property
and/or Reproductions.
iv. Further information on the conditions under which disclosure, publication and
commercialisation of this thesis, the Copyright and any Intellectual Property and/or
Reproductions described in it may take place is available in the University IP Policy (see
http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487), in any relevant Thesis
restriction declarations deposited in the University Library, The University Library’s
regulations (see http://www.manchester.ac.uk/library/aboutus/regulations) and in The
University’s policy on Presentation of Theses
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I would like to dedicate this thesis to my family and teachers
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Acknowledgements
This Thesis would not have been possible without guidance, advice, support and
encouragement received from several individuals.
First and foremost, I would like to convey my sincere gratitude to my supervisors Prof.
Ray Oakey and Dr. Elvira Uyarra for invaluable guidance, advice and encouragement
provided throughout my PhD. I would also like to extend my deepest thank to Prof.
Jeremy Howells and Prof. Jakob Edler for offering me a PhD bursary and extremely
valuable advice and guidance. Furthermore, I would like to express my great gratitude to
Ms. Kate Barker and Prof. Philippe Laredo for continuous guidance and support, which
was of great value to shape my thesis. I would also like to thank all the members of staff of
the Manchester Institute of Innovation Research, who have been extremely friendly and
extended their support to shape my career as a young scholar of the institute.
My special thanks go to all my school and university (i.e. both undergraduate and
postgraduate) teachers who have shaped my career since I was a child, without which I
would not have been able to reach this stage.
I would also like to thank all the participants of the survey and in-depth interviews, without
their support I would not have been able to make original contributions in this thesis.
I would also like to extend my gratitude to Beatrice D’Ippolito and all of my PhD
colleagues for both academic and moral support.
Last but not least, I would like to thank my parents, Lionel De Silva and Malathimala
Alwis, husband, Shalika Siriwardhana, and all my relations and friends for moral support
and encouragement extended, without which this career path would not have been easy.
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The Author
The author, Ms. Lasandahasi Ranmuthumalie de Silva, graduated with a First Class
honours degree (in Economics and Business Management) in 2005, from the University of
Peradeniya, Sri Lanka, receiving the gold medal for the most outstanding performance. In
2007 she was awarded a Commonwealth Postgraduate Scholarship to pursue an MBA at
the Bradford University School of Management, for which she gained a Distinction and
also ‘Strategic Planning Society Prize’ for the best performance in Strategic Management.
In both of these degree programmes she specialised in Entrepreneurship. She enrolled in
the PhD programme at the Manchester Business School in 2008, for which she was offered
a bursary attached to the Eddie Davies Chair in Entrepreneurship and Innovation.
She has previous research experience in the disciplines of Entrepreneurship, Strategy, and
Innovations. She was a lecturer at the University of Peradeniya (2005-2007). She also
served as a Research Assistant at the Bradford University School of Management (2008-
2010) and the Manchester Business School (2009-2012). During that period she carried out
several research projects, which were funded by international funding bodies such as
European Commission, United States Department of Agriculture, International
Development Research Centre, Department of Enterprise, Trade and Investment-Northern
Ireland, Northwest Regional Development Agency-UK and GTZ. Her contribution to these
projects varied from applying for funding, collecting and analysing data to writing project
reports. During the last 3.5 years, she secured funding worth a total of approximately
£40,000 from sponsors such as Commonwealth Commission, Manchester Business School,
Northwest Regional Development Agency -UK, British Academy of Management, and
Research and Development Management.
Currently she is involved in the Channel Arc Manche Integrated Strategy project, which
has been initiated under the Arc Manche partnership and co-funded by the Interreg IVA.
She is responsible for achieving two visions, the main aim of which is to investigate how
to induce ‘Port Centric Cluster’ formation as a strategy to maximise productivity, reduce
congestion, and increase sustainability in the European Union. Her publications and
working papers are as follows:
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Refereed Book Chapters De Silva, L.R. Uyarra, Elvira and Oakey, Ray (2012). ‘Academic Entrepreneurship in a Resource Constrained Environment: Diversification and Synergistic Effects’ in Audretsch, D.B., Lehmann, E.E., Link, A.N., and Starnecker, A. (eds.) Technology Transfer in a
Global Economy. International Handbook Series on Entrepreneurship Acs, Zoltan and Audretsch, David (series eds.), Vol 6: Springer (In Press) De Silva, L.R. and Kodithuwakku, K.A.S.S. (2011).‘Pluriactivity, Entrepreneurship and Socio-economic Success of Farming Households’. in Gry Alsos, Sara Carter, Elisabet Ljunggren and Friederike Welter (eds). The Handbook of Research on Entrepreneurship in
Agriculture and Rural Development, Cheltenham: Edward Elgar Publishing Ltd, pp. 38-53. Refereed Full Papers De Silva, Ranmuthumalie and Wapshott. Robert The Dynamisms of Entrepreneurial Motivation: A Case of Academic Entrepreneurs in a Resource Constrained Environment (November 3, 2011). Manchester Business School Research Paper No. 617. Available at SSRN: http://ssrn.com/abstract=1954580 - revised and resubmitted to International Small
Business Journal (3*) Refereed Conference Publications De Silva, L.R. Uyarra, Elvira and Oakey, Ray (2012). ‘Academic Entrepreneurial Diversification in a Resource Constrained Environment’. British Academy of Management
Conference to be held in Cardiff, UK 11-13 September 2012. De Silva, L.R. Uyarra, Elvira and Oakey, Ray (2012). ‘Academic Entrepreneurial Diversification in a Resource Constrained Environment’. Academy of Management
Conference held in Boston, Massachusetts, USA 3-7 August 2012. De Silva, L.R. and Wapshott. Robert (2012) ‘The Motivations of Academic Entrepreneurs in a Resource Constrained Environment’. The 15
th Uddevalla Symposium, hosted by Research Centre for Spatial and Organizational Dynamics (CIEO), University of Algarve, Faro Portugal, June 14-16 2012. De Silva, L.R. Uyarra, Elvira and Oakey, Ray (2011). ‘Diversification and Academic Entrepreneurship in a Resource Constrained Environment’. Technology Transfer Society
Conference held at the University of Augsburg, Germany 21-23 September 2011. De Silva, L.R. Uyarra, Elvira and Oakey, Ray (2011). ‘Academic Entrepreneurship in a Resource Constrained Environment: Diversification and Synergistic Effects’. Eu-Spri
Conference held at the Manchester Institute of Innovation Research, UK 20-22 September 2011. De Silva, L.R. Uyarra, Elvira and Oakey, Ray (2011). ‘The Nature of Academic Entrepreneurial Engagement in a Resource Constrained Environment’ The Annual
International High Technology Small Firms Conference held at the Manchester Business School, 9-10 June 2011.
17
De Silva, L.R. (2010) ‘Business Start-Up and Growth Motives of Entrepreneurs who own Small and Medium Enterprises in regional context of the UK’. British Academy of
Management Conference held at the University of Sheffield, Sheffield 14-16 September 2010. De Silva, L.R. and Kodithiwakku Sarath S. (2010) ‘Pluriactivity among Rural Farming Households: Survival or Capital Accumulation Strategy?’ British Academy of Management
Conference held at the University of Sheffield, Sheffield 14-16 September 2010. De Silva, L.R. (2010) ‘Business Start-Up and Growth Motives of Entrepreneurs who own Small and Medium Enterprises in regional context of the UK’. 5th
European Conference
on Entrepreneurship and Innovations held at National and Kapodistrian University of Athens on the 16-17 September 2010. Prasada, P., De Silva Ranmuthumalie and Weerahewa, J. (2005). ‘An Analysis of Incidence of Commodity Taxation on the Income Distribution in Sri Lanka’. Proceedings of Fourth Poverty and Economic Policy (PEP) International General Meeting and Conference (Paper was presented at the Fourth Poverty and Economic Policy (PEP) International General Meeting and Conference held in Colombo Sri Lanka, 13th to 17th June 2005) https://idl-bnc.idrc.ca/dspace/handle/123456789/27957 Working Papers Multilevel influence on entrepreneurial engagement: A case of academic entrepreneurs in a resource constrained environment - Target journal - Journal of Management Studies (4*) - Intend to submit the paper by November 2012 I have examined the relative influence of micro, meso, and macro level factors on the
diversification strategies of academic entrepreneurs.
Academic entrepreneurship and normal academic duties in a resource constrained environment: symbiosis or rivalry? - Target journal - Research Policy (4*) - Intend to submit the paper by December 2012 I have investigated the extent to which the diversification strategies of academic
entrepreneurs affect their normal academic duties, and identified synergies between
academic entrepreneurship and normal academic duties.
De Silva, Ranmuthumalie, ‘Business Start-Up and Growth Motives of Entrepreneurs: A Case in Bradford, United Kingdom’ (May 16, 2010). Manchester Business School Research Paper No. 597. Available at SSRN: http://ssrn.com/abstract=1625667
De Silva, Ranmuthumalie ‘Academic Entrepreneurship: The role of universities as knowledge intensive service providers’ – Target journal - ‘Research Policy’ (4*) - Intend to submit the paper by December 2012 De Silva, Ranmuthumalie, and Robins, Dawn ‘Port-centric Clusters: Sustainable intermodal transportation in the European Union’ - Target journal -‘Regional Studies’ (3*) - Intend to submit the paper by January 2013 De Silva, Ranmuthumalie, and Cooper, David ‘Business Model Innovation: Reuse of empty properties in the UK high street’ - Target journal -‘Entrepreneurship and Regional Development’ (3*) - Intend to submit the paper by February 2013
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Chapter 1: Introduction
Expectations regarding the contributions of academics to entrepreneurial activity in
addition to their primary role of carrying out teaching and research (Laukkanen, 2003)
have increased in recent years (Venkataraman et al., 1992). At a government policy level,
the commercialization of university-generated knowledge is often considered to be a way
of achieving national competitiveness (McMullan and Vesper, 1987, Henderson et al.,
1998, Mowery et al., 2002) and innovation (Lam, 2005). Therefore, university industry
partnerships are encouraged through making a wide array of funding options available to
such collaborative projects (Phan and Siegel, 2006, Wright et al., 2006). This has escalated
pressure on universities to generate additional economic returns (Storey and Tether, 1998,
Shane and Stuart, 2002) through bridging the gap between industry and the universities
(Mowery and Shane, 2002).
Nevertheless, research on academic entrepreneurship has, to date, been carried out mainly
in developed nations with special emphasis on the UK and US. There has been little
discussion about academic entrepreneurship in developing countries, particularly low
income ones (Eun et al., 2006, Adesola, 1991). Developing countries, when compared with
developed nations, have been reported to face relatively high levels of resource scarcity
that involve shortages of skills (Alexander and Andenas, 2008, Griffith-Jones et al., 2003),
finance (United Nations Human Settlements Programme, 2005), physical infrastructure,
technology (World Bank, 2010), and institutions (Claude and Weston, 2006) needed for
innovation and entrepreneurship. The literature has identified the environment of
entrepreneurs as a major factor influencing their entrepreneurial behaviour (Ucbasaran et
al., 2000). Hence, it is possible that academic entrepreneurship in a resource constrained
country might be different from that in a resource-rich nation.
On the other hand, in recent years, developing nations have been investing increasingly in
higher education (World Bank EdStat, 2011). Growing academic engagement in
entrepreneurial activities in these countries has underscored the need to address the
significance of these activities in any higher education policy. Therefore, in order to derive
optimal outcomes from investments in higher education, it is important to adopt strategies
appropriate to developing, resource constrained nations rather than merely imitating
developed, resource rich nations (Bernasconi, 2005, Eun et al., 2006). Moreover, such
context specific understanding would be useful when developing domestic capacities to
19
promote applied research that would be necessary to achieve economic growth (Pardey et
al., 2006). Furthermore, since higher education has been reported to generate broad
externalities to a society (Patel, 2003), a context specific knowledge on academic
entrepreneurship would be needed to ensure the delivery of positive social benefits. The
above highlighted knowledge gap leads to the broad research question of this study, which
is ‘what is the nature of academic entrepreneurial engagement in resource constrained
environments?’. In order to address this research question, this thesis has identified four
specific objectives, which are briefly discussed in the following Sections.
1.1. Specific Objectives
Recent evidence suggests that entrepreneurs operating in resource-barren environments
tend to engage in multiple income generation activities (Kodithuwakku and Rosa, 2002).
Therefore, it is possible to argue that academics operating in such environments may carry
out several entrepreneurial activities, which may include different knowledge transfer
activities as well as spin-off firm formation. In line with the literature that defined the
carrying out of multiple income generation activities as diversification (Alsos et al., 2003),
this study argues that engaging in several entrepreneurial activities by academics may also
represent diversification. Hence, in order to understand academic entrepreneurship in a
resource constrained environment, this research will investigate the portfolio of
entrepreneurial activities carried out by academics. Adapting from ‘pluriactivity’, which is
defined as the combination of income generation activities carried out by individuals
(Evans and Ilbery, 1993), this current study has named the portfolio of entrepreneurial
activities carried out by academics as ‘plural activities’. Accordingly, the first specific
objective of this thesis is to investigate the ‘plural activities’ of academic entrepreneurs
operating in a resource constrained environment.
There has been increasing interest in the investigation of what motivates academics to
engage in entrepreneurial endeavour, despite experiencing a reward system that mainly
encourages publications (Jones-Evans, 1997). Some motives identified in studies mainly
focused on developed nations includes a desire for novelty and wealth (Franklin et al.,
2001), a need to make use of technical expertise (Otto, 1999), a need for independence and
control (Oakey, 2003), and to develop university policies towards the encouragement of
academic entrepreneurial activity (Van Dierdonck and Debackere, 1988). Nevertheless, the
motives of academic entrepreneurs operating in resource constrained environments are
20
under researched, even though their motivations have been found to play a critical role in
achieving success in these environments (Erdıs and Varga, 2009). Hence, the second
specific objective of this study is to investigate the motivations of academic entrepreneurs
operating in a resource constrained environment.
The literature also suggests that the entrepreneurial activities of academics are shaped by
the characteristics of the parties involved in this process, namely academics (micro level),
universities (meso level), and the macro environment, mainly comprising government and
industry (O’Shea et al., 2004, Etzkowitz and Leydesdorff, 2000, Siegel et al., 2004).
However, most academic studies have been performed in resource-rich developed nations,
rather than in resource constrained environments. Moreover, they have only investigated
differences between academic entrepreneurs and non-entrepreneurs, without paying
attention to the heterogeneity of academic entrepreneurs. Nonetheless, academic
entrepreneurs might not be homogeneous, and may differ in the ways they diversify their
entrepreneurial activities. This heterogeneity might be particularly prominent in a resource
constrained environment since entrepreneurs in such environments have been reported to
use diversification to extract added value from limited opportunities (Kodithuwakku and
Rosa, 2002). Hence, the third specific aim of this thesis is to address this gap in our
knowledge by investigating how multi-level causal factors influence the ‘plural activities’
of academic entrepreneurs operating in resource constrained environments.
It has also been highlighted in the literature that academic entrepreneurship may have an
influence on normal academic duties (i.e. university teaching and research) (Dasgupta and
David, 1994, Rosenberg and Nelson, 1994) and the wider national economy (Pattyn, 2006,
Etzkowitz, 1998). These previous studies have argued that academic entrepreneurship
compensates for plummeting direct government funds available to universities (Phan and
Siegel, 2006, Wright et al., 2006), since it generates additional income to academics and
universities (Wright et al., 2004). Furthermore, spin-off formation has been reported to
generate wealth and to create jobs (Birch, 1987). University-industry technology transfer
provides opportunities for industry to capitalise on the knowledge and skills of academics
and to access the infrastructural facilities of universities (Meyer-Krahmer and Schmock,
1998). However, the change of focus from basic science to applied science, and the use of
limited physical (Van Dierdonck and Debackere, 1988) and human resources (Bercovitz
and Feldman, 2003) in universities to promote academic entrepreneurship have been
criticised for causing negative impacts on the quality of teaching and research (Dasgupta
21
and David, 1994, Rosenberg and Nelson, 1994). Almost all studies that discuss the positive
and negative impacts of academic entrepreneurship to date have mainly tended to focus on
developed countries. Therefore, so far, there has been little discussion about the impacts of
academic entrepreneurship on the universities and wider economy of developing, resource
constrained nations. Hence, the final specific objective of this thesis is to investigate the
impacts of academic entrepreneurship in a resource constrained environment.
Thus, to summarise, in order to investigate academic entrepreneurship in a resource
constrained environment, the thesis has four specific objectives; namely, investigating the
‘plural activities’ of academic entrepreneurs, studying the motivations of academic
entrepreneurs, examining the influence of multilevel causal factors on ‘plural activities’,
and investigating the impacts of academic entrepreneurship on universities and wider
economy.
1.2. The Structure of the Thesis
The thesis consists of ten chapters. This introductory chapter is followed by a second
chapter, which defines the term, resource constrained environment. This is followed by the
third chapter, which reviews relevant literature. The fourth chapter illustrates the
hypotheses of this thesis, and the fifth chapter exemplifies the methodology. The
subsequent four chapters present an analysis of data, while the final chapter presents
conclusions together with the implications of this study. The following Sections of this
chapter briefly point out the content of each of the above mentioned chapters.
Chapter 2 provides an explanation of the term, resource constrained environment. It
initially provides an overview of how national level resources shape academic
entrepreneurship. Subsequently, it compares and contrasts resources statuses in different
world nations to evaluate the suitability of a study context to represent a resource
constrained environment.
Chapter 3 reviews the literature on academic entrepreneurship in order to provide a
theoretical background to the study. Initially, the chapter provides an overview of the
general entrepreneurship literature. Subsequently, it illustrates the different definitions of
academic entrepreneurship used in the literature, with the aim of deriving a suitable
definition with which to investigate the nature of academic entrepreneurial engagement in
22
a resource constrained environment. Finally, it discusses the literature relevant to factors
affecting, the impacts of, and barriers to, academic entrepreneurship. In this discussion,
contradictions and gaps in the literature are highlighted.
Chapter 4 states the hypotheses of this research on academic entrepreneurship in a resource
constrained environment. The chapter develops eleven hypotheses, derived from the four
specific research objectives.
Chapter 5 discusses the methodology adopted in this research. It initially justifies the
choice of the research philosophy, and subsequently, discusses sampling, data collection,
and data analysis, together with methodological and philosophical justifications. Since the
study has used a sequential mixed method design with three phases; namely, context
specific data gathering, an on-line survey, and in-depth interviews, each Section of this
chapter illustrates how these different methods are amalgamated to achieve the research
objectives.
Chapter 6 addresses the first objective of the thesis, which is to examine the ‘plural
activities’ of academic entrepreneurs in a resource constrained environment. It initially
highlights the relevant literature on the key issues addressed, and subsequently, presents
qualitative and quantitative data analysis. The data analysis is structured around three key
aspects; namely, whether a resource constrained environment inhibits or encourages
academic entrepreneurial engagements, what is the nature of the ‘plural activities’ of
academic entrepreneurs, and whether potential synergies between entrepreneurial activities
vary, depending on ‘plural activities’.
Chapter 7 presents an analysis of the second objective of this thesis, which is to investigate
the motivations of academic entrepreneurs operating in a resource constrained
environment. Initially, the chapter highlights the relevant literature on the key issues
addressed. Subsequently, it provides qualitative and quantitative data analyses on whether
there is an association between the ‘plural activities’ of academic entrepreneurs and their
motivations, and how entrepreneurial motivations dynamically change over the
entrepreneurial careers of academics.
Chapter 8 presents an analysis of the third objective of this thesis, which is to investigate
how multilevel causal factors influence the ‘plural activities’ of academic entrepreneurs
23
operating in a resource constrained environment. This chapter initially briefly restates the
relevant literature, followed by qualitative and quantitative data analysis. The analysis first
investigates whether there is an association between the ‘plural activities’, and the personal
characteristics, of academic entrepreneurs. Then, it examines the relative effect of micro -
and meso - level causal factors on the propensity to adopt specific ‘plural activity’ types.
Last, the chapter analyses how the interactions between universities, industry and
government in a resource constrained environment vary from those in a resource-rich
environment.
Chapter 9 presents an analysis of the final objective of this thesis, which investigates the
impacts of academic entrepreneurship in a resource constrained environment. The chapter,
initially, briefly restates the relevant literature, followed by qualitative and quantitative
data analysis. The analysis first investigates how the entrepreneurial engagements of
academics affect their normal academic duties, and then, examines whether there is an
association between the ‘plural activities’ of academic entrepreneurs and their impacts on
normal academic duties. Last, the chapter studies whether there is a difference between
academic entrepreneurial activities with respect to their national economic importance as
perceived by academic entrepreneurs.
Chapter 10 summarises the results of the study and draws general conclusions. In light of
the findings of this thesis, this chapter discusses the theoretical contributions, limitations,
policy implications, and potential future research avenues, of the current study.
Figure 1.1 illustrates how each chapter contributes to the four major Sections addressed in
this thesis.
24
Figure 1.1: The Layout of the Thesis
PART 1: INTRODUCTION Chapter 1: Introduction
Chapter 2: A Resource Constrained Environment
Chapter 3: Academic Entrepreneurship: A Review of the Literature
PART 2: RESEARCH DESIGN Chapter 4: Research Hypotheses Chapter 5: Research Methodology
PART 3: ANALYSIS Chapter 6: The ‘Plural Activity’ of Academic Entrepreneurs in a Resource
Constrained Environment
Chapter 7: The Motivations of Academic Entrepreneurs operating in a
Resource Constrained Environment
Chapter 8: The Influence of Multilevel Factors on the ‘Plural Activities’ of
Academic Entrepreneurs operating in a Resource Constrained Environment
Chapter 9: The Impacts of Academic Entrepreneurship in a Resource
Constrained Environment
PART 4: CONCLUSIONS Chapter 10: Conclusions and the Implications of the Study
25
Chapter 2: A Resource Constrained Environment
The previous chapter of the thesis provided an introduction by illustrating the main
purpose of this research, which is to investigate academic entrepreneurship in a resource
constrained environment. As briefly discussed in the previous chapter low income
developing countries, when compared with developed countries, face a higher scarcity of
resources needed for innovation and entrepreneurship. Hence, this research chose Sri
Lanka, which is a low income developing country, as the location for the study. This
chapter initially provides an overview of how national level resources shape academic
entrepreneurship, and subsequently, compares and contrasts resources in Sri Lanka with
other world nations to evaluate relative resource scarcity.
2.1. Academic Entrepreneurship in Resource Constrained Environments
Relevant literature has argued that the ability of entrepreneurs to identify, and capitalize
on, opportunities is influenced by the environment in which they operate (Scott et al.,
2000, Ucbasaran et al., 2001). An academic entrepreneur’s environment mainly consists of
the university, which comprises the internal environment, and actors in the wider economic
and social environment, especially government and industry (O’Shea et al., 2004,
Etzkowitz and Leydesdorff, 2000, Siegel et al., 2004, Eun et al., 2006). According to the
concept of ‘National Innovation System’ (NIS) government, universities, and industry in a
nation interact with each other (Freeman, 1987, Lundvall, 1992, Nelson, 1993). As a result,
universities are closely intertwined with the wider national environment. Hence, it is
possible to argue that the national environment of academics may shape their engagements
in entrepreneurial endeavour.
Porter and Stern (2002) have further confirmed the above argument, by introducing the
term ‘National Innovative Capacity’ (pp.105), which illustrates how a national
environment influences innovation and entrepreneurship. They argue that, a country’s
potential to produce commercially relevant innovations (e.g. academic entrepreneurship) is
dependent upon three factors, namely; a ‘common innovation infrastructure’, a ‘cluster-
specific environment’, and the ‘quality of linkages’ (pp. 105-106). The common innovation
infrastructure of a nation includes the human and financial resources devoted to
innovation, public policy towards science, technology, and innovation, as well as the
technological sophistication of the nation. A cluster-specific environment is the geographic
26
concentration of companies and institutions that foster innovation. The quality of linkages
is the extent to which a country’s formal and informal institutions and networks, and
particularly a nation’s university system, are involved in building relationships between the
‘common innovation infrastructure’ and the ‘cluster specific environment’.
By measuring the quality of these factors, Porter and Stern (2002) have constructed a
National Innovative Capacity Index1, which is a composite of four sub-indices; namely, a
‘scientific and technical personnel subindex’ (measures the proportion of highly skilled
human resources), ‘innovation policy subindex’ (a measure of a nation’s innovation public
policy environment), ‘cluster innovation environment subindex’ (a measure of the
prevalence of technologically sophisticated and geographically concentrated institutions
involved in innovation), and ‘linkages subindex’(a measure of the quality of scientific
research institutions and the availability of venture capital). These indices rank countries,
in which the lower the rank, the better the national environments for commercially oriented
innovations. Table 2.1 illustrates the ranks of selected developed and developing countries
calculated by Porter and Stern. These ranks suggest that Sri Lanka, and other developing
countries, when compared with developed nations, are poor in terms of national resources
relevant to innovation and entrepreneurship, which include high skilled labour, policy and
institutional frameworks, technological sophistication, and the availability of finance.
1 It should be noted that, even though the National Innovative Capacity Index seems to be useful to gain a relative understanding of national environments that influence innovation and entrepreneurship, critics argue that the index has low face validity with respect to the outcome of innovation such as introducing new products to a market FABER, J. & HESEN, A. B. 2004. Innovation capabilities of European nations Cross-national analyses of patents and sales of product innovations. Research Policy, 33, 193–207.. Furthermore, the index is criticised since it uses data and indicators calculated by different countries, which tend to be different in terms of measurement practices adopted by different countries BALZAT, M. & HANUSCH, H. 2004. Recent Trends in the Research on National Innovation Systems. Journal of Evolutionary Economics, 14, 197-210.
27
Table 2.1: National Innovative Capacity Index
Country Basis Developing Countries Developed Countries
Sri Lanka
India
Bangladesh
Indones
ia
UK
USA
France
German
y
Canada
Australi
a
National Innovative Capacity Index
A composite of four sub-indices
57 38 70 54 4 1 9 3 10 7
SUBINDICES 1 Scientific and technical personnel subindex
Common innovation infrastructure
56 59 67 47 18 6 9 11 14 8
2. Innovation Policy Subindex
60 39 74 48 13 1 6 7 5 10
3. Cluster Innovation Environment Subindex
Cluster-specific environment
62 31 73 58 3 1 10 4 12 9
4. Linkages Subindex
Quality of linkages
48 23 67 62 9 1 8 10 11 5
Source: Porter and Stern (2002)
In addition to the resources considered in the above indices, the literature (e.g. Yusuf and
Schindehutte, 2000, Acs and Virgill, 2000) suggests that the physical infrastructure of a
nation also influences the level of innovation and entrepreneurial activity. For instance, De
(2010) has found a positive relationship between the per capita income of a country and the
quality of physical infrastructure. These differences between developed and developing
nations in terms of their resource statuses are further confirmed by the literature on
economic development. These studies argue that developing countries face relatively high
levels of resource scarcity, that is typified by a dearth of highly skilled labour (Alexander
and Andenas, 2008, Griffith-Jones et al., 2003), finance (United Nations Human
Settlements Programme, 2005), infrastructure, technology (World Bank, 2010), and
institutions (Claude and Weston, 2006) relevant to innovation and entrepreneurship.
Hence, it seems that the resources of a national environment, that are relevant to innovation
and entrepreneurship, are generally meagre in developing countries, including Sri Lanka.
Since the above comparison was performed only using rank order, the following Sections
of this chapter, will use further statistical evidence and secondary qualitative information
to carry out a detailed analysis of the extent to which Sri Lankan academics, in relation to
other world nations, face the above discussed resource scarcities.
28
2.2. An Overview of Sri Lankan Economy
Sri Lanka is an island nation in South Asia, a region that comprises Afghanistan,
Bangladesh, Bhutan, India, Iran, Maldives, Nepal, and Pakistan, with an area of 65000 km2
and the population of about 20 million. From independence in 1948 until 1977, Sri Lanka
adopted closed economic policies, such as import substitutions and nationalization, which
were then replaced by major economic and structural reforms that introduced deregulation,
privatization, and international trade (Asian Development Bank, 2008, Dasanayake, 2003).
Alongside these policy reforms, the Sri Lankan economy has been found to shift from an
agriculture-based to a service-based orientation. For instance, while the contribution of the
agriculture sector to Gross Domestic Product (GDP) was 34.7% in 1970, it had reduced to
12.8% by 2010. Conversely, the contribution of services sector to GDP has increased from
44.7% in 1970 to 57.8 % by 2010. The contribution to GDP by the ‘mining,
manufacturing, and construction’ sector has also shown a slight increase from 20.6% in
1970 to 29.4 % by 2010 (Central Bank of Sri Lanka, 2011).
However, despite these policy reforms and structural changes, Sri Lanka remains a
developing country. Judged in terms of a Gross National Income (GNI) (i.e. the sum of
value added by citizens of a nation within the country or abroad) Sri Lankan per capita
income in 2010 was US $ 2240, causing it to be classified as a ‘lower middle income
country’ by the World Bank. The World Bank has categorised world nations into four
groups; namely, low income (i.e., $1,005 or less), lower middle income (i.e., $1,006 -
$3,975), upper middle income (i.e., $3,976 - $12,275) and high income (i.e., $12,276 or
more) countries. Dasanayake (2003) argued that the lack of commitment by both
government and private sector on technological advancement and innovation had been the
major cause of low Sri Lanka’s per capita income. Additionally, it seemed that the civil
war, which persisted from 1983 to 2009, had hindered the country’s economic
development and technological advancement, since a large percentage of government
income (on average about 5% of GDP, which represents about 17% of total government
expenditure) was allocated to the war (Asian Development Bank, 2008, Dasanayake,
2003).
Following this initial introduction to Sri Lankan economy, the next Sections of this chapter
compare and contrast the resource status in Sri Lanka with different ‘income groups’
constructed by the World Bank (i.e. high income, upper middle income, and lower middle
29
income countries). Since the sole basis for constructing the above groups is the financial
performance of a country, this study investigates whether statuses of high skilled human,
technological, infrastructural, and institutional, resources relevant to entrepreneurship and
innovation also follow the same trend. Additionally, South Asian countries (i.e.
Afghanistan, Bangladesh, Bhutan, India, Iran, Maldives, Nepal, and Pakistan) are also used
for this comparison, whereby the extent to which resources status in Sri Lanka is similar to,
or different from, countries in the same geographical region is analysed. There are two
major purposes of these comparisons; first, to confirm the nature of the resource
constrained environment of Sri Lanka, and second, to identify economic groups and
geographical regions similar to Sri Lanka (i.e. in terms of the availability of resources),
which are later used when discussing to what extent the findings of this thesis could be
generalised. Please note that, whenever there is a high variation in the resource status of
different income groups, two graphs are used, without which the clarity of the analysis
would have been reduced. Hence, with respect to such indicators, the first graph (i.e.
Figure 2.1.1, 2.5.1, 2.6.1, and 2.7.1) compares and contrasts the statistics of Sri Lanka with
those of lower middle income, South Asian, and middle income countries, while the
second graph (i.e. Figure 2.1.2, 2.5.2, 2.6.2, and 2.7.2) introduces upper middle income and
high income countries to the comparison.
2.2.1. Financial Resource Status in Sri Lanka
The comparison made in the previous Section, using a per capita GNI, which is considered
a traditional indicator of national economic performance (Malhotra, 2001), illustrated the
low financial resource status of Sri Lanka. However, since this previous comparison used
only the data for one year (i.e. 2010), in order to obtain a historical understanding of the
financial status of Sri Lanka, this study decided to extend the analysis using data for the
past 50 years. As illustrated in Figure 2.1.1 and 2.1.2, the per capita GNI of Sri Lanka has
historically been low, and furthermore, over the years the gap between Sri Lanka and high
income countries has increased (Figure 2.1.2). On the contrary, the GNI of Sri Lanka is
quite similar to other South Asian countries (Figure 2.1.1), even though the performance of
Sri Lanka has been slightly better than these countries since 1990. Interestingly, the Sri
Lankan economy seems to be growing at a high rate in recent years, illustrated by the 7.02
% GNI per capita growth rate in 2010, which is on a par with the economic development of
South Asia (i.e. 7.31% GNI per capita growth rate in 2010).
Figure 2.1.1: GNI per capita Source: The World Bank (2011)
Figure 2.1.2: GNI per capita Source: The World Bank (2011)
Low government income
restricted government budget for research and development (R&D) in Sri Lanka. For
instance, government expenditure on R&D as a percentage of GDP was only 0.11% in
2008 (latest available data) (Figure 2.2), which is far less than developed
example, EU – 0.24%, US
India and 0.67% Pakistan in 2007).
few companies in Sri Lanka are interested in investing on R&D (Esha
on private sector R&D expenditure as a percentage of GDP further confirmed the above,
where in Sri Lanka it was only 0.02% in 2008 (National Science Foundation Sri Lanka,
2008), while it was much higher in developed nations (e.g. EU
2008) as well as some South Asian countries (e.g. India
Figure 2.1.1: GNI per capita (current US$) Income: without High Income CSource: The World Bank (2011)
Figure 2.1.2: GNI per capita (current US$) Income: with High Income CSource: The World Bank (2011)
Low government income and its priorities of poverty alleviation
restricted government budget for research and development (R&D) in Sri Lanka. For
instance, government expenditure on R&D as a percentage of GDP was only 0.11% in
2008 (latest available data) (Figure 2.2), which is far less than developed
0.24%, US- 0.3%) and some South Asian developing countries (e.g. 0.8%
India and 0.67% Pakistan in 2007). Furthermore, recent research has revealed that only a
few companies in Sri Lanka are interested in investing on R&D (Esha
on private sector R&D expenditure as a percentage of GDP further confirmed the above,
where in Sri Lanka it was only 0.02% in 2008 (National Science Foundation Sri Lanka,
2008), while it was much higher in developed nations (e.g. EU –
2008) as well as some South Asian countries (e.g. India – 0.23%) (Eurostat, 2011).
30
Income: without High Income Countries
High Income Countries
and its priorities of poverty alleviation have resulted in a
restricted government budget for research and development (R&D) in Sri Lanka. For
instance, government expenditure on R&D as a percentage of GDP was only 0.11% in
2008 (latest available data) (Figure 2.2), which is far less than developed countries (for
0.3%) and some South Asian developing countries (e.g. 0.8%
Furthermore, recent research has revealed that only a
few companies in Sri Lanka are interested in investing on R&D (Esham, 2008). Statistics
on private sector R&D expenditure as a percentage of GDP further confirmed the above,
where in Sri Lanka it was only 0.02% in 2008 (National Science Foundation Sri Lanka,
– 1.21%, US – 2.02% in
0.23%) (Eurostat, 2011).
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
1996
Figure 2.2: Government Expenditure on Research and Development (as a % of GDP)Source: International Monetary Fund (2011)
Similarly, government expenditure on universities as a percentage of GDP was only
0.31%, which represented 1.42% of total government expenditure (Figure 2.3). This is low
when compared with developed (e.g. OECD average 1.2%) and some developing nations
(e.g. India-0.67%) (OECD, 2010). On the other hand, since Sri Lankan universities provide
free undergraduate education, they have limited sources of income. These facts illustrate
strong financial resource barriers that must be faced by academics in Sri Lankan
universities.
Figure 2.3: Government Expenditure on University as a Percentage of GDPSource: University Grant Commission of Sri Lanka
2.2.2. Human Resources in Sri Lanka
The World Bank data on human resources suggests that, in addition to f
constraints, Sri Lanka suffers from high skilled labour shortages. As illustrated in Figure
2.4, the number of researchers per 1 million people in 2006 was only 93, which is far lower
than developed nations (e.g. UK
1996 2000 2004
Figure 2.2: Government Expenditure on Research and Development (as a % of GDP)International Monetary Fund (2011)
government expenditure on universities as a percentage of GDP was only
0.31%, which represented 1.42% of total government expenditure (Figure 2.3). This is low
when compared with developed (e.g. OECD average 1.2%) and some developing nations
0.67%) (OECD, 2010). On the other hand, since Sri Lankan universities provide
free undergraduate education, they have limited sources of income. These facts illustrate
strong financial resource barriers that must be faced by academics in Sri Lankan
Figure 2.3: Government Expenditure on University as a Percentage of GDPUniversity Grant Commission of Sri Lanka (2011)
2.2.2. Human Resources in Sri Lanka
The World Bank data on human resources suggests that, in addition to f
constraints, Sri Lanka suffers from high skilled labour shortages. As illustrated in Figure
2.4, the number of researchers per 1 million people in 2006 was only 93, which is far lower
than developed nations (e.g. UK- 2909, USA-4584 , Australia-
31
2006
Figure 2.2: Government Expenditure on Research and Development (as a % of GDP)
government expenditure on universities as a percentage of GDP was only
0.31%, which represented 1.42% of total government expenditure (Figure 2.3). This is low
when compared with developed (e.g. OECD average 1.2%) and some developing nations
0.67%) (OECD, 2010). On the other hand, since Sri Lankan universities provide
free undergraduate education, they have limited sources of income. These facts illustrate
strong financial resource barriers that must be faced by academics in Sri Lankan
Figure 2.3: Government Expenditure on University as a Percentage of GDP
The World Bank data on human resources suggests that, in addition to financial resource
constraints, Sri Lanka suffers from high skilled labour shortages. As illustrated in Figure
2.4, the number of researchers per 1 million people in 2006 was only 93, which is far lower
-4230), as well as some
32
developing countries (e.g. India-130, Indonesia 706, Malaysia – 371) (The World Bank,
2011). This skill shortage seems to be a ‘vicious circle’ linked to financial resources. For
instance, due to a lack of funding, Sri Lanka has a few universities (N=13), which have
capacity to educate only about 10% of those who sit for Advanced Level exams, although
about 62% of them meet the minimum requirements necessary to pursue university
education (University Grant Commission of Sri Lanka, 2011). As a result, the training of
highly skilled labour in Sri Lanka is very low. On the other hand, the Asian Development
Bank (2008) highlighted that a “brain drain” from Sri Lanka (which is a phenomenon of
the emigration of highly skilled labour) has further weakened the human resource base of
Sri Lanka. This is further confirmed by statistical evidence, which reported that 27.5 per
cent of academics leave the country every year, which is much higher than other Asian
countries (e.g. 4.2 per cent in India, 9.2 per cent in Pakistan, 4.7 per cent in Bangladesh,
2.7 per cent in Nepal and 2.2 per cent in Maldives) (Kariyawasam, 2010).
0
20
40
60
80
100
120
140
160
180
200
1996 2000 2004 2006
Figure 2.4: Researchers in Research and Development (per million people) Source: International Monetary Fund (2011)
2.2.3. Technological Resources in Sri Lanka
The technological sophistication of a country has also been identified in the literature as an
important resource that determines the extent of innovation and entrepreneurship
(Khandwalla, 1976). In order to measure the quality of technological resources available in
Sri Lanka, three indicators compiled by the World Bank are used, namely, high-technology
exports, patent applications by residents in Sri Lanka, and internet usage. High-technology
exports are products that result from high research and development intensity. As
illustrated in Figure 2.5.2, high-technology exports as a percentage of total manufactured
exports in Sri Lanka are significantly lower than high income, middle income, or lower
middle income countries, while somewhat similar to other South Asian countries (Figure
2.5.1).
Figure 2.5.1: High-technology EIncome Countries Source: The World Bank (2011)
Figure 2.5.2: High-Income Countries Source: The World Bank (2011)
A similar pattern is observed with respect to the number of international or national patent
applications by residents in Sri Lanka, in which th
of high income and upper middle income countries (Figure 2.6.2), but similar to other
South Asian and lower middle income countries (Figure 2.6.1).
middle income countries, while somewhat similar to other South Asian countries (Figure
technology Exports (% of manufactured exports): w
Source: The World Bank (2011)
-technology Exports (% of manufactured exports): with High
Source: The World Bank (2011)
A similar pattern is observed with respect to the number of international or national patent
applications by residents in Sri Lanka, in which the figures are significantly lower than that
of high income and upper middle income countries (Figure 2.6.2), but similar to other
South Asian and lower middle income countries (Figure 2.6.1).
33
middle income countries, while somewhat similar to other South Asian countries (Figure
xports (% of manufactured exports): without High
of manufactured exports): with High
A similar pattern is observed with respect to the number of international or national patent
e figures are significantly lower than that
of high income and upper middle income countries (Figure 2.6.2), but similar to other
Figure 2.6.1: The Number of Patent Applications by Residents:Countries Source: The World Bank (2011)
Figure 2.6.2: The Number of Patent Applications by Residents: with High Income Countries Source: The World Bank (2011)
Furthermore, internet usage, which
Communication Technology (ICT), is also considered a measure of technological
sophistication of a country (UNCTAD, 2011). A
usage (i.e. users per 100 people) in Sri Lanka is significantly lower
upper middle income countries, but comparable to either South Asian or lower middle
income countries (Figure 2.7.1).
scarcity of Sri Lanka.
Figure 2.6.1: The Number of Patent Applications by Residents:
Source: The World Bank (2011)
Figure 2.6.2: The Number of Patent Applications by Residents: with High Income
Source: The World Bank (2011)
internet usage, which is considered an important indicator
Communication Technology (ICT), is also considered a measure of technological
sophistication of a country (UNCTAD, 2011). As illustrated in Figure 2.7.2, the internet
usage (i.e. users per 100 people) in Sri Lanka is significantly lower
upper middle income countries, but comparable to either South Asian or lower middle
income countries (Figure 2.7.1). These comparisons confirm the technological resource
scarcity of Sri Lanka.
34
Figure 2.6.1: The Number of Patent Applications by Residents: without High Income
Figure 2.6.2: The Number of Patent Applications by Residents: with High Income
is considered an important indicator of Information and
Communication Technology (ICT), is also considered a measure of technological
s illustrated in Figure 2.7.2, the internet
usage (i.e. users per 100 people) in Sri Lanka is significantly lower than high income and
upper middle income countries, but comparable to either South Asian or lower middle
These comparisons confirm the technological resource
Figure 2.7.1: Internet USource: The World Bank (2011)
Figure 2.7.2: InterneSource: The World Bank (2011)
2.2.4. Institutional and Policy Framework in Sri Lanka
The literature has argued that institutional and policy frameworks for innovation play a
major role in promoting commercially oriented innovation
study of the history of Sri Lankan Science and Technology Policy, Vitarana (1996) has
stated that, even though there were several initiatives to form research and development
institutes since independence in 1948, these were not successful. As a result, there was no
formal science and technology policy until the National Science Council (NSC) was
established in 1968, after which the first policy document
Policy Statement 1969’ was written. However, the government was not keen to implement
this policy due to financial constraints and other priorities linked to poverty allev
a result, Sri Lanka did not have a formal Science and Technology policy until 1998, the
year in which the ‘
successfully implemented. As a result of this act, the National Science and Tec
Commission (NASTEC) was established to formulate and implement the Science and
Figure 2.7.1: Internet Users (per 100 people): without High Income CSource: The World Bank (2011)
Figure 2.7.2: Internet Users (per 100 people): with High Income CSource: The World Bank (2011)
2.2.4. Institutional and Policy Framework in Sri Lanka
argued that institutional and policy frameworks for innovation play a
major role in promoting commercially oriented innovation (Porter and Stern, 2002)
study of the history of Sri Lankan Science and Technology Policy, Vitarana (1996) has
even though there were several initiatives to form research and development
institutes since independence in 1948, these were not successful. As a result, there was no
formal science and technology policy until the National Science Council (NSC) was
lished in 1968, after which the first policy document, namely, the ‘National Science
Policy Statement 1969’ was written. However, the government was not keen to implement
this policy due to financial constraints and other priorities linked to poverty allev
a result, Sri Lanka did not have a formal Science and Technology policy until 1998, the
year in which the ‘Science and Technology Development Act
successfully implemented. As a result of this act, the National Science and Tec
Commission (NASTEC) was established to formulate and implement the Science and
35
people): without High Income Countries
t Users (per 100 people): with High Income Countries
argued that institutional and policy frameworks for innovation play a
(Porter and Stern, 2002). In a
study of the history of Sri Lankan Science and Technology Policy, Vitarana (1996) has
even though there were several initiatives to form research and development
institutes since independence in 1948, these were not successful. As a result, there was no
formal science and technology policy until the National Science Council (NSC) was
namely, the ‘National Science
Policy Statement 1969’ was written. However, the government was not keen to implement
this policy due to financial constraints and other priorities linked to poverty alleviation. As
a result, Sri Lanka did not have a formal Science and Technology policy until 1998, the
Science and Technology Development Act No. 11 of 1994’ was
successfully implemented. As a result of this act, the National Science and Technology
Commission (NASTEC) was established to formulate and implement the Science and
36
Technology policy (Wickremasinghe and Krishna, 2006). Additionally, another eight
institutions have been established, all of which are functioning under the umbrella of the
Ministry of Technology and Research (MoTR), which is the main body responsible for
handling Science and Technology development in Sri Lanka.
Currently Sri Lanka is implementing the ‘National Strategy for Science, Technology, and
Innovation 2011-2015’ introduced by MoTR in 2010 (National Science Foundation of Sri
Lanka, 2011). The major vision of this policy document is to improve the scientific
capability in order to make Sri Lanka a competitive knowledge hub in Asia. It is also
reported that the vision, goals, and objectives of the above policy have been incorporated
into the Ten Year National Development Framework prepared by the National Planning
Department of the Ministry of Finance and Planning. These initiatives suggest that, despite
a fragile start, Sri Lanka is now aiming at strong innovation and technology development.
Together with these developments, the government has formed public research institutes. It
is evident that these institutes account for about 20% of the total scientist population, while
the majority of the scientist population (i.e. more than 65%) is derived from universities.
The rest of the scientist population (i.e. less than 15%) comprises private sector research
and development personnel (National Science Foundation Sri Lanka, 2008). Furthermore,
it is apparent that there are formal and informal professional networks, which act as bodies
that link professionals between institutes. Based on the above information, the main
institutions responsible for innovation in Sri Lanka seem to be the government, represented
by institutions responsible for the formulation and implementation of Science, Technology,
and Innovation strategies, universities, public research institutes, the private sector, and
other professional bodies.
Even though these actors of national innovation in Sri Lanka are deemed to be similar to
those in developed nations, recent evidence suggests that collaborations between these
actors in Sri Lanka are weak and fragmented (Kumarasena, 2007). Furthermore, these
studies report that currently there is no Sri Lankan policy to promote ‘university-industry’
interactions (Esham, 2008). The only policy that indirectly promotes ‘university-industry’
interactions seem to be the promotion scheme of academics (stated in the University Grant
Commission Circulars 723/1997, 869/2005, 721/1997, 879/2006), which rewards the
carrying out of some entrepreneurial activities (See Table 8.3 of Chapter 8 for details).
37
In order to further compare and contrast the quality of institutions in Sri Lanka with other
countries, the Worldwide Governance Indicator (WGI), constructed by the World Bank
was used (WGI, 2011). WGI measures the quality of a country’s institutions as well as
economic and social interactions among them. It reports the institutional quality of 213
economies in the world over the period 1996–2009 on six criteria; namely, ‘voice and
accountability’, ‘political stability and the absence of violence’, ‘government
effectiveness’, ‘regulatory quality’, ‘rule of law’, and ‘control of corruption’. Since a
comparison of the quality of institutions specifically responsible for innovation was
performed in the Section 2.1 of this chapter (using ‘the quality of linkages sub-index’),
WGI, which measures the quality of institutions in general, is considered an appropriate
measure of gaining a holistic picture.
Each country has been given a rank from 0 to 100, in which ‘100’ indicates the best
quality, while ‘0’ indicates the worst. Table 2.2 provides rankings for 11 countries,
selected to represent different income groups and regions. Based on rankings, it is apparent
that, the quality of institutions in Sri Lanka is similar to other low income and South Asian
countries, while it is lower than high income countries.
Table 2.2: Worldwide Governance Indicators (WGI) in 2009 Country Sri
Lanka
India Pakistan
Banglades
h
Maldives
UK USA
France
Spain
Canad
a
Australia
Income group LMI LMI LMI LI UMI HI HI HI HI HI HI
Region South Asian Other Regions
Voice and Accountability
32 60 21 35 44 92 86 91 87 95 95
Political Stability and Absence of Violence
12 13 0 8 39 55 59 66 38 85 76
Government Effectiveness
49 54 19 17 42 91 89 90 78 97 95
Regulatory Quality 43 44 33 23 37 94 90 85 85 96 98 Rule of Law 53 56 19 28 53 94 92 90 85 97 95 Control of Corruption
45 47 13 17 30 91 85 90 80 97 96
LMI- Lower middle income, LI-Low income, HI-High income
Source: WGI (2011)
2.2.5. Physical Infrastructure in Sri Lanka
In the literature, the physical infrastructure of a nation has been found to influence the
extent of entrepreneurial engagements (Yusuf and Schindehutte, 2000, Acs and Virgill,
2000). Recent evidence suggests that, in Sri Lanka, a lack of physical infrastructure, such
38
as transport and telecommunication facilities, is a barrier to academic entrepreneurship
since it negatively affects communications between universities and industry (Esham,
2008). This has been due to the physical distance between Sri Lankan universities and
industry. Although most private sector companies are situated in the capital city of the
country (i.e. Colombo), as a result of a government strategy for rural development,
universities have been established throughout the country.
Even though the establishment of universities in rural areas is considered a strategy that
stimulates the emergence of clusters and promotes rural development in the long run,
Barkley and Henry (1997) have argued that such promotions might not necessarily work in
many rural communities. It seems that the Sri Lankan situation supports this view, since so
far, most Sri Lankan industries have not moved to these rural areas. As a result of the
physical distance between universities and industry, interactions between more peripheral
universities and centrally located companies might be inhibited by the poor quality of
physical infrastructure, such as transport and telecommunication links.
The above illustrated deficiency in infrastructure facilities in Sri Lanka is further
confirmed by De (2010). He has constructed a Physical Infrastructure Index (PII), which is
a composite of six physical infrastructure indicators; namely, roadways, railways, airports,
seaports, telecommunications, and electricity, calculated for 124 countries for the period
1995 to 2006. His study revealed that the per capita income of a country positively
correlates with the quality of physical infrastructure, where developing countries were
found to occupy the lowest rankings, while developed countries occupied the highest
ranking. Furthermore, with respect to geographical regions, South Asian countries
(including Sri Lanka) have been ranked lowly in comparison to other developed regions.
2.3. Chapter Summary
This chapter has discussed the nature of the resource constrained environment in which Sri
Lankan academics operate. Initially, the chapter, by referring to ‘National Innovative
Capacity Index’, developed by Porter and Stern (2002), argued that national level resources
influence innovation and entrepreneurship. Subsequently, in order to evaluate relative
resource scarcity of Sri Lanka, the chapter compared and contrasted the resource status in
Sri Lanka with different ‘income groups’ constructed by the World Bank (i.e. low income,
lower middle income, upper middle income, and high income countries). Additionally,
39
South Asian countries (i.e. Afghanistan, Bangladesh, Bhutan, India, Iran, Maldives, Nepal,
and Pakistan) were also used for this comparison, whereby the extent to which resources
status in Sri Lanka is similar to, or different from, countries in the same geographical
region was analysed.
It was evident that low government income, and its priority of poverty alleviation, have
resulted in a restricted government budget for education and research and development
(R&D) in Sri Lanka. This has resulted in skilled-labour shortages within the country.
Furthermore, judged in terms of three indicators, namely, high-technology exports, patent
applications, and internet usage, it was apparent that technological resources in Sri Lanka
were also significantly lower than high income, or middle income countries, while
somewhat similar to lower middle income or South Asian countries.
The discussion indicated that public research institutes, government ministries (those are
responsible for designing and implementing Science and Technology strategies), private
sector firms, formal and informal professional networks, and universities are the main
actors responsible for innovation and entrepreneurship in Sri Lanka. However, it was
evident that, even though these actors independently contribute to innovation, there is a
lack of collaboration between them. This was further confirmed by the Worldwide
Governance Indicator (WGI), which revealed that the quality of institutions in Sri Lanka
was far lower than high income countries, while similar to other low income or South
Asian countries.
It was also apparent that Sri Lanka lacks physical infrastructure, such as transport and
telecommunication facilities, which might have negative impacts on academic
entrepreneurship, particularly due to physical distance between Sri Lankan universities and
industry. Although most private sector companies were situated in the capital city of Sri
Lanka (i.e. Colombo), as a result of a government strategy for rural development,
universities were established throughout the country. Even though the establishment of
universities in rural areas was considered a strategy that stimulates the emergence of
clusters, so far, most Sri Lankan industries have not moved to rural areas. Therefore, the
poor quality of physical infrastructure, such as transport and telecommunication links, may
have been found to inhibit interactions between more peripheral universities and centrally
located companies. The chapter suggested that the status of Sri Lanka with respect to
financial, human, infrastructural, technological, and institutional resources (that are
40
relevant to academic entrepreneurship) was considerably lower than high and upper middle
income countries, but more or less similar to those of lower middle income and South
Asian countries. Hence, Sri Lanka is likely to be a resource constrained environment,
which is quite similar to other low income developing countries and South Asian nations.
41
Chapter 3: Academic Entrepreneurship: A Review of the Literature
The previous chapter of this thesis discussed the nature of the resource constrained
environment in which Sri Lankan academics operate. The purpose of this chapter is to
review the literature on academic entrepreneurship in order to provide a theoretical
background relevant to the objectives of this research. As the term implies, academic
entrepreneurship is considered a branch of the entrepreneurship literature (Mars and Rios-
Aguilar, 2010). Therefore, initially this chapter provides an overview of the
entrepreneurship literature. Subsequently, it illustrates the different definitions of academic
entrepreneurship used in the literature in order to derive a suitable definition with which to
investigate the nature of academic entrepreneurial engagement in the resource constrained
environment of Sri Lanka. Finally, the chapter discusses the literature relevant to factors
affecting, the impacts of, and barriers to, academic entrepreneurship. This discussion also
highlights contradictions and gaps in the literature.
3.1. The Definition of Entrepreneurship
Research on entrepreneurship can be traced back to the 19th century. Say (1816), who was
one of the earliest authors on entrepreneurship, defined an entrepreneur as someone who
obtains and organizes factors of production to create value. This view of entrepreneurship
argues that the roots of entrepreneurship are embedded in economics. Later, another
theoretical perspective, which differentiated entrepreneurs from any other business owner,
(Baumol, 1993) emerged. This viewpoint was strengthened by the seminal work of
Schumpeter (1950, 1934) who highlighted the significance of entrepreneurs by
emphasising their entrepreneurial role regarding innovation (Baumol, 1968, 1993).
Schumpeter described an entrepreneur as a ‘creative destructor’, who innovatively destroys
existing market equilibrium. Such destruction is perceived to be made possible mainly by
introducing new technological breakthroughs.
Defining entrepreneurship in terms of its impact on market equilibrium was extended by
Kirzner (1973) who exposed another facet of entrepreneurship. He defined an entrepreneur
as someone who identifies opportunities in an industry experiencing disequilibrium, and
makes profits by way of coordinating resources, which ultimately result in the creation of a
new equilibrium. Kirzner (1997) argued that the creative destruction of the existing
equilibrium argued by Schumpeter, and the creation of a new equilibrium in an industry
42
experiencing disequilibrium could happen simultaneously. According to Kirzner,
opportunities to introduce technological breakthroughs exist as a result of an already
existing disequilibrium not seen by others. Therefore, both the entrepreneurs that achieve
disequilibrium and equilibrium earn profits by way of reaching a new equilibrium, either
through creative destruction or resource coordination. In addition to this complementarity,
both Kirzner’s and Schumpeter’s entrepreneurs, highlight the significance of the
entrepreneur in the innovation process and delineate the fact that entrepreneurs make
strong contributions to economic growth.
With the highlighted significance of the role of entrepreneurs in the entrepreneurial
process, the use of the characteristics of entrepreneurs to define entrepreneurship became
common. Traits which were widely used in the literature to differentiate entrepreneurs
from non-entrepreneurs were the tolerance of ambiguity (Begley and Boyd, 1987), risk
taking propensity (Khilstrom and Laffont, 1979), hardworking nature (Southon and West,
2002), the internal locus of control (Chen et al., 1998), being optimistic (Cooper et al.,
1988), being committed (Timmons, 2003), challenge seeking nature (Khilstrom and
Laffont, 1979) and creativity (Timmons, 2003).
In addition to the importance of the entrepreneur, highlighted in the above definitions,
Casson (1982) has emphasized the importance of entrepreneurial opportunity. He stated
that entrepreneurs only differ from non-entrepreneurs in terms of having access to
information which is mandatory to perceive market opportunities when making
‘judgmental decisions’ (Casson 1982, pp. 24), and to coordinate scarce resources.
Judgmental decisions are non-routine, and have no obvious correct answer. Entrepreneurs,
as a result of having access to information, make these decisions which allow them to
capitalise on market opportunities unnoticed by others. Shane and Venkataraman (2000)
added further value to this definition, by describing entrepreneurship as a process of
capitalising on perceived opportunities by matching these with resources as a means of
accumulating wealth. In addition to recognizing the role of entrepreneurial opportunity,
these definitions take the emphasis of entrepreneurship definition away from economic
equilibrium towards opportunity identification (Shane and Venkataraman, 2000). Eckhardt
and Shane (2003) have also mentioned that it is more appropriate to define
entrepreneurship through opportunity identification than to define the entrepreneur as a
creator of a new equilibrium, since it is impossible to create a new equilibrium from
individual interventions.
43
Despite this lack of consensus, these different definitions seem to serve the purpose of
highlighting the myriad of facets of entrepreneurship. Additionally, this flexibility of
definition had resulted in the entrepreneurship literature being considered as a suitable
framework for a wide array of disciplines (Baumol, 1993). As a result, in recent years, with
the increased significance of knowledge-transfer activities, a large body of higher
education research has begun to use entrepreneurship frameworks (Mars and Rios-Aguilar,
2010). Hence, academic engagement in entrepreneurial endeavour has been referred to as
‘academic entrepreneurship’.
With the introduction of the Bayh-Dole Act in the US in 1980, and similar policies across
the world, a significant increase in university engagement in academic entrepreneurial
activities was observed (Rothaermel et al., 2007). Mowery and Shane (2002) referring to
the statistics of the Association of University Technology Managers (2000), stated that the
licensing revenues of US universities had increased by over 315% from 1991 to 1997.
Further, spin-off companies, established from 1980 to 1999 by US universities, have
created 280,000 jobs (O'Shea et al., 2005). Following this trend research publications,
focused on university entrepreneurship, have also remarkably increased since the late
1990s with a significant boost from 2000 to 2005 (Rothaermel et al., 2007).
3.2. The Definition of Academic Entrepreneurship
The term academic entrepreneurship has mostly been used in a focused manner to illustrate
academics’ engagement in the formation of spin-off companies (Radosevich, 1995,
Samson and Gurdon, 1993, Daniels and Hofer, 1993). However, other authors have also
used the term to represent a much broader spectrum of knowledge-transfer activities
(Jones-Evans and Klofsten, 2000). Therefore, the following Sections of the chapter analyse
these two major ways of defining academic entrepreneurship in order to select an approach
appropriate to the study of academic entrepreneurial engagement in the resource
constrained environment of Sri Lanka.
3.2.1. Defining Academic Entrepreneurship: The Focused View
The significance of the formation of academic spin-off companies across the world as a
means of generating wealth in universities and the wider economy (Shane, 2004, Wright et
al., 2004) has necessitated in-depth research on aspects related to spin-off activities, and
44
thus, the focused definition was of value for these studies. For example, the literature had
used a focus definition to investigate the heterogeneity of spin-off companies. According
to Mustar et al. (2006), who developed a taxonomy of research-based spin-off companies,
these companies are heterogeneous in terms of the type of resources used, business models
adopted, and institutional links developed. Owing to this heterogeneity, they suggest that
policy makers should design better targeted policies by addressing the specific needs of
spin-offs, rather than arguing these to be homogeneous.
Moreover, Wright et al (2007) have indentified three types of spin-offs in a recent
European study; namely, venture capital backed spin-offs, prospector spin-offs, and
lifestyle spin-offs. The first category is established by a team of technologically well
renowned researchers and venture capitalists in order to commercialise a technological
advancement. The second type comprises university or public research laboratories formed
through external public or private funding, and intended to produce commercially valuable
products. The third type is formed by researchers and professors with consulting
experience in order to carry out contract research and/or consultancy. Similarly, through
research carried out in China, Eun et al. (2006) differentiated spin-offs from University
Research Enterprises (UREs). UREs are established, staffed, funded, and controlled by
universities, while spin-offs are set up by individual academics from personally raised
funds and “off-duty” inventions. It was the use of the focused definition in the above
studies that has been useful in unveiling the heterogeneity of academic spin-off companies,
and their specific needs.
In line with the focused definition of academic entrepreneurship, the term academic
entrepreneur has been used to differentiate academics who have engaged in spin-off
formation from those who have not. As illustrated in Table 3.1, some studies have
attempted to demarcate the boundary of the definition by considering the specific role of
the academic in spin-off formation; for example, the extent of involvement by the
academic (full-time or part-time), the objective of spin-off formation (growth oriented or
technology oriented), or whether the academic was the founder of the company, are some
of the criteria used to define an academic entrepreneur.
Despite having no consensus on the definition of an academic entrepreneur, these different
classifications have served the purpose of helping to understand the different roles played
by individual academics in the spin-off formation process, and their wider impacts. For
45
example, the differentiation between academic entrepreneur and entrepreneurial academic
by Meyer (2003) had resulted in the highlighting of a policy dilemma of unsuccessful
attempts to promote academic entrepreneurship. According to Meyer, even though a public
support mechanism is interested in promoting ‘academic entrepreneurs’ who form fast
growing academic enterprises, in reality, this has only resulted in the production of
‘entrepreneurial academics’ who form companies to pursue their research interests, which
hampers fast growth.
Table 3.1: The Definition of Academic Entrepreneur
Reference
Basis for differentiation
Term Description
(Radosevich, 1995)
Whether the academic going to be the founder of the company
Academic/Inventor Entrepreneur
Academic who acts as the founder of a ‘spin-off’ company established mainly with the objective of commercializing technological innovation
Surrogate Entrepreneur
Not the actual inventor but has acquired the right for a technology from the university and intends to commercialise it.
(Meyer, 2003, Dickson et al., 1998)
(1) Full-time or part-time engagement (2) the main interest for forming the venture (3) the type of knowledge
Academic entrepreneur
Academic who engaged in entrepreneurial activity in addition to their academic work.
Entrepreneurial scientist
Scientist who is engaged in the business venture on full-time basis while still essentially devoted to scientific interests
Scientific entrepreneur
One with both scientific and business knowledge, operating in a scientific business venture on full-time basis.
(Meyer, 2003)
(1)The expectation on growth of the venture (2) Objective for the formation of the venture
Entrepreneurial academic
Scientists in public sector organizations who are basically relying on public research grants, have achieved moderate-growth (e.g. start-up in an incubator facility with little management advice and a small network of business contacts) where not necessarily interested in achieving a fast growth but are looking for avenues in which they can pursue their research interests.
Academic Entrepreneur
Academic who is interested in establishing a fast-growing venture.
(Nicolaou and Birley, 2003)
(1) Level of involvement of the academic in the venture (2) The existing relationship between academic and university
Academic Entrepreneur (in Orthodox spinout)
Academic who has left their host university to form a company and such a company was named as orthodox spinout.
Academic in Technology spinout
The inventor academic who sold the intellectual property to an outside investor/manager to form a company where the academic has no involvement in running the company. But academic might have equity in the company and/or involves in offering advice on a consultancy basis.
Academic in Hybrid spinout
Inventor(s) who also acts as a founding academic(s) by holding a directorship, membership of the scientific advisory board or other part time position within the company while being attached to the university.
This focused research also discusses scepticism over the ability of academics to manage
their basic role while simultaneously engaging in the formation and management of spin-
46
offs (Wright et al., 2004). Delays encountered as a result of having academic partners in
the commercialization process, and company creation being time consuming and risky
(Franklin et al., 2001) are other problems with academic entrepreneurship highlighted in
these studies. Additionally, by using the focused view to analyse the effects of the Bayh-
Dole Act, Mowery and Sampat (2005) have questioned its appropriateness and highlighted
the risk of providing a skewed emphasis on patent oriented activities, while neglecting
other forms of technology transfer. Based on the above discussion it is apparent that the
focused definition has been of use in studying the heterogeneity of the spinoff process, the
role of academics in this process, and the effectiveness of their engagement, as well as
highlighting the policy implications of spin-off formation.
3.2.2. A Definition of Academic Entrepreneurship: The Broader View
Some studies define academic entrepreneurship as an academic’s engagement in a broad
spectrum of knowledge-transfer activities. For example, Jones-Evans and Klofsten (2000),
studying academic entrepreneurship in Sweden and Ireland, defined academic
entrepreneurship as the academic’s engagement in activities in addition to their normal
academic duties. Based on this broader definition, several activities have been identified in
the literature as academic entrepreneurial activities. Some of these activities are external
teaching (Jones-Evans, 1997), consultancy (Glassman et al., 2003, Jones-Evans, 1997,
Louis et al., 1989, Goldfarb and Henrekson, 2003), conducting training and seminars for
industry (Schmoch, 1997), joint research projects with industry (Louis et al., 1989),
developing patents (Glassman et al., 2003, Jones-Evans, 1997, Siegel et al., 2004) and the
formation of business ventures (Glassman et al., 2003) (Table 3.2. illustrates a full list of
these activities).
47
Table 3.2: Academic Entrepreneurial Activities
Academic Entrepreneurial Activities Reference 1. External teaching
(Jones-Evans, 1997)
2. Initiating the development of new degree programmes
(Laredo, 2007)
3. Placing students as trainees in the industry (D’Este and Patel, 2007) 4. Conducting seminars and training sessions for industry
(D’Este and Patel, 2007, Schmoch, 1997)
5. Working in the industry (research based) (Lashley, 2011, Arlett et al., 2010) 6. Research based consultancy for industry through university centres 7. Research based consultancy privately
(Glassman et al., 2003, Jones-Evans, 1997, Louis et al., 1989, Goldfarb and Henrekson, 2003)
8. Collaborating with industry through joint research projects
(Louis et al., 1989)
9. Acquiring research funding from government, non-governmental or international bodies (those without collaborations with industry)
(Lockett and Wright, 2005)
10. Developing products or services which have potential for commercialization.
(Glassman et al., 2003, Jones-Evans, 1997, Siegel et al., 2004)
11. Research related assistance to small business owners.
(Wani et al., 2003)
12. Contributing to the formation of joint ventures in which university and industry are the joint partners. 13. The formation of joint venture/(s) privately through collaborating with industry
(Louis et al., 1989, Goldfarb and Henrekson, 2003, Hall et al., 2001)
14. Contributing to the formation of one or more new spin-off companies 15. The formation of your own company/(s) 16. Contributing to the formation of university centres designed to carry out commercialization activities
(Radosevich, 1995, Samson and Gurdon, 1993, Daniels and Hofer, 1993)
17. Contributing to the establishment of university incubators and/or science parks
(Mian, 1996)
Such a broader definition has been used to study the dynamism with respect to academic
engagement in different entrepreneurial activities. For example, Jain et al (2009), in
studying modifications to the role identity of academics, revealed that most academics
perceive that their identity changes, not only when they become involved in spin-off
formation, but also through their involvement in other forms of knowledge-transfer
activities. Therefore, the authors highlight the importance of considering these changes in
deriving relevant university policy. In some research, an academic’s engagement in
different knowledge-transfer activities was considered to be a process in which academics
initially engage in activities involving less interaction with industry, and subsequently
decide to engage in such activities as company creation (Tijssen, 2006). In line with these
48
arguments, Franzoni and Lissoni (2009) have highlighted the importance of emphasising
dynamism with respect to an academic’s engagement in a spectrum of knowledge-transfer
activities, when designing incentive structures to encourage academics.
This broader definition has also been of use in comparing and contrasting different
academic entrepreneurial activities. The literature has highlighted a higher prevalence of
academic engagement in other knowledge-transfer activities when compared to that of
spin-off formation (Faulkner and Senker, 1995, Arundel and Geuna, 2004, Jones-Evans
and Klofsten, 2000, Louis et al., 1989). For instance, Cohen et al., (2002), found that
licensing and venture creation by academics represented only a minor part of their
technology transfer activities. According to Cohen et al., public conferences and meetings,
papers and project reports, informal information exchange, and consultancy are more
frequent modes of technology transfer. Similarly, Agrawal and Henderson (2002), have
also stated that patents represent less than 10% of the total knowledge transfer from their
labs. Additionally, Jones-Evans (2000, 1997) in a similar study in Europe, mentioned that
there is a higher propensity for academics to carry out contract research, consulting, large
scale science projects, and external teaching than spin-off formations. Further, D’Este and
Patel (2007), in their European study, found that other knowledge-transfer activities are
equally, or even more, important than company creation, both in terms of frequency and
economic impact. A higher occurrence of these forms of knowledge transfer was mainly
due to their rapidity, their less demanding nature in term of university resources, and their
lower expense (Jones-Evans, 2000).
Therefore, it can be concluded that the broader definition has been useful in understanding
the dynamism of the academic entrepreneur with respect to engaging in a wide range of
knowledge-transfer activities and in comparing and contrasting different academic
entrepreneurial activities in terms of frequency and economic impact.
3.2.3. The Definition of Academic Entrepreneurship for this Study
The above analysis of the “focused” and “broader” definitions of academic
entrepreneurship suggests that specific research questions require specific definitions of
entrepreneurship. Therefore, the selection of a definition in this case had been dependent
upon the objectives of the thesis. This is a strategy often adopted and recommended in the
entrepreneurship literature (Hebert and Link, 1989, Gartner, 1990). On this basis, it was
49
decided to select a definition which is more suitable to address the main objective of this
research, which is to investigate the nature of academic entrepreneurial engagement in the
resource constrained environment of Sri Lanka. Therefore, it was decided that the broader
definition of entrepreneurship is more suitable than the focused approach, since in this
instance, due to resource constraints, knowledge-transfer activities might be more
prevalent than spin-off formation. Moreover, the fact that no prior research on academic
entrepreneurship has been conducted in Sri Lanka further supports the above selection,
since the broader definition allows investigation of the whole subject of academic
entrepreneurship. It could also be argued that, if the effect of university and government
related factors are to be discussed, and meaningful policies on academic entrepreneurship
are to be derived, it is important to consider a broad spectrum of academic entrepreneurial
activities (D’Este and Patel, 2007).
However, although the broader definition attempts to categorise different knowledge-
transfer activities as ‘academic entrepreneurial activities’, it does not define this term
theoretically (Mars and Rios-Aguilar, 2010). Therefore, this thesis decided to use a
definition of entrepreneurship to define the broad definition of academic entrepreneurship.
By doing so, this current study attempts to position academic entrepreneurship within
general entrepreneurship theory.
The definitions of entrepreneurship derived by considering the entrepreneur as a ‘creative
destructor’ who destroys the existing equilibrium using his/her innovations (Schumpeter,
1934), or as someone who coordinates resources to move the economy to a new
equilibrium (Kirzner, 1973), assume that the entrepreneur makes radical changes.
However, it is questionable to what extent academics can make radical changes or move
the economy to a new equilibrium, by engaging in knowledge-transfer activities alone,
although spinoff companies might be involved in the development of highly destructive
technologies. Therefore, these definitions were not considered as appropriate to embody
the broader definition of academic entrepreneurship. On the contrary, the definition of
Shane and Venkataraman (2000), which recognised entrepreneurship as capitalising on
perceived opportunities by matching these with resources as a means of accumulating
wealth, seems to be more in line with the broader perspective of academic
entrepreneurship. This is mainly because perceiving and capitalising on opportunities are
important to engage in both knowledge transfer activities and spin-off formation.
50
Therefore, by adopting the definition of Shane and Venkataraman (2000), academic
entrepreneurship is defined as academics capitalising on perceived ‘opportunities’ by
matching these with resources which results in the accumulation of ‘wealth’. This study,
considering socially oriented entrepreneurship, defined ‘wealth’ as monetary and/or
social/non-monetary outcomes of entrepreneurial engagement (Mars and Rios-Aguilar,
2010). Following Eckhardt and Shane (2003) opportunities are defined as ‘situations in
which new goods, services, raw materials, markets and organizing methods can be
introduced through the formation of new means, ends, or means-ends relationships’ (pp.
336). Means and ends resemble actions and outcomes in which people have different
beliefs about the value of resources. For example, engaging in new ways of combining
resources to produce innovative products (means), which result in entrepreneurs
accumulating wealth (ends), are called the “means-ends” relationships (Shane et al., 2003).
It could also be stated that entrepreneurs are involved in the identification and the creation
of new means and ends, while non-entrepreneurs utilise previously established means and
ends (Eckhardt and Shane, 2003).
This suggests that, in addition to knowledge-transfer activities, the introduction of new
means and ends to the normal academic duties of academics also represent academic
entrepreneurship. A similar argument was made by Etzkowitz et al (2000) in a comparative
study of Europe, Asia, South and North America by stating that universities could be
entrepreneurial through introducing innovations to teaching. Thus, the definition of
academic entrepreneurship used in this study is in line with other research studies (e.g.
Laredo 2007) that acknowledge the existence of a link between academic entrepreneurship
and normal academic duties. However, it should be noted that the level of entrepreneurship
would differ, depending upon the nature of academic entrepreneurial activity. For example,
academic involvement in the formation of spin-off companies could be considered
showing a higher level of entrepreneurship than engaging in external teaching.
3.3. Academic Entrepreneurial Engagement in a Resource Constrained Environment
Powers and McDougall (2005), utilizing data from 120 US universities, found that the
financial, human, and organizational capital of universities are strong predictors of
academic entrepreneurial success. A lack of research capacity and resources in universities,
a limited absorptive capacity of both universities and industry, underdeveloped
intermediary institutions, and a lack of funding provided by governments characterise a
51
resource constrained environment (Eun et al., 2006, Adesola, 1991, Bowonder, 2001)
(Monck and Segal, 1983).
In the resource based view theory, it is argued that firms decide to produce when they have
sustainable competitive advantage, which is achieved by possessing rare, valuable,
imperfectly imitable and non-substitutable resources (Barney, 1991). Based on this view,
Eun et al. (2006) have argued that, if the resource status of the university is weak, there is a
lower tendency for academics to engage in entrepreneurial endeavour, and vice versa.
Similar arguments were made by research which highlighted the possibility of conflicts
arising from trying to balance limited resources, with academic entrepreneurship and
normal academic duties (Monck and Segal, 1983, Adesola, 1991).
However, the general entrepreneurship literature argues that the ownership of resources is
not mandatory, and entrepreneurs generally go beyond their safe resource limitations to
capitalize on perceived opportunities (Kirzner, 1973, Saylor, 1987, Hart et al., 1995).
These studies have argued that entrepreneurs creatively find alternative means of making
use of resources when capitalising on opportunities (Shane and Venkataraman, 2000).
Therefore, it could be argued that, while the resource based view is applicable in a
resource-rich environment, in resource constrained universities, entrepreneurs may use
academic entrepreneurship as a vehicle with which to overcome resource barriers.
Besides these internal resources, the external macro environment, which mainly comprises
industry and government, also affects academic engagement in entrepreneurial endeavour
(O’Shea et al., 2004, Siegel et al., 2004). Etzkowitz and Leydesdorff (2000) when
introducing their Triple Helix III model highlighted the importance and the role of
government in mediating the academic entrepreneurial process. Government support in
terms of policy initiatives and public funding to foster university industry interaction/
academic entrepreneurship was found to contribute to academic entrepreneurial success
(Shane, 2004). In contrast, a lower absorptive capacity of industry (Eun et al., 2006), a lack
of resources in the macro environment (Monck and Segal, 1983, Adesola, 1991), and
underdeveloped intermediary institutions could hamper academic entrepreneurship.
Therefore, it could be argued that a resource constrained macro environment inhibits
academic entrepreneurship.
52
However, academic entrepreneurship is also viewed as a potent solution for plummeting
direct funds available to universities from the government (Phan and Siegel, 2006, Wright
et al., 2006, Adesola, 1991). Therefore, it could be conversely argued that a lack of
resources in the macro environment may induce academic engagement in entrepreneurial
endeavour. The general entrepreneurship literature also supports this argument by stating
that, in extremely unpromising and constrained environments, entrepreneurial skills are
very important in spotting opportunities and matching these with available resources, and
thus, more entrepreneurial behaviour is often observed in such contexts (Kodithuwakku
and Rosa, 2002). Accordingly, resource barriers have been identified as pushing academics
to be more entrepreneurial in order to overcome these constraints (Adesola, 1991, Gilad
and Levine, 1986).
Based on the above arguments, this study argues that, in a resource constrained
environment (both university/internal and macro environment), academics may engage in
entrepreneurial endeavour in order to overcome resource barriers, which will in turn
enhance opportunities and resources for them to engage in academic entrepreneurial
endeavour. In other words, it could be argued that, while resources assist entrepreneurship
in a resource-rich environment, being entrepreneurial might be a means to become
resource-rich in a resource constrained environment.
3.4. Multiple Academic Entrepreneurial Activities carried out by Academic
Entrepreneurs
Even though an individual academic is considered the major driving force of academic
entrepreneurship, (D’Este and Patel, 2007, Ambos et al., 2008) the literature has mainly
attempted to analyse different academic entrepreneurial activities, without putting due
emphasis on the academic entrepreneur (Jain et al., 2009, Wright et al., 2007, Yang et al.,
2006, Krabel and Mueller, 2009, Link and Siegel, 2007). On the other hand, even the
literature, which considers the academic entrepreneur as the key unit of analysis, has
mostly analysed academic engagements in spin-off formations. This has resulted in a lack
of emphasis on the wide array of entrepreneurial activities that academics are often
engaged in (Fini et al., 2010).
Among few studies that focus on individual academics, Tijssen (2006) identifies three
phases of ‘being entrepreneurial’. He argues that academics move from an initial
53
application oriented/science driven phase (which relates to the entrepreneurial awareness
within the university unit, or industry's awareness of university research and researchers),
then on to product oriented phase (which relates to university–industry interactions, such
as contract research and joint research), and finally to a business oriented/market driven
phase (including patents and licences, and other related indicators of commercialisation
efforts). According to Tijssen, the level of entrepreneurship is minimal in the first phase,
while it is at the highest in the third phase. He considers the shift from the first to the third
phase as a process of becoming entrepreneurial. He also argues that moving to the third
phase does not result in academic disengagement from other two phases, since academics
tend to engage in combinations of entrepreneurial activities. Thursby et al. (2005) also
argue that patenting, spin-offs, consulting, and joint-research agreements interact when
transferring university generated knowledge, which induces academics to engage in
multiple academic entrepreneurial activities. Similarly, D’Este and Patel (2007) state that
academics tend to interact with industry for diverse reasons, and that a combination of
activities will allow them to achieve these multiple goals. The same authors have further
argued that carrying out a number of activities may bridge the gap between industry and
academia more effectively than relying on one mechanism.
Alongside these developments, Wright et al. (2004) have highlighted the need for, and the
importance of, studying academics who are engaged in multiple business ventures
simultaneously, which he names “portfolio academic entrepreneurs”. In line with this, the
current study argues that an academic’s engagement in a combination of academic
entrepreneurial activities is also portfolio entrepreneurship, and thus, could be used as a
basis for identifying portfolio entrepreneurs. Jain (2009), by considering the extent of
engagement in traditional job roles and academic entrepreneurship, had identified a
spectrum with two extreme ends; namely, ‘pure’ scientists and ‘pure’ entrepreneurs. Even
though the focus of Jain (2009) is slightly different to that of this research, it provides
evidence of the need to identify different academic entrepreneurs, depending on the diverse
combinations of academic entrepreneurial activities in which academics are engaged.
Therefore, this research will attempt to construct and identify typologies of academic
entrepreneurs, based on the different combinations of academic entrepreneurial activities.
These typologies will represent the nature of academic entrepreneurial engagement in any
given context.
54
3.5. Synergistic Effects of Diversifying Academic Entrepreneurial Activities
The diversification and portfolio entrepreneurship literature argues that an engagement in
multiple entrepreneurial activities provides additional benefits due to the synergies that can
develop between activities (Westhead et al., 2005, Alsos et al., 2003). Elsewhere,
considering dynamic capabilities of firms Chandler (1990) had argued that, when firms
grow, employees develop capabilities that provide firms with competitive advantage.
Hence, it is possible that academics, during the diversification process, may develop
additional capabilities due to interactions between different entrepreneurial activities. This
phenomenon of generating synergistic effects is defined in the literature on systems theory
as ‘the whole is better than the sum of its parts’ (Von Bertalanffy 1972, pp 407). Adapting
from this definition, for the purpose of this study, synergistic effects are defined as
‘additional benefits generated by plural active academic entrepreneurs as a result of
interactions between entrepreneurial activities’. Some of these synergistic effects,
identified in the literature, are social networking (Westhead et al., 2005, Mayer and
Schooman, 1993), knowledge and skills (Shane, 2000, Westhead et al., 2005, Alsos et al.,
2003), input-output flows, and physical resources (Westhead et al., 2005, Alsos et al.,
2003) Hence, these are regarded as relevant to academics diversifying the entrepreneurial
activities considered here.
The literature has mentioned that the social network of academics is very important when
engaging in academic entrepreneurial endeavour. Social networks have been recognized as
important when obtaining resources (Birley, 1985, Mayer and Schooman, 1993),
identifying opportunities, and acquiring legitimacy (Aldrich and Fiol, 1994). Besides
reaping benefits from contacts with industrial partners (Krabel and Mueller, 2009),
networking with peers with commercialization experience has also been found to have
positive impacts on entrepreneurial endeavours (Azoulay et al., 2007). The portfolio
entrepreneurship literature suggests that those who carry out multiple entrepreneurial
activities are capable of forming, and working in, productive teams, owing to their
extensive network of contacts (Westhead et al., 2005).Therefore, this study argues that,
when an academic is engaged in multiple entrepreneurial activities, he or she could
capitalise on a network of contacts developed from one activity to carry out another
activity, which generates synergistic effects.
55
Recent evidence suggests that when entrepreneurs are engaged in multiple entrepreneurial
activities, they make use of knowledge and skills developed from one activity to engage in
another activity. As a result, the literature has stated that portfolio entrepreneurs have a
higher ability to identify and capitalise on opportunities than other entrepreneurs
(Westhead et al., 2005, Alsos et al., 2003). On the other hand, a lack of knowledge and
skills on business management, entrepreneurship, and the application of theory has been
recognized as barriers to achieving success during academic entrepreneurial engagement
(Franklin et al., 2001, Monck and Segal, 1983, Fowler, 1984, Dickson et al., 1998).
Accordingly, the current study argues that knowledge and skills developed by engaging in
entrepreneurial activities might be used by academic entrepreneurs to further diversify
their entrepreneurial activities, which generate knowledge and skill synergies.
The academic entrepreneurship literature has argued that one reason why academics form
spinoff companies is to commercialise their knowledge. In such an instance a patent, which
is an output of one entrepreneurial activity (i.e. applied research or joint research projects
with industry), might be used as an input to a spinoff company (Eun et al., 2006).
Furthermore, it may also be the case that the output of one consultancy assignment or joint
research project might be used as an input to another project. Hence, input output flow is
considered another type of synergistic effect.
The literature suggests that an engagement in multiple income generation activities enables
resources acquired from one activity to be used in another activity (De Silva and
Kodithuwakku, 2011). The efficacy of this phenomenon might be high in resource
constrained environments, since it is necessary to utilize resources efficiently and
effectively in order to go beyond resource limitations and be successful through
entrepreneurial engagements (Vyankarnam, 1990). Hence, it could be argued that the
carrying out of a combination of academic entrepreneurial activities may result in
synergistic effects in terms of physical resources.
3.6. Academic Motivation
Engagement in academic entrepreneurial activities is not achieved without friction.
Maintaining a balance between normal academic duties and entrepreneurial activities, and
managing cultural differences between academia and industry have been identified in the
literature as challenging (Jones-Evans, 1997). Moreover, a lack of entrepreneurial skills
56
among academics (Laukkanen, 2003), and a reward system that does not intend to promote
academic entrepreneurship (Jones-Evans, 1997), have been viewed as hindering the
potential benefits of academic entrepreneurship. Hence, in recent years, there has been
increasing interest in the investigation of what motivates academics to engage in
entrepreneurial endeavour, despite experiencing a reward system that mainly values
publications (Jones-Evans, 1997).
Motivation can be defined as the cognitive decision making process through which goal
directed decision making behaviour is initiated, energized, directed, and maintained
(Huczynski and Buchanan, 2007). The general entrepreneurship literature, categorizes
‘motivation’, under two major headings; namely, ‘pull’ and ‘push’. ‘Push’ motives are the
elements of necessity in which entrepreneurs start new businesses as a way of overcoming
negative external influences, while in contrast, ‘pull’ motives are attractive reasons why
entrepreneurs decide to form new ventures (Gilad and Levine, 1986). It is stated in the
literature that the motives of entrepreneurs play critical roles in the entrepreneurial process
by identifying and capitalizing on opportunities (Shane et al., 2003, Ambos et al., 2008).
Moreover, the significance of individual motive is higher when there is a lack of, or no,
institutional support for academics to assist them in engaging in entrepreneurial
endeavours (Erdıs and Varga, 2009). Therefore, this Section reviews the literature, which
illustrates the role of entrepreneurial motivation.
The motivation of academics is found to shape their behaviour, and in turn, the level of
their success achieved through entrepreneurial engagement (Jones-Evans, 1997). For
example, Franklin et al (2001), in studying UK universities, stated that, when academics’
desire for novelty overtakes that of wealth, the growth and the success of their ventures can
be retarded. Similarly, Otto (1999), in considering the European context, states that, if
academic entrepreneurs are mainly motivated by the need to make use of technical
expertise, the growth and the success of their ventures will be negatively affected. In
discussing technical entrepreneurship process, Oakey (2003) identified motivation as a key
strategic drive which determines the nature of involvement of entrepreneurs in their
businesses; motivation determines the way in which entrepreneurs capitalize on technical
and business management skills, the extent to which they access external resources, and
the degree to which they control the daily operations of the business. Oakey further states
that entrepreneurs who are motivated by need for control, which is a sub-motive of need
57
for independence, might cause conflict, if their ability to control the venture is threatened
by external agents (e.g. banks, venture capitalists).
Entrepreneurial motivation has also been identified in the literature as determining the type
of academic entrepreneurial engagement. For example, Jones-Evans (1997) stated that
when academics are motivated only by a need to earn additional income, they tend to
engage in consultancy rather than face the hazards of company creation. The literature has
also revealed that academics are often driven by diverse motives. Based on this, D’Este
and Patel (2007) argue that it is the combination of academic entrepreneurial activities
which provide entrepreneurs with the ability to satisfy different motives, such as the need
to access industrial resources, to learn from industrial problems, and to earn an additional
income. D’Este and Patel further elaborate this by stating that, while consultancy allows
entrepreneurs to earn an additional income, joint research provides access to industrial
resources and skills. As a result, a single mechanism may not be sufficient to satisfy these
multiple motives. Therefore, it could be stated that, since academics are motivated by
diverse motives, they often tend to engage in several academic entrepreneurial activities
simultaneously.
The literature also attempts to relate these motives to the context in which entrepreneurs
operate. For instance, Global Entrepreneurship Monitor (GEM) project (2006), by
analysing the motivations of entrepreneurs in different countries, differentiated opportunity
driven entrepreneurs from necessity driven entrepreneurs. Opportunity driven
entrepreneurs are those who are motivated by a need to capitalize on perceived business
opportunities, which is a pull motive, whereas necessity driven entrepreneurs are motivated
by a necessity, which is a push motive. GEM concluded that the majority of opportunity
driven entrepreneurs were found in high income countries, while necessity driven
entrepreneurs were found in middle or low-income countries (Bosma and Harding, 2006).
This was further supported by (Acs, 2006) who revealed that, the higher the level of
economic development, the higher the ratio of opportunity to necessity entrepreneurs.
Based on these arguments, it is possible to propose that, in a resource constrained
environment, academics might be mainly motivated by push motives.
However, previous studies have also shown that motives may change during the process of
business growth. For instance, de Silva and Kodithuwakku (2011) found that, in an
extremely constrained environment, entrepreneurs are initially ‘pushed’ to engage in
58
entrepreneurial activities, but subsequently, as the business develops, the motive changes
from push to pull. Similarly, Rosa et al (2006) have argued that entrepreneurs who start
their businesses with a necessity motive often shift their focus to opportunity as the
business grows. By adopting this concept, this research argues that, in a resource
constrained environment, an academic’s engagement in entrepreneurial activities may be
initially motivated by push motives, but subsequently, by pull factors.
3.7. Multi-level Factors affecting the Nature of Academic Entrepreneurial
Engagement
Previous research on academic entrepreneurship has identified three major actors involved
in the process of academic entrepreneurship, namely academics, universities, and external
environments (mainly involving government and industry) (O’Shea et al., 2004, Etzkowitz
and Leydesdorff, 2000). As illustrated in Figure 3.1, these different parties could be
categorised into three levels namely, micro, meso, and macro. The academic entrepreneur
is considered to represent the micro level, while universities are at the meso level, and
industry and government are on the macro level. The characteristics of each party, as well
as the nature of interactions between them, have been identified as major determinants of
the success of academic involvement in entrepreneurial activities (O’Shea et al., 2007).
Therefore, the following Sections of this chapter discuss the literature on how academic
entrepreneur, the university, the government, and industry influence academic
entrepreneurship.
Figure 3.1: The Effect of Multi-level Factors on Academic Entrepreneurship
ACADEMIC
ENTREPRENEURSHIP
Micro- Academic Entrepreneur
Meso- University
Macro- Government, Industry
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3.7.1. Academic Entrepreneur and Academic Entrepreneurship
Based on research carried out in the UK, D’Este and Patel (2007) have stated that the
personal characteristics of academics have a greater impact on determining their success
than the characteristics of their academic departments or universities. Furthermore, Ambos
et al (2008), who claim to be the first to conduct research on academic decision to
commercialize university generated knowledge, revealed that the personal characteristics
of academic has a greater influence on his/her decision than organizational factors.
Similarly, the entrepreneurship literature has also stated that successful entrepreneurial
outcomes are mainly determined by the quality of the entrepreneur (Herron and Sapienza,
1992).
Age (Audretsch, 2000), position (Levin and Stephan, 1991), gender (Smith-Doerr, 2004),
knowledge and skills (Franklin et al., 2001), experience (Agarwal et al., 2004), academic
discipline (Mowery and Sampat, 2005) and the social network (Siegel et al., 2007) of
academics have all been identified in the literature, as personal characteristics affecting
academic entrepreneurship. Therefore, the following Sections of this chapter review the
literature on the effects of these factors on academic entrepreneurship.
3.7.1.1. The Age and Position of the Academic
Despite age being identified as a factor affecting academic entrepreneurial engagement,
there is no consensus with respect to the nature of this effect. Since the age and the position
(lecturer/professor) of an academic seem to be highly positively correlated (Levin and
Stephan, 1991), this Section discusses the literature on both of these factors.
Audretsch (2000), in a study which investigated the propensity of academics to establish
biotechnology firms, concluded that older academics, with longer scientific experience,
have a higher tendency to engage in company creation. This view is further supported by
Levin and Stephan (1991) who state that well established academics have a higher
propensity to engage in academic entrepreneurship, in comparison to those who are at the
initial stages of their career. Levin and Stephan explain this by stating that experienced and
renowned scientists/professors, who do not have much pressure for publications, capitalize
on their experience, credential, and stronger social network to engage in entrepreneurial
60
activities. In contrast, young researchers, who have not yet developed their reputation, are
more focused on publications.
However, other research has revealed that younger scientists, who are trained on the basis
of new paradigms, have a better understanding of both academic and market demands.
Therefore, they tend to engage in academic entrepreneurship to a greater extent and to
produce high quality outputs through such engagements (Owen-Smith and Powell, 2001,
Zucker et al., 2002, Ambos et al., 2008, Lam, 2005). Similarly, D’Este and Patel (2007)
found that, in applied disciplines, the younger the scientist, the higher the probability of
him or her engaging in academic entrepreneurial endeavour. Bercovitz and Feldman (2003)
support this view by stating that researchers, a few years after completing their PhDs, have
more ability to interact with industry, and thus, to engage in entrepreneurial activities. In
line with this argument, Markides (2007) also stated that older academics have a lower
tendency to carry out entrepreneurial activities, since they may not be interested in
changing their academic life style.
Amid these contradictions with respect to which age group engages in academic
entrepreneurship to a higher degree, Krabel and Mueller (2009) stated that both young
scientists, who are pursuing their PhD degrees without a tenured position, as well as
Directors or Professors with tenured position, are more likely to engage in entrepreneurial
endeavour. Interestingly, in this debate on contradictions with respect to the effect of old
and young academics, Jones-Evans and Klofsten (2000) found that middle aged academics
have a higher tendency to engage in entrepreneurial endeavour than other age groups.
Accordingly, it could be concluded that, even though age and position have been identified
as factors which help determine an academic’s engagement in entrepreneurial endeavour,
the effect of age remain controversial.
3.7.1.2. The Gender of the Academic
Some research has found gender to be a determining factor regarding the extent to which
academics engage in entrepreneurial endeavour. From research carried out in the life
sciences, Whittington and Smith-Doerr (2005) have concluded that, despite the commercial
value of patenting being the same for both the genders, females have a lower propensity to
obtain patents than their male counterparts. It was also revealed that male academics have
61
a higher tendency to engage in a wider array of academic entrepreneurial activities (Jones-
Evans and Klofsten, 2000). However, Murray and Graham (2007), in US research,
revealed that despite the above mentioned gender difference, the gap has been reduced as a
result of institutional support.
3.7.1.3. The Knowledge and Skills of the Academic
The knowledge and skills of academics in relation to scientific/technological aspects,
potential applications, and relevant business/market have been identified as influencing the
success of academic entrepreneurial engagement (Dickson et al., 1998, Franklin et al.,
2001). Entrepreneurial skills are considered to be crucial, particularly when forming
academic spin-off companies (McMullan and Vesper, 1987, Henderson et al., 1998,
Mowery et al., 2002). On the other hand, a lack of entrepreneurial, business and
management skills has been recognized as a barrier to achieving the success of ventures
formed by academics (Franklin et al., 2001, Monck and Segal, 1983, Fowler, 1984, Lockett
et al., 2003). Therefore, it could be concluded that high levels of scientific/technical as well
as business/ entrepreneurial knowledge and skills positively promote academic
entrepreneurial success.
3.7.1.4. The Experience of the Academic
The prior experience of academics has been recognized as playing a major role in their
success in entrepreneurial endeavour. This argument is supported by the theory of path
dependency, which states that current involvements are a function of past experience
(Adkins, 1995, Floyd and Wooldridge, 1999). An academic’s experience in collaborating
with industry (Feeser and Willard, 1990, Barnes et al., 2002, D’Este and Patel, 2007),
raising funds (Landry et al 2005), forming new ventures (Stuart and Abetti, 1990, Mosey
and Wright, 2007), obtaining patents (Krabel and Mueller, 2009), engaging in management
related activities (MacMillan et al 1985), and working in industry (Almeida and Kogut,
1999, Packalen, 2007) are all identified as having positive effects on academic
entrepreneurship. Prior experience enables academics to understand the needs of industry
(Agarwal et al., 2004), and to form relationships with industrial partners more effectively
and productively. The literature also argues that academics who have prior experience
engage in a greater variety of academic entrepreneurial activities (D’Este and Patel, 2007).
62
However, Ambos et al (2008) have found no significant relationship between academic
entrepreneurial engagements and the previous experience of academics on collaborating
with industry. Ambos et al justified this by stating that it is, rather, specific experiences
with the industry which are more important than general experience. These findings of
previous literature indicate that there is no consensus with respect to the effect of prior
experience on an academic’s engagement in entrepreneurial activities.
3.7.1.5. The Social Network of the Academic
In the literature, the social network of academics has been found to be a decisive factor in
their engagement in entrepreneurial endeavour, as well as achieving success (Siegel et al.,
2007). Social networks have been recognized as contributing to enhancing access to
resources (Birley, 1985), to identifying and capitalising on opportunities in a timely
manner (Nicolaou and Birley, 2003), and to acquiring legitimacy (Aldrich and Fiol, 1994).
The influence of social network was found to vary depending on the type of social ties. For
example, some researchers have found that, perhaps not surprisingly, strong ties are the
most productive (Nicolaou and Birley, 2003, Ambos et al., 2008). However, De Koning
and Muzyka (1999) have argued that different ties play specific roles, which are of
importance to entrepreneurs throughout their entrepreneurial career. De Koning and
Muzyka justify this by explaining four types of ties; first, the inner circle involving those
with whom entrepreneurs have long-term stable ties (but not partners). These ties are very
useful in sharing mutually beneficial, crucial information; Second, team members/partners
of the start-up – as the name implies, they are crucial throughout the entrepreneurial
process. Third, an action set - those who are recruited to provide resources and
opportunity. Fourth, a network of weak-ties, which are important for information
gathering.
Previous experience has been found to assist academic entrepreneurs in building strong
social networks. Mosey and Wright (2007) state that habitual entrepreneurs (who have
prior experience in forming new ventures) have a strong network of ties, and thus, have a
higher tendency to achieve success in comparison with novice entrepreneurs who lack such
ties. Therefore, having a habitual entrepreneur in a founding team enables academics to
achieve success for their spin-off companies (Mosey and Wright, 2007). Similarly, Grandi
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and Grimaldi (2003) have stated that having external agents from industry as partners
provides academic entrepreneurs access to the networks of these partners, which have been
developed as a result of their prior experience. Besides reaping benefits of having networks
with industrial partners (Krabel and Mueller, 2009), networking with peers with
commercialization experience was also found to have a positive impact on an academic’s
propensity to engage in entrepreneurial endeavour (Azoulay et al., 2007).
Furthermore, referring to the resource based view, Grandi and Grimaldi (2003) have
argued that having all the necessary resources within universities reduces the importance of
interacting with external agents. This could result in academic entrepreneurs not receiving
certain other advantages of external networks, such as making spin-off companies known
in the market, attracting new clients, and receiving access to agents who may provide them
with resources (which may not be important at the start-up stage, but will be of value
during company growth). The above discussion indicates that, social networks involving
different ties, which may have been developed as a result of prior experience, and/or
accessed as a result of having partners with their own strong networks, serve diverse
purposes for academic entrepreneurs.
3.7.1.6. The Discipline of the Academic
Owen-Smith and Powell (2001) have argued that academics from specific disciplines share
common sets of cultural norms which shape their engagement in entrepreneurial activities.
For instance, it was found that opportunities to engage in academic entrepreneurship vary
across academic disciplines (Wright et al., 2004). Opportunities are relatively higher in
engineering, medical sciences (mainly biotechnology and pharmaceuticals), agriculture and
other applied science in comparison to pure (Mowery and Sampat, 2005) or social sciences
(Laukkanen, 2003). The research findings on these applied disciplines indicate that they
have higher, direct, and immediate impacts on industry. This has been recognized as the
main reason for this discipline disparity (Mowery and Sampat, 2005). However, Mowery
and Sampat have stated that this does not mean that basic sciences have no relevance to
industrial research, but rather, it is simply the case that there can be a lag period with
respect to commercialising basic research findings.
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Furthermore, the need for industry to access highly skilled university scientists has also
been dependent upon academic discipline. For example, Kodama and Branscomb (1999)
have found that the dependence of industry on highly skilled university researchers in
disciplines such as microelectronics, software, biotechnology, medicine and new materials
is very high, and thus, these disciplines have more opportunities to interact with industry.
The availability of funding from industry has also been dependent upon academic
discipline, where physical sciences generally receive a substantial amount of funding in
comparison to social sciences (Meyer-Krahmer and Schmock, 1998).
Additionally, the literature provides evidence that academic disciplines determine the
strength of social networks which, in turn, influence academic entrepreneurial engagement.
In comparison to engineering disciplines, which traditionally have close links with
industry, social science was found to be experiencing a lack of external well established
networks (Etzkowitz et al., 2000). This is mostly a result of the inherent nature of these
two disciplines (Ambos et al., 2008) which had rendered achieving academic
entrepreneurial success in social science difficult (Laukkanen, 2003). Similarly, disciplines
such as mechanical engineering and information technology are found to collaborate with
industry to a greater extent compared to chemistry, because of higher opportunities
provided by strong networks (Meyer-Krahmer and Schmock, 1998). Further, according to
Mosey and Wright (2007) inexperienced academic entrepreneurs in engineering and
material sciences encounter fewer problems when developing networks, while those in
biosciences face relatively higher barriers. Even among applied disciplines, the formation
and the operation of spin-off companies could vary across disciplines. For instance, Oakey
(1995) found that initial funding requirements vary across disciplines whereby, for
example, software companies need lower amounts of initial capital in comparison to
biotechnology ventures. It was also noted that the nature of a discipline determines the
suitability of different business models when forming spin-off companies (Siegel et al.,
2007).
Based on the above discussion, it could be concluded that academic discipline influences
academic engagement in entrepreneurial endeavour since it determines the availability of
opportunities, the relevance of the discipline to industrial research, the need of industry to
interact with university researchers, the strength of social network, and the nature of and
the propensity for academic entrepreneurial engagement.
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3.7.2. The Environmental Context of Academic Entrepreneur
The environmental context is involved in shaping the activities of entrepreneurs since it
determines the availability of data and exploitable resources (Ucbasaran et al., 2000). The
availability of data determines an entrepreneur’s ability to perceive opportunities, while
resources are required to capitalize on these opportunities (Scott et al., 2000). The literature
has further argued that the success of entrepreneurs is dependent upon to what extent they
can adapt to the changes in the environment (Kirzner, 1973, Bryant, 1989) and changes the
conditions of the environment (Schumpeter, 1934). Therefore, it can be argued that the
entrepreneurial process cannot be isolated from the environmental context of entrepreneurs
(Beckford, 1995). An academic entrepreneur’s environment mainly consists of the
university, which comprises the internal environment, and actors in the wider economic
and social environment, especially government and industry (O’Shea et al., 2004,
Etzkowitz and Leydesdorff, 2000, Siegel et al., 2004, Eun et al., 2006). Therefore, the next
Sections of this chapter will discuss the literature on how academic entrepreneurial
engagement is shaped by interactions with the university, industry and government.
3.7.2.1. Interactions between University and Academic
The role played by universities at which academics are employed (Franklin et al., 2001,
Siegel et al., 2007) and educated (Packalen, 2007) has been recognized as of paramount
importance in determining the success of academic entrepreneurship. Similarly, previous
studies have mentioned that the quality of departments to which academics are attached is
also crucial in shaping their engagement in entrepreneurial endeavour (Erdıs and Varga,
2009).
The extent to which universities/departments have engaged in research with industry
shows their institutional ability to engage in academic entrepreneurship (Schartinger et al.,
2001). Therefore, previous studies have argued that the commercial orientation of
universities, and their departments, determine an individual’s propensity to engage in
entrepreneurial endeavour (Di Gregorio and Shane, 2003, Friedman and Silberman, 2003).
Not only does the commercial orientation of universities or their departments, but also their
research strength may influence academic entrepreneurship (Di Gregorio and Shane, 2003,
Ambos et al., 2008).
66
Similarly, the quality of faculty members has also been recognized as a decisive factor in
an academic’s engagement in entrepreneurial endeavour, and particularly, when acquiring
external funding (Di Gregorio and Shane, 2003). Additionally, the literature has also
mentioned that working with colleagues who have obtained patents and started businesses
has a positive influence on an academic’s decision to become entrepreneurial (Azoulay et
al., 2007, Mosey and Wright, 2007). Furthermore, the role of the host institution of spin-
offs (i.e. university) as a provider of resources has also been highlighted in the literature as
an important factor (Zucker et al., 1998, Kinsella and McBrierty, 1997). These studies have
argued that the success of spin-offs is dependent upon the utilization of a wide range of
resources, skills, and partnerships (i.e. financial, technological, and international etc)
(Mustar, 1998) in which the university is a major contributor by providing access to these
assets (Brennan et al., 2005). Furthermore, Franklin et al (2001), in a study conducted in
the UK, revealed that successful university spin-offs are those that have received better
access to the sources of pre-seed stage capital from universities.
Despite the positive influence of universities on academic entrepreneurship highlighted
above, some previous studies have taken a different view. For example, Schartinger et al
(2001) has shown that, except for joint research, the research quality of the university does
not have a significant effect on determining the entrepreneurial engagement of its staff.
D’Este and Patel (2007) have also revealed that being a member of a university department
which has a strong research reputation does not have an effect on the level of interaction
with the industry.
On the other hand, it was also revealed that, a spin-off company is able to achieve a high
growth rate and success, if the academic entrepreneur becomes involved with the company
full-time, by leaving the host university (Doutriaux, 1987, Samson and Gurdon, 1993).
This evidence questions the appropriateness of university incentive structures, and other
organizational policies on spin-off formation (Jones-Evans, 1997, Samson and Gurdon,
1993). University reward systems, which mainly encourage peer reviewed publications as
opposed to engagement in academic entrepreneurial endeavour, have also been reported to
suppress academic engagement in entrepreneurial endeavour (Siegel et al., 2007).
Furthermore, Erdis and Varga (2009) have also found that European university policies
discourage academic entrepreneurship. Accordingly, introducing changes to university
regulations and strategies in order to provide flexible employment contracts (Samson and
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Gurdon, 1993), and to overcome other barriers within universities by fostering an
entrepreneurial culture is considered important in order to promote academic
entrepreneurship (Siegel et al., 2004).
3.7.2.2. Interactions between Academic Entrepreneurs, their Universities and
Industry
It is widely accepted that interactions between universities and industry, which promote the
commercialization of scientific knowledge, are mutually beneficial (Etzkowitz et al., 2000,
Mustar, 1997). Capitalising on the knowledge and skills of academics by developing and
improving products and processes, and receiving access to the infrastructural facilities of
universities (e.g. labs) are some of the benefits industry receives by interacting with
universities (Meyer-Krahmer and Schmock, 1998). From a university perspective, the
obtaining of industrial funds has been recognized as a major benefit. Meyer-Krahmer and
Schmoch (1998), in a research carried out in Germany, have stated that, in recent years, the
allocation of industrial funds to universities has significantly increased. Universities use
these funds to improve resources, such as additional laboratory equipment and
infrastructural facilities (Siegel et al., 2004). Receiving the most up-to-date information
and knowledge from industry, which is of use to curricula development and future research
(D’Este and Patel, 2007, Siegel et al., 2004), bringing qualified industrial personnel to
universities, and obtaining assistance and opportunities for students (Siegel et al., 2004) are
additional benefits that universities receive from these interactions.
In addition to the general advantages of university-industry interactions stipulated above,
surrogate entrepreneurship, which is another form of university industry interaction, seems
to provide certain unique benefits. A surrogate entrepreneur is an external individual, or a
company, that takes the responsibility of commercializing university innovations. This type
of arrangement avoids inventors deviating from their primary role as academics, and
enables them to overcome the disadvantage of inventors not possessing the required level
of entrepreneurial or management skills (Radosevich, 1995). Moreover, according to
Franklin et al (2001), external entrepreneurs add value due to their previous commercial
experience, wider social networks and motivation towards capital gains. However, some
researchers argue that this arrangement might not be successful due to the conflicting
interests of surrogate entrepreneur and academics (Radosevich, 1995, Samson and Gurdon,
68
1993, Jones-Evans, 1997). Nevertheless, Franklin et al (2001), when researching UK
universities, had shown that there are universities who have been successful in working
with surrogate entrepreneurs. Hence, these findings suggest that the way universities
manage these relationships might determine outcomes.
Previous studies have mentioned that universities create several mechanisms with which to
encourage interactions with industry. The development of university-affiliated Science
Parks is one such strategy. However, the contribution of science parks to enhance
academic-business interactions, and to promote the emergence of new business, has been
questioned in the literature (Oakey, 1985, Westhead and Cowling, 1995). Therefore, the
creation of incubators is perceived as a better mechanism for promoting academic and
industry interactions (Franklin et al., 2001). Meyer (2003) argues that the success and the
growth of companies in incubators are dependent upon the nature of the support they
receive from incubator managers. Meyer has found that companies placed in a networked
incubation programme with an experienced board, supervisory members, successful initial
public offerings and bigger grants have a better chance of achieving a high growth rate. On
the contrary, if incubators are bureaucratic and risk averse, it could result in academics
deciding to create their own private companies, independent of incubators (Morales-
Gualdrón et al., 2009).
The establishment of Technology Transfer Offices (TTO) is another mechanism
universities have adopted to facilitate university industry interactions (Powers and
McDougall, 2005). These support offices are considered useful in bridging cultural gaps
between university and industry (Ambos et al., 2008, Lockett and Wright, 2005). Carlsson
and Fridh (2005) revealed that, the higher the experience of TTOs, the better the benefits to
universities. However, in certain instances TTOs are accused of possessing insufficient
marketing and negotiation skills, which is attributed to not recruiting appropriate personnel
for these offices (Siegel et al., 2004), or not having efficient administrative structures (Van
Dierdonck and Debackere, 1988). It also has been revealed that the inflexible nature of
TTOs has led industry to contact individual researchers directly, bypassing TTOs (Siegel et
al., 2004). Links between academics and industry have also been facilitated by some
institutions such as ANGLE Technology Limited, UK. They recruit high calibre,
experienced individuals into start-up ventures initiated by academics with the condition
that, surrogate entrepreneurs could resume duties at ANGLE Technology Ltd, if the spin-
69
off company fails. This has been found to minimize the risk to surrogate entrepreneurs
(Franklin et al., 2001).
On the other hand, the literature argues that, in addition to support infrastructure, the level
of commitment from industry and universities is an important factor which governs
success. In certain instances, industry deems to presume that providing funds and technical
resources suffice, since university partners have the required knowledge and skills.
However, previous studies have argued that a higher level of contribution and commitment
from both parties results in a greater success. Therefore, it is of paramount importance to
select partners who share common strategic interests, and are committed to make greater
contributions (Barnes et al., 2002).
In addition to the above discussed factors, the literature argues that industry level
conditions also determine the extent to which universities and industry collaborate.
According to this concept, the National System of Innovation (Nelson, 1993), absorptive
capacity of industry, incentives, and framework conditions determine the extent of
interactions between university and industry. Eun et al., (2006), in a research carried out in
China, have argued that, if firms have a higher absorptive capacity to make use of
university knowledge, and if intermediary institutions facilitate the flow of knowledge,
universities tend to use other modes of entrepreneurial endeavour (e.g. knowledge transfer
activities) than setting up enterprises by themselves.
3.7.2.3. Interaction between the Academic Entrepreneur, Industry, and Government
In addition to micro and meso level factors, the macro environment, which mainly
comprises government and industry, has also been found, in the literature, to shape
academic entrepreneurship (O’Shea et al., 2004, Etzkowitz and Leydesdorff, 2000, Siegel
et al., 2004). By mainly emphasising developed countries, Etzkowitz and Leydesdorff
(2000) have developed three ‘Triple Helix Models’ to show how interactions between
universities, government and industry have evolved from governments directing these
relationships to dynamic and strong links among the three parties.
In the first model (i.e. “Triple Helix I”), Etzkowitz and Leydesdorff (2000) illustrate the
initial stage of these relationships, during which government direct interactions between
industry and universities. They then argued that, over time, government interventions
70
decline in response to active collaborations between universities and industry, but there
still remain tight institutional boundaries (illustrated in the “Triple Helix II” model).
Eventually, institutional boundaries start to disappear with the formation of joint-ventures
by government, industry, and universities. As a result, interactions become intensified and
dynamic (demonstrated in the “Triple Helix III” model) (Figure 3.2).
Triple Helix 1 Triple Helix 2 Triple Helix 3
Figure 3.2 : The Role of Government Source: Etzkowitz and Leydesdorff (2000)
The triple helix model has argued that, in a knowledge economy, entrepreneurial
universities increasingly interact with government and industry, which result in the transfer
of knowledge. In this perspective it is proposed that these interactions are promoted
through high availability of research funding, infrastructure facilities, support mechanisms,
and joint institutions. However, critiques have shown that this model does not explain the
nature of interactions between university, industry, and government in less developed
nations (Gunasekara, 2006). Furthermore, research has highlighted the weakness of not
recognizing institutions other than universities which also act as the sources of knowledge.
Another criticism is the lack of emphasis of the “triple helix” model on the impact of
society on the knowledge development and transfer process (Cooke, 2005).
3.8. The Impacts of Academic Entrepreneurship
So far, this chapter has discussed the definition of academic entrepreneurship and micro,
meso, and macro level causal factors that influence academic engagement in
entrepreneurial endeavour. This Section reviews the literature on the impacts of academic
entrepreneurship on universities and the wider economy. Previous studies have shown that
academic entrepreneurship generates wealth in universities and benefits to the wider
economy (Wright et al., 2004). Academic entrepreneurship also enables the capitalising on,
U
S
I
S
I U
State
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and reaping direct economic benefits from, university generated knowledge, which is
considered as a solution to plummeting government funds available to universities (Wright
et al., 2004, Wright et al., 2007). It was also expected that academic entrepreneurship has a
socio-economic value since it allows the commercialising of university generated
knowledge and technologies, which would not have been utilised otherwise (Shane, 2004).
However, changing the focus from basic science to applied science has been questioned for
resulting in a deterioration in the advancement in science and technology in the long-run
(Dasgupta and David, 1994, Rosenberg and Nelson, 1994). It is also argued that, when
limited facilities available in universities are used for entrepreneurial activities, the quality
of education and research suffers (Van Dierdonck and Debackere, 1988). Moreover, when
academic entrepreneurial engagement demands substantial time commitment and effort, it
is found to be difficult to balance normal academic duties and entrepreneurial endeavours
(Wright et al., 2004). This could result in academics not performing any of their tasks
successfully (Bercovitz and Feldman, 2003)
On the other hand, there is scepticism over the ability of academic entrepreneurs to
successfully form and manage spin-off companies because of a lack of entrepreneurial,
business and management skills, not having strong social networks, and insufficient
knowledge of market demands/trends etc (Grandi and Grimaldi 2003). Additionally,
activities such as joint research projects have been found to encounter delays in delivering
output due to the conflicting interests of theoretically oriented university staff and profit
oriented industry partners (Hall et al., 2000). Similarly, Sampat (2006) has argued that
patenting university generated knowledge could reduce the rate of knowledge transfer in
comparison to having free access.
Regardless of above discussed negative impacts of entrepreneurship on the careers of
academics (Stephan and Levin, 1992), recent research findings have revealed a positive
relationship between the number of publications and the engagement of academics in
entrepreneurial endeavour (Calvert and Patel, 2003, Van Looy et al., 2006, Lowe and
Gonzalez-Brambila, 2007, Brooks and Randazzese, 1999). It has also been found in the
literature that ‘star scientists’ tend to engage in more academic entrepreneurial activities
than others (Zucker and Darby, 2001, Erdis and Varga, 2009), and that academic
entrepreneurs are more productive than academics without entrepreneurship (Louis et al.,
2001). Siegel et al (2004) support this argument by stating that academic entrepreneurship
72
has positive impacts, even when conducting basic research. Similar findings have been
found at the university level as well, where university involvement in entrepreneurial
endeavour was not found to reduce the quality and quantity of basic research (Siegel et al.,
2004). These contradictory arguments with respect to the impacts of academic
entrepreneurship seem to suggest that even though academic entrepreneurial engagement
may generate socio-economic value to universities and to society at large, it is not
advisable to over-rely on its potential.
3.9. Barriers to Academic Entrepreneurship
As a result of universities engaging in activities beyond what they traditionally do, and are
familiar with, they have to face a myriad of challenges both at organizational and
individual level (Ambos et al., 2008, Barnes et al., 2002, Monck and Segal, 1983).
Maintaining a balance between normal academic duties and entrepreneurial activities, and
managing cultural differences between academia and industry have been identified in the
literature as challenging (Jones-Evans, 1997). While industry is profit oriented, the
traditional environment/culture of universities does not have a commercial orientation
(Lockett and Wright, 2005, Azaroff, 1982). This leads industry and universities to
encounter conflicting research priorities (Ambos et al., 2008, Barnes et al., 2002).
Industry often seeks to prioritize less risky, short-term research with direct commercial
applicability, while universities tend to undertake long-term research with less
predictability. Furthermore, universities are interested in disseminating knowledge, and
having as many publications as possible. On the contrary, industry seeks to acquire
ownership, and sometimes to keep certain findings secret as a strategy of achieving
competitive advantage (Barnes et al., 2002). It is also evident in the literature that, while
universities are motivated by the need to generate additional research income, industry is
interested in the informal transfer of know-how and knowledge on product development.
Moreover, with respect to joint start-up companies, the risk-averse nature of universities
could restrict growth (Siegel et al., 2004). Therefore, if cultural differences are not handled
properly, it could result in a failure (Barnes et al., 2002) or the deterioration of the quality
of interactions with industry (Siegel et al., 2004).
In addition to cultural differences, the presence of subcultures within universities has also
been identified as a barrier. Academics and university managers are reported to have
73
different sub-cultures which might deter the possible positive effects of academic
entrepreneurship (Siegel et al., 2004). Moreover, with respect to certain joint activities, not
having appropriate agreement on how to share income among university, industry, and
academics has also been considered a difficulty (Van Dierdonck and Debackere, 1988).
Additionally, Siegel et al (2004) found that the insufficient allocation of patent or royalty
rights to academics is a disincentive to engage in academic entrepreneurship. The reward
system of academics being not favourable towards promoting entrepreneurial engagement
has also been identified as a major obstacle (Siegel et al., 2004).
Some of the barriers could be attributed to the individualistic nature of academics (Van
Dierdonck and Debackere, 1988). According to Ambos et al (2008) academics experience
tension because of distinctively different demands arising from academic career and the
commercial world. Academics are mostly familiar with normal academic duties and are
less able to adapt to change. This had made the delivery of commercial outcomes
challenging. It was also stated in the literature that academic involvement in spin-off
companies being part-time is an obstacle to the growth of these ventures (Doutriaux,
1987). Moreover, a lack of entrepreneurial skills among academics (Laukkanen, 2003), and
a reward system that does not promote academic entrepreneurship (Jones-Evans, 1997)
have been viewed as hindering potential benefits.
Research based on a sample of 300 Belgian university laboratories, Van Dierdonck and
Debackere (1988) has claimed that barriers are highly context specific. They further
elaborated this by highlighting the barrier of having low autonomy in Belgian universities
to enable them to engage in academic entrepreneurship since they are highly controlled by
governmental authorities. A lack of resources within universities (Van Dierdonck and
Debackere, 1988), and not having enough inventions with the potential for
commercialization (McMullan and Melnyk, 1988), are also other context specific barriers
to academic entrepreneurship (Shane, 2000).
3.10. Chapter Summary
This chapter has reviewed relevant literature in order to provide a theoretical underpinning
of this study. Initially, the chapter highlighted the lack of consensus in the literature with
respect to a definition of academic entrepreneurship. While this term has mostly been used
in a focused manner to illustrate academic engagements in the formation of spin-off
74
companies, some studies have used it to represent a much broader spectrum of knowledge-
transfer activities. Analysis of these definitions suggested that the use of a definition is
dependent upon the objective of a study. Hence, this research has decided to use the broad
view, since its objective is to investigate the nature of academic entrepreneurial
engagement in a context that has received inadequate attention in prior research, which
required investigating the whole subject of academic entrepreneurship. As the broad view
has not defined the term precisely, this study has defined academic entrepreneurship as
‘academics capitalising on perceived opportunities, by matching these with resources, in
order to accumulate wealth, which could be monetary and/or social’.
The chapter then reviewed the literature on how contexts in which entrepreneurs operate
shape their entrepreneurial activity. Based on this discussion, the current study argued that,
even though resources seem to be a means of becoming entrepreneurial in a resource-rich
environment, being entrepreneurial might be a means of overcoming resource barriers in a
resource constrained environment. The chapter has also highlighted recent evidence that
suggests that entrepreneurs tend to engage in multiple income-generation activities in order
to extract value from their limited resource environments. Therefore, this research argues
that academics operating in resource constrained environments may also engage in several
academic entrepreneurial activities. Hence, in order to represent the nature of academic
entrepreneurial engagement, this study decided to construct a typology of academic
entrepreneurship, on the basis of the combinations of academic entrepreneurial activities
carried out by them.
This chapter also discussed how academic entrepreneurship could be affected by the
motivations and the personal characteristics of academic entrepreneurs, as well as meso
and macro level factors. The review of literature indicated that motivations shape the
behaviour of, the type of activities carried out by, and the level of success achieved by,
academic entrepreneurs. Furthermore, based on the literature, it was argued that in a
resource constrained environment academic engagement in entrepreneurial activities may
be motivated initially by push motives, and subsequently, as the development of academic
entrepreneurial careers, by pull motives. The personal characteristics found in the literature
that affect academic entrepreneurship were the age, position, gender, knowledge and skills,
experience, social networking, and the academic discipline of academics. Contrary
viewpoints in the literature with respect to the effect of these factors on academic
entrepreneurial engagement were also highlighted. Meso-level factors that affect academic
75
entrepreneurship mentioned in the literature were the quality of universities, departments,
and staff members (both in terms of research and commercial orientation), university
policies, and the resource status of universities and/or their departments. The review of
literature also suggested that industry and government are the main actors in the macro
environment that influence academic entrepreneurship. The literature provided evidence to
state that academic entrepreneurship could be mutually beneficial to industry as well as to
universities.
The chapter also reviewed the literature on the impacts of, and barriers to, academic
entrepreneurship. The chapter highlighted that academic entrepreneurship generates wealth
for universities, and for a wider economy, by commercializing university generated
knowledge. Furthermore, this review indicated that there is a positive relationship between
the number of publications and the engagement of academics in entrepreneurial endeavour.
However, changing the focus from basic science to applied science has been criticised for
the deteriorating advancement of science and technology in the long-run. Additionally, it
was also apparent that the literature is sceptical of the ability of academics to manage
normal academic duties and academic entrepreneurial activities. These contradictory
arguments with respect to the impacts of academic entrepreneurship led to a conclusion
that even though academic entrepreneurial engagement might prove to generate positive
impacts, it is not advisable to over-rely on its potential. The literature on the barriers to
academic entrepreneurship highlighted that barriers may arise due to cultural differences
between university and industry, university related disincentives for engagement, and
negative circumstances specific to individual academics (e.g. a lack of business
management and entrepreneurial skills) or to their environments (e.g. a lack of
entrepreneurial culture). It was also emphasized that if these barriers are not managed
properly, the success of academic entrepreneurial engagement could be at risk. The next
chapter of the thesis discusses the hypotheses developed to address the four specific
objectives of this research.
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Chapter 4: Research Hypotheses
The previous chapter of this thesis has reviewed academic entrepreneurship and general
entrepreneurship literature to provide a theoretical background for this study. The purpose
of this chapter is to state the hypotheses of this research that seek to investigate academic
entrepreneurship in a resource constrained environment. The research hypotheses are
structured around the four specific research objectives of this study; namely to investigate
the ‘plural activities’ of academic entrepreneurs, to examine the motivations of academic
entrepreneurs, to study the effects of multilevel causal factors on ‘plural activities’, and to
investigate the impacts of academic engagement on entrepreneurial endeavour.
4.1. Investigating the ‘Plural activity’ of Academic Entrepreneurs in a Resource
Constrained Environment
The literature had argued that entrepreneurial engagements by academics are shaped by
their environment, which determines the availability of exploitable resources (Ucbasaran et
al., 2000) that influence an entrepreneur’s ability to identify and capitalize on opportunities
(Scott et al., 2000, Bryant, 1989, Stevenson and Jarillo, 1990). The total environment of
the academic entrepreneur mainly consists of the university (Eun et al., 2006), which is the
internal environment, and government and industry, which are the major components of
the external environment (O’Shea et al., 2004, Etzkowitz and Leydesdorff, 2000, Siegel et
al., 2004).
Based on the Resource Based View of firms, Eun et al (2006) have argued that, the
stronger the universities are in terms of resources, the higher the tendency for academics to
engage in entrepreneurial endeavour. Similarly, other literature suggests that there is a
higher propensity for academics to engage in entrepreneurial endeavour when their
external macro-environment is resource rich (Etzkowitz and Leydesdorff, 2000, Siegel et
al., 2004). Studies of this type have led to a belief that the propensity for entrepreneurship
is highly encouraged by a resource-rich environment. This argument is further supported
by research that has found resource limitations to be strong barriers to academic
entrepreneurial engagement (Monck and Segal, 1983). Indeed, when a full range of
facilities are unavailable in universities, these resource deficiencies may critically inhibit
entrepreneurship (Van Dierdonck and Debackere, 1988).
77
However, some studies in the entrepreneurship literature have argued that, in extremely
unpromising and resource constrained environments, entrepreneurial skills may remain
important in spotting opportunities, and matching these with available resources. Thus,
resource constraints can conversely stimulate entrepreneurial behaviour in such relatively
impoverished environments (Kodithuwakku and Rosa, 2002, Gilad and Levine, 1986).
This argument is further supported by the literature which states that the availability of
resources is not critically damaging, and that entrepreneurs can creatively overcome
resource barriers (Hart et al., 1995). The proponents of this view have further stated that
entrepreneurs generally go beyond resource limitations by creatively arranging ways to
obtain maximum use of available resources, and to be able to make use of resources which
are not owned by them (Kirzner, 1973, Saylor, 1987, Penrose, 1959). On the basis of the
above discussion, it is possible to argue that resource barriers may not necessarily inhibit
academic entrepreneurship, and that being entrepreneurial may be a means of overcoming
resource constraints. This has led to the first null-Hypothesis of this Section, which asserts:
H1.1: Being entrepreneurial is not a means of overcoming resource barriers in a
resource constrained environment
In order to shed further light on academic entrepreneurship in a resource constrained
environment, it was decided to investigate the entrepreneurial engagements of individual
academics in detail, since they are the agents of academic entrepreneurship (D’Este and
Patel, 2007, Ambos et al., 2008). It has been found in some literature that entrepreneurs
operating in these environments tend to engage in multiple income generation activities
(Kodithuwakku and Rosa, 2002). Therefore, it is possible to argue that academics
operating in resource constrained environments may also engage in several academic
entrepreneurial activities. Since carrying out multiple income generation activities is
defined as diversification in the entrepreneurship literature (Alsos et al., 2003), engaging in
a number of entrepreneurial activities by academics may also represent diversification.
However, diversification has not yet been a topic widely discussed in the academic
entrepreneurship literature. Therefore, in order to develop relevant hypotheses to
investigate academic entrepreneurial diversification this thesis uses corporate
diversification literature, which has discussed quite a similar scenario where firms carry
out several business activities. The corporate diversification literature has identified two
types of diversification strategies; namely, related diversification and unrelated
78
diversification. Related diversification involves firms diversifying into activities that are
related to their main activities (e.g. related markets, industries, or products). In contrast,
unrelated diversification involves firms diversify into substantially new areas of business
(Rumelt, 1982). Although the above literature is not directly relevant to academic
entrepreneurial engagements, its basic concept of related and unrelated diversification
seems to provide a theoretical background for the discussion of the diversification of
entrepreneurial activities by academics.
In order to develop a theoretical framework to understand the diversification of academic
entrepreneurs, it was necessary to investigate whether it is possible to differentiate
academic entrepreneurial activities in terms of their ‘relatedness’ to the core task of
academics, which is to engage in teaching and research activities (Etzkowitz et al., 2000).
The academic entrepreneurship literature argues that company creation by academics is
substantially different from normal academic duties, while other forms of knowledge
transfer activities are related to normal academic duties (Schartinger et al., 2001, Samson
and Gurdon, 1993, Daniels and Hofer, 1993). On the other hand, to some degree, teaching
and research are independent of each other. For example, Marsh and Hattie (2002) have
stated that teaching effectiveness and research productivity are mutually exclusive, and
thus, they concluded that these two activities are independent.
The above discussion suggests that academic entrepreneurial activities might be
categorized into three groups; namely, teaching related activities, research related
activities, and company creation. However, categorizing activities into these three groups
would not restrict the potential for interactions between these groups. The rationale for
such a categorization is that activities categorised within groups are more similar in terms
of their relatedness to normal academic duties, than activities between groups. In line with
these arguments, seventeen academic entrepreneurial activities identified in the literature
review (please refer Section 3.2.2 of the A Review of Literature Chapter) are categorised
into three groups (Table 4.1). This categorization is achieved by analysing the relatedness
of each academic entrepreneurial activity to teaching, research, and company creation.
Grouping activities according to their nature is a strategy adopted in the academic
entrepreneurship literature (e.g. D’Esta and Patel 2007). The appropriateness of this
grouping approach will be checked against empirical evidence during the data gathering
stage, which is recommended in the literature as a strategy to enhance validity (Tsoukas,
1989, Kwok and Sharp, 1998).
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Table 4.1: Types of Academic Entrepreneurial Activities
Teaching related academic entrepreneurial activities
Research related academic entrepreneurial activities
Company creation
(1)External teaching (2)Initiating the development of new degree programmes (3) Placing students as trainees in industry (4)Conducting seminars and training sessions for industry (Jones-Evans, 1997, Jones-Evans and Klofsten, 2000, Schmoch, 1997, D’Este and Patel, 2007)
(1) Working in the industry (research based) (2)Research based consultancy for industry through the university (3)Research based consultancy privately (but without forming a company) (4)Developing products or services with potential for commercialization. (5)Acquiring research funding from government, non-governmental or international bodies (those without collaborations with industry) (6)Collaborating with industry through joint research projects (7)Research related assistance to small business owners. (Glassman et al., 2003, Jones-Evans, 1997, Louis et al., 1989, Goldfarb and Henrekson, 2003, Siegel et al., 2004, Calvert and Patel, 2003)
(1) Contributing to the formation of joint ventures in which university and industry are the joint partners (2)The formation of joint venture/(s) privately through collaborating with industry (3) Contributing to the formation of one or more new spin-off companies (4)Contributing to the establishment of university incubators and/or science parks (5) Contributing to the formation of university centres designed to carry out commercialization activities (6) The formation of your own company/(s) (Clarysse et al., 2005, Di Gregorio and Shane, 2003, Louis et al., 1989, Goldfarb and Henrekson, 2003, Hall et al., 2001)
As discussed above, an academic may engage in a combination of entrepreneurial
activities, and using the three types of activities, eight possible combinations of
entrepreneurial activities were constructed (i.e. 23) (Table 4.2). When the category of
academics who had not engaged any activity was excluded, seven combinations could be
considered to account for the different portfolio of possible entrepreneurial activities.
Hence, in order to understand academic entrepreneurial engagements in a resource
constrained environment, it was decided to investigate the portfolio of entrepreneurial
activities carried out by academics, named in this research as ‘plural activity’. Hence,
‘plural activity’, which seems to be a ‘role’ comprising possible combinations of academic
entrepreneurial activities, was used to differentiate academic entrepreneurs. As a result,
different typologies of academic entrepreneurs were identified, depending on ‘plural
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activities’ adopted by them. The use of roles to differentiate entrepreneurs is consistent
with diversification and portfolio entrepreneurship literature, which had used roles to
distinguish individuals or companies. For instance, Westhead et al (2005) had
differentiated entrepreneurs into three categories as novice, serial, and portfolio on the
basis of the type of entrepreneurial activities carried out by them. Similarly, Rumelt (1982)
differentiated companies depending on their involvements in related and unrelated
diversification.
Table 4.2: The ‘Plural activities’ of Academic Entrepreneurs
‘Plural activity’ types Teaching Related
Research Related
Company Creation
Type 1 (Only teaching related AEAs) √ Type 2 (Only research related AEAs) √ Type 3 (Only company creation) √ Type 4 (Teaching related AEA + Research related AEA) √ √ Type 5 (Teaching related AEA + Company creation) √ √ Type 6 (Research related AEA.+ Company creation) √ √ Type7 (Teaching related+ Research related + Company
creation) √ √ √
√ indicate that academics have engaged in at least one activity in the given group of activities
AEA – Academic Entrepreneurial Activity
The diversification and portfolio entrepreneurship literature argues that engagement in
multiple entrepreneurial activities provides additional benefits, due to the synergies that
can be developed between activities (Westhead et al., 2005, Alsos et al., 2003). This is
defined in the literature on systems theory as ‘the whole is better than the sum of its parts’
(Von Bertalanffy 1972, pp 407). Therefore, social network (Westhead et al., 2005, Mayer
and Schooman, 1993), knowledge and skills (Shane, 2000, Westhead et al., 2005, Alsos et
al., 2003), input-output flows , and physical resources (Westhead et al., 2005, Alsos et al.,
2003), identified in the literature as (at least) four types of additional advantages derived
from diversification, are regarded as relevant to diversifying academic entrepreneurial
activities considered here (please refer the Section 3.5 of A Review of Literature Chapter
for more details).
It is also stated in the literature that diversification into similar activities generates greater
synergistic effects than diversifying into diverse activities, since capabilities and resources
could be shared between similar activities (Markides and Williamson, 1996). However, the
literature also argues that an ability to derive synergies is dependent upon how effectively
81
the linkages between activities are managed (Gupta and Govindarajan, 1986). Therefore, it
has been argued that, in certain circumstances, poor coordination between similar activities
might offset potential synergistic benefits (Zhou, 2011). This has led to the second null-
Hypothesis of this Section, which proposes:
H1.2: There is no association between the ‘plural activities’ of academic entrepreneurs
and the extent of synergistic effects generated in a resource constrained environment.
4.2. Investigating the Motivation of Academic Entrepreneurs in a Resource
Constrained Environment
The motives of entrepreneurs have been found to play critical roles in the entrepreneurial
process by identifying and capitalizing on opportunities (Shane et al., 2003, Ambos et al.,
2008). Motivation is defined in the management literature as “a cognitive decision making
process through which goal directed decision making behaviour is initiated, energized,
directed, and maintained” (Huczynski and Buchanan 2004, pp 244).
As discussed in the Section 4.1 of this chapter, academics in resource constrained
environments may be motivated by a need to overcome resource barriers. In addition to
overcoming resource constraints, academics might also be motivated by a myriad of other
motives. A desire for novelty, and wealth (Franklin et al., 2001), a need to make use of
technical expertise (Otto, 1999), a need for independence and control (Oakey, 2003), and
university policy towards the encouragement of academic entrepreneurial activity (Van
Dierdonck and Debackere, 1988) are some motives identified in studies carried out in
comparatively resource-rich environments. However, there has been a lack of research
performed to investigate the motives of academic entrepreneurs in resource constrained
environments, even though it is highlighted in the literature that the significance of
individual motives are higher when there is a lack of, or no, institutional support
mechanisms to assist academic entrepreneurs (Erdıs and Varga, 2009).
On the other hand, most of the studies carried out in resource-rich environments have
focused on investigating what motivates academics to form spin-off companies (Morales-
Gualdrón et al., 2009). However, the motives for forming a spinoff company could be
different from engaging in other academic entrepreneurial activities. For example, Jones-
Evans (1997) has stated that, when academics are motivated only by a need to earn
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additional income, they tend to engage in consultancy rather than face the hazard of
company creation. Furthermore, D’Este and Patel (2007) have stated that, while engaging
in consultancy is motivated by a need to earn additional income, contributing to joint
research may be motivated by a need to access industrial resources and skills. Similarly,
D’Esta and Perkmann (2011) argue that, whilst patenting and spin-off formation are
inspired by commercial needs, consulting, joint-research, and contract research are often
motivated by a need to strengthen their research.
Even though these studies have investigated entrepreneurial motives with respect to each
academic entrepreneurial activity, as discussed in the previous Section, academics may
engage in a combination of entrepreneurial activities, which may have different
motivations. Hence, the current study decided to investigate what motivates academics in a
resource constrained environment to adopt different ‘plural activity’ types (please refer
Section 4.1 of this chapter for further details about the seven ‘plural activity’ types adopted
by academic entrepreneurs). This has led to the first null-Hypothesis of this Section, which
states:
H 2.1: In resource constrained environments, there is no association between the ‘plural
activity’ of academic entrepreneurs and their motivations
The literature has categorised motives into two major types; namely, ‘pull’ and ‘push’
factors. ‘Push’ motives are the elements of necessity in which entrepreneurs start a
business to overcome negative external or internal influences. In contrast, ‘pull’ motives
are the attractive reasons why entrepreneurs decide to form new ventures (Gilad and
Levine, 1986). Studies carried out to investigate the effects of these motives have produced
two seemingly contradictory viewpoints. One perspective has argued that academics are
motivated by one type of motive (i.e. either pull or push), while the other believes that
academics are motivated by a mix of pull and push factors.
For example, Similor (1990), in a study of 23 technology-based spin-out companies
from the university of Texas at Austin, concluded that academics are highly motivated
by pull factors in comparison to push factors. The pull factors identified were the
recognition of a market opportunity, a drive to try something new, and a desire to
put theory into practice. Insufficient income was the only push factor found to be
important, but university or job related dissatisfaction was not found to be of great
83
importance. Considering the effect of one type of motive, Amit and Muller (1995)
categorised entrepreneurs as both ‘pull entrepreneurs’ and ‘push entrepreneurs’. Moreover,
Hessels et al (2008) has stated that entrepreneurs who are motivated by push factors are
unlikely to make great economic contributions, and thus, they suggested that policy makers
should discourage entrepreneurship which is driven by a push motive.
The above described significant effect of one type of motive (i.e. pull or push) has been
further extended by relating it to the context in which entrepreneurs operate. For example,
Wright et al (2004) concluded that spin-off formation in the Massachusetts Institute of
Technology or the University of Stanford was motivated by pull factors due to the high
level of innovation in the surrounding region, while it is often ‘technology push’ in an
environment with less innovation and entrepreneurship. Similarly, in the Global
Entrepreneurship Monitor (GEM) project (2006), the majority of entrepreneurs who were
motivated to capitalize on perceived business opportunities (which are pull motives) were
found in high income countries, while those who were motivated by necessities (which are
push motives) were found in middle or low income countries (Bosma and Harding, 2006).
This was further supported by Acs (2006) who revealed that, the higher the level of
economic development, the higher the ratio of opportunity to necessity entrepreneurs.
However, some studies have argued against the above discussed significant effect of only
one type of motive. For instance, Weatherston (1995), in studying UK academic
entrepreneurs, stated that it is a combination of pull and push motives that affect their
engagement. Job related dissatisfaction, involving a need to financially support the
activities of university departments, and a desire to improve personal incomes were major
push factors, while personal satisfaction was a pull factor identified in his research. Balázs
(1996) also theoretically argued that both pull and push factors govern academic
engagement in spin-off formation. The findings of Morales-Gualdrón et al (2009), in a
survey of 152 Spanish academic entrepreneurs, also supported the combined impact of
push and pull motives. This was further endorsed by several authors in the general
entrepreneurship literature (Tagiuri and Davis, 1992, Williams, 2008, Snyder, 2004). For
example, these studies have argued that motivation is rarely a clear cut case of whether
‘pull’ or ‘push’ factors have driven entrepreneurs, and that factors are often combined
(Brush, 1990) and entrepreneurs are motivated by multiple motivating factors rather than
one single overarching factor (Tagiuri and Davis, 1992).
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Even though the above stated views, which were mainly derived from cross-sectional data,
seem contradictory, if the dynamic impact of motivation is taken into account, both the
views can be accepted. The literature suggests that entrepreneurial motivations vary
depending on the stage of the entrepreneurial process (Shane et al., 2003). For instance,
Schjoedt and Shaver (2007), in their US research revealed that entrepreneurs who are in
their early careers (i.e. nascent entrepreneurs) are significantly motivated by push factors
when compared to ‘mature’ entrepreneurs. On the other hand, relating the context to
changes in entrepreneurial motive, the literature has argued that, in extremely constrained
environments, entrepreneurs are initially pushed to engage in entrepreneurial activities, but
with the development of their business, motives gradually change towards pull (De Silva
and Kodithuwakku, 2011, Rosa et al., 2006). Therefore, it could be argued that academic
entrepreneurs in resource constrained environments may be motivated initially by push
motives, while later the significance of pull motives may increase. Hence, this highlights
the importance of studying the dynamism of entrepreneurial motivation. Therefore, this
study decided to investigate how the entrepreneurial motivations of academics, operating
in resource constrained environments, change over their entrepreneurial careers.
Accordingly, the second null-Hypothesis of this Section asserts:
H 2.2: The motivations of academic entrepreneurs operating in resource constrained
environments do not change over their entrepreneurial careers
4.3. The Influence of Multilevel Factors on the ‘Plural Activity’ of Academic
Entrepreneurs in a Resource Constrained Environment
Academics (micro-level), universities (meso-level), and the macro environment, mainly
comprising government and industry, are the three major parties identified in the literature
as involving in the process of academic entrepreneurship (O’Shea et al., 2004, Etzkowitz
and Leydesdorff, 2000). The literature has investigated the influence of these parties on the
propensity for academics to be entrepreneurial. However, as discussed in the Section 3.4 of
A Review of Literature chapter and the Section 4.1 of this chapter, academics may engage
in a combination of entrepreneurial activities, and it will be interesting to investigate how
multilevel causal factors influence the ‘plural activities’ of academics.
The age (Audretsch, 2000), position, level of education, (Levin and Stephan, 1991), gender
(Smith-Doerr, 2004), business management and entrepreneurial knowledge and skills
85
(Franklin et al., 2001), academic discipline (Mowery and Sampat, 2005), and social
network (Siegel et al., 2007) of academics are the personal factors identified in the
literature as statistically related to the propensity of academics to engage in entrepreneurial
endeavour. The following Sections illustrate contradictory arguments in the literature with
respect to the influence of each of these micro-level factors on academic entrepreneurial
engagement, which is followed-up by the proposition of a Hypothesis to investigate the
effects of micro level factors.
Some studies have argued that senior academics have a higher tendency to engage in
entrepreneurial endeavour, owing to their extensive experience, strong social networks,
excellent reputations, and a lack of pressure for publications (Audretsch, 2000, Levin and
Stephan, 1991). Conversely, other research had claimed that, there is a higher probability
for young academics to engage in entrepreneurial endeavour since they have been trained
using new paradigms that promote entrepreneurship (Owen-Smith and Powell, 2001);
(Zucker et al., 2002, Ambos et al., 2008). Markides (2007) also supports this view by
stating that older academics have a lower tendency to engage in entrepreneurial endeavour
since they are generally reluctant to change their traditional academic life styles, while
Jones-Evans and Klofsten (2000) have found that middle aged academics have a higher
tendency to engage in entrepreneurial endeavour. These studies have investigated only the
differences between entrepreneurs and non-entrepreneurs with respect to their
age/seniority. However, academic entrepreneurs might not be homogeneous, and may
diversify their entrepreneurial engagements differently. For example, it may be the case
that young academics adopt one type of ‘plural activity’, while older academics tend to
adopt other types, which have not been captured by previous studies. Therefore, it could be
argued that, there may be links between the ‘plural activity’ of academic entrepreneurs and
their age and position.
It is also stated in the literature that female academics have a lower tendency to engage in
entrepreneurial activities (Whittington and Smith-Doerr, 2005), while male academics
have a relatively high propensity to carry out a wide array of entrepreneurial activities
(Jones-Evans and Klofsten, 2000). Therefore, this study argues that males may diversify
their engagement to a greater extent than females.
The engagement in academic entrepreneurial endeavour has also been found to vary across
academic disciplines (Wright et al., 2004). For example, it has been observed that there are
86
higher levels of opportunities in the applied in comparison to pure (Mowery and Sampat,
2005) or social sciences (Laukkanen, 2003). Furthermore, the need for industry to access
highly skilled university scientists has also been found to be dependent upon academic
disciplines. For instance, Kodama and Branscomb (1999) found that the dependence of
industry on highly skilled university researchers in disciplines such as microelectronics,
software, biotechnology, medicine, and new materials is very high, and that these
disciplines have more opportunities to interact with industry. The availability of funding
from industry has also varied between academic disciplines, whereby physical sciences
generally receive a substantial amount of funding in comparison to the social sciences
(Meyer-Krahmer and Schmock, 1998). Accordingly, it could be argued that the ‘plural
activity’ of academics in applied science disciplines may be different from those who work
in pure and social sciences.
With respect to the level of education, Bercovitz and Feldman (2003) have argued that
academics with PhDs have a higher propensity to interact with industry, and thus, to
engage in entrepreneurial activities to a greater extent. Furthermore, possessing scientific
and/or technological knowledge and skills, which reflect levels of education, have also
been found to be positively correlated with academic entrepreneurial engagement (Dickson
et al., 1998, Franklin et al., 2001). Hence, it could be assumed that academics with PhDs
may adopt ‘plural activity’ types that are different from those who have lower educational
qualifications.
Business management and entrepreneurial knowledge and skills of academics have also
been identified in the literature as influencing the success of academic entrepreneurial
engagement (Dickson et al., 1998, Franklin et al., 2001). Furthermore, entrepreneurial
skills are considered to be crucial when forming academic spin-off companies (McMullan
and Vesper, 1987, Henderson et al., 1998, Mowery et al., 2002). On the other hand, a lack
of entrepreneurial and business management skills has been recognized to be a barrier to
the achievement of success in ventures formed by academics (Franklin et al., 2001, Monck
and Segal, 1983, Fowler, 1984, Lockett et al., 2003).
Therefore, it is possible that the ‘plural activity’ types adopted by academics, who have
high business management and entrepreneurial skills, may be different from those who
have low business management and entrepreneurial skills. On the other hand, as discussed
in the Section 3.5 of A Review of Literature chapter it could also be argued that, as a result
87
of engaging in academic entrepreneurial activities, academics might be able to improve
business management and entrepreneurial knowledge and skills, which could, in turn, be
used to diversify their engagements further. Therefore, even though the direction of
causality is not clear, there may be a relationship between the ‘plural activities’ of
academics and their business management and entrepreneurial knowledge and skills.
The social network of academics has also been found to be a decisive factor in their
engagement in entrepreneurial endeavour and achieving success (Siegel et al., 2007).
Mosey and Wright (2007) stated that habitual entrepreneurs, who have prior experience in
forming new ventures, have a strong network of ties, and thus, have a higher tendency to
achieve success in comparison to novice entrepreneurs who lack such ties. Therefore, it is
possible that the ‘plural activity’ types adopted by academics, who have strong social
networks, may be more effective than those who have weak networks of ties. On the other
hand, as discussed in the Section 3.5 of A Review of Literature chapter it could also be
argued that, as a result of engaging in academic entrepreneurial activities, academics might
be able to develop networks of contacts, which could, in turn, be used to diversify their
engagements further (Agarwal et al., 2004). Therefore, despite the fact that the direction of
causality is unclear, it is possible to have a relationship between the ‘plural activities’ of
academic entrepreneurs and the strength of their social network.
The above stated arguments with respect to the possible associations between the ‘plural
activities’ of academic entrepreneurs and their personal characteristics (i.e. micro level
factors) led to the development of the first null-Hypothesis of this Section, which asserts:
H.3.1: There is no relationship between the ‘plural activities’ of academic entrepreneurs
and their personal characteristics
When testing this Hypothesis 3.1, separate tests will be conducted with respect to each
personal characteristic of academic entrepreneurs (i.e. the age, position, level of education,
gender, business management and entrepreneurial knowledge and skills, academic
discipline, and social networks, of academics).
In addition to micro level factors, meso/university level factors have also been found to
shape academic engagement in terms of entrepreneurial endeavour (Franklin et al., 2001,
Siegel et al., 2007). Such meso level factors, highlighted in the literature, are the research
88
strength (Di Gregorio and Shane, 2003, Ambos et al., 2008), commercial orientation
(Friedman and Silberman, 2003), and resource status (Powers and McDougall, 2005)
(Zucker et al., 1998, Kinsella and McBrierty, 1997) of universities. Therefore, it is possible
to consider that academics within one university are more alike in terms of their
entrepreneurial engagement than those between universities. This had raised the doubt
whether it is micro or meso level factors that have a higher level of influence on academic
entrepreneurship. Based on research carried out in the UK, D’Este and Patel (2007) have
stated that the individual characteristics of academics have a greater impact on determining
the success of entrepreneurial engagements than the characteristics of their academic
departments or universities. This has been further supported by Ambos et al (2008), who
revealed that individual related factors have a greater influence on the decision to
commercialise university generated knowledge than organizational factors for UK
academics. Similarly, Clarysse et al (2011) have also found that personal factors have a
greater influence on starting a new company than environmental factors.
However, these studies have investigated only the relative effects of micro and meso level
factors on the propensity of academics to be entrepreneurial, without considering
heterogeneity among academic entrepreneurs. As discussed before, academic entrepreneurs
may adopt different ‘plural active’ types. Therefore, this research decided to investigate the
relative influence of micro and meso level factors on the propensity to adopt a specific
‘plural active’ type by academic entrepreneurs. Hence, the second null-Hypothesis of this
Section states:
H3.2: There is no difference between the influence of micro and meso level factors on
academic propensity to adopt specific ‘plural activity’ types
This Hypothesis will be tested by developing a model, which will also allow the testing of
how each meso- and micro- level factors affect a propensity to adopt a specific ‘plural
activity’. The previously discussed personal characteristics of academic entrepreneurs (i.e.,
the age, gender, position, level of education, academic discipline, business management
knowledge and skills, entrepreneurial knowledge and skills, and strength of social network
of academics) will be used as micro level independent variables. The objective measures of
the quality of universities, which have been identified in the literature as influencing
academic entrepreneurship (Table 4.3), will be used as meso level independent variables.
Since certain departments in Sri Lankan universities have very few academics, it was
89
decided to use only the university level factors stated in the Table 4.3 in this instance (i.e.
the research strength of universities, commercial orientation of universities, and resource
status of universities).
Table 4.3: The Qualities of Universities affecting Academic Entrepreneurial Endeavour Factors Reference 1. Research strength of the department (Di Gregorio and Shane, 2003, Ambos et al.,
2008) 2. Research strength of the university (Di Gregorio and Shane, 2003, Ambos et al.,
2008) 3. The commercial orientation of the department
(Schartinger et al., 2001)
4. The commercial orientation of the university
(Di Gregorio and Shane, 2003, Friedman and Silberman, 2003)
5. The resources status of the university
(Powers and McDougall, 2005, Zucker et al., 1998, Kinsella and McBrierty, 1997)
The perception of entrepreneurs of their environment has also been found to shape their
entrepreneurial behaviour. For example, it has been argued in the general entrepreneurship
literature that an ability to pursue opportunities is dependent upon the way an individual
perceives the environmental context (Stevenson and Jarillo, 1990, Binks and Vale, 1990).
Therefore, it is interesting to investigate whether the perceptions of academics regarding
the quality of their universities (which might not necessarily reflect the objective measures
of quality used in the above stated model) are associated with the ‘plural activity’ of them.
For example, if the research strength of universities is considered, it could be argued that
academics who believed that the research strength of their universities was high might
have adopted ‘plural activity’ types that are different from those adopted by academics
who believed that the research strength of their universities was low. Furthermore,
comparing and contrasting the effects of the objective measure of quality (i.e. in
Hypothesis 3.2) and that of the perception of quality will allow understanding the role of
the perception of academics (concerning the quality of their universities) in their
entrepreneurial engagements. Accordingly, considering the five types of qualities
mentioned in the Table 4.3, a Null-Hypothesis is proposed to test each quality separately.
H 3.3: There is no relationship between the ‘plural activity’ of academic entrepreneurs
and their perception of university quality
90
In addition to micro- and meso- level factors, the external macro environment, which is
mainly comprised of government and industry, has also been found to shape academic
entrepreneurship (O’Shea et al., 2004, Etzkowitz and Leydesdorff, 2000, Siegel et al.,
2004). By mainly emphasising developed country contexts, the ‘Triple Helix Model’
illustrates how these interactions have been changed over time, from governments
directing university industry interactions to dynamic and strong interactions among three
parties represented by joint innovation efforts. These changes have occurred due to the
development of established institutional frameworks aimed at the encouragement of
academic entrepreneurship (Etzkowitz and Leydesdorff, 2000), which provide stable and
coherent structures for diverse interactions (Delbridge and Edwards, 2007).
However, it is questionable to what extent the triple helix model could be generalised to
apply to resource constrained environments. For instance, it is found in the literature that,
innovations by the industry in developing resource constrained environments are weak
(Intarakumnerd et al., 2002), and less formal (Arocena and Sutz, 2001). It has also been
revealed that institutional frameworks for innovation in developing countries are neither
integrated nor well developed, and are mostly isolated. As a result, strengths at the micro
level are not integrated with those at the macro level (Arocena and Sutz, 2001). It has been
confirmed that Sri Lanka is no exception to this trend, since supportive mechanisms and
institutional framework for university industry interactions are very weak, and the research
and development spending of Sri Lankan industry is extremely low (Esham, 2008).
The weak innovation capabilities of industry and supporting mechanisms for university-
industry interactions could mean that there is less scope for academics in resource
constrained environments to collaborate with industry. However, it is also possible to argue
that the weak innovation capabilities of industry may provide a window of opportunity for
academics to collaborate with, since industry may seek to capitalise on the knowledge and
skills of academics, in order to receive access to the infrastructure facilities of universities
(e.g. labs) (Meyer-Krahmer and Schmock, 1998). Despite this dependence, a lack of
institutional frameworks could mean that university-industry interactions are rather
scattered, and occur mainly at the micro level, without integrating with government level
missions (Arocena and Sutz, 2001). Therefore, in this research it was decided to
investigate the nature of interactions between the university, industry, and government in
resource constrained environments, and thus, the fourth null-Hypothesis of this Section
states:
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H3.4: Interactions between university, industry and government in a resource
constrained environment do not differ from those in a developed environment
4.4. The Impacts of Academic Engagement in Entrepreneurial Activities in a
Resource Constrained Environment
It is highlighted in the literature that academic entrepreneurship could have negative
impacts on normal academic duties (Dasgupta and David, 1994, Rosenberg and Nelson,
1994). First, this may be due to resource conflicts that arise when limited facilities
available in universities are used for multiple activities (Van Dierdonck and Debackere,
1988). Second, negative impacts can occur through difficulties faced by academics in
balancing normal academic duties and entrepreneurial endeavour since academic
entrepreneurial engagements demand substantial efforts and time commitments (Wright et
al., 2004), which could result in academics not performing any task successfully (Bercovitz
and Feldman, 2003).
On the other hand, previous studies have also argued that academic entrepreneurship
generates additional income streams for academics (Wright et al., 2004) and for their
universities, which is perceived to be a potent way of compensating for scarce direct
government funds available to universities (Phan and Siegel, 2006, Wright et al., 2006).
Academic entrepreneurship has also been found to improve the status (Orhan and Scott,
2001), knowledge and skills (D'Este et al., 2010), and professional network (Siegel et al.,
2007) of academics. Furthermore, it has been reported that academic entrepreneurship
enhances future opportunities for collaboration (D’Este and Patel, 2007), access to
facilities/resources in industry (Siegel et al., 2004), and mobility between academia and
industry (Van Dierdonck et al., 1990).
Moreover, recent research findings have revealed a positive relationship between the
number of academic publications and academic engagement in entrepreneurial endeavour
(Calvert and Patel, 2003, Van Looy et al., 2006, Lowe and Gonzalez-Brambila, 2007,
Brooks and Randazzese, 1999). Similarly, academic experience in interacting with industry
is deemed to have positive influences on education since it contributes to producing
graduates suitable for industry (Baldini et al., 2006). It was also found that academic
entrepreneurs are more productive in terms of teaching and research than academics
without entrepreneurial engagements (Louis et al., 2001, Siegel et al., 2004). In a similar
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vein, it has been stated in the literature that, “star” scientists have engaged in more
academic entrepreneurial activities than others (Zucker and Darby, 2001, Erdis and Varga,
2009).
Etzkowitz (1998) argues that this proposed positive symbiotic relationship between
academic entrepreneurship and normal academic duties has been mainly caused by using
additional income, experience, knowledge, and contacts developed through academic
entrepreneurship, to improve normal academic duties. These findings are consistent with
those at the university level, in which university involvement in entrepreneurial endeavour
has not been found to jeopardise the quality or quantity of basic research (Siegel et al.,
2004). Therefore, it could be argued that, in addition to synergies between academic
entrepreneurial activities described in the Section 4.1 of this chapter, there may be
beneficial synergies between academic entrepreneurship and normal academic duties.
On the basis of the above discussion, the current study argues that, on the one hand,
academic entrepreneurship in a resource constrained environment could have positive
impacts on normal academic duties owing to synergies between academic entrepreneurship
and normal academic duties, which are of paramount importance to overcome resource
constraints. On the other hand, however, it could be argued that the quality of normal
academic duties could be negatively affected by the entrepreneurial engagements of
academics due to likely resource conflicts. Therefore, the first Null-Hypothesis of this
Section proposes that:
H 4.1: The entrepreneurial engagements of academics in resource constrained
environments have no impact on their normal academic duties
It will also be interesting to investigate whether the possible impacts of academic
entrepreneurship on normal academic duties vary across the ‘plural activity’ types of
academic entrepreneurs. For instance, based on the seven ‘plural activity’ types described
in the Section 4.1 of this chapter, it could be hypothesised that those who carry out
activities related to normal academic duties may benefit more from synergies than those
who have engaged in activities distantly related to teaching and research (e.g. company
creation). Accordingly, the second Null-Hypothesis of this Section asserts:
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H 4.2: In resource constrained environments, there is no association between the ‘plural
activity’ of academic entrepreneurs and their impact on normal academic duties
In addition to university and individual level impacts, academic entrepreneurial
engagement has also been found to have wider economic impacts (Pattyn, 2006,
Etzkowitz, 1998). Previous studies have shown that academic entrepreneurship allows the
deriving of direct economic benefits from university generated knowledge (Pattyn, 2006,
Etzkowitz, 1998). For example, spin-off formation is reported to generate wealth, and to
create jobs (Birch, 1987). University-industry technology transfer provides opportunities
for industry to capitalise on the knowledge and skills of academics, and to gain access to
the infrastructural facilities of universities (e.g. labs) (Meyer-Krahmer and Schmock,
1998). It has also been argued in the literature that, universities have the potential of
contributing to regional economic development through the fuelling of industry and
converting ideas into profits (Uyarra, 2010, Baldini et al., 2006).
However, the extent of these economic impacts can vary, depending on the type of
academic entrepreneurial activity. For instance, Cohen et al (2002), using data from the
Carnegie Mellon Survey on industrial research and development in the U.S. manufacturing
sector, concluded that, licensing and venture creation by academics represent only a minor
form of technology transfer in comparison to published papers and reports, public
conferences and meetings, and consulting. Moreover, Agrawal and Henderson (2002),
studying the Departments of Mechanical and Electrical Engineering at Massachusetts
Institute of Technology (MIT), found that patents represent less than 10% of the total
knowledge transferred from their labs (mainly in comparison to publications).
These findings have led to a recent debate which considers whether creating companies by
academics, or training students to be entrepreneurial, produces the greatest economic value
(Shane, 2005). Therefore, it was decided in this research to investigate the relative national
economic importance of different knowledge transfer activities. As a common measure of
national economic importance of different academic entrepreneurial activities, it was
decided to use the perceived economic importance of each activity by academic
entrepreneurs. The use of such a subjective measure has been recommended in the absence
of an objective measure (Dess and Robinson, 1984), which in this research is judged to be
the dearth of a common measure of national economic importance of different academic
entrepreneurial activities. Accordingly, the third Null-Hypothesis of this chapter states:
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H4.3: There is no difference among academic entrepreneurial activities with respect to
the academic perception of their national economic importance
The Table 4.4 summarises the hypotheses of this research.
Table 4.4: Research Objectives and Hypotheses
Objective 1 Investigating the ‘Plural activities’ of Academic Entrepreneurs in a Resource Constrained Environment
Hypothesis
1.1
Being entrepreneurial is not a means of overcoming resource barriers in a
resource constrained environment
Hypothesis
1.2
There is no association between the ‘plural activity’ of academic
entrepreneurs and the extent of synergistic effects generated in a resource
constrained environment
Objective 2 Investigating the Motivation of Academic Entrepreneurs in a Resource Constrained Environment
Hypothesis
2.1
In resource constrained environments, there is no association between the
‘plural activity’ of academic entrepreneurs and their motivations
Hypothesis
2.2
The motivations of academic entrepreneurs operating in resource
constrained environments do not change over their entrepreneurial careers
Objective 3 Investigating the Influence of Multilevel Factors on ‘Plural Activities’ in a Resource Constrained Environment
Hypothesis
3.1
There is no relationship between the ‘plural activity’ of academic
entrepreneurs and their personal characteristics Hypothesis
3.2
There is no difference between the influence of micro and meso level
factors on academic propensity to adopt specific ‘plural activity’ types
Hypothesis
3.3
There is no relationship between the ‘plural activity’ of academic
entrepreneurs and their perception of university quality
Hypothesis
3.4
Interactions between university, industry and government in a resource
constrained environment do not differ from those in a developed
environment
Objective 4 The Impacts of Academic Entrepreneurial Engagement in a Resource Constrained Environment
Hypothesis
4.1
The entrepreneurial engagements of academics in resource constrained
environments have no impact on their normal academic duties Hypothesis
4.2
In resource constrained environments, there is no association between the
‘plural activity’ of academic entrepreneurs and their impact on normal
academic duties Hypothesis
4.3
There is no difference among academic entrepreneurial activities with
respect to the academic perception of their national economic importance
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Chapter 5: Research Methodology
The previous chapter of this thesis discussed the hypotheses formulated to study academic
entrepreneurship in a resource constrained environment. The purpose of this chapter is to
discuss the methodology adopted in this research. The research used a three stage
sequential mixed method design. During the first phase, context specific data was collected
which was used to design the two subsequent data gathering stages; namely, an on-line
survey and in-depth interviews. The methodology was shaped by the philosophical stance
of this research, which was critical realism. The following Sections of the chapter initially
justify the choice of this research philosophy, and subsequently, discuss sampling, data
collection, and data analysis, together with methodological and philosophical justifications.
Finally, the chapter concludes with a chapter summary.
5.1. Research Philosophy
The research philosophy adopted in a study, which explains the nature and development of
knowledge (Saunders et al., 2009), is believed to underpin its research design (Ritchie and
Lewis, 2003). Therefore, philosophical assumptions are often used in the literature to
justify the use of a particular methodology (Midgley, 2000). Since there is no widely
accepted single best research philosophy, it is logical to select a philosophy which is most
suitable to the objectives of a research project (Ritchie and Lewis, 2003, Tashakkori and
Teddlie, 1998). This necessitates justifying the choice of one philosophy over other
alternatives (Johnson and Clark, 2006).
Positivism (Pugh and Hickson, 1976), pragmatism (Howe, 1988), critical realism (Bhaskar,
1998), interpretivism (Schwandt, 2000), philosophical hermeneutism, and social
constructionism (Ritchie and Lewis, 2003) are the main philosophies highlighted in the
literature. These previous studies have argued that positivism is generally equated with
quantitative methods, while constructionism (which consists of interpretivism,
philosophical hermeneutism, and social constructionism) is most often associated with
qualitative methods (Guba and Lincoln, 1994). On the other hand, pragmatism is
considered to be associated with mixed methods, since it promotes the use of a
combination of qualitative and quantitative methods that are best suited to answer specific
research questions (Howe, 1988). Similarly, critical realism is gaining popularity in mixed
96
method research since its ontological perspective resembles the assumptions of positivism,
while its epistemological stance is related to constructivism (Ackroyd, 2000, Sayer, 2000).
As discussed above, since there seems to be a generally accepted association between
methodologies and research philosophies, this study has used the type of data (i.e.
qualitative data, quantitative data, or both) required to achieve the current research
objectives as a basis for narrowing down the selection process to a more appropriate
philosophy (Maxcy, 2003). The analysis illustrated in Table 5.1 suggests that this research
needs both qualitative and quantitative data. Therefore, the selection process was reduced
to two philosophies associated with mixed methods; namely, critical realism and
pragmatism.
Table 5.1: The Types of Data needed to achieve Research Objectives
Research Objectives The type of data Investigating the ‘Plural activities’ of Academic Entrepreneurs in a Resource Constrained Environment
Quantitative data – about academic engagement in 17 activities to identify ‘plural activity’ types adopted by academic entrepreneurs Qualitative data – in-depth qualitative data about ‘plural activity’ types adopted by them, including synergies among academic entrepreneurial activities
Studying the Motivation of Academic Entrepreneurs in a Resource Constrained Environment
Quantitative data – about the extent to which each pull and push factor motivated them Qualitative data – in-depth qualitative data about their motivation and particularly, how entrepreneurial motivation has been changed over their academic entrepreneurial careers.
Examining the Influence of Multilevel Factors on ‘Plural Activities’ in a Resource Constrained Environment
Quantitative data – about the personal characteristics of academic entrepreneurs, the perception of quality of university level factor, and the quantitative measures of university quality Qualitative data- in-depth qualitative data about the potential complex relationships between the plural activity of academic entrepreneurs and micro and meso level factors, and nature of interactions between universities, government, and industry, in relation to academic entrepreneurship.
The Impacts of Academic Entrepreneurial Engagement in a Resource Constrained Environment
Quantitative data – the extent of positive or negative impacts of academic entrepreneurial engagement on normal academic duties, and the level of national economic importance of each academic entrepreneurial activity Qualitative data – in-depth qualitative data about synergies or rivalries between normal academic duties and academic entrepreneurial activities, and the national economic importance of each activity
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The proponents of pragmatism have recommended the use of a mixture of both qualitative
and quantitative methods that are most appropriate to answer specific research questions
without giving too much emphasis on philosophical underpinnings (Seale, 1999).
However, it is argued in the literature that even though pragmatism seems to be practically
sound, it does not ensure the validity of a mixed method research methodology (Maxcy,
2003). This criticism has been mainly due to pragmatism allowing the combining of
different incompatible philosophical perspectives that do not serve the purpose of
triangulation, but sacrifice the strengths of one perspective for another (Blaikie, 1991).
Therefore, the literature has highlighted the importance of balancing pragmatic viewpoints
and philosophical perspectives (Silverman, 1993). Considering this dichotomy, Modell
(2009) has convincingly illustrated how critical realism could be used to asses validity in
mixed methods research, which overcomes the weaknesses of pragmatism. Hence, it was
decided to use critical realism as the philosophical stance of this research and its use in this
study is illustrated in the following Sections.
As a result of selecting critical realism, this study was underpinned by its ontological
perspective, which stated that the world is ‘real’, and exists and acts at least partially
independent of our knowledge of it (Sayer, 2000). Similarly, the methodology of this study
was shaped by its epistemological perspective. This perspective affirmed that the findings
may hold true under particular context specific circumstances since humans could
experience only a subset of actual events (Sayer, 2000, Danermark et al., 2002, Outhwaite,
1998). In an attempt to elaborate the ontological and epistemological viewpoints of critical
realism, Bhaskar (1998) has illustrated three major domains of reality, namely the ‘real’
domain, the ‘event’ domain, and the ‘empirical’ domain. It is stated that empirical
experience (in an ‘empirical’ domain) is a result of ‘actual events’ (in an ‘event’ domain)
generated by causal powers embedded in context-specific real mechanisms (in a ‘real’
domain), where empirical experience represents only a portion of ‘actual events’. It is also
stated that the real mechanisms that generate events are complex and not simply
unidirectional (Bhaskar, 1998, Outhwaite, 1998).
When adapting these concepts to this study, it could be considered that empirical data
about the nature of academic entrepreneurship (i.e., academic engagement in different
entrepreneurial activities), which is in the ‘empirical’ domain, is a result of events that are
generated by causal powers (e.g. multilevel causal factors that influence academic
entrepreneurship) in the ‘real’ domain. It could also be stated that these causal powers are
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complex, and specific to a resource constrained environment. Based on this philosophical
foundation, the following Sections of the chapter illustrate the use of mixed methods in this
research, together with philosophical and methodological justifications.
5.2. The Mixed Method Design
As discussed above, the main reason for deciding to use mixed methods in this research
was the need to have both qualitative and quantitative data to achieve the research
objectives. The use of mixed methods has additional advantages, such as overcoming the
weaknesses of using either qualitative or quantitative methods (Brewer and Hunter, 1989),
and improving the validity of research through triangulation (Cook and Campbell, 1979).
Sequential (where collection and analysis are performed at different times and one method
reinforces the other), and parallel, data collection (in which evidence is collected at the
same time and the data analysis is complementary) are two different mixed method designs
described in the literature (Tashakkori and Teddlie, 1998). Previous studies of academic
entrepreneurship, which are carried out in contexts that are not subject to prior research,
have mostly used sequential mixed methods research designs. For instance, in an
exploratory study of university entrepreneurship centres in Canada, Menzies (2000) used a
sequential mixed method approach, in which qualitative interviews were followed by a
questionnaire survey. Qualitative interviews were used for the purpose of identifying issues
specific to the context, which were later addressed in a questionnaire survey. Similarly, in
assessing the preferences of nascent academic entrepreneurs, Brennan et al (2005) adopted
a two stage research design. During the first stage, data was collected by conducting in-
depth interviews with policy makers, the managers of innovation, and academic
entrepreneurs, which was then used to develop a survey questionnaire for the second stage.
In a similar vein, Yang et al (2006), studying factors nurturing academic entrepreneurship,
piloted questionnaires in a specific context via a qualitative interview phase, which was
followed by a postal survey.
These research designs highlighted the importance of amalgamating existing theory with
context specific findings when designing a major data collection phase of a study, carried
out in a context that lacks prior research (Downward and Mearman, 2007). Further
justification for conducting initial context-specific data gathering was provided by critical
realism, which argues that integrating theory with context specific factors allows the
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identification of context specific causal powers which are not accounted for by initial
theorizing (Modell, 2009). This strategy has been found to improve the construct validity
of mixed method research (Tashakkori and Teddlie, 1998, Bisbe et al., 2007). Since this
research was conducted in Sri Lanka, where no prior research on academic
entrepreneurship has been conducted, it was decided initially to gather context specific
data, which was then amalgamated with the literature when designing subsequent major
data collection phases.
The designing of subsequent major data collection phases was shaped by the type of data
required for this research, which was both qualitative and quantitative data (Table 5.1).
While the main purpose of quantitative data was to obtain a broad understanding of
entrepreneurial engagements by academics, qualitative data was needed to investigate their
engagements in detail. Therefore, it was decided to carry out a survey first to gather
relevant quantitative data, and then, follow this up by a qualitative data gathering phase.
This strategy was supported by critical realism, which assumes that statistically derived co-
variations between variables are only superficial representations of causal powers in real
mechanisms, and thus, is insufficient to provide an in-depth understanding (Modell, 2009).
Hence, this approach suggests gathering in-depth qualitative data, as a strategy to
understand context specific causal mechanisms (Bhaskar, 1998). Therefore, it was
considered that following the survey with a qualitative data collection phase would
improve the internal validity of this research (Downward and Mearman, 2007).
Additionally, the qualitative data gathering stage was used to collect any relevant emerging
data that were not captured by initial theorizing. As described above, this research used a
sequential mixed method design with three major phases namely, an initial data gathering
stage, a questionnaire survey, and a qualitative data gathering phase. The following
Sections of the chapter discuss these three stages in detail.
5.3. The Initial Data Gathering Stage
The main purpose of the initial data gathering stage was to collect general information
about the entrepreneurial engagements of academics in Sri Lanka. Sri Lanka did not have
technology transfer offices, and thus, this study decided to collect data from the registrars
of universities. Accordingly, in-depth telephone interviews were conducted with the
registrars of 8 out of 15 universities in Sri Lanka. The data was initially analysed to check
whether academics in Sri Lanka carry out the 17 academic entrepreneurial activities
100
identified from the literature. As illustrated in Appendix 5.1, the analysis confirmed that
academics in Sri Lanka do carry out these activities, but respondents suggested modifying
the descriptions of certain activities in order to be in line with the context specific use of
terms. These initial findings were incorporated when designing the survey questionnaire,
and thus, it is believed that this process has improved the construct validity of the survey
(Bisbe et al., 2007).
Furthermore, the data gathered during the initial phase was used to gauge to what extent
the theoretical categorization of activities into three groups (i.e., teaching related academic
entrepreneurial activities, research related academic entrepreneurial activities, and
company creation) (for more details, please refer Section 4.1, Research Hypotheses
Chapter) was applicable in a Sri Lankan context. Rather than the categorization being
solely driven by either theory or data, complementing data with theory was considered as a
better strategy that enhances the validity of a study (Tsoukas, 1989, David and Christopher,
1996, Kwok and Sharp, 1998). Further justification is provided by critical realism, which
states that data in the ‘empirical’ domain (i.e. what researchers observe), illustrate only a
portion of ‘events’ (i.e. real outcomes) generated by real mechanisms (i.e. causal factors,
which are being identified from theories), and thus, data or theory alone might not allow an
understanding of reality. Therefore, the respondents of the initial data gathering stage were
asked to categorize 17 academic entrepreneurial activities into three groups, while the
researcher also independently analysed the detailed information about general
engagements by academics to check the appropriateness of this theoretical categorization.
As illustrated in the Appendix 5.1, these analyses confirmed the validity of the theoretical
categorization of activities.
5.4. The Survey and Qualitative Data Gathering Phase
Survey and qualitative data gathering, which reinforce each other, were the two major data
collection phases of this study. Hence, the following Sections discuss how these two
phases were integrated during sampling, data collection, and data analysis.
5.4.1. Sampling Strategy – The Survey and Qualitative Data Gathering Phase
The design of a sampling strategy is dependent upon the unit of data collection and
analysis, which is shaped by the objectives and hypotheses of a study (Yin, 2003). Since
101
the focus of the four objectives of this study was to investigate entrepreneurial
engagements by academics, factors affecting them, and the impacts of their engagements,
it was decided to consider the academic as the unit of data collection and analysis.
Sri Lanka had 15 public universities. There were not any private universities, other than
some private institutions mainly focused on teaching. Out of the 15 universities, the
University of Jaffna was excluded due to issues related to accessibility since it was situated
in previous war zone. This study considered the University of Visual and Performing Arts
a part of the University of Kalaniya. This was due to the reason that the University of
Visual and Performing Arts was attached to the University of Kalaniya until 2005, and
even after separation both were located in close proximity. The above decision was further
supported by the fact that visual and performing arts was a department of the faculty of arts
in other universities in Sri Lanka. Accordingly, the population/sampling frame of this study
involved academics in 13 universities (i.e. a total of 4215 academics as at 01.01.2009)
(University Grant Commission of Sri Lanka, 2011). Even though it would have been
possible to send the survey to all the academics in Sri Lanka, this was not considered an
option due to cost and time constraints.
Since this study has two major data collection phases, it was necessary to select an
appropriate unified sampling strategy, which could serve the purposes of both the phases.
Probability and non-probability sampling were the two main types of sampling techniques
mentioned in the literature. In the probability sampling technique, each element of the
sampling frame has a known non-zero probability of being selected, and it is generally
used in quantitative research. On the other hand, the non-probability sampling technique
requires that units are selected purposively, and it is mostly used in qualitative research
(Groves, 2004). Teddlie and Yu (2007) have discussed how probability and non-
probability sampling techniques could be combined to create mixed method samples, and
have identified four main types of mixed methods sampling techniques; namely, basic
mixed methods sampling, sequential mixed methods sampling, concurrent mixed methods
sampling, and multilevel mixed methods sampling (Table 5.2).
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Table 5.2: Mixed Method Sampling Techniques
Sampling Technique Description Basic Mixed Methods Sampling
This sampling technique uses an element of probability sampling within non-probability sampling. e.g. stratified purposive sampling, purposive random sampling
Sequential Mixed Methods Sampling
This represents the sequential use of probability and non-probability sampling. The information gathered from one sample is used to derive the other sample.
Concurrent Mixed Methods Sampling
Both probability and non-probability sampling techniques are used simultaneously and independently.
Multilevel Mixed Methods Sampling
Adopting different sampling techniques for selecting elements which are at different levels (e.g. micro, meso, and macro)
Source: Teddlie and Yu (2007)
Concurrent mixed method sampling uses both probability and non-probability sampling
techniques simultaneously and independently, and thus, is suitable mainly for parallel
mixed method designs. Since this study used a sequential mixed method design, concurrent
mixed method sampling was not considered appropriate. Similarly, multilevel mixed
method sampling was excluded since this study collected data only from academics. Out of
the two remaining sampling techniques, the current research selected the sequential mixed
method sampling technique since the main purpose of qualitative data gathering phase was
to obtain an in-depth understanding of the findings of the survey. This justified the use of
the findings of the survey to derive a sample for in-depth interviews. A probability
sampling technique is used in the survey, and a representative sample of academics who
have responded to the survey is selected for qualitative data gathering phase (Teddlie and
Yu, 2007). Therefore, the sampling strategy used for the qualitative data gathering phase
was non-probability based, since all the units in the population of academics in Sri Lanka
did not receive an equal chance of being selected. Only those who have responded to the
survey had an equal chance of being selected. The following Sections discuss the sampling
strategy of these two phases in detail.
5.4.1.1.Sampling Strategy - Survey
The main probability sampling techniques associated with quantitative methods are simple
random sampling, stratified random sampling, systemic sampling, and cluster sampling
(Gravetter and Forzano, 2009). Simple random sampling is recommended only when the
population is homogeneous (Snedecor and Cochran, 1989). Since the population of this
study is heterogeneous in terms of their personal characteristics (which were found from
the personal profiles of academics on university websites and may influence their
103
entrepreneurial engagements), a simple random sampling technique was excluded.
Systemic sampling was not considered appropriate since there was no systemic dimension
to elements in the population.
Even though stratified random sampling was appropriate for a heterogeneous population
with known strata, it was not used in this research for several reasons. Since the sample of
the qualitative data gathering phase was a subsample of the respondents of the survey, the
use of stratified random sampling for the survey would have resulted in a costly and time
consuming qualitative data gathering phase (i.e. gathering qualitative data from academics
in all 13 universities). On the other hand, a list of elements of the sampling frame was not
available. Even though it was possible for the researcher to prepare a list using data
available on university websites, it would have been time consuming. Furthermore, only
data on departments and faculties to which academics were attached, and their positions
and genders, were available on these websites. If the department or faculty of academics
had been selected as the criterion for stratification, it would have caused difficulties due to
a higher number of strata, since there were 458 departments and 79 faculties (University
Grant Commission of Sri Lanka, 2011) in total. Furthermore, some departments had very
few academics. Although gender and position would have been used as criteria for
stratification, due to the above stated cost and time concerns, it was decided not to use a
stratified random sampling technique.
Therefore, it was decided to use cluster sampling. The use of cluster sampling due to
pragmatic reasons, such as the unavailability of a list of elements of the sampling frame,
time and cost savings, has been recommended in the literature (Levy and Lemeshow,
2008). The difference between strata in stratified random sampling and clusters in cluster
sampling is that elements in one stratum is homogeneous (based on a given criterion),
whereas elements in a cluster sampling are heterogeneous. Furthermore, while strata are
different, based on a given criterion, clusters are similar (Levy and Lemeshow, 2008).
Even though it might be sensible to think that universities are ‘clusters’ consisting of a
group of academics, this assumption has been criticised by Fleiss and Zubin (1969) since
these ‘clusters’ do not yield any statistical or mathematical evidence to say that they are
homogeneous (which is a requirement of simple cluster sampling technique).
Therefore, as a strategy to reduce potential sampling errors (Arber, 2001), this study
selected a representative sample of clusters (i.e. universities) in terms of criteria which
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might influence academic entrepreneurship. Franklin et al (2001) have argued that old
established universities could out-perform new universities in terms of their engagements
in entrepreneurial activities. According to them, this was due to old universities having
high calibre academics and well-established research profiles, while new universities had
relatively low research capacity and limited access to funding. Similarly, the location of
universities has also been considered a factor affecting technology transfer attempts, in
which being situated in an industrialised area with a higher number of technology related
companies was found to have positive impacts on academic entrepreneurship (Friedman
and Silberman, 2003, Agrawal and Henderson, 2002). Furthermore, the size of universities
has also been identified as a factor affecting academic engagement in entrepreneurial
endeavour (Baldini et al., 2006). Therefore, it was decided to use the age, location and size
of universities as criteria for cluster sampling.
When using the age of the university as a criterion, initially the universities in Sri Lanka
were categorised into three groups; namely those which have been established between
1940 and 1950 (4 universities), 1970 to 1980 (4 universities), and 1990 to 2000 (5
universities). Two universities from each category were selected, and when selecting two
universities from each category attempts were made to maintain their representativeness in
terms of the location and size (See Appendix 5.2 for details about 13 universities in Sri
Lanka). Initial interviews with the registrars of universities revealed that a location being
rural or urban, and being closer to capital city (i.e. Colombo) or not, were the main
determinant factors of the location of universities. In the total population, 6 out of 13
universities were located in urban areas, and in the sample, 3 out of 6 universities were
situated in urban areas. In the total population, 5 out of 13 universities were located in
close proximity to Colombo, while in the sample, 2 out of 6 universities were located
closer to Colombo. In terms of the size of universities, 5 out of 13 universities had more
than 10% share of the population of university students in Sri Lanka, and in the sample, 2
out of 6 universities represented this category. Each of the rest of the universities had a
share of less than 5%. Furthermore, 5 out of 13 universities each had more than 10% of the
population of university academics in Sri Lanka, and in the sample, 2 out of 6 universities
represented this category. Each of the rest of the universities had less than 10% of the total
population of university academics (See Appendix 5.2 for details about the characteristics
of 13 universities in Sri Lanka).
105
The above strategy on selecting a representative sample of universities based on their age,
location, and size, was to make sure that the influence of universities on academic
entrepreneurship would not negatively affect the representativeness of the sample. After
collecting data, a multilevel analysis was conducted to test how much variation in ‘plural
activity’ types adopted by academic entrepreneurs was explained by the variation in terms
of the universities of academics. Interestingly, the analysis revealed that the ‘plural
activities’ of academics was not significantly influenced by the universities. Therefore, this
finding confirmed the appropriateness of using cluster sampling technique in this research,
since universities qualified to be considered homogeneous ‘clusters’ (which was a
prerequisite of cluster sampling technique) (Levy and Lemeshow, 2008).
Even though the statistics of University Grant Commission stated that there were 2,016
permanent staff members in the six selected universities, the email addresses of only 1,321
academics were found from the websites of respective universities and in certain cases, by
contacting respective departments. Accordingly, the survey questionnaire was sent to 1,321
academics. However, 139 emails were returned due to errors in the email addresses.
Therefore, the total sample size of this survey was 1,182. As illustrated in Table 5.3, out of
those who received a request to participate the survey 30.29% completed (N=358) it.
Incomplete questionnaires (N=23) were excluded. Non-response bias test (Armstrong and
Overton 1977) revealed that respondents do not differ significantly from non respondents
with respect their universities X2(5, 1182) = 2.976 , p=.704 > 0.05, gender X2(1, 1182)=
3.674 p=.06>.052, academic discipline X2(7, 1182)= 10.410, p=.167>.05, and position
X2(2, 1182)= 1.015, p=.602>.05 (See Appendix 5.3 for the detailed results of non-
parametric tests).
Table 5.3: Sampling – On-line Survey
Description Number/percentage
Number of emails sent 1321 Number of emails returned owing to errors in email addresses 139 The size of sample (1321 – 139) 1182 Number of questionnaires returned 378 Number of incomplete questionnaires 23 Number of completed questionnaires 358
Rate of response (358/1182) 30.29%
2 The author acknowledges possible gender bias at 90% confidence level. However, it was not possible to amend it since the bias test was calculated after data collection.
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5.4.1.2. Sampling Strategy – The Qualitative Data Gathering Phase
A sample of in-depth interviews was derived based on the findings of the previous survey.
This is a technique successfully adopted in mixed method research in social and
behavioural sciences, and is considered to result in data with both breadth and depth
(Teddlie and Yu, 2007).
Out of those who responded to the survey (N=358), 43 academics had not engaged in any
entrepreneurial activity. Except for 13, the rest of them (N=302) had adopted three ‘plural
activity’ types (i.e. type 1, type 4, and type 7) (Table 5.4). Hence, it was decided to select a
representative sample of academics from those who have adopted the three prominent
‘plural activity’ types. The sample size of the qualitative data gathering phase was 78,
which comprised 15 academics who had adopted the type 1 ‘plural activity’, 28 academics
who had adopted the type 4 ‘plural activity’, and 35 academics who had adopted types 7
‘plural activity’ (Table 5.4). Those who have adopted other ‘plural activity’ types, namely,
type 2 (N=8), 3 (N=1), and 6 (N=4) ‘plural activity’ types were contacted via emails to
obtain further information about their engagements. Non-entrepreneurs were not
interviewed, since data needed from them to achieve the research objectives has already
been obtained in the previous survey.
Table 5.4: Basis for the Sampling of Qualitative Data Gathering Stage
‘Plural activity’ Types adopted by Academic Entrepreneurs
Teaching related academic entrepreneurial activities
Research related academic entrepreneurial activities
Company Creation
Frequency Qualitative Data Gathering Phase*
Type 1 √ 30 15 Type 2 √ 8 Type 3 √ 1 Type 4 √ √ 150 28 Type 5 √ √ 0 Type 6 √ √ 4 Type 7 √ √ √ 122 35 Total 302 78 √ indicate that academics have diversified into at least one activity in the respective
category
* It was attempted to maintain the representativeness in terms of university, gender,
position, and academic discipline when selecting academics for qualitative interviews.
However, the size of the sample was also constrained by the availability and willingness of
academics to participate for an in-depth interview.
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5.4.2. Data Collection and Data Analysis – The Survey and Qualitative Data
gathering Phases
In order to conduct the survey, it was necessary to select one out of two common survey
tools; namely, postal surveys or on-line surveys. The advantages of an on-line survey over
a postal survey are cost (Bachmann and Elfrink, 1996) time saving (Bachmann and Elfrink,
1996, Taylor, 2000), and a proven ability to receive higher response rates (Mehta and
Suvadas, 1995). Therefore, the current study decided to use an on-line survey. However,
unlike postal surveys, invitations sent to participate in an on-line survey have often been
found to be misinterpreted as spam (Andrews et al., 2003). Therefore, in order to minimize
this risk, this research sent personally addressed official emails, for which personal
information (i.e., gender, position, department and faculty) was obtained from university
websites. This researcher having been a lecturer in one of the universities in Sri Lanka,
also added another element of credibility.
Separate web links were created for each academic, which enabled the linking of data
obtained from the on-line survey, and that gathered from university websites without
asking personal information during the survey. This had an additional advantage, since it
allowed the recognition of each academic, which was useful when contacting them during
the qualitative data gathering phase. Due to ethical reasons, academics were informed that
they were sent personalised on-line survey links. The first round of emails was sent during
the 21st February 2010 – 27th February 2010, and in addition to these initial emails, two
reminders were sent. The first round of reminders was sent during the second week of
March 2010, the second round reminders was sent during the last week of March, and the
survey was closed on the 4th of April 2010. Since data was collected in less than 1.5
months, it was considered that there the chance of bias was reduced with respect to time
taken to respond to the survey.
For qualitative data gathering, it was necessary to decide on a method from major
qualitative data collection methods, namely, in-depth interviews (Kvale, 1983), focus
group discussion (Krueger, 1994), and observations (Douglas, 1976). Since this research
required an in-depth understanding of the entrepreneurial engagements and motivations of
academics, as well as the impacts of their engagements, it was decided to use in-depth
interviews. Silverman (1993) had described ‘in-depth interview’ as a humanistic approach
in which the interviewer and interviewee become ‘peers’ or even ‘companions’ where the
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knowledge gained and the validity of the analysis are based on ‘deep’ understanding (pp.
95). Focus group discussions were not considered appropriate since certain types of
information were personal, which interviewees might not be willing to share with
colleagues.
Structured, semi-structured, and unstructured questionnaires are the three main types of
questionnaires generally used for in-depth interviews (Gillham, 2000). Since the in-depth
interview phase was shaped by the findings of the on-line survey, it was necessary that the
questionnaire should be structured to some extent. However, since it was also needed to
gather in-depth qualitative data, and to allow some space to incorporate emerging data,
open ended questions were also included in the questionnaire. Therefore, the study used a
semi-structured questionnaire. The survey questionnaire and interview questionnaire are
illustrated in Appendix 5.4 and Appendix 5.5, respectively, and are referred in following
Sections when explaining data collection procedures.
The on-line survey was piloted with 16 academics, and the in-depth interviews were
piloted with 5 academics. The feedback was incorporated into finalised questionnaires,
which is a strategy adopted in the literature to improve research validity and reliability
(Fink, 2006). SPSS 16.0 was used to analyse quantitative data, and NVivo 8 was used to
analyse qualitative data. Unlike using either qualitative or quantitative methods, when
mixed methods are used, the literature recommends clear illustration of how qualitative
and quantitative data collection and analyses were amalgamated to answer research
questions (Morgan, 1998, Creswell, 2003). Therefore, the following Sections of this
chapter illustrate how qualitative and quantitative data gathering and analyses were
amalgamated to test the hypotheses formulated to achieve the four research objectives.
5.4.2.1. Mixed Methods: Objective 1: Investigating the ‘Plural Activities’ of Academic
Entrepreneurs in a Resource Constrained Environment
In order to test two hypotheses formulated to investigate the nature of academic
entrepreneurial engagement, this study gathered data on academic engagement for 17
academic entrepreneurial activities (for more details about 17 academic entrepreneurial
activities please refer Appendix 5.1). Therefore, in the on-line survey, academics were
asked to state whether they had engaged in these activities over the last five years (i.e. 1st
January 2010- 1st January 2005) and/or before (survey options- 1. no, never, 2. yes,
engaged in during last 5 years, 3. yes, engaged in before 1 January 2005, 4. yes, engaged in
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both before and during last 5 years) (Survey Question No 2). The following Sections
illustrate how data collection and analysis were performed with respect to each Null-
Hypothesis of the first objective.
H1.1: Being entrepreneurial is not a means of overcoming resource barriers in a
resource constrained environment
In order to test the above Hypothesis, initially the data gathered via the on-line survey
about the entrepreneurial engagements of academics over the last five years was used to
calculate the number of academic entrepreneurs and non-entrepreneurs. If an academic was
not engaged in any of the 17 academic entrepreneurial activities, he/she was considered a
non-entrepreneur (Table 5.5).
Academic entrepreneurs were then regrouped based on the combinations of activities that
they were engaged in, which indicated the ‘plural activity’ types adopted by them (Please
refer the Section 4.1 of Research Hypotheses Chapter for more details about 7 ‘plural
activity’ types). If an academic had diversified into at least one activity grouped under a
particular type of activity (i.e. this study has categorised four activities into teaching
related entrepreneurial activities, seven activities into research related entrepreneurial
activities, and six activities into company creation) he/she was regarded as engaged in the
respective type of activity. The purpose of this initial categorization was to obtain a general
understanding of the entrepreneurial engagements of academics in a given context, which
was then used when analysing qualitative data, and testing subsequent hypotheses.
In addition to the above stated data collected via the on-line survey about entrepreneurial
engagements, detailed information was collected during in-depth interviews on how
academics had engaged in these activities, by probing specific questions with respect to
each activity (Interview Question No. 1.1). Furthermore, academics were asked to state
reasons for their engagements (Interview Question No. 1.2) or non-engagements in each
academic entrepreneurial activity (Interview Question No 8 and 9). These qualitative data
were analysed to investigate the impacts of the resource constrained environment in which
they operated. Particularly, whether they had mentioned ‘resources being constrained’ as a
reason for non-engagement, or as a push factor for engagement, was investigated.
Moreover, the qualitative data of those who had engaged in entrepreneurial activities was
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analysed to understand why and how they had engaged in entrepreneurial activities, despite
resources being constrained.
H1.2: There is no association between the ‘plural activity’ of academic entrepreneurs
and the extent of synergistic effects generated in a resource constrained environment
Data gathered during in-depth interviews about how academics had engaged in each
entrepreneurial activity (Interview Question No. 1.1), the benefits of their engagement
(Interview Question No. 1.3), and how academics had made use of business management
and entrepreneurial knowledge and skills (Interview Question No. 4.1 and 4.2) were
initially analysed (qualitatively). The aim of this analysis was to test whether there were
synergies between academic entrepreneurial activities in terms of knowledge and skills,
input-output flow, resources, and the network of contacts. In particular, the study analysed
whether academics had mentioned the four types of synergies stated above as benefits of
engaging in one activity, which was useful when engaging in other academic
entrepreneurial activities. Subsequently, data was analysed (qualitatively) to check whether
there was a difference between different ‘plural activity’ types with respect to the extent of
synergistic effects generated.
Quantitative data collected via the on-line survey (Survey Question No1.3 and 1.4) was
analysed to test whether there was a significant difference between those who had adopted
different ‘plural activity’ types in relation to entrepreneurial and business management
knowledge and skills and the strength of their social networks (Table 5.5). This approach
sought to improve internal validity of the study (Modell 2009) by checking to what extent
the findings of quantitative data were in line with the findings derived from qualitative
data. Therefore, this was believed to avoid the potential miss-interpretation of the findings
of quantitative data analysis. For example, it is possible to argue that rating high in
entrepreneurial and business management knowledge and skills and the strength of social
networks might not necessarily reflect synergies between activities, since those who had
high levels of these skills and networks may be the ones who engaged in entrepreneurial
activities. This possibility was avoided by comparing and contrasting the findings of
quantitative data and that of qualitative data. This allowed the investigation of whether
academics had mentioned that their engagement in entrepreneurial activities had resulted in
improved knowledge and skills, social network, and resources that had been useful when
engaging in other entrepreneurial activities (i.e. synergies between activities).
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Table 5.5: Objective 1- Quantitative Data Analysis
Hypotheses Variable Analysis 1.1: Being entrepreneurial is not
a means of overcoming resource
barriers in a resource
constrained environment
Categorical data – whether each academic is an entrepreneur or a non entrepreneur
Descriptive analysis
1.2: There is no association
between the ‘plural activity’ of
academic entrepreneurs and the
extent of synergistic effects
generated in a resource
constrained environment
Ordinal/Categorical - Dependent 1. The level of Business management knowledge and skills 2. The level of Entrepreneurial knowledge and skills 3. The level of The Strength of social network Categorical – Independent Plural activity types
Three Separate Chi-Square tests
5.4.2.2. Mixed Methods: Objective 2: Investigating the Motivation of Academic
Entrepreneurs in a Resource Constrained Environment
By referring to academic entrepreneurship and entrepreneurship literature, five push
factors and ten pull factors were identified (Table 5.6). This list of motives was used for
data collection and analysis related to testing two hypotheses constructed to investigate the
motivations of academic entrepreneurs.
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Table 5.6: The Motivations of Academic Entrepreneurs
Push Motives 1. Insufficient income (Alstete, 2002, Tagiuri and Davis, 1992, Dunn and Holtz-Eakin, 2000, Shane et al., 2003, Basu and Goswami, 1999) 2. Job related dissatisfaction (Alstete, 2002) 3. Not having an industrial partner capable of commercializing the new product/technology (Eun et al., 2006) 4. Lack of resources within university (Phan and Siegel, 2006, Wright et al., 2006) 5. Pressure for academics to engage in entrepreneurial activities (Van Dierdonck and Debackere, 1988) Pull Motives
1. In order to achieve career development (McClelland, 1961, Greenbank, 2001) 2. In order to acquire new knowledge and skills (D'Este et al., 2010, Howell et al., 1998, Meyer-Krahmer and Schmock, 1998) 3. In order to capitalise on the opportunity perceived by academic by him/herself (Basu (Basu and Goswami, 1999, Shane and Venkataraman, 2000) 4. In order to capitalise on the opportunity perceived by the university (Basu and Goswami, 1999, Shane and Venkataraman, 2000) 5. In order to provide a service to students (e.g. lab equipments industry placements employment opportunities and other opportunities for students etc) (Van Dierdonck and Debackere, 1988, Meyer-Krahmer and Schmock, 1998, Siegel et al., 2004) 6. In order to make use of industrial resources (D'Este et al., 2010, Howell et al., 1998, Meyer-Krahmer and Schmock, 1998) 7. Desire for wealth (Hisrich and Brush, 1986) 8. For personal satisfaction (e.g. associate with people outside the university, and independence, social status, challenge seeking nature etc) (Turnbull et al., 2001, Lumpkin and Dess, 1996, Barrow, 1993, Sexton and Bowman-Upton, 1985) 9. As result of role models (Dunn and Holtz-Eakin, 2000, Erdıs and Varga, 2009) 10. Belief that it will not interfere with academic career (Ambos et al., 2008)
H2.1: In resource constrained environments, there is no association between the ‘plural
activity’ of academic entrepreneurs and their motivations
In the online survey, academic entrepreneurs were asked to rate to what extent they were
motivated by each of the 15 motives, on a Likert scale of 1 to 4 (1= extremely low, 2=low,
3=high, 4= extremely high, N/A= not applicable) (Survey Question No.3.1 and 3.2). When
deciding an appropriate number of options for the Likert scale, contradictory arguments in
the literature were taken into account. The use of very low number of choices has been
found to result in reducing the ability to capture the variation, while a large number of
choices have been reported to reduce respondent’s capacity to discriminate between items,
both of which would have negative impacts on the reliability of a scale (Komorita and
Graham, 1965). Hence, Bendig (1954) has found that 3 to 9 point scales are appropriate
since there is no significant difference between these scales with respect to their reliability.
However, some studies have criticised the use of a middle point in a Likert scale, since
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generally respondents have a higher tendency to select the middle point (particularly in
Asian cultures) (Lee et al., 2002, Cao et al., 2007). Therefore, this research decided to
avoid the middle point whenever possible. Accordingly, for most of the questions, a four
item Likert scale was used. However, in the questions that had potential responses from
positive to negative together with ‘no effect’ (e.g. when academics were asked to rate the
impacts of academic entrepreneurial engagement) five item Likert scales were used (1-
extremely negative, 2- negative, 3- no effect, 4- positive, 5- extremely positive).
In order to test the Hypothesis stated above, ‘plural activity’ types adopted by academics
were used as the predictor variable, and the extents to which academic entrepreneurs were
motivated by each motive were used as outcome variables. Accordingly, separate tests
were conducted with respect to each motive (Table 5.7). Additionally, the qualitative data
collected via in-depth interviews on what made academics engage in each academic
entrepreneurial activity (Interview Question No.1.2), and how they carried out these
activities (Interview Question No.1.1), were analysed to check to what extent the findings
of qualitative data analysis confirm or reject that of quantitative data analysis.
Table 5.7: Objective 2- Quantitative Data Analysis Hypotheses Variables Data Analysis 2.1: In resource
constrained
environments, there is no
association between the
‘plural activity’ of
academic entrepreneurs
and their motivations
Outcome variables- ordinal Motivation (10- pull motives, 5-push motives) Predictor variable- categorical ‘plural activity’ types
Separate tests for each 15 motives If normally distributed - parametric tests- Anova, and Tukey’s Posthoc test If data is not distributed normally – non parametric test - Krukal-Wallis test, and Mann-Whitney-U test
H2.2: The motivations of academic entrepreneurs operating in resource constrained
environments do not change over their entrepreneurial careers
Data gathered via in-depth interviews on the dynamism of motivation (Interview Question
No1.2) were analysed to test whether and how entrepreneurial motivations of different
academic entrepreneurs change over their careers.
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5.4.2.3. Mixed Methods: Objective 3: Investigating the Influence of Multilevel Causal
Factors on the ‘Plural Activities’ of Academic Entrepreneurs in a Resource
Constrained Environment
As illustrated in the Section 4.3 of the Research Hypotheses Chapter, four hypotheses were
constructed to investigate the influence of multilevel causal factors on the nature of
academic entrepreneurial engagement as follows:
H.3.1: There is no relationship between the ‘plural activity’ of academic entrepreneurs
and their personal characteristics
Data on the gender, university, academic discipline, and the position of academics were
obtained from the personal profiles of academics in respective university websites, while
data on age, the level of education, the strength of social network, as well as business
management and entrepreneurial knowledge and skills was obtained via the online survey
(Survey Questions 1.1-1.4). In order to assess the strength of social networks, academics
were asked to rate, to what extent they agree/disagree with three statements on a four point
Likert scale (Survey Questions 1.4). These three statements reflect three different types of
social networks namely; having strong personal ties with industry (Nicolaou and Birley,
2003, Ambos et al., 2008), knowing someone who has strong contacts with industry, and
being a member of a team who has contacts with industry (De Koning and Muzyka, 1999,
Mosey and Wright, 2007). As illustrated in Table 5.9, eight different statistical tests were
performed with respect to eight personal characteristics. Furthermore, data collected via in-
depth interviews were used to check, to what extent, qualitative data supports correlations
derived from statistical analyses.
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Table 5.9: Objective 3- Hypothesis - 3.1- Quantitative Data Analysis Hypotheses Variables Data Analysis 3.1: There is no
relationship between
the ‘plural activity’ of
academic
entrepreneurs and
their personal
characteristics
Predictor variable-Categorical – ‘Plural activity’ types 1. Outcome variable- Continuous Age
Parametric tests- Anova controlling the effect of position
2. Outcome variable – Categorical Position
Non-parametric tests – Chi-square
test
controlling the effect of age
3. Outcome variable - Categorical Gender
Non-parametric tests – Chi-square
test
4. Outcome variable- Categorical Academic discipline
5. Outcome variable- Categorical The level of education
6. Outcome variable - Ordinal Business management
knowledge and skills
If normally distributed - parametric tests- Anova, and Tukey’s Posthoc test If data is not distributed normally – non parametric test - Krukal-Wallis test, Mann-Whitney-U test
7. Outcome variable - Ordinal Entrepreneurial
knowledge and skills
8. Outcome variable - Ordinal
Three statements to
represent the strength of
social network
If normally distributed - parametric tests- Internal consistency and unidimentionality tests to check the construct validity of the measure then Anova, and Tukey’s Posthoc test to test the Hypothesis If data is not distributed normally – non parametric test - Krukal-Wallis test, Mann-Whitney-U test
Hypothesis 3.2: There is no difference between the influence of micro and meso level
factors on academic propensity to adopt specific ‘plural activity’ types
In order to test the relative influence of micro- and meso-level factors on the propensity to
adopt specific ‘plural activity’ types, the personal characteristics of academics (i.e. age,
position, gender, education level, academic discipline, business management and
entrepreneurial knowledge and skills, and strength of the social network of academic) were
used as micro level independent variables.
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With respect to meso level independent variables, since certain university departments in
Sri Lanka had only a few academics, it was decided not to use departmental level variables
for the analysis, but only to use university level variables. Secondary data was collected to
gauge research strength, commercial orientation, and resource status of the universities. In
similar research, the research strength of universities in the UK had been measured using
the output of Research Assessment Exercise (RAE) (Ambos et al., 2008, D’Este and Patel,
2007). However, Sri Lanka does not have such quality measures, and thus, it was decided
to use the number of publications produced by academics in each university to represent
the research strength of universities. ISI web of knowledge was used as the source of data
collection. Since this research focused on academic engagement during the last five years
(2005-2010), it was decided to use the same timeline when calculating the number of
publications. In order to control for the size of universities, the number of publications per
100 academics was calculated. Therefore, the number of publications during 2005-2010
per 100 academics was used as a measure of the research strength of universities.
The proportions of university budget funded by industry, and whether universities had a
mission to support regional developments, are two indicators used in the literature to gauge
the commercial orientation of universities (D’Este and Patel, 2007). However, in this
context, it was not possible to obtain a figure to denote total income generated by
universities from industry. On the other hand, all the universities had a mission to support
regional development. Therefore, it was necessary to use a different measure, which would
resemble commercial orientation. During in-depth interviews, and initial discussions with
the registrars of universities, it was revealed that the number of university centres that had
a mission to engage in any form of interactions with industry reflects the commercial
orientation of universities. In order to control for the effect of size, the number of centres in
each university was divided by the number of academics in respective universities.
Government funding in 2009 per 100 academics was used as a measure for the resource
strength of universities. It was also confirmed during initial discussions with registrars that
government funding reflects the resource status of universities, since universities are
mainly funded by the government.
Micro- and meso- variables were compiled in two levels. Therefore, the entrepreneurial
engagements of academics in one university might be more alike than those in different
universities. If a traditional regression analysis was used, with both micro and meso level
variables, it would result in an underestimation of the standard error of the regression
coefficient, since it would not incorporate the effect of the hierarchical structure of data
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(Rasbash et al., 2008, Tranmer and Elliot, 2007). Furthermore, if traditional regression
analysis was used, it would not be possible to use both university (i.e. the use of a dummy
variable to test the effect of university) and other university level predictor variables (e.g.
the research strength of universities, the commercial orientation of universities, and the
resource status of universities) in the same equation, since this would result in
multicollinearity.
Therefore, the literature suggests using multilevel-analysis, since it allows the assessment
of relationships at different levels, simultaneously (Tranmer and Elliot, 2007).
Furthermore, it also avoids the possible multicollinearity explained above (Rasbash et al.,
2008). Another advantage of a multi-level analysis is that, if data are collected using a
cluster sampling technique, multilevel analysis enables sampling strategy to be
incorporated into inferences made from the data, which ultimately improves the reliability
and validity of analysis (Rasbash et al., 2008). Therefore, it was decided to use multilevel
analysis in this research, to test the Hypothesis 3.2 (Table 5.10). MLwiN software,
developed by the Centre for Multilevel Modelling, by the University of Bristol (Rasbash et
al., 2008), was used for this multilevel analysis.
Table 5: 10: Objective 3 – Hypothesis 3.2- Quantitative Data Analysis Hypotheses Variables Data Analysis H 3.2: There is no
difference between
the influence of
micro and meso level
factors on academic
propensity to adopt
specific ‘plural
activity’ types
Dependent variable –Categorical ‘plural activity’ types
Levels – Individual level, University level
Independent variables –
Categorical/Continuous
Meso level –
Research strength, commercial orientation,
and resource strength of universities
Micro level – Age, Position, Gender,
Education level, Academic discipline,
Business management and Entrepreneurial
knowledge and skills, and strength of the
social network of academic
Data Analysis –
Multi level
analysis using
MLWin software
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H 3.3: There is no relationship between the ‘plural activity’ of academic entrepreneurs
and their perception of university quality
The on-line survey asked academics to rate the quality of five aspects of their universities
(i.e. research strength of university, research strength of department, commercial
orientation of university, commercial orientation of department, and resource status of
university) on a four point Likert scale (Survey Question No. 6.2). As illustrated in Table
5.11, five separate statistical tests were carried out to test whether there was a relationship
between the ‘plural activity’ of academic entrepreneurs and their perception of university
quality.
Table 5.11: Objective 3- Hypothesis 3.3- Quantitative Data Analysis
Hypotheses Variables H 3.3: There is no
relationship between
the ‘plural activity’
of academic
entrepreneurs and
their perception of
university quality
Predictor variable –’plural activity’ types – Categorical
Outcome variable – the level of quality with respect to five Criteria - Ordinal 1. The research strength of
department
2. The research strength of
university
3. The commercial orientation of
department
4. The commercial orientation of
university
5. The resources status of the
university
Separate tests will be
conducted with respect to
each outcome variable
If normally distributed -
parametric tests- Anova, and Tukey’s Posthoc test If data is not distributed
normally – non parametric test - Krukal-Wallis test, Mann-Whitney-U test
Hypothesis 3.4: Interactions between university, industry and government in a resource
constrained environment do not differ from those in a developed environment
In-depth interviews gathered data on the interactions between university, industry
(Interview Question No 7, 10) and government (Interview Question No 11, 12). Data
analysis was performed qualitatively to investigate to what extent the interactions in a
resource constrained environment are similar to or different from those in a developed
environment.
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5.4.2.4. Mixed Methods: Objective 4: Investigating the Impacts of Academic
Entrepreneurial Engagement in a Resource Constrained Environment
In order to achieve the fourth objective, data collection and analysis were carried out to test
the three hypotheses constructed to investigate the impacts of academic entrepreneurial
engagement on normal academic duties and the wider national economy.
H 4.1: The entrepreneurial engagements of academics in resource constrained
environments have no impact on their normal academic duties
As illustrated in Table 5.12, several criteria were identified from the literature to
demonstrate different aspects of normal academic duties, which were used to test for
potential impacts (positive/negative) of academic entrepreneurial engagements on normal
academic duties (Table 5.11). Although the third item in the Table (i.e. ‘income status as
an academic’) does not exactly represent an aspect related to normal academic duties, it
was decided that it would be interesting to investigate how entrepreneurial engagements by
academics affect their income status in comparison to normal academic duties.
Table 5.12: Aspects of Normal Academic Duties
Impacts Reference
1. The quality of basic research of academic
(Siegel et al., 2004, Calvert and Patel, 2003) (Van Looy et al., 2006, Lowe and Gonzalez-Brambila, 2007, Brooks and Randazzese, 1999)
2. The quality of teaching of academic (Shane, 2004) 3. Income status as an academic (Wright et al., 2004) 4. Social status as an academic (Orhan and Scott, 2001) 5. The knowledge and skills as an academic
(D'Este et al., 2010)
6. Professional network as an academic (Siegel et al., 2007) 7. Academic’s future opportunities for collaboration
(D’Este and Patel, 2007)
8. The funding status of universities (Wright et al., 2004, Wright et al., 2007) 9.Academic’s access to facilities/resources in the industry
(Siegel et al., 2004)
10.Academic’s potential mobility between academia and industry
(Van Dierdonck et al., 1990)
Although certain criteria such as the quality of basic research of academics, and the
funding status of universities would have been measured objectively, there was a lack of
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secondary data available in Sri Lanka. Furthermore, there was a dearth of a common
measure to compare and contrast the degree of impact on different aspects related to
normal academic duties. In the absence of objective measures or objective data, the use of
subjective measures is recommended in the literature (Dess and Robinson, 1984).
Therefore, it was decided to ask academic entrepreneurs to rate the nature (positive or
negative) and the extent of impacts, on a Likert scale of one to five (1- extremely negative,
2- negative, 3- no effect, 4- positive, 5- extremely positive) (Survey Question No 4).
A post-hoc analysis was conducted to compare and contrast the extent of positive or
negative influence of different criteria that represent the aspects of normal academic duties
(See Table 5.12 for different aspects). The aspects of normal academic duties that have
been positively influenced by entrepreneurial endeavour were further analysed, using data
collected via in-depth interviews on the benefits of each academic entrepreneurial activity
(Interview Question No 2, and No 1.3). Similarly, the aspects of normal academic duties,
which had been negatively influenced by entrepreneurial endeavour, was further analysed
using data collected via in-depth interviews about the reasons for non-engagement
(Interview Question No 2 and No. 1.3), in order to investigate potential reasons as to why
entrepreneurial engagement had negative influences on normal academic duties.
H 4.2: In resource constrained environments, there is no association between the ‘plural
activity’ of academic entrepreneurs and their impact on normal academic duties
In order to test this Hypothesis, the data collected via the on-line survey on the degrees of
positive and negative impacts on normal academic duties were used as outcome variables,
while the ‘plural activity’ type of academic entrepreneurs was used as a predictor variable.
As illustrated in Table 5.13 relevant statistical tests were used to investigate whether there
was an association between the ‘plural activity’ types of academic entrepreneurs and their
impacts on normal academic duties. Separate tests were conducted with respect to each
aspect of normal academic duties.
In-depth interviews also collected data to investigate how academics balance academic
entrepreneurial engagement with normal academic duties. These were analysed to obtain
an in-depth understanding about interrelationship between academic entrepreneurship and
normal academic duties (Interview Question No 2.1 and 2.2). Additionally, a few students
were interviewed to obtain general viewpoints and opinions about the teaching quality of a
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few selected academics (i.e. those who had engaged in different ‘plural activity’ types).
Data obtained from students were used for triangulation in order to improve the internal
validity of the study.
H 4.3: There is no difference among academic entrepreneurial activities with respect to
the academic perception of their national economic importance
In order to test this Hypothesis, it was necessary to collect data on the national economic
importance of each academic entrepreneurial activity. Even though the economic
importance of certain academic entrepreneurial activities, such as company creation, could
have been measured objectively, it was questionable to what extent such economic
importance could be captured by the use of these measures. For example, the performance
of a company, which is one aspect of the economic importance of spin-off formation, could
be multifaceted (Venkatraman and Ramanujam, 1986) represented by outputs, efficiency,
effectiveness, responsiveness and democratic outcomes (Boyne et al., 2002). Objectively
measuring these different aspects might be impossible (Venkatraman and Ramanujam,
1986). On the other hand, there was a lack of a common measure of national economic
importance of different entrepreneurial activities. In the absence of objective measures, the
use of subjective measures to assess the performance of organizations was considered
adequate (Dess and Robinson, 1984). Therefore, asking academic entrepreneurs (who have
engaged in these activities) to rate the level of economic importance of each academic
entrepreneurial activity was considered appropriate.
Therefore, academics were asked to rate the level of economic importance to Sri Lanka of
each academic entrepreneurial activity, on a Likert scale (Survey Question No 2). A
Tukey’s Posthoc test was carried out to compare and contrast the national economic
importance of different activities (Table 5.13). Furthermore, data gathered from in-depth
interviews about national economic importance of these activities was analysed to
triangulate the findings of the on-line survey (Interview Question No. 12).
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Table 5:13: Objective 4- Quantitative Data Analysis
Hypotheses Variables Data Analysis H 4.1: The entrepreneurial
engagements of academics
in resource constrained
environments have no
impact on their normal
academic duties
The extent of positive or negative impact of 10 impacts illustrated in Table 5.12.
Mean value of each impact. Tukey’s Posthoc tests to identify homogeneous subsets of outcomes, based on the degree of outcomes
H 4.2: In resource
constrained environments,
there is no association
between the ‘plural
activity’ of academic
entrepreneurs and their
impact on normal
academic duties
Predictor variable - Categorical ‘plural activity’ types – Outcome variables- Ordinal 10 impacts on normal academic duties
If normally distributed -
parametric tests- Anova, and Tukey’s Posthoc test If data is not distributed
normally – non parametric test - Krukal-Wallis test, Mann-Whitney-U test
H 4.3: There is no
difference among
academic entrepreneurial
activities with respect to
the academic perception of
their national economic
importance
The extent of national economic importance of each academic entrepreneurial activity
Mean values of economic importance with respect to each activity. Tukey’s Posthoc tests to identify homogeneous subsets of activities, based on the level of economic importance, which indicates the order of importance
5.5. The Characteristics of Respondents
In addition to the data collection and analyses discussed above, this study also performed a
descriptive analysis in order to provide an overview of the characteristics of respondents.
The online survey achieved a rate of response of 30.29% (N=358). As illustrated in Table
5.14, 69.8% of respondents were males. Respondents consisted of 15% professors, 54%
senior lecturers, and 31% lecturers. With respect to their educational attainments, 9% of
them had only bachelor’s degrees, while 32% had a master’s degree and 59% of them had
a PhD. There were eight major disciplines the respondents had specialised in namely, the
Arts (2.5%), Social Science (16.2%), Architecture (3.4%), Engineering (23.7%),
Computing and Information Technology (5.3%), Medicine, Dentistry, and Veterinary
Practise (6.4%), Agriculture (21.8%), and the Sciences (20.7%).
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Table 5.14: The Characteristics of Respondents
No. of Respondents
% Respondents (as a percentage of total
number of respondents)
Gender Male 250 69.8%
Female 108 30.2% Position Professor 57 15.2% Senior Lecturer 185 53.9%
Lecturer 116 30.9%
The Level of Education
Only Bachelors 32 9%
Bachelors and Masters 113 31.8%
Bachelors &/or Masters & Doctorate 210 59.2%
Academic Discipline
Arts 9 2.5% Social Sciences 58 16.2% Architecture 12 3.4% Engineering 85 23.7% Computing, Information Technology 19 5.3% Medicine, Dental, Veterinary 23 6.4% Agriculture 78 21.8% Science 74 20.7% Total 358 100%
5.6. An Overview of Academic Entrepreneurial Engagement
The current study also considered that, before testing hypotheses, it was important to
understand the entrepreneurial engagements of academics in general. It was evident that
the majority of academics had engaged in teaching related entrepreneurial activities and
research related entrepreneurial activities. These activities were external teaching (65.9%),
initiating the development of new degree programmes (64.2%), placing students as trainees
in industry (69%), conducting seminars and training sessions to industry (64.5%),
acquiring funding from government, non-governmental or international bodies (those
without collaborations with industry) (51.3 %), and collaborating with industry through
joint research projects (60.6%). On the contrary, the percentage of academics who had
engaged in the formation of privately owned company/(s) (9.9%), new spin-off companies
(6.5%), joint venture/(s) privately through collaborating with industry (11.3%), and
university incubators and/or science parks (15.2%) was low (Table 5.15). Furthermore, in-
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depth interviews with academics revealed that those who had mentioned that they have
contributed to the establishment of university incubators and/or science parks had carried
out only initial discussions, but owing to a lack of funds and some administrative
difficulties, either science parks or incubators had not been formed. Hence, it was decided
not to consider this activity in further discussions. This exclusion did not change the initial
categorization of academics based on their ‘plural activities’ since there were no academics
(See Table 5.4 for the categorization of academics) who had only engaged in this activity.
Table 5.15: Academic’s Engagement in Academic Entrepreneurial Activities
The nature of engagement Percentage
(1) External teaching 65.9 (2) Initiating the development of new degree programmes 64.2 (3) Placing students as trainees in the industry 69 (4) Conducting seminars and training sessions for industry 64.5 (5) Working in the industry 34.1 (6) Research based consultancy for industry through the university 54.4 (7) Research based consultancy privately (but without forming a company) 39.7 (8) Developing products with intellectual property rights 20.6 (9) Acquiring funding from government, non-governmental or international bodies (those without collaborations with industry) 51.3 (10) Collaborating with industry through joint research projects 60.6 (11) Assisting small business owners to commercialize their innovations 24.8 (12) Contributing to the formation of joint ventures in which university and industry are the joint partners 24.2 (13) The formation of joint venture/(s) privately through collaborating with industry 11.3 (14) Contributing to the formation of one or more new spin-off companies 6.5 (15) Contributing to the establishment of university incubators and/or science parks 15.2 (16) Contributing to the formation of university centres designed to carry out commercialization activities 28.2 (17) The formation of your own company/(s) 9.9
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5.7. Chapter Summary
Sri Lanka, which is a resource constrained environment, was the study context of this
research. Academics in 13 universities in Sri Lanka were chosen as the population of this
study. Mixed methods were used in a sequential manner in three steps as follows:
1. An initial context specific data gathering stage
2. An on-line survey
3. In-depth qualitative interviews.
Since most of the literature was derived from Western developed nations, an initial data
gathering phase was conducted to gather context specific information required to design
subsequent major data collection phases, which was designed to improve the construct
validity of the study. Furthermore, the findings of the initial data gathering stage were used
to assess the reliability of categorizing academic entrepreneurial activities into three
groups. Telephone interviews were conducted with the registrars of 8 universities to obtain
general information about context specific entrepreneurial engagements by academics. An
on-line survey was piloted with 16 academics in order to further improve the construct
validity of the research.
The above measures were followed-up by an on-line survey, which was used to gather
quantitative data required to test research hypotheses. The unavailability of a list of
elements in the population, as well as cost and time constraints, led to a decision to use a
cluster sampling technique. Selecting a representative sample of clusters was
recommended in the literature to reduce the sampling error associated with this technique,
and thus, the age, location and size of universities were used as criteria for selecting
universities. Accordingly, academics in 6 out of 13 universities were selected as the
sample. The rate of response to the online survey was 30% (358 responses in total). There
were no significant differences between respondents and non-respondents with respect to
their gender, position, university, and academic discipline, which confirmed that there was
no non-response bias.
The on-line survey was followed by in-depth qualitative interviews in order to gather the
qualitative data required to test the research hypotheses, and to improve internal validity
through triangulation. A sample of 78 academic entrepreneurs, derived on the basis of
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findings from the on-line survey, was used for in-depth interviews. Using the findings of
an initial phase to derive a sample for a subsequent phase is a technique successfully used
in a number of studies in social and behavioural sciences, which has been found to
generate data with both good breadth and depth. A semi-structured questionnaire, which
was piloted with 5 academics, was used for in-depth interviews.
Data gathered through the on-line survey were analysed quantitatively (using SPSS) and
that gathered through in-depth interviews were analysed qualitatively (using NVivo) to test
relevant hypotheses. This chapter also illustrated how quantitative and qualitative data
analyses were combined to test each Hypothesis.
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Chapter 6: The ‘Plural Activities’ of Academic Entrepreneurs operating in a
Resource Constrained Environment
The previous chapter of this thesis discussed the research methodology by initially
justifying the use of critical realism as the philosophical standpoint for this study, and
subsequently, illustrating the adoption of mixed methods in three sequential phases;
namely, an initial data gathering stage, an on-line survey, and face-to-face in-depth
interviews. Finally, it proposed a plan for analysing data and discussed the characteristics
of respondents.
The methodology chapter is now followed by the analysis of the thesis, the main objective
of which is to investigate academic entrepreneurship in a resource constrained
environment. Each analytical chapter addresses a different specific research objective.
Hence, the next four chapters of the thesis discuss investigations on the ‘plural activity’ of
academic entrepreneurs, the motivations of academic entrepreneurs, the effects of
multilevel causal factors on ‘plural activities’, and the impacts of academic entrepreneurial
engagements. This chapter addresses the first of these objectives, which is to examine the
‘plural activities’ of academic entrepreneurs in a resource constrained environment.
Initially, the chapter briefly restates the relevant literature that had been discussed in detail
in the Chapter 3 and 4 of the thesis. The chapter subsequently, presents qualitative and
quantitative data analysis, and finally, concludes with a chapter summary.
6.1. Academic Entrepreneurship in a Resource Constrained Environment
In relatively resource-rich developed countries, the resources of universities and macro
environments have been found to be a means of becoming entrepreneurial, and thus, the
propensity for entrepreneurship is encouraged by the high availability of resources (O’Shea
et al., 2004, Etzkowitz and Leydesdorff, 2000). This is further supported by the literature
which has indicated that a lack of resources tends to inhibit academic entrepreneurial
engagements (Monck and Segal, 1983). Nevertheless, some studies in the entrepreneurship
literature have argued that resource constraints do not necessarily inhibit entrepreneurial
activity, and conversely, trigger entrepreneurship as a means of overcoming resource
barriers (Hart et al., 1995, Kodithuwakku and Rosa, 2002, Gilad and Levine, 1986).
Therefore, this study argues that academics in resource constrained environments may
become entrepreneurial as a means of becoming resource-rich, as opposed to resources
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being a means of becoming entrepreneurial in resource rich environments. Therefore, the
first objective of this chapter is to examine whether the resource constrained environment
of Sri Lanka inhibits or encourages academic entrepreneurial engagements (which equates
to Hypothesis 1.1: Being entrepreneurial is not a means of overcoming resource barriers
in a resource constrained environment).
Some previous studies have suggested that, entrepreneurs operating in resource constrained
environments engage in multiple income generation activities, as a strategy to extract value
from their environments (Kodithuwakku and Rosa, 2002). Therefore, the current study
argues that academics operating in relatively impoverished environments may also engage
in several entrepreneurial activities, named in this research, as ‘plural activities’. The
diversification and portfolio entrepreneurship literature argues that an engagement in
multiple entrepreneurial activities provides additional benefits, due to the synergies that
can develop between activities (Westhead et al., 2005, Alsos et al., 2003). Social network
(Westhead et al., 2005, Birley, 1985, Mayer and Schooman, 1993), knowledge and skills
(Shane, 2000, Westhead et al., 2005, Alsos et al., 2003), input-output flows, and physical
resources (Westhead et al., 2005, Alsos et al., 2003), identified in the literature as (at least)
four types of additional advantages derived from diversification, are regarded as relevant to
diversifying entrepreneurial activities considered here. Hence, the second objective of this
chapter is to make an in-depth investigation of the ‘plural activities’ of academic
entrepreneurs and potential synergies between entrepreneurial activities carried out by
them (which equates to Hypothesis 1.2: There is no association between the ‘plural
activities’ of academic entrepreneurs and the extent of synergistic effects generated in a
resource constrained environment).
6.2. Analysis: Academic Entrepreneurial Engagement in a Resource Constrained
Environment
Academic engagement in 17 entrepreneurial activities over the last 5 years (from January
2005-January 2010) revealed that 87.9 % of survey academics (i.e. 315 out of 358) had
engaged in at least one entrepreneurial activity. In order to understand the nature of
academic entrepreneurial engagements in detail, data collected via the on-line survey were
analysed to identify any ‘plural activity’ of academics. If survey academics engaged in at
least one out of the four teaching related entrepreneurial activities, they were considered
engaged in teaching related academic entrepreneurial activities. Similarly, if an academic
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has engaged in at least one out of seven research related entrepreneurial activities, he/she
was regarded as engaged in research related academic entrepreneurial activities. Likewise,
if an academic has carried out at least one out of six company creation activities, he/she
was considered to be engaged in company creation (please see Table 4.1 for categorization
of activities). As illustrated in Table 6.1, academic engagement in each type of activity was
then used to investigate any ‘plural activity’. Even if academics had engaged in only one
teaching related entrepreneurial activity (or only research related activity or only company
creation), it was considered a form of diversification, since they carried out this in addition
to their normal academic duties.
The analysis revealed that, except for 13 survey participants, the rest of the academics
(N=302) had adopted Type 1 (teaching related entrepreneurial activities), Type 4 (teaching
and research related entrepreneurial activities), or Type 7 (company creation as well as
teaching and research related entrepreneurial activities) ‘plural activity’ types. However,
not a single academic had engaged in the Type 5 category (i.e. teaching related
entrepreneurial activities and company creation) of ‘plural activity’ (Table 6.1).
Table 6.1: ‘Plural Activity’ types adopted by Academic Entrepreneurs – Results
Types of ‘plural activity’ Teaching Related
Research Related
Company Creation
Frequency
Type 1 Only teaching related A.E.As √ 30 Type 2 Only research related A.E.As √ 8 Type 3 Only company creation √ 1 Type 4 Teaching related A.E.A+Research related
A.E.A. √ √ 150
Type 5 Teaching related A.E.A+Company
creation √ √ 0
Type 6 Research related A.E.A.+Company
creation √ √ 4
Type7Teaching related+ Research related+
Company creation √ √ √ 122
√ indicates that academics had engaged in at least one activity grouped under each type of
activity
A.E.A – Academic Entrepreneurial Activities
It was revealed during in-depth interviews that Type 1 (only teaching related), Type 4
(teaching and research related), and Type 7 (company creation as well as teaching and
research related) ‘plural activity’ types were prominent because of the process adopted by
academics when engaging in entrepreneurial endeavour. Typically, they started their
academic entrepreneurial careers by engaging in teaching related entrepreneurial activities,
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and then some of them diversified into research related entrepreneurial activities and
company creation. The following quotation from one of the respondents, who had adopted
the Type 7 ‘plural activity’ type, illustrates this sequence of engagement:
‘Soon after my PhD I started engaging in external teaching at postgraduate institutes.
Most of the students were from industry and this opportunity allowed me to develop
contacts, and later these students invited me to conduct some training and seminar
sessions for industry. These enabled me to develop reputation in industry, which paved the
path for me to secure opportunities to engage in joint research. Constant engagement in
joint research with company ‘X’ (a telecommunication company) had resulted in it
deciding to open a joint research lab in our university’
However, diversifying into company creation had not stopped survey participants (i.e. who
had engaged in all three activities), from engaging in other teaching and research related
entrepreneurial activities and, as a result, they engaged in a mix of entrepreneurial
activities. One academic stated:
‘......after creating the company we got more opportunities to engage in consultancy, joint-
research projects, and external teaching. Moreover, we were able to use resources in our
company to engage in these activities’
These findings are in line with those of Tijssen (2006), who found that academic
entrepreneurship is a process, which starts from engaging in ‘lesser entrepreneurial’
activities, and then, extends to ‘highly entrepreneurial’ activities. The prominence of the
three ‘plural activity’ types (i.e. Type 1, Type 4, and Type 7) was further confirmed by the
analysis of data collected from academics who adopted three other ‘plural activity’ types
(i.e. Type 2, Type 3, and Type 6). It was revealed that those academics who adopted less
prominent ‘plural activity’ types had also followed the sequence of engagement described
above, but due to some personal circumstances, they had not engaged in certain
entrepreneurial activities during the last 5 years (but previously they had engaged in these
activities and they will resume them in future). For instance, those who carried out only
research related activities during the last five years (i.e. Types 2), had previously carried
out both teaching and research related activities. Had they not encountered some personal
circumstances that prevented them from engaging in teaching related activities, they would
have been grouped into Type 4, which is a prominent type. Similarly, those who carried
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out Type 3 (only company creation), and Type 6 (research related activities and company
creation) ‘plural activity’ during the last five years, had previously carried out Type 7
‘plural activity’, which is a prominent type (teaching related activities, research related
activities, and company creation).
Therefore, it could be concluded that, due to the process by which academics diversify
their entrepreneurial engagements, only three ‘plural activity’ types were prominent in this
context. These three ‘plural activity’ types illustrate the heterogeneity evident among
academic entrepreneurs, and thus, were named as follows:
1. Those who had engaged in only teaching related entrepreneurial activities (i.e. Type 1)
were named ‘single role’ academic entrepreneurs since they had diversified into one type
of activity.
2. Those who had engaged in both teaching and research related entrepreneurial activities
(i.e. Type 4) were named ‘double role’ academic entrepreneurs since they had diversified
into two types of entrepreneurial activities.
3. Those who had engaged in teaching and research related entrepreneurial activities as
well as company creation (i.e. Type 7) were named ‘triple role’ academic entrepreneurs
since they had diversified into three types of activities.
As described above, since academic entrepreneurship was found to be an evolutionary
process (i.e. starting from teaching related academic entrepreneurial activities, and then,
diversifying into research related entrepreneurial activities and company creation), it is
possible that single role and double role academics were still in the process of adding
activities (mainly with respect to young ones). Therefore, whether the three types of
entrepreneurs significantly differ with respect to their age was tested. The analysis did not
find a significant difference F (2, 295) = 0.831, p=0.437 (Single role M = 42 SD=9, Double
role M= 44 SD=10, Triple role M= 45 SD=10). Therefore, it is possible that most of the
single role and double role academics in this sample were those who had decided not to
add other activities to their portfolio of entrepreneurial activities. In order to understand the
nature of their engagements further, this study decided to investigate the extent to which
academics diversified their engagements into teaching and research related entrepreneurial
activities.
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6.2.1. Teaching related Academic Entrepreneurial Activities
A chi-square test revealed that there was a significant difference between the three types of
entrepreneurs with respect to the number of teaching related activities they had carried out
X2(6, N=302) = 48.350, p = 0.000. The majority of single role academics had engaged in
only one (43.3%) or two (23.3%) teaching related activities. Conversely, most of the triple
role academics (43.4%) had engaged in all four teaching related activities, and a large
proportion of double role academics had engaged in two (29.3%) or three (28.7%) teaching
related activities.
Further analysis of the types of teaching related activities carried out by the three types of
entrepreneurs revealed that a majority of single role academics had engaged in external
teaching (60%) and designed new degree programmes (53%), which did not require
extensive interactions with industry. However, a relatively low percentage of single role
academics, in comparison to their double and triple role colleagues, had engaged in other
two activities (i.e. finding industrial placements for students, and conducting training and
seminars for industry personnel), which involved high interactions with industry (Table
6.2).
Table 6.2: Extent of engagement- Teaching related academic entrepreneurial activities Activity Single role b Double role b Triple role b External teaching 60% (18) 64.7% (97) 73.8% (90) Introducing new degree programmes 53.3% (16) 73.3% (110) 71.3% (87) Finding industrial placements for students
46.7% (14) 68% (102) 90.2% (110)
Conducting training and seminars for industry personnel
33.3% (10) 62.7% (94) 83.6% (102)
b values indicate the percentage of academics who had engaged in each activity as a percent of the total
number of academics in respective typologies
6.2.2. Research related Academic Entrepreneurial Activities
A chi-square test revealed that triple role academics had engaged in a significantly higher
number of research related entrepreneurial activities (5-7 activities – 54.2%) when
compared with double role counterparts (1-3 activities – 56%) (X2 (7, N= 272) = 56.404, p
= 0.000). Further analysis of the types of research related activities carried out by
academics revealed that a higher percentage of triple role academics, than double role
academics, had engaged in each of the seven research related activities (Table 6.3).
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Table 6.3: The Extent of engagement- research related academic entrepreneurial activities Activity Double role c Triple role c Working in the industry on secondments 24% (36) 55.7% (68) Research based consultancy for industry through the university
51.3% (77) 77% (94)
Research based consultancy privately 34% (51) 54.9% (67) Developing products with the potential for securing patents
16.7% (25) 37.7% (46)
Acquiring funding from government, non-governmental or international bodies (those without collaborations with industry)
54% (81) 63.1% (77)
Collaborating with industry through joint research projects
70% (105) 82.8% (101)
Assisting small business owners to commercialize their innovations
18% (27) 46.7% (57)
c values indicate the percentage of academics who had engaged in each activity as a percent of the total
number of academics in respective typologies
Even though there was not a comparable previous study carried out in a resource-rich
environment to obtain an understanding of the relative extent of academic entrepreneurial
engagements, the above analysis does suggest that the resource constrained environment of
Sri Lanka has not inhibited entrepreneurial engagements by academics. Furthermore, it
was evident that these academics had carried out different ‘plural activity’ types. For
instance, single role academics diversified into a limited number of similar activities (i.e.
teaching related activities), while their triple role counterparts diversified into a higher
number of diverse activities (i.e. teaching and research related activities and company
creation) (Figure 6.1). The engagement of double role academics was positioned between
that of single and triple role academics, whereby they diversified into different activities at
an average level (i.e. teaching and research related activities). However, there was no
entrepreneur who had engaged in a higher number of similar activities (e.g. a higher
number of teaching related activities), one reason for which was found to be a lack of
opportunities available in this constrained economic environment to diversify into similar
activities. Similarly, there were no entrepreneurs who carried out a limited number of
diverse activities (e.g. less number of each of the three types of activities), one reason for
which was found to be the lack of resources to engage in one activity extensively. The
following Sections of the chapter intend to discuss the heterogeneity of academic
entrepreneurs in terms of their ‘plural activity’ further.
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No. of Teaching related activities
No. of Research related activities
No. of company creation types
Single role – limited number of similar activities
Triple role – a higher number of diverse activities
Double role – an average number of different activities
Figure 6.1: ‘Plural activities’ of Academic Entrepreneurs
6.3. Analysis: ‘Plural activity’ and Synergistic Effects
As argued in the theoretical context of this chapter, ‘plural activity’ could generate
synergistic effects because of interactions between entrepreneurial activities. Since
academics in this context were found to adopt different ‘plural activity’ types, it is possible
that they might generate varied extents of synergistic effects. Hence, their heterogeneity
with respect to ‘plural activities’, illustrated by single role, double role or triple role
academics, was used to test whether there was an association between the degree of
synergistic effects and the ‘plural activities’ of academic entrepreneurs. This analysis was
performed separately for each of the four types of synergistic effects mentioned in the
theoretical context of this thesis; namely, social networks, knowledge and skills, input-
output flows, and physical resources.
6.3.1. The Synergistic Effect on Social Networks
The analysis of data gathered through in-depth interviews revealed that engaging in
teaching related entrepreneurial activities enabled academics to develop contacts with
industry, while carrying out research related entrepreneurial activities and company
LOW HIGH
Triple
Role
Single
Role
Double
Role
Limited number of diverse activities (i.e.
lower number of each type of activities, but
carrying out all three types)
Higher number of similar activities
(i.e. a higher number of one type of
activity)
No. of activities categorised in each type
(i.e. No. of teaching related activities, No.
of research related activities, and No. of
company creation types)
135
creation widened and strengthened their social networks. It was also evident that social
networks, developed by engaging in one activity, were capitalised on, since they led to
further activities, which increased the synergistic effects of social networks. These findings
are in line with the entrepreneurship literature, which has identified the capitalising on
social networking as a quality of entrepreneurs (Black, 1989). A further analysis was
carried out to investigate whether the degree of synergistic effects of social networking
varied, depending on the complexity of the ‘plural activities’ involved.
The analysis revealed that the social networks developed by single role academics, by
engaging in external teaching, were used to secure opportunities to conduct training and
seminars for industry personnel and to find industrial placements for students. However, it
was evident that single role academic entrepreneurs had not capitalised on their social
networks extensively, and as a result, they derived less synergistic effects when compared
to double role and triple role academics. For example, the following quotation from one
double role academic entrepreneur explained how the social networks, developed by
engaging in external teaching, were helpful when diversifying into other types of
entrepreneurial activities:
‘The majority of students in external teaching were the employees of industry and such
contacts had provided us with opportunities to engage in consultancy projects, conduct
training and seminars, place students as trainees in industry, and gain access to industrial
resources (to engage in research related activities)’
Similarly, the networks of contacts developed by triple role academics when engaging in
teaching and research related entrepreneurial activities had paved the way for them to
secure opportunities for long-term involvements such as forming joint venture research
labs. As a result, they were able to improve the resources of their universities, which were
then used to engage in further entrepreneurial activities. For instance, one triple role
academic entrepreneur said:
‘We were constantly engaging in providing consultancy services to the company ‘X’
(which specialises in computer engineering). They have the highest market share (in Sri
Lanka) in this industry. The company was extremely happy with our delivery. I think that
regular contacts with them enabled us to build trust and reputation. This resulted in them
deciding to establish a joint research lab in our university’
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As indicated in the above quotations, making use of social networks in order to access
resources, to acquire legitimacy, and to identify and capitalise on opportunities for
diversification, is congruent with the literature that has highlighted the benefits of social
networks (Birley, 1985, Mayer and Schooman, 1993, Aldrich and Fiol, 1994). After
diversifying into company creation, triple role academics constantly interacted with
industry, which enabled them to develop a strong and diverse network of contacts.
Developing strong ties has been regarded in the literature as a productive way of making
use of social networks (Nicolaou and Birley, 2003, Ambos et al., 2008). Since triple role
academics used these social networks to identify, and capitalise on, several opportunities
and to obtain resources (e.g. access to resources in industry and joint research labs etc),
they generated more synergies than the other two types of academics. This was found to be
one of the reasons why triple role academics had diversified into a higher number of
teaching and research related activities (as illustrated in the Tables 6.2 and 6.3 above).
These findings stated above on how ‘plural active’ types differ with respect to the
generation of the synergistic effects of social networks were further confirmed by an
analysis of data collected via the on-line survey. Academics were asked to state to what
extent they agreed with two statements (i.e. ‘I have very strong personal contacts with
industrial partners’ and ‘I’m a member of a team(s) that has (have) very good contacts with
industry’) on a Likert scale. The analysis revealed that a significant majority of triple role
academics, in comparison to double role and single role academics, had very strong
personal contacts with industrial partners X2 (6, N=296) = 54.447, p = 0.000. Similarly, it
was found that a significantly higher percentage of triple role academics, in comparison to
double role and single role counterparts, were members of a team(s) that had very good
contacts with industry’ X2 (6, N=276) = 43.917, p = 0.000 (please refer Section 8.2.6 for
more details).
Based on the analysis illustrated above, it could be concluded that, the synergistic effects
of social networking were capitalised on by academics in order to overcome resource
barriers. It was also evident that there was an association between the ‘plural activities’ of
academics and the synergistic effects of social network in which carrying out a higher
number of diverse entrepreneurial activities (e.g. triple role academics) delivered more
synergistic effects than carrying out a lower number of similar activities (e.g. single role
academics).
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6.3.2. Synergistic Effects on Knowledge and Skills
The in-depth interviews revealed that engaging in teaching related entrepreneurial
activities had helped academics to understand the needs of industry, while carrying out
research related activities and company creation had enabled them to develop knowledge
and skills in business management, entrepreneurship, and applied research. Furthermore,
engaging in joint research projects and forming joint ventures with industry had facilitated
the exchange of tacit knowledge. Hence, the ‘plural activity’ of academics generated the
positive synergistic advantages regarding knowledge and skills since they used knowledge
and skills, developed by engaging in one activity, to carry out other entrepreneurial
activities elsewhere. Further analysis was carried out to investigate whether the levels of
synergistic effects of knowledge and skills varied in relation to the complexity of ‘plural
activity’ types.
An enhanced understanding of the needs of industry, which was developed by engaging in
external teaching, had been used by single role academics when conducting training and
seminars for industry personnel. However, single role academics, when compared to their
double role and triple role colleagues, were found to generate relatively less synergistic
effects in terms of knowledge and skills. In-depth interviews revealed that double role
academics made use of their new knowledge to identify and capitalise on opportunities to
create several entrepreneurial engagements. For example, one double role academic
mentioned:
‘I was working in industry on a secondment and that had resulted in me understanding
industrial culture and developing business and management skills. After the secondment, I
realised the potential for collaborating with industry and started a number of collaborative
projects which were completed with a great success. I believe that my experience in
working in industry immensely helped me in identifying and engaging in these activities’.
In a similar vein, both double role and triple role academics noted that research based
consultancy, the development of products and/or processes with potential for securing
patents, and joint research projects, helped them understand industrial culture, and improve
their applied research and business management knowledge and skills, which were then
capitalised on and used to engage in other activities. Furthermore, knowledge and skills
gained by engaging in teaching and research related activities had positive impacts on the
company creation process developed by triple role academics, since new knowledge and
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skills facilitated the identification of opportunities and the acquisition of financial and
infrastructural resources. Moreover, company creation enabled triple role academics to
further develop business management, entrepreneurial, applied research, and market
related knowledge and skills, which had been additionally beneficial when identifying, and
capitalizing on, opportunities to engage in further teaching and research related activities.
Hence, the synergistic effects of knowledge and skills was one of the reasons why triple
role academics engaged in a higher number of teaching and research related activities than
single and double role academics (as illustrated in the Tables 6.2 and 6.3). For instance,
two triple role academics stated:
‘now I know where to go and what to do when I need more funds [i.e. as a result of
knowledge developed through previous engagements].’
‘after forming the company I get more opportunities for consultancy...I feel that in
comparison to early stages, I can understand them (industry) very well and provide a
better service.’
The findings stated above on how ‘plural active’ types differ with respect to the generation
of the synergistic effects of knowledge and skills were further confirmed by an analysis of
data collected via the on-line survey. It was revealed that triple role academics had
significantly higher levels of business management skills X2 (6, N=278) = 10.718, p =
0.097<0.1, and entrepreneurial skills X2 (6, N=276) = 34.426, p = 0.000 in comparison to
single role and double role counterparts (please refer Tables 8.7 and 8.8 of Section 8.2.5
for percentage values). These findings are in line with Westhead et al (2005), who have
stated that portfolio entrepreneurs receive additional advantages through their ability to
capitalise on knowledge and skills acquired through diverse engagements.
Based on the analysis illustrated above, it could be concluded that, the synergistic effects
of knowledge and skills were capitalised on by academics in order to overcome resource
barriers. The analysis also revealed that there was an association between the ‘plural
activity’ of academics and the synergistic effects of knowledge and skills in which carrying
out a higher number of diverse activities (e.g. triple role academics) delivered more
synergistic effects than carrying out a limited number of similar activities (e.g. single role
academics).
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6.3.3. Synergistic Effects and their Impacts on Input-output flows
It was also evident that ‘plural activities’ had made it possible for academics to use the
outputs of one activity as inputs for another, which generated additional synergistic effects
from these input-output flows. For example, the outputs of carrying out applied research
and assisting small business owners (e.g. patents and commercially oriented innovations
etc) were used by triple role academics as inputs for company creation. This was
stimulated by their need to overcome certain barriers in the environment, such as inability
to find appropriate industrial partners to commercialise innovations, the lack of
opportunities to sell intellectual property rights, and weak intellectual property right laws.
Hence, the synergy of input-output flow enabled triple role academics to overcome these
constraints.
A similar flow was also observed in a number of consultancy projects, where the outputs of
an initial consultancy were used as inputs in subsequent instances. Similarly, the outputs of
short-term joint research projects with industry had been used as inputs for longer-term
projects. Furthermore, coursework developed for one teaching related activity was used for
numerous other teaching related activities. Therefore, it could be stated that all the ‘plural
activity’ types had generated the synergistic effects of the using the outputs of one activity
as inputs for others, which in turn, was useful to overcome resource constraints. However,
sufficient evidence was not available to gauge which type of ‘plural activity’ caused the
greatest number of, or best, input-output flows.
6.3.4. Synergistic Effects on Physical Resources
The above analysis of the three types of synergistic effects, namely; social networks,
knowledge and skills, and input-output flows revealed that academics made use of these
synergistic effects to overcome resource barriers. The analysis of data gathered via in-
depth interviews further revealed that resources acquired by engaging in one
entrepreneurial activity were used to engage in other activities, which generated the
synergistic effects of physical resources. An in-depth analysis was carried out to
investigate whether the amount of synergistic effects generated with respect to physical
resources varied, depending on the complexity of ‘plural activity’ types.
Since universities receive limited funding from the government and offer free
undergraduate education, clearly, they are financially constrained. The all three types of
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academic entrepreneurs contributed to ameliorating financial constraints since a portion of
additional income gained from engaging in each activity obtained by the universities, was
reinvested in order to carry out further activities, which had generated financial resource
synergies between activities. However, apart from the synergistic effects of financial
resources, the engagements of single role academics were not reported to generate other
types of physical resources synergies. Conversely, the engagement of double role and triple
role academics caused the generation of different types of physical resource synergies
between activities. For instance, one double role academic entrepreneur stated:
‘The funding we acquired from industry and international bodies by carrying out
consultancy and other research projects had resulted in improving resources such as lab
equipment, chemicals, stationery, computers, printers, photocopy machines, and
buildings....When we prepare budgets we always try to include elements to improve
resource status of the university..........the development of these facilities was important to
engage in more activities, which bring additional resources.
The above quotation illustrates how double role academics have made use of
entrepreneurial engagements to improve the infrastructural and financial resources of their
universities, which were then used to carry out other teaching and research related
activities. Another double role academic entrepreneur stated:
‘I have expertise in ‘designing and implementing infrastructure development projects’ and
my project partner who is working in company ‘y’(which works on environment and
conservation related aspects) has expertise in ‘risk assessment’. These are complementary
(with respect to rural development projects).......his expertise and industrial exposure
complement with my academic background. I find that working with him allows me to
secure more external project funds............I also get the opportunity to make use of their
lab,’
This quotation shows how double role academics have entrepreneurially overcome human
(high skilled) and technological resource scarcities, and subsequently, used these resources
to engage in other activities, which generated synergies between activities.
In-depth interviews further revealed that, due to university “red-tape”, such as
bureaucracies, inefficient financial services, and restrictive rules, it was very difficult to
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engage in competitive bidding to secure consultancy projects, and to carry out research
related activities efficiently. Furthermore, it was apparent that government regulations in
Sri Lanka do not permit universities to establish profit-making companies. Therefore, triple
role entrepreneurs had entrepreneurially introduced several mechanisms with which to
overcome these institutional barriers. One of such strategies was to establish independent,
external companies owned by academics, but physically located at their universities, by
paying rent for the use of the location and other resources. Since the companies were
owned by academics and not by the universities, they were registered as independent profit
making entities, which improved company growth. Furthermore, these companies had their
own (efficient) staff, responsible for interacting with industry, which enabled academics to
engage in competitive bidding and efficiently meet industry requirements.
Additionally, data suggested that triple role academics made use of resources in these
academic “spin off” companies (e.g. new equipment and facilities – infrastructural and
technological resources, efficient staff- human resources, and profits) to engage in teaching
and research related activities. Furthermore, it was reported that some of the spin-off
companies had contributed to university ‘departmental funds’ (i.e. financial resources)
which were used to improve the resource status of the department (e.g. infrastructural,
technological, and human resources), and in turn, to engage in teaching and research
related entrepreneurial activities. As explained above, triple role academics were able to
generate a higher amount of physical resource synergies than double role and single role
colleagues, which was one of the reasons why triple role academics engaged in a higher
number of teaching and research related activities than other two types (as illustrated in the
Tables 6.2 and 6.3).
The above analysis has demonstrated that there is an association between the ‘plural
activities’ of academics and the increased synergistic effects of physical resources in which
carrying out a higher number of diverse activities (e.g. triple roles) has generated more
physical resource synergies than engaging in a limited number of similar activities (e.g.
single roles).
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6.4. Analysis: The ‘Plural activity’ of Academic Entrepreneurs: An Emergent
Strategy to Extract Values from Resource Constrained Environments
The above analysis suggests that resource constraints do not totally inhibit academic
engagement in entrepreneurial endeavour, but academics entrepreneurially overcome
various resource barriers. Therefore, the Null-Hypothesis 1.1, which stated that being
entrepreneurial is not a means of overcoming resource barriers in a resource constrained
environment, is rejected. These findings are largely in line with the entrepreneurship
literature from developed economic environments that highlighted overcoming resource
barriers as a key quality of entrepreneurship (Saylor, 1987, Hart et al., 1995, Binks and
Vale, 1990). It was also apparent that academics were heterogeneous in terms of the nature
of their entrepreneurial engagements. Those who had engaged in a higher number of
diverse activities (e.g. triple roles) were able to overcome resource barriers to a greater
extent by capitalizing on a relatively high level of synergistic effects generated by their
engagements than those who had engaged in a limited number of similar activities (e.g.
single roles). Therefore, the Null-Hypothesis 1.2, which asserted that there was no
association between the ‘plural activity’ of academic entrepreneurs and the amount of
synergistic effects generated in resource constrained environments, was also rejected.
In-depth interviews also revealed that since opportunities were not abundant in their
environment, capitalising on every minute opportunity was of paramount importance for
academics in Sri Lanka. For example, one triple role academic stated:
‘opportunities to engage in external teaching and to conduct training and seminars to
industry were limited....... Furthermore, we do not have a continuous flow of consultancy
projects......Therefore, it was required to engage in different activities’
Interestingly, this reflects the way that triple role academics use resource constraints as a
trigger to overcome resource conflicts (Van Dierdonck and Debackere, 1988) by engaging
in several entrepreneurial activities. Furthermore, companies created by triple role
academics generated a myriad of resources, which were of utmost importance in
overcoming resource barriers. Hence, these findings do not agree with the literature which
stated that diversifying into similar activities (e.g. diversifying only into teaching related
activities) generates more synergistic effects (since similar activities allows sharing
common resources and competencies) (Markides and Williamson, 1996). In a resource
constrained environment, there were not enough opportunities to diversify into similar
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activities extensively. Therefore, the creation of resources, and minimizing resource
conflicts by engaging in diverse activities, was more important than sharing common
resources, which led to the argument that engaging in a higher number of diverse activities
is an espoused strategy for extracting value from a resource constrained environment.
Since each academic entrepreneurial engagement demands substantial time commitments
and effort (Wright et al., 2004), the chapter also investigated how triple role academics
balanced their engagements in a higher number of diverse entrepreneurial activities. This
analysis revealed that academics play different roles. While triple role academics were the
initiators and leaders of entrepreneurial activities, they received immense assistance from
other types of academics (i.e. double role and single role) to carry out these activities.
Although triple role academics, who engaged in a higher number of diverse activities,
generated more synergistic effects in terms of social networks, knowledge and skills, and
physical resources, than their single and double role counterparts, it was revealed that triple
role academics would not have been able to carry out their activities successfully, without
the support received from their double and single role colleagues.
Hence, it was apparent that the three types of academics play different but interdependent
roles. For example, triple role academics had engaged in establishing postgraduate
institutes, introducing new postgraduate courses, establishing joint research labs, and being
the principle investigators of international and industrial funding opportunities etc. Single
role colleagues, in collaboration with other types of academic entrepreneurs, taught on
postgraduate programmes and conducted training and seminar sessions for industry.
Similarly, double role academics, in addition to carrying out teaching related activities,
engaged in research projects and provided consultancy services using resources made
available by companies formed by triple role counterparts (e.g. joint research labs, spin-off
companies, and university commercial centres). Accordingly, it could be stated that, in
addition to synergies between activities at the individual level, there were synergies
between different entrepreneurs at the university level. Triple role academics were able to
balance their engagements in a number of activities due to these synergies.
Based on the above analysis, a conceptual framework was developed to illustrate the
entrepreneurial engagement of academics in a resource constrained environment (Figure
6.2). The main aim of this framework is to highlight synergies between entrepreneurial
activities at the individual level and between different entrepreneurs at the university level,
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which are found to be of the utmost importance when extracting value from a resource
constrained environment.
Figure 6.2: Academic Entrepreneurship: Strategy to Extract Values from Resource Constrained Environments
Teaching related
Activities
Company Creation
Research related
Activities
Single role
Academic
Entrepreneur
Dual role
Academic
Entrepreneur
Triple role
Academic
Entrepreneur
Knowledge
and Skills
Social
Network
Resources Input &
output flow
Synergies between Academic Entrepreneurial Activities
Synergies between Academic Entrepreneurs
Extracting Value from Resource Constrained Environments
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6.5. Chapter Summary
This chapter has presented qualitative and quantitative data analysis of the first objective of
this study, which was to investigate the ‘plural activities’ of academic entrepreneurs. The
analysis seems to suggest that being entrepreneurial is a means of overcoming resource
barriers in the resource constrained environment of Sri Lanka. Academic entrepreneurship
was found to be a process in which academics started their entrepreneurial careers by
engaging in teaching related entrepreneurial activities, and then, some of them diversified
into research related entrepreneurial activities and company creation. As a result,
academics engaged in different combinations of entrepreneurial activities, which
represented ‘plural activities’. These findings were in line with Tijssen (2006), who had
found that academic entrepreneurship was a process that started from ‘lesser
entrepreneurial’ activities, and then, extended to ‘highly entrepreneurial’ activities.
The chapter has demonstrated that academics had adopted three ‘plural activity’ types,
based on which three typologies of entrepreneurs were identified, namely single role,
double role, and triple role academics. Analysis indicated that single role academics
diversified into a limited number of similar activities (i.e. teaching related activities), while
their triple role counterparts diversified into a higher number of diverse activities (i.e.
teaching and research related activities and company creation). The engagement of double
role academics was positioned between that of single and triple role academics, whereby
they diversified into different activities at an average level (i.e. teaching and research
related activities).
It was also apparent that the extent of synergistic effects generated varied depending on the
complexity of the ‘plural activities’ of academics, in which, diversifying into a higher
number of diverse activities (e.g. triple roles) was found to generate more synergistic
effects than diversifying into a limited number of similar activities (e.g. single role).
Nevertheless, there remained synergies between those who adopted different
diversification strategies, which emphasizes the importance of having different and clear
role identities (Jain et al., 2009) by which universities might extract value from a resource
constrained environment.
Even though synergistic effects help explain the extent of diversification, and the ways of
overcoming resource barriers, this chapter did not address extensively why some
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academics decide to be single or double role entrepreneurs. It is possible to argue that
there may be several other micro-, macro-, and meso- level causal factors that determine
academic propensity to adopt different ‘plural active’ types, which will be discussed in the
following three chapters of the thesis. Thus, the next chapter of the thesis discusses how
academic entrepreneurs, who adopt different ‘plural active’ types, differ from each other
with respect to their motivations.
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Chapter 7: The Motivations of Academic Entrepreneurs operating in a Resource
Constrained Environment
In recent years, there has been increasing interest in the investigation of what motivates
academics to engage in entrepreneurial endeavour, despite experiencing a reward system
that mainly encourages publications (Jones-Evans, 1997). Motives that influence academic
entrepreneurship identified in these studies are desire for novelty, and wealth (Franklin et
al., 2001), a need to make use of technical expertise (Otto, 1999), a need for independence
and control (Oakey, 2003), and university policy towards the encouragement of academic
entrepreneurial activity (Van Dierdonck and Debackere, 1988). However, there is a lack of
research performed to investigate the motives of academic entrepreneurs in resource
constrained environments, although entrepreneurial motivation has been found to play a
critical role in environments that lack support mechanisms (Erdıs and Varga, 2009).
Therefore, the purpose of this chapter is to present an analysis of the second of the four
objectives of this thesis, which was to investigate the motivations of academic
entrepreneurs who operate in the resource constrained environment of Sri Lanka. This
chapter initially briefly recalls the literature that is relevant to the key issues addressed, and
subsequently, provides qualitative and quantitative data analysis. Finally, the chapter
concludes with a summary.
7.1. The Motivations of Academic Entrepreneurs
Motivation is defined in the management literature as “a cognitive decision making process
through which goal directed decision making behaviour is initiated, energized, directed,
and maintained” (Huczynski and Buchanan 2004, pp 244). Two categories of motives have
been identified in the entrepreneurship literature; namely, ‘pull’ and ‘push’ factors. ‘Push’
motives are the elements of necessity which encourage entrepreneurial engagement as a
means of overcoming constrained circumstances. In contrast, ‘pull’ motives are the
positive reasons why someone decides to be entrepreneurial (Gilad and Levine, 1986).
Research to date has tended to focus on the motives of entrepreneurs founding spin-off
companies (Morales-Gualdrón et al., 2009, Prodan and Drnovsek, 2010). However
academics, particularly those operating in resource constrained environments, have been
found to engage in multiple activities (named in this study as ‘plural activity’), as a
strategy to extract value from their environments. Hence, the first objective of this chapter
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is to investigate whether there is an association between the ‘plural activities’ and the
motivations of academic entrepreneurs (which relates to Hypothesis 2.1: In resource
constrained environments, there is no association between the ‘plural activity’ of academic
entrepreneurs and their motivations).
It has also been stated in the literature that academic entrepreneurship is a process, which
starts from carrying out ‘lesser entrepreneurial’ activities, and then, extends to ‘highly
entrepreneurial’ activities (Tijssen, 2006). Recent evidence suggests that entrepreneurial
motivations may change during the entrepreneurial process (Shane et al., 2003), and that,
entrepreneurs who are initially motivated by push motives, may be driven by pull motives
following the development of their business (Schjoedt and Shaver, 2007, De Silva and
Kodithuwakku, 2011, Rosa et al., 2006). So far, however, there has been little research on
the dynamism of academic entrepreneurial motivation. Hence, the second objective of this
chapter is to investigate how the motivations of academics operating in a resource
constrained environment change over their entrepreneurial careers (which relates to
Hypothesis 2.2: The motivations of academic entrepreneurs operating in resource
constrained environments do not change over their entrepreneurial careers).
7.2. Analysis: The ‘Plural Activity’ and Motivations of Academic Entrepreneurs
Five push motives and ten pull motives were identified from the literature, and the ‘plural
activity’ of academics discussed above, was used as variables to test whether there was an
association between the ‘plural activities’, and motivations, of academic entrepreneurs
(Table 7.1). Academics were asked to state to what extent they were motivated by each
motive. Since normality tests (for 15 motives) indicated that the data were not distributed
normally, it was decided to use non-parametric testing for the analysis. Accordingly, a
‘Krukal-Wallis test’ was used to investigate whether there was an association between the
types of ‘plural activity’ and each of the 15 motivations, and a ‘Mann-Whitney-U test’ was
used for pair-wise comparisons.
As illustrated in Table 7.1, analysis revealed that there was a significant association
between the ‘plural activities’ of academic entrepreneurs and seven out of the fifteen
motivations. However, four of these seven motives, namely, ‘a lack of resources within
universities’, ‘desire for wealth’, ‘to acquire new knowledge and skills’, and ‘to capitalise
on self-perceived opportunities’ had similar ‘mode values’ for three ‘plural activity’ types.
Despite modes being similar, the reason why there was a significant association between
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‘plural active’ types and the above motives was due to the skewed distributions of the level
of motivations. Hence, in order to compare and contrast the difference between ‘plural
activity’ types with respect to the above stated four motives, the analysis used qualitative
data gathered from in-depth interviews.
Table 7.1: A Comparison of the Motives of Academic Entrepreneurs
Motive Kruskal-Wallis Test (p) Mode
Single role
Double role
Triple role
Push Motives Insufficient income .489 (N=211, X2 =1.429) 3 3 3 Job related dissatisfaction .178 (N=206, X2 = 3.448) 1 2 2 Not having an industrial partner capable of commercializing the new product/technology
.020 (N=186, X2 = 7.826) 1 1-2, 1-3 21-2 2 1-3
Lack of resources within university .028 (N=213, X2 = 7.153) 31-2 31-2, 2-3 32-3 The pressure for academics to engage in entrepreneurial activities
.884 (N=225, X2 = .246) 2 2 2
Pull Motives In order to achieve career development .513 (N=233, X2 = 1.336) 3 3 3 In order to acquire new knowledge and skills .004 (N=234, X
2 = 10.809)
31-2, 1-3 31-2 31-3
In order to capitalise on the opportunity perceived by you (self-perceived)
.006 (N=224, X2 =
10.136) 31-2, 1-3 31-2 31-3
In order to capitalise on the opportunity perceived by your university
.953 (N=225, X2 = .097) 3 3 3
In order to provide benefits to students (e.g. lab equipments, industry placements, and opportunities etc)
.473 (N=236, X2 = 1.497) 3 4 3
In order to make use of industrial resources .252 (N=223, X2 = 2.760) 2 3 2 Desire for wealth .090 (N=226, X2 = 4.807) 3 32-3 32-3 For personal satisfaction (e.g. associate with people outside the university, and independence, social status, challenge seeking nature etc)
.023 (N=232, X2 = 7.516) 3 42-3 42-3
As result of role models .184 (N=215, X2 = 3.388) 2 2 2 The belief that it will not interfere with my academic career
.218 (N=93, X2 = 3.047) Single vs triple U= -1.770, p= .077, r= .12
11-3 3 31-3
1-2 - A significant difference between single role and double role at 0.05
1-3 – A significant difference between single role and triple role at 0.05
2-3- A significant difference between double role and triple role at 0.05
7.2.1. Push Motives that have no Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs
Three of the five push motives did not have a significant association with academics who
recorded ‘plural activities’. These were ‘insufficient income’, ‘job related dissatisfaction’,
and ‘pressure from universities for academics to engage in entrepreneurial activities’. The
analysis suggests that, regardless of the type of ‘plural activity’, insufficient income was a
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highly rated push factor (Single role Mode = 3, Double role Mode =3, Triple role Mode
=3), while job related dissatisfaction was a lowly rated one (Single Mode=1, Double
Mode=2, Triple Mode=2). In-depth interviews further confirmed that most of the
academics initially decided to engage in entrepreneurial activities due to insufficient
personal income, but there was no job related dissatisfaction. It seemed that entrepreneurial
engagements extended the service of academics to a wider community. These findings
support research carried out in developed countries, which found that insufficient income,
but not job related dissatisfaction, tended to motivate academic entrepreneurship (Smilor et
al., 1990).
Furthermore, the motive, ‘pressure by universities for academics to engage in
entrepreneurial activities’ was rated lowly by all the three types of academic entrepreneurs
(Single Mode=2, Double Mode=2, Triple Mode=2). This was further confirmed by in-
depth interviews, which revealed that the engagement in academic entrepreneurship was
mostly a result of the drive of academics, not pressure from their universities. It was also
evident that, even though entrepreneurial engagement was a general goal of all Sri Lankan
universities, none of them had a clear university policy to promote academic
entrepreneurship.
7.2.2. Push Motives that have a Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs
The two push factors that had a significant association with ‘plural activity’ types were
‘not having an industrial partner capable of commercializing a new product/technology’ X2
(2, 186) = 7.826, p = 0.02< 0.05 and ‘a lack of resources within universities’ X2 (2, 213) =
7.153, p = .028 < 0.05. The influence of ‘not having an industrial partner capable of
commercializing new product/technology’ was significantly lower for single role academic
entrepreneurs in comparison to their double role U= -2.692, p= .007, r=.27 and triple role
counterparts U=-2.706, p=.007, r=.2. On the other hand, although double and triple role
academic entrepreneurs, when compared with single role counterparts, were significantly
more motivated by this factor, the extent of motivation for them was low (i.e. double role -
Mode= 2 and triple role - Mode=2). In-depth interviews further confirmed this by revealing
that, although some activities (e.g. the developing products or services with potential for
commercialization, establishing academic owned companies, and engaging in joint
research activities) by double role and triple role academic entrepreneurs were, to some
extent, motivated by ‘not having an industrial partner capable of commercializing new
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product/technology’, it was not a main motive. Furthermore, since only a few triple role
academic entrepreneurs were reported to form companies to commercialise these
innovations, commercialization was not a motive for a large proportion of them.
The analysis suggested that ‘the lack of resources within universities’ was a significantly
higher motive for double role academic entrepreneurs than single role U= -1.884, p= .060,
r=.17 and triple role ones U= -2.293, p= .022, r=.16. In-depth interviews revealed that ‘a
lack of university resources’ stimulated the engagement of double role academic
entrepreneurs in research related academic entrepreneurial activities, such as joint research
projects with industry, working in industry, and acquiring funding from industry and other
national and international funding bodies. Interestingly, even though triple role academic
entrepreneurs were not highly motivated by a lack of university resources, their activities
had resulted in the significant improvement of the resource status of universities (e.g.
through joint research labs, commercial/sales centres, and consultancy related companies
etc).
The above analysis of push motives has suggested that there was a significant association
between ‘plural activities’ and two of the five push motives, namely, ‘not having an
industrial partner capable of commercializing a new product/technology’ and ‘a lack of
resources within universities’. Hence, in relation to these two motives, Hypothesis 2.1,
which stated that, in a resource constrained environment there would be no associations
between the ‘plural activities’ of academic entrepreneurs and their motivations, was
rejected.
7.2.3. Pull Motives that have no Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs
There was no significant association between ‘plural activities’ and five out of the ten pull
motives, where three were highly rated and the other two were lowly rated by all three
types of academic entrepreneurs. The three highly rated pull motives were ‘to achieve
career development’ (Single Mode = 3, Double Mode =3, Triple Mode =3), ‘to provide
benefits to students (e.g. lab equipments, industry placements, and opportunities etc)’
(Single Mode=3, Double Mode=4, Triple Mode=4), and ‘to capitalise on opportunities
perceived by universities’ (Single Mode=3, Double Mode=3, Triple Mode=3). In-depth
interviews suggested that the Sri Lankan university promotion scheme (there is a common
point based promotion scheme for all the universities) award points for carrying out some
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academic entrepreneurial activities such as external teaching, acquiring funding, engaging
in consultancy, securing patents, developing university infrastructure, and providing
national service. Hence, it seemed that entrepreneurial engagements made a direct
contribution to their career success. Moreover, it was found that academic entrepreneurship
enabled academics to overcome resource barriers, as a result of which, more opportunities
and resources were available for them to engage in university research and teaching (See
Section 9.3 of Chapter 9 for more information about the positive impacts of entrepreneurial
engagements on university teaching and research). Hence, all three types of entrepreneurs
were motivated by a need to achieve career development and to provide benefits to
students, which in turn increased demand for their degree programmes.
Furthermore, in-depth interviews revealed that, in Sri Lanka, since there is no university
policy on academic entrepreneurship, academic entrepreneurship was mainly driven by
individual academics. Therefore, it seemed that the motive, ‘opportunities perceived by
universities’, mentioned in the on-line survey, was interpreted by respondents as
‘opportunities perceived by other academic entrepreneurs’. As indicated by the statistical
analysis presented above, all three types of academic entrepreneurs were motivated to
capitalise on opportunities perceived by other academic entrepreneurs, which further
justified the synergies between academic entrepreneurs discussed in the Section 6.4 of the
Sixth Chapter of this thesis. For instance, it was revealed that both double role and single
role academics capitalised on opportunities identified by triple role academics (which
showed their motivation to capitalise on opportunities perceived by others). This enabled
everyone to benefit from these opportunities and also, for triple role academics, to
successfully carry out a higher number of different activities.
The above identified pull factors that were highly rated by all entrepreneurs in this resource
constrained environment (i.e. ‘a need to achieve career development’, ‘to provide benefits
to students’, and ‘to capitalise on opportunities perceived by other academic
entrepreneurs’) also have been recognized as important pull motives in studies conducted
in developed countries (e.g. Collins et al., 2004, Basu and Goswami 1999, Van Dierdonck
and Debackere, 1988, Meyer-Krahmer and Schmock, 1998, Siegel et al., 2004). Despite
this similarity, it was evident that, in a resource constrained environment, these pull
motives were shaped by resource scarcities. For example, it was apparent that, since
resources were scarce, academics in Sri Lanka had to engage in entrepreneurial activities to
secure funding and physical resources with which to carry out normal academic duties.
Hence, due to resource scarcities academic entrepreneurial engagements were needed for
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career development, which was mainly achieved from academic performance in normal
academic duties. Similarly, since opportunities were rare, when an academic identified an
opportunity, others were also motivated to assist in capitalizing on that opportunity, which
in turn provided benefits to everyone.
The two motives that were rated lowly by all three types of academic entrepreneurs were
‘need to make use of industrial resources’ (Single Mode=2, Double Mode=3, Triple
Mode=2) and ‘the influence of role models’ (Single Mode=2, Double Mode=2, Triple
Mode=2). A need to capitalise on industrial resources was rated lowly by all of the
entrepreneurs due to lower research and development investments made by Sri Lankan
industry when compared with more developed nations (for more details please refer to the
Section 2.2.1 of Chapter Two). As a result, this finding is different from studies carried out
in developed nations, which recognized that a need to make use of industrial resources was
an important motive (e.g. D’Este et al 2010, Howell et al 1998, Meyer-Krahmer and
Schmock, 1998). Nevertheless, it should be noted that, although the difference is not
significant, double role entrepreneurs (Mode=3) rated a need to use industrial resources
marginally higher than the other two types (Single role Mode=2, Double role Mode = 2).
In-depth interviews suggested that it was due to an engagement in joint research activities
by double role academics. This was motivated by a need to use industrial resources. These
respondents stated that, even though industry investment in research and development, on
average, was low, there were a few companies who made high investments.
7.2.4. Pull Motives that have a Significant Association with the ‘Plural activities’ of
Academic Entrepreneurs
The pull factors found to have a significant association with the ‘plural activities’ of
academic entrepreneurs were ‘need to acquire knowledge and skills’ X2 (2, 234) = 10.809,
p = .004 < 0.05, ‘need to capitalise on self-perceived opportunities’ X2 (2, 234) = 10.136, p
= .006 < 0.05, ‘desire for wealth’ X2 (2, 226) = 4.807, p = .090 < 0.05, and ‘personal
satisfaction (e.g. associate with people outside the university, and independence, social
status, challenge seeking nature etc)’ X2 (2, 232) = 7.516, p = .023 < 0.05. Additionally, a
pair-wise comparison, using Mann-Whitney-U test, indicated that there was a significant
difference between single role and triple role academic entrepreneurs with respect to the
motive, ‘due to a belief that entrepreneurial engagements would not interfere with their
academic careers’ U= -2.202, p= .028, r= .15.
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Triple role (Mode= 3, U=-2.813, p=.005, r= .18) and double role (Mode= 3, U=-3.409,
p=.001, r= .3) academic entrepreneurs were significantly more highly motivated by ‘a need
to acquire knowledge and skills’ than their single role counterparts. In depth interviews
revealed that the carrying out of some research related entrepreneurial activities and
company creation, to some extent, were motivated by the need to understand current trends
and gaps in industry, and to acquire knowledge and skills relevant to application oriented
research. In these instances, working with industry had resulted in sharing tacit knowledge.
‘A need to capitalise on self-perceived opportunities’ was a significant pull motive for
triple role (Mode= 3, U=-3.233, p=.001, r= .21) and double role (Mode= 3, U=-2.863,
p=.004, r= .26) academic entrepreneurs in comparison to their single role counterparts. In-
depth interviews revealed that, while the recognition of an opportunity by individuals was
mandatory for all the entrepreneurial engagements (Shane and Venkataraman, 2000), it
was a major incentive when engaging in company creation, and some research related
academic entrepreneurial activities, such as acquiring funding, joint research, and
consultancy.
Similarly, it seemed that triple role (Mode=4) and double role (Mode=4) academic
entrepreneurs were significantly more highly motivated by personal satisfaction U= -2.648,
p= .008, r= .17 than single role colleagues (Mode=3). Informal discussions conducted with
students further confirmed this by revealing that triple role and double role academic
entrepreneurs had relatively high social status among students and the community.
It was also evident that ‘the belief that an engagement in entrepreneurial activities will not
interfere with academic careers’ was a significantly higher motive for triple role
entrepreneurs (Mode= 3) when compared to their single role counterparts (Mode=1) U= -
1.770, p= .077, r= .12. Qualitative data suggested that most of the triple role academic
entrepreneurs, who were either senior lecturers or professors, received support from double
and single role colleagues when engaging in academic entrepreneurial activities and
normal academic duties. Furthermore, it seemed that, since professors had already
developed their academic careers, they had less pressure to produce publications.
Nevertheless, they received several invitations from junior members of their staffs for joint
publications owing to their professorial status.
The analysis also indicated that triple role academics were significantly more motivated by
‘desire for wealth’ (Mode= 3) U= -2.202, p= .028, r= .15 than their double role colleagues.
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It was evident that out of the research related activities carried out by double role academic
entrepreneurs, it was only engagement in consultancy that generated additional personal
income. For example, they did not make extra income by working in industry since salary
scales in most of these places were not different from universities. Furthermore, based on
university rules, any engagement in funded projects did not bring academics additional
income, other than covering the cost of engaging in research. Hence, engagement in these
activities was more motivated by a need to pursue their research careers than desire for
wealth. In contrast, it was apparent that academics earned significantly higher additional
income through company creation. Generally, these companies were in academic
specialities such as architecture, construction engineering, healthcare, agriculture, textile,
software, computer hardware, information technology, information security, medicine,
dentistry, veterinary practise, and community services. In-depth interviews indicated that,
even if a company was formed to provide consultancy services, the company provided the
founder with a constant flow of consultancy work, when compared with ad hoc
consultancy assignments received without forming a company.
Based on the above discussion, it was evident that, five out of the ten pull factors
encouraged diversifying into all three types of entrepreneurial activities (i.e. teaching and
research related as well as company creation- e.g. triple role) than carrying out only
teaching related entrepreneurial activities (e.g. single role). These were the ‘need to acquire
new knowledge and skills’, ‘in order to capitalise on self-perceived opportunities’, ‘the
belief that an engagement in academic entrepreneurial activities will not interfere with their
academic careers’, ‘desire for wealth’, and ‘for personal satisfaction’. Hence, Hypothesis
2.1, which stated that, in a resource constrained environment, there would be no
associations between the ‘plural activity’ of academic entrepreneurs and their motivations,
was rejected in terms of these five pull factors.
7.3. Analysis: Dynamisms in Entrepreneurial Motivation
As previously argued in this chapter, in addition to investigating what motivated academics
to carry out the type of ‘plural activities’ that they are currently involved in, it was also
interesting to examine whether their motives changed over their entrepreneurial careers.
Hence, the following Sections of this chapter analyse qualitative data on the dynamism of
entrepreneurial motivation. The analysis is performed separately for each type of academic
entrepreneur since the Section 7.2.1 of this Chapter revealed that there was an association
between their ‘plural activities’ and motivations.
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7.3.1. Dynamism in Entrepreneurial Motivation: Single Role Academic
Entrepreneurs
Single role academics had engaged in at least one out of four teaching related
entrepreneurial activities; namely, external teaching, initiating the development of new
degree programmes, placing students as trainees in industry, and conducting seminars and
training sessions for industry personnel. It was evident that their engagement was initially
motivated by push motives such as insufficient income, inadequate contacts with industry,
a lack of knowledge and skills among students on the applications of theories, and a low
level of demand for their degree programmes etc. However, over time, certain pull factors
such as need for recognition/status, to improve employment opportunities for students, and
to make use of their expertise etc had been added to the list of motives.
One single role academic entrepreneur stated:
‘I started engaging in external teaching since my salary was insufficient....... During my
sabbatical leave period, I got experience abroad, and then, decided to introduce a new
course in the external degree programme. ........There was a gap in the education market in
Sri Lanka with respect to the “Radar Remote Sensing” subject area (i.e. academic
discipline in which he received experience abroad), even though it was highly demanded
by industry’
It seemed that his engagement was initially motivated by insufficient personal income,
which was a push factor. Subsequently, pull factors, such as the identification of an
opportunity and the need to make use of his expertise were added, and as a result, lately he
was motivated by a combination of pull and push motives. It was also evident that none of
the single role academic entrepreneurs was motivated only by pull factors. Therefore, it
was apparent that almost all of the single role academic entrepreneurs were initially
motivated by push factors, and subsequently, by a combination of pull and push factors.
7.3.2. Dynamism in Entrepreneurial Motivation: Double Role Academic
Entrepreneurs
In addition to carrying out teaching related entrepreneurial activities, double role
academics had engaged in at least one activity categorised under research related
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entrepreneurial activities; namely, working in the industry (research based), carrying out
research based consultancy for industry via their universities or privately (but without
forming a company), developing products or services with potential for commercialization,
acquiring research funding from government, non-governmental or international bodies,
collaborating with industry through joint research projects, and providing research related
assistance to small business owners. According to the double role academic entrepreneurs,
their engagement in each type of activity (i.e. teaching related academic entrepreneurial
activities, and research related academic entrepreneurial activities) was motivated initially
by push factors, while lately, the significance of pull factors had increased. For example,
one double role academic explained how his motivations to engage in teaching related
entrepreneurial activities were changed over time:
‘I decided to conduct training and seminars for industry since I didn’t have contacts with
industry personnel, which made it difficult for me to secure contracts (i.e. research related
contracts) from industry. Therefore, I made a great effort to secure opportunities to
conduct training and seminars to industry....... However, now I conduct these only if I’m
invited by industry. The reasons for engagement now is to maintain contacts and for
personal satisfaction’.
In the above case, although conducting training and seminars for industry personnel (i.e. a
teaching related academic entrepreneurial activity) was initially motivated by a lack of
contacts with industry, which is a push factor, subsequently it was driven by pull factors
such as need to maintain contacts and for personal satisfaction. Nevertheless, his
engagement in certain research related entrepreneurial activities was motivated by push
factors. He said:
‘Since university lacks resources, I try to engage in joint research projects, so that I could
make use of industrial resources. When preparing budgets for consultancy or other
research projects, I try my level best to find ways to improve the resource status of the
university’.
Another double role academic entrepreneur stated:
‘I decided to do consultancy since my income was not sufficient. My decision to apply for
international funding was driven by a lack of funding received from my university to
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conduct research. I couldn’t at least recruit a research student. I wanted to develop my
publication profile. I was successful in both consultancy and funding grants. After my
initial successes, later funding applications were driven by my need to provide
opportunities to students, to improve resource status of university, and to provide a service
to the country/tax payers, in return for receiving free education. ............Two years back, I
was promoted as a professor, So now I’m not pressurised to have publications, but I need
to have funding to maintain my academic calibre. .............The motive for applying for
consultancy also changed from insufficient income to need to improve my personal income
in order to have more savings for my children’.
It seemed that his engagement in research related academic entrepreneurial activities was
initially motivated by insufficient personal and research income. With the success achieved
by these activities, some pull factors, such as need to provide a service to students as well
as a desire to improve the resource status of his university were added. However, it was
apparent that lately he was mainly motivated by pull factors such as desire for wealth and
maintaining a high academic standard. Data further indicated that with respect to most of
the double role academics, even though the significance of pull factors increased over time,
most push factors that related to resource constraints (e.g. a lack of resources in
universities, and research funding etc) did not completely disappear.
7.3.3. Dynamism in Entrepreneurial Motivation: Triple Role Academic
Entrepreneurs
In addition to engaging in teaching and research related entrepreneurial activities, triple
role academics carried out at least one activity categorised under company creation;
namely, the formation of joint ventures in which the university and industry were joint
partners, joint ventures privately through collaborating with industry, new spin-off
companies, university centres designed to carry out commercialization activities, and
privately owned companies. In-depth interviews revealed that triple role academics
initially decided to engage in teaching related entrepreneurial activities due to insufficient
personal income and a lack of reputation with industry. However, their engagement in
teaching related entrepreneurial activities was later changed to pull motives such as
personal satisfaction, social status, a need to make use of knowledge/expertise, and career
progression.
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For example, one triple role academic argued:
‘My attempt to engage in external teaching was initially prompted by insufficient personal
income. However, now I conduct external teaching as a service to students and for
personal satisfaction since there is no expert in my discipline to conduct relevant classes.
The current income I gain from external teaching is insignificant in comparison to my total
income’
This quotation illustrates a shift in motives from push to pull with respect to engaging in
teaching related entrepreneurial activities by triple role academic entrepreneurs. The same
trend was observed with respect to their motivations to engage in research related
entrepreneurial activities. One academic entrepreneur said:
‘I initially decided to engage in consultancy since I didn’t have sufficient income. My
decision to engage in joint research projects with industry was driven by not having
adequate resources in the university to conduct research. With the development of these
activities, further engagement was driven by status I received, need to do something
beyond publications, and my creativity.........I would say, these changes occurred
gradually........Now I have a joint research lab (software related) and a privately owned
company. Now I am motivated to engage in consultancy and joint research projects in
order to bring more businesses’
In the above case, push factors such as insufficient personal income and a lack of resources
in universities were gradually replaced by pull factors such as status, creativity, and desire
for commercial success and wealth. Another triple role academic entrepreneur commented:
‘Initially, most of the engagements (i.e., teaching and research related academic
entrepreneurial activities) were due to insufficient income and a lack of resources in my
university. After starting our company, motives (for engaging in teaching and research
related academic entrepreneurial activities) changed drastically. We were able to improve
resource status of the university and to develop reputation and credibility in the industry.
As a result, we received a lot of opportunities to engage in teaching and research related
academic entrepreneurial activities and had resources in the university to capitalise on
such opportunities. .......Sometimes, we provide services free for small scale entrepreneurs’
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This quotation also shows how motives for engaging in teaching and research related
academic entrepreneurial activities changed as a result of diversifying into company
creation. In this example, motives were changed from push factors such as insufficient
personal income and university resources to pull factors such as need to capitalise on
opportunities, to make use of resources, and for personal satisfaction. In a similar vein, the
engagement of academics in company creation was initially motivated by push factors, and
lately, by a combination of pull and push factors. One triple role academic entrepreneur
explained:
‘University bureaucracy made it very difficult to be competitive when engaging in
consultancy. Further, university rule doesn’t support competitive bidding. Therefore, I with
a group of my colleagues started a company to provide consultancy services. This
arrangement had resulted in us receiving substantially higher personal income. I think that
it is due to the effective and efficient service delivered by us’.
It seems that his motivations to establish a company were a need to overcome barriers
created by university “red-tape”, such as bureaucracies, inefficient financial services, and
restrictive rules, which was a push factor, as well as a desire for wealth which was a pull
factor. It was also evident that, while the decision by most of the triple role academic
entrepreneurs to set up a company was initially motivated by push factors, this was
immediately followed by pull factors. In their opinion, the presence of push factors, such
as insufficient personal income, a lack of resources within universities, and delays and
difficulties encountered as a result of engaging in academic entrepreneurial activities
through universities, would not have motivated them to start a company, had they not been
encouraged by strong pull factors. This finding is in agreement with Jones-Evans (1997)
who has stated that, when academics are motivated only by a need to earn additional
income, they tend to engage in consultancy rather than face the hazard of company
creation. The pull factors found to motivate triple role academics to start and operate
companies were the recognition of opportunity, need to try something new, creativity,
status, desire for wealth, personal satisfaction, and a sense of achievement.
The above analysis suggested that the motivations of academics to engage in each type of
entrepreneurial activity (i.e. teaching related academic entrepreneurial activities, research
related academic entrepreneurial activities, and company creation) changed over time. The
engagement of each type of activity was initially motivated by push factors, and
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subsequently, the significance of pull factors increased. However, since academics initially
engaged in teaching related academic entrepreneurial activities, and subsequently,
diversified into research related academic entrepreneurial activities and company creation,
a similar pattern of dynamism was observed in the entrepreneurial careers of academics at
the secondary level. This led to reject the Null-Hypothesis 2.2, which stated that the
motivations of academic entrepreneurs operating in resource constrained environments do
not change over their entrepreneurial careers. Figure 7.1 illustrates a conceptual framework
derived from the findings of this chapter. The figure presents the dynamism in the motives
of academics with respect to carrying out each entrepreneurial activity.
Figure 7.1: Dynamism in Academic Entrepreneurial Motivation
7.4. Chapter Summary
This chapter has investigated the motivations of academic entrepreneurs operating in the
resource constrained environment of Sri Lanka. The analysis suggested that the
engagement in each type of entrepreneurial activity (i.e. teaching related entrepreneurial
activities, research related entrepreneurial activities, and company creation) was initially
motivated by push factors, and subsequently, that the influence of pull motives increased.
It was evident that some push factors encouraged engaging in any type of entrepreneurial
activity, while other push motives encouraged carrying out specific types of
entrepreneurial activities. For instance, ‘insufficient personal income’ was a strong push
factor that motivated engagement in any entrepreneurial activity. Push motives that
especially encouraged the carrying out of teaching related entrepreneurial activities were ‘a
low level of demand for degree programmes’, ‘a lack of contacts with, and reputation in,
the industry’, as well as ‘inadequate knowledge and skills’ among students on applied
aspects. Similarly, push factors that particularly motivated diversifying into research
Single Role A.E Double Role A.E Triple Role A.E
Mainly Push Push+Pull Mainly Pull
Mainly Push Push+Pull Mainly Pull
Mainly Push Push+Pull Mainly Pull
Teaching Related
Research Related AE
Company Creation
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related entrepreneurial activities were ‘inadequate research income’, and ‘a lack of
resources in universities’. Likewise, push motives that encouraged diversifying into
company creation were some barriers such as ‘university red-tapes’, and ‘not having an
industrial partner to commercialise their innovations’ (only with respect those who
innovate commercializable products and/or services). However, no respondent rated ‘job
related dissatisfaction’, and ‘pressure from universities for academics to engage in
entrepreneurial activities’ as important push motives.
Interestingly, it was evident that over time, the importance of push factors declined, while
pull factors increased. Although pull factors that motivated the engagement in teaching and
research related entrepreneurial activities gradually became important, it seemed that pull
factors that encouraged company creation immediately followed push factors. This finding
is in agreement with Jones-Evans (1997) who has stated that, when academics are
motivated only by a need to earn additional income, they tend to engage in consultancy
rather than face the hazard of company creation.
Pull factors that were identified as important, regardless of the type of entrepreneurial
activity, were ‘need to achieve career success’, ‘to capitalize on opportunities perceived by
colleagues’, and ‘to provide benefits to students (industry placements, and job
opportunities etc)’. Interestingly, these were also recognized as important pull motives in
studies conducted in developed countries (e.g. Collins et al 2004, Basu and Goswami 1999,
Van Dierdonck and Debackere, 1988, Meyer-Krahmer and Schmock, 1998, Siegel et al.,
2004). Despite this similarity it was evident that, in a resource constrained environment,
these pull motives were shaped by resource scarcities. For example, it was apparent that,
since resources were scarce, academics in Sri Lanka had to engage in entrepreneurial
activities to secure funding and physical resources to carry out entrepreneurial activities
and normal academic duties, the performance of which was important for career
development. Similarly, since opportunities were rare, academics were interested in
capitalizing on those perceived by other academic entrepreneurs, which in turn provided
benefits for everyone.
It was also apparent that some pull factors had differential impacts. For instance,
diversifying into company creation as opposed to carrying out only teaching related
activities was significantly more highly motivated by a ‘need to acquire new knowledge
and skills’, ‘in order to capitalise on self-perceived opportunities’, ‘the belief that an
engagement in academic entrepreneurial activities will not interfere with their academic
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careers’, ‘desire for wealth’, and ‘for personal satisfaction’. Since academic entrepreneurial
diversification was found to be a process, those who engaged in company creation, were
also involved in teaching and research related entrepreneurial activities. Therefore, it is
possible to argue that those who were motivated by the above pull factors tend to carry out
a higher number of different activities.
Interestingly, ‘a need to make use of industrial resources’ was a pull factor, which was
regarded as having low importance. Data suggested that this has been mainly due to lower
research and development investments made by Sri Lankan industry when compared to
more developed nations. As a result, this finding was different from studies carried out in
developed nations, which recognized that a need to make use of industrial resources was an
important motive (e.g. D’Este et al 2010, Howell et al 1998, Meyer-Krahmer and
Schmock, 1998).
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Chapter 8: The Influence of Multilevel Factors on the ‘Plural Activities’ of Academic
Entrepreneurs operating in a Resource Constrained Environment
There has been recent interest in the investigation of factors influencing the entrepreneurial
activity of academics. These previous studies have revealed that academic
entrepreneurship is affected by multilevel causal factors, which comprise the personal
characteristics of academics, the qualities of their universities, as well as the attributes of
industry and government at a national level (O’Shea et al., 2004, Etzkowitz and
Leydesdorff, 2000, Siegel et al., 2004). However, most of these studies have been
performed in resource-rich developed nations, rather than in resource constrained
environments. Hence, the purpose of this chapter is to addresses this gap in our knowledge
by investigating these influences in the resource constrained environment of Sri Lanka,
which is the third objective of this thesis. Accordingly, this chapter, initially, briefly recalls
the relevant literature that had been discussed in detail in the Chapter Three and Four of the
thesis. This is followed by qualitative and quantitative data analysis, and finally, the
chapter concludes with a summary.
8.1. The Influence of Multilevel Factors on Academic Entrepreneurship
The personal factors identified in the literature as statistically related to the propensity of
academics to engage in entrepreneurial endeavour were the age (Audretsch, 2000),
position, level of education, (Levin and Stephan, 1991), gender (Smith-Doerr, 2004),
business management and entrepreneurial skills (Franklin et al., 2001), academic discipline
(Mowery and Sampat, 2005), and social networks (Siegel et al., 2007), of academics.
However, most of these studies have only investigated differences between academic
entrepreneurs and non-entrepreneurs, without paying attention to the heterogeneity of
academic entrepreneurs. As discussed in the Section 4.1 of Research Hypothesis Chapter,
academic entrepreneurs might not be homogeneous, and may differ in the way they
diversify their entrepreneurial activities. This heterogeneity might be particularly
prominent in a resource constrained environment since entrepreneurs in such environments
have been reported to use diversification to extract added value from limited opportunities
(Kodithuwakku and Rosa, 2002). Hence, the first aim of this chapter is to investigate
whether there is an association between the personal characteristics, and the ‘plural
activities’, of academic entrepreneurs operating in a resource constrained environment
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(which equates to Hypothesis 3.1: There is no relationship between the ‘plural activity’ of
academic entrepreneurs and their personal characteristics).
Additionally, the literature has shown that the characteristics of universities also influence
academic entrepreneurship (Franklin et al., 2001, Siegel et al., 2007). Some of these
influencing factors were research strength (Di Gregorio and Shane, 2003, Ambos et al.,
2008), commercial orientation (Friedman and Silberman, 2003), and resource status
(Powers and McDougall, 2005, Zucker et al., 1998, Kinsella and McBrierty, 1997). On the
other hand, a comparison between the influence of the effect of the personal characteristics
of academics (i.e. micro level) and their universities (i.e. meso level) has raised the
question as to whether it is micro or meso level factors that have the highest level of
influence on academic entrepreneurship. Most of these studies have found that the personal
characteristics of academics (i.e. micro level variables) have a greater impact on their
entrepreneurial activities than university characteristics (i.e. meso level variables) (D’Este
and Patel, 2007, Ambos et al., 2008, Clarysse et al., 2011). However, far too little attention
has been paid to the relative influence of micro- and meso- level factors on the way
academics adopt diversification strategies. Therefore, the second aim of this chapter is to
examine whether there is a difference between the influence of micro- and meso- level
factors on the ‘plural activities’ adopted by academics in a resource constrained
environment (which equates to Hypothesis 3.2: There is no difference between the
influence of micro and meso level factors on academic propensity to adopt specific ‘plural
activity’ types).
On the other hand, the entrepreneurship literature has argued that the pursuit of
opportunities is dependent upon the way individuals perceive their environments
(Stevenson and Jarillo, 1990, Binks and Vale, 1990). These studies suggest that the
perception of entrepreneurs regarding their environment determines their ability to identify
and capitalize on opportunities. Hence, in addition to the above mentioned objective
qualities of universities, the subjective perception of academics on the quality of their
universities (which is not an objective measure of quality) might also shape academic
entrepreneurship. Thus, the third objective of this chapter is to investigate whether there is
a relationship between the academic perceptions of the qualities of their universities and
‘plural activities’ (which relates to Hypothesis 3.3: There is no relationship between the
‘plural activity’ of academic entrepreneurs and their perception of university quality).
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In addition to micro and meso level factors, the macro environment, which mainly
comprises the government and industry, has also been found, by the literature, to shape
academic entrepreneurship (O’Shea et al., 2004, Etzkowitz and Leydesdorff, 2000, Siegel
et al., 2004). Etzkowitz and Leydesdorff (2000) have argued that, even though initially
governments direct university-industry relationships, over time dynamic and strong
institutional and other types of links are established between the three parties (i.e. ‘Triple
Helix Model’). Hence, it seems that the Triple Helix Model discusses a context that has
well structured institutional infrastructure frameworks to promote innovation and
entrepreneurship. However, the literature indicates that the institutional frameworks of
developing countries are neither integrated, nor well developed. As a result, strengths at the
micro level do not integrate with those at a macro level (Arocena and Sutz, 2001).
Therefore, it is questionable whether the models that illustrate how university, government,
and industry interact in developed nations could apply to resource constrained
environments. Hence, the fourth aim of this chapter is to investigate how university,
industry and government interact in the resource constrained environment of Sri Lanka
(which relates to Hypothesis 3.4: Interactions between university, industry and government
in a resource constrained environment do not differ from those in a developed
environment)
8.2. Analysis: The Relationship between the Personal Characteristics, and ‘Plural
activities’, of Academic Entrepreneurs
8.2.1. The Relationship between the Age and Position, and ‘Plural activities’ of
Academic Entrepreneurs
Not surprisingly, there was a significant correlation between the age and the position of
academics F(2, 338) = 262.4, p=0.000<0.05 (Lecturer M=34 SD=5, Senior Lecturer M=45
SD=7, Professor M= 57, SD=7). Therefore, when testing whether there was an association
between age and ‘plural activities’, position was used as a control variable. Position was a
categorical variable with three hierarchical levels; namely, lecturers, senior lecturers, and
professors. As might be expected, an ANOVA test revealed no significant association
between the age of lecturers and ‘plural activities’ adopted by them, F(2, 82) = 0.228, p=
0.797 (single M=42 SD=9, double M=44 SD=10, triple M=45 SD=10). Similarly, no
significant association was found between ‘plural activities’ and the age of, senior lecturers
F (2, 157)=0.568, p=0.568 (single M=47, SD=7, double M=45 SD=7, triple M=46, SD=7),
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or professors t (50) = 0.542, p=0.590 > 0.05 (double- M=57, SD=6, triple role
entrepreneurs M=56, SD=7) (Table 8.1).
Since the above analysis indicated that age is not related to the ‘plural activities’ of
academic entrepreneurs, it was decided to test whether the age of entrepreneurs differ from
non-entrepreneurs. An ANOVA test revealed that the mean age of non-entrepreneurial
lecturers (M=34, SD=1) did not significantly differ from entrepreneurial lecturers F (3,
104) = 0.229, p=0.876 > 0.05. However, the age of non-entrepreneurial senior lecturers
(M=38 SD=8) was significantly lower than entrepreneurial senior lecturers F (3, 174) =
2.936, p=0.035 < 0.05. This analysis was not performed for professors, since there were
only two non-entrepreneurial professors. These results with respect to the difference
between entrepreneurs and non-entrepreneurs are, to some extent, in line with research that
argues that older academics have a higher tendency to engage in entrepreneurial activities
than their younger counterparts (e.g. Audretsch 2000; Levin and Stephan 1991).
Table 8.1: The Age of Academics
Position The type of AE Mean age Test Statistics Lecturer Non-entrepreneurs 34 (SD 1) F (3, 104) = 0.229, p=0.876
F (2, 82) = 0.228, p= 0.797
Single roles 35 (SD 1) Double roles 34 (SD 0.6) Triple roles 34 (SD 1)
Senior Lecturer
Non-entrepreneurs 41 (SD 4) F (3, 174) = 2.936, p=0.035 F (2, 157)=0.568, p=0.568 Single roles 47 (SD 7)
Double roles 45 (SD 7) Triple roles 46 (SD 7)
Professor Double roles 57 (SD 6) t (50) = 0.542, p=0.590 Triple roles 56 (SD 7)
*Please note that due to insufficient number of single role professors, only double role and
triple role ‘plural activity’ types were considered
A chi-square test revealed that there was a significant association between the position, and
‘plural activities’, of academic entrepreneurs, but only at a 90% confidence level X2 (4,
302) = 8.902 p=0.064 <0.1. Other data indicated that, when compared with lecturers
(33.7%), a slightly high percentage of senior lecturers (42.9%) and professors (42.1%)
were triple role entrepreneurs. Additionally, it was also revealed that non-entrepreneurs
were significantly different from entrepreneurs in terms of their position X2 (6, 345) =
21.484 0.002 <p=0.05, where the majority of non-entrepreneurs were lecturers (53.5%)
(Table 8.2). In-depth interviews revealed that, compared to lecturers, professors and senior
lecturers had higher credibility, stronger social networks, wider knowledge and skills,
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better access to resources, and more opportunities for collaboration. As a result, professors
and senior lecturers were able to diversify into all three entrepreneurial activities. These
results indicated that the position of academics did influence their ‘plural activities’.
Table 8.2: The Position of Academics
Position
Professor Senior
Lecturer Lecturer Total
Non-entrepreneurs
Count (N) 2 18 23 43
% within Academics 4.7% 41.9% 53.5% 100.0%
% within Position 3.5% 10.1% 21.1% 12.5%
Single Role Academic Entrepreneurs
Count(N) 1 15 14 30
% within Academics 3.3% 50.0% 46.7% 100.0%
% within Position 1.8% 8.4% 12.8% 8.7%
Double Role Academic Entrepreneurs
Count(N) 30 77 43 150
% within Academics 20.0% 51.3% 28.7% 100.0%
% within Position 52.6% 43.0% 39.4% 43.5%
Triple Role Academic Entrepreneurs
Count(N) 24 69 29 122
% within Academics 19.7% 56.6% 23.8% 100.0%
% within Position 42.1% 38.5% 26.6% 35.4%
Total Count(N) 57 179 109 345
% within Academics 16.5% 51.9% 31.6% 100.0%
% within Position 100.0% 100.0% 100.0% 100.0%
On the other hand, an analysis of secondary data on the promotion scheme for academics
in Sri Lanka suggested that the ‘plural activities’ of academic entrepreneurs determined
their academic positions. The promotion scheme of academics is centrally determined by
the University Grant Commission (via Commission Circulars 723/1997, 869/2005,
721/1997, 879/2006). Upon the appointment of a lecturer there are five main levels in the
hierarchical structure of academics; namely, Senior Lecturer Grade II, Senior Lecturer
Grade I, Associate Professor, Professor and Senior Professor. As illustrated in Table 8.3, it
was evident that the carrying out of some academic entrepreneurial activities received
points in a marking scheme used to promote senior lecturers to professorships.
Furthermore, in-depth interviews revealed that, those who carried out ‘highly
entrepreneurial activities’ (e.g. spin-off formations) were able to overcome resource
barriers in order to engage in normal academic duties. Hence, their performance of normal
academic duties also won points for promotion. Therefore, it was apparent that,
entrepreneurial engagements, in turn, determined the positions of academics. Hence, while
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qualitative data further confirmed that there was a significant relationship between the
position, and ‘plural activities’, of academic entrepreneurs, it appeared that causality
occurred in both the directions (i.e. position affects ‘plural activity’ and vice versa).
Table 8.3: Academic Entrepreneurial Activities considered in the Promotion Scheme
Category in the promotion scheme Academic Entrepreneurial Activities considered for the promotion scheme
Teaching, Scholarships and Academic Development
External teaching, conducting training and seminars, and introducing new courses/degree programmes
Research, Scholarships and Creative Work
Patents (only two patents could be claimed), innovation in local community, industry (only two such activities could be claimed), Obtaining research funds, which is reflected by journal articles (unlimited) and commissioned reports by national and international bodies (only two reports could be claimed)
Contributions to University & National Development
Director or coordinator of a centre (only three such appointments could be claimed), Chairmen, member or secretary of national committees (only three such appointments could be claimed), and memberships in Board of Management (only three such appointments could be claimed)
8.2.2. The Relationship between the Gender, and ‘Plural activities’, of Academic
Entrepreneurs
A chi-square test revealed that there was a significant association between the ‘plural
activities’, and gender, of academics X2 (2, 302) = 0.022 <0.05. A comparatively high
percentage of male entrepreneurs (45%) were triple role academics, while a majority of
female entrepreneurs (61.3%) were no more than double role academics (Table 8.4).
Similarly, a significantly higher proportion of females (19.2%) were non-entrepreneurs in
comparison to their male counterparts (9.8%) X2 (3, 345) = 0.005 <0.05. A possible
explanation for these results would be family commitments, which female academics
mentioned as a reason for non-engagement. Furthermore, a belief that academic
engagement in entrepreneurial endeavour would negatively affect the quality of normal
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academic duties was also highlighted by most of the females as a reason for not carrying
out ‘highly entrepreneurial activities’ such as company creation. Additionally, it also
transpired that the majority of female academics did not have financial problems, since
their husbands, who are culturally considered responsible for the financial status of their
families, earned high incomes. Hence, these female academics were not motivated by
insufficient personal income, which was found to be a strong push motive for academic
entrepreneurship (See the Section 7.2.1 of Chapter Seven for motivations). Conversely,
most of the female entrepreneurs were mainly motivated by the need for research income,
which explained why the majority of them engaged in teaching and research related
entrepreneurial activities.
However, anecdotal evidence (via in-depth interviews) indicated that there were a few
female academic entrepreneurs who had formed companies. One of these cases concerned
a female professor who collaborated with a large company in the telecommunication
industry to form a joint-research lab. This lab was used not only to carry out academic
entrepreneurial activities (e.g. joint-research projects, consultancy, and applied research),
but also to perform normal academic duties. In-depth interviews suggested that this
initiative resulted in a massive improvement of the resource status of her department, and
hence, its ability to capitalize on entrepreneurial opportunities. Similarly, another female
academic, who was the first to introduce banana tissue culture technique to Sri Lanka,
initiated a large scale rural development project by using this technique. Eventually, she
formed several research centres, commercial outlets, and training institutes. These training
institutes provided technology related education to farmers regarding the use of computers
and internet for farming activities. She managed to achieve these developments while
carrying out several teaching and research related entrepreneurial activities. At the time of
interview, she was the Vice-Chancellor of one of the Sri Lankan universities.
While the results of this Section are consistent with those of Jones-Evans and Klofsten
(2000), who found that male academics had a relatively high tendency to engage in a wider
array of entrepreneurial activities than female academics, this analysis has also highlighted
heterogeneity among female academics. Even though a higher percentage of females
diversified only into teaching and research related entrepreneurial activities, there were a
small number of females who diversified into a large number of different activities (i.e.
triple roles), which was not revealed in terms of statistical significance.
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Table 8.4: The Gender of the Academic
The type of Academic Entrepreneur
Gender
Male Female Total
Non Entrepreneurs Count (N) 24 19 43
% within Academics 55.8% 44.2% 100.0%
% within Gender 9.8% 19.2% 12.5%
Single Role Academic Entrepreneurs
Count(N) 21 9 30
% within Academics 70.0% 30.0% 100.0%
% within Gender 8.5% 9.1% 8.7%
Double Role Academic Entrepreneurs
Count(N) 101 49 150
% within Academics 67.3% 32.7% 100.0%
% within Gender 41.1% 49.5% 43.5%
Triple Role Academic Entrepreneurs
Count(N) 100 22 122
% within Academics 82.0% 18.0% 100.0%
% within Gender 40.7% 22.2% 35.4%
Total Count(N) 246 99 345
% within Academics 71.3% 28.7% 100.0%
% within Gender 100.0% 100.0% 100.0%
8.2.3. The Relationship between the Discipline, and ‘Plural activities’, of Academic
Entrepreneurs
There were ten faculties in Sri Lankan universities namely, the faculty of ‘Social
Sciences’, ‘Architecture’, ‘Engineering’, ‘Computing and Information Technology’,
‘Medicine’, ‘Dentistry’, ‘Veterinary’, ‘Agriculture’, ‘Science’, and ‘Arts’. Since there were
not enough respondents from some of the faculties to perform Chi-Square tests, it was
decided to merge disciplines of similar type with respect to their entrepreneurial
engagements. Accordingly, ‘Architecture’ and ‘Engineering’ were merged to create one
category, and similarly, ‘Medicine’ and ‘Dentistry’ were also merged. Since no significant
difference was observed between two tests that run with, and without, combining
‘Veterinary’ with ‘Medicine and Dentistry’, it was decided to combine all three.
Accordingly, one category was created namely, ‘Medicine, Dentistry, and Veterinary’. As
there were only nine academics from the ‘Faculty of Arts’, this discipline was excluded
from the analysis. As a result of the above discussed amendments, six disciplines were
used for the analysis, which were ‘Social Sciences’, ‘Architecture and Engineering’,
‘Computing and Information Technology’, ‘Medicine, Dentistry, and Veterinary’,
‘Agriculture’, and ‘Science’.
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A chi-square test revealed that there was a significant association between ‘plural
activities’ and academic disciplines X2(15, 336) = 49.96, p=0.000. As illustrated in Table
8.5, the majority of academics in ‘Engineering and Architecture’ disciplines were triple
role entrepreneurs (48.5%). In-depth interviews revealed that several academics from these
disciplines established joint venture research labs/centres with industry, and academic
owned companies in their specialities such as construction, textile, food processing,
environmental engineering, architecture, consultancy, hardware, and software/computer
engineering. Furthermore, it was found that they engaged in interdisciplinary research with
academics in other faculties. For example, in-depth interviews revealed that academics in
the Faculties of Engineering collaborated with those in Faculties of Medicine to produce
low cost medical equipment (e.g. to develop a non-invasive blood glucose measuring
technique, and low cost surgical tools etc). Additionally, academics in the Faculty of
Architecture (particularly Town and Country Planning Division) were reported to
collaborate with those in Social sciences, Archaeology, and Agriculture in rural
development projects. These interdisciplinary projects had given academics additional
entrepreneurial opportunities, which enabled them to extract value from their limited
opportunity environment.
Similarly, a relatively high proportion of academics in Social Sciences (38.9%)
Computing, and Information Technology (38.9%), and Agriculture (37.3%) disciplines had
triple roles when compared with those in Pure Sciences (i.e. 16.2%). Even though the
literature (e.g. Laukkanen 2003) has argued that academics in Social Sciences have
comparatively less opportunities for entrepreneurship, in-depth interviews revealed that
they had overcome this barrier by carrying out interdisciplinary applied research. For
example, academics in the Social Sciences had carried out large scale projects in
collaboration with those in the Faculties of Engineering, Architecture, and Agriculture. In
these projects, academics in Social sciences had provided services such as assessing
economic, environmental, employment, and youth impacts, developing marketing
strategies, and carrying out project planning. Furthermore, it was reported that some
academics carried out rural development projects with Non-Governmental Organizations,
which gave them access to international funds.
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Table 8.5: The Discipline of the Academic
Social Sciences
Architecture,
Engineering
Computing, Information Technology
Medicine, Dental,
Veterinary
Agriculture Science Total
Non- entrepreneurs
Count 4 12 5 5 7 8 41
Expected Count
6.6 11.8 2.2 2.2 9.2 9.0 41.0
% within Academics
9.8% 29.3% 12.2% 12.2% 17.1% 19.5% 100%
% within discipline
7.4% 12.4% 27.8% 27.8% 9.3% 10.8% 12.2%
Single role academic entrepreneu
Count 5 4 5 3 3 10 30
Expected Count
4.8 8.7 1.6 1.6 6.7 6.6 30.0
% within Academics
16.7% 13.3% 16.7% 10.0% 10.0% 33.3% 100%
% within discipline
9.3% 4.1% 27.8% 16.7% 4.0% 13.5% 8.9%
Double role academic entrepreneurs
Count 24 34 1 6 37 44 146
Expected Count
23.5 42.1 7.8 7.8 32.6 32.2 146.0
% within Academics
16.4% 23.3% .7% 4.1% 25.3% 30.1% 100%
% within discipline
44.4% 35.1% 5.6% 33.3% 49.3% 59.5% 43.5%
Triple role academic entrepreneurs
Count 21 47 7 4 28 12 119
Expected Count
19.1 34.4 6.4 6.4 26.6 26.2 119.0
% within Academics
17.6% 39.5% 5.9% 3.4% 23.5% 10.1% 100%
% within discipline
38.9% 48.5% 38.9% 22.2% 37.3% 16.2% 35.4%
Total Count 54 97 18 18 75 74 336
Expected Count
54.0 97.0 18.0 18.0 75.0 74.0 336.0
% within Academics
16.1% 28.9% 5.4% 5.4% 22.3% 22.0% 100%
% within discipline
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100%
Additionally, academics in the Social Sciences had established consultancy firms, research
centres, and companies directly or indirectly related to their specialities (e.g. marketing
services, business consultancy, employee training, economic assessment services, rural
development services, entrepreneurial education and training, book publishing companies,
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book stores, and community service centres). It was also revealed that the formation of
companies in the Social Science disciplines required less initial capital than some
Engineering disciplines, which also explained their high entrepreneurial activity. Similarly,
companies formed by academics in the discipline of Computing, and Information
Technology (such as consultancy, web based, software, and IT service oriented etc) were
also reported to need low initial capital. These results support the findings of Oakey
(1995), who argued that initial funding requirements vary across high technology sectors.
Those who specialised in Agriculture discipline had established university farms, sales
centres for farming products, and consultancy firms. The carrying out of interdisciplinary
projects was prominent in this discipline as well. This was mainly due to the departmental
composition of the Faculties of Agriculture. These departments were Agricultural
Engineering, Food science, Economics and Business Management, as well as Crop,
Animal, and Soil Sciences etc. It was apparent that most of the consultancy carried out by
them were rural development projects, in which experts from different departments worked
together to provide a holistic solutions. Some of these different aspects in one major
project were introducing new farming techniques, conducting farmer training programmes
(by Crop and Animal Science Departments), developing the entrepreneurial skills of
farmers (by Economics and Business Management Department), improving farming
equipment (by Agricultural Engineering Department), providing access to water (by
Agricultural Engineering and Soil Science Departments), and introducing new high
yielding crop varieties and animal breeds (Crop and Animal Science Departments).
The majority of academics in Medicine and Dentistry were reported to carry out private
practices in large scale private hospitals. They had various opportunities to work in private
practices, since a well developed system with several private hospitals, was available in Sri
Lanka. Hence, even though private practice was an activity additional to their normal
academic duties, and generated very high additional income (more than 10 times of their
salary as a lecturer), it was questionable to what extent this involvement should be
considered an entrepreneurial activity. It appeared that doctors were simply practicing their
speciality, which does not seem to qualify as entrepreneurship. However, in-depth
interviews also revealed that a few doctors established their own companies. While some
of these companies such as hospitals, pharmacies, and the development and sale of medical
equipment were related to their profession, other companies were not related to their
specialities (e.g. real-estate, food processing, and automobile sale). They mentioned that
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their role was mainly limited to providing funding and advice to someone (or a group) who
was given the responsibility of establishing and operating these businesses. The reason for
this lack of involvement by doctors was that they enjoyed treating patients, and
particularly, carrying out challenging surgery, but not establishing or managing businesses.
For them the establishment of companies was an investment, and hence, they hired
someone who would perform the company formation. As illustrated above, even though
there were similarities between the entrepreneurial activity of doctors and academics in
other disciplines, the nature of work of doctors implied that their entrepreneurial behaviour
was different from others. An investigation of the entrepreneurial behaviours of doctors
may be a future research avenue.
The majority of academics in pure sciences were double role academic entrepreneurs
(59.5%). In-depth interviews revealed that research activities in pure sciences had a little
scope for commercialization. Hence, they were interested in acquiring funding for basic
research which, in turn, had positive impacts on teaching, since they had recruited research
students and sustained improved lab facilities. These results are in agreement with Mowery
and Sampat (2005), who also showed that academics in pure sciences have fewer
opportunities for company creation than those in applied disciplines. As discussed above,
while ‘plural activities’ statistically differ depending on the discipline, a similarity between
disciplines was the carrying out of interdisciplinary projects in collaboration with
academics from different disciplines, which enabled academics to extract value from their
constrained environments. This strategy was also found to be useful in overcoming the
dearth of entrepreneurial opportunities in some disciplines such as the Social Sciences.
8.2.4. The Relationship between the Educational Level, and ‘Plural activities’, of
Academic Entrepreneurs
A chi-square test revealed no significant association between the level of education, and
the ‘plural activities’, of academic entrepreneurs X2 (4, 302) = 4.57, p=0.334>0.05 (Table
8.6). However, there was a significant difference between the level of education of non-
entrepreneurs and entrepreneurs X2 (6, 345) = 13.13, p=0.041<0.05, where when compared
with non entrepreneurs (46.5%), a higher percentage of double (62.7%) and triple role
(64.8%) entrepreneurs had a PhD.
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Table 8.6: The Level of Education of the Academic
Only
Bachelors Bachelors
and Masters
Bachelors &/or Masters & Doctorate Total
Non-Entrepreneurs
Count 8 15 20 43
% within Academics
18.6% 34.9% 46.5% 100.0%
% within Level of education
29.6% 13.5% 9.7% 12.5%
Single Role A.E
Count 3 13 14 30
% within Academics
10.0% 43.3% 46.7% 100.0%
% within Level of education
11.1% 11.7% 6.8% 8.7%
Double Role A.E
Count 11 45 94 150
% within Academics
7.3% 30.0% 62.7% 100.0%
% within Level of education
40.7% 40.5% 45.4% 43.5%
Triple Role A.E
Count 5 38 79 122
% within Academics
4.1% 31.1% 64.8% 100.0%
% within Level of education
18.5% 34.2% 38.2% 35.4%
Total Count 27 111 207 345
% within Academics
7.8% 32.2% 60.0% 100.0%
% within Level of education
100.0% 100.0% 100.0% 100.0%
8.2.5. The Relationship between the Business Management and Entrepreneurial
Knowledge and Skills, and ‘Plural activities’, of Academic Entrepreneurs
Academics were asked to rate their level of business management and entrepreneurial
knowledge and skills. A chi-square test revealed a significant association between the
claimed business management knowledge and skills, and the ‘plural activities’, of
academics X2 (6, 278) = 24.650, p=0.00<0.05. The business management knowledge and
skills of the majority of triple role entrepreneurs (57%) were ‘high’, whilst those of their
single role counterparts (67%) were ‘low’. Double role academics were between single and
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triple role colleagues, where 41.3% had ‘high’, and 43.5% had ‘low’, business
management knowledge and skills (Table 8.7).
Table 8.7: The Business Management Knowledge and Skills of the Academic
Very low Low High
Very high Total
Single Role A.E
Count 1 18 3 4 26
% within Academics 3.8% 69.2% 11.5% 15.4% 100.0%
% within Business and Management Skills 7.7% 17.6% 2.3% 11.4% 9.4%
Double Role A.E
Count 5 57 60 16 138
% within Academics 3.6% 41.3% 43.5% 11.6% 100.0%
% within Business and Management Skills
38.5% 55.9% 46.9% 45.7% 49.6%
Triple Role A.E
Count 7 27 65 15 114
% within Academics 6.1% 23.7% 57.0% 13.2% 100.0%
% within Business and Management Skills
53.8% 26.5% 50.8% 42.9% 41.0%
Total
Count 13 102 128 35 278
% within Academics 4.7% 36.7% 46.0% 12.6% 100.0%
% within Business and Management Skills
100.0% 100.0% 100.0% 100.0% 100.0%
Count 4.7% 36.7% 46.0% 12.6% 100.0%
Similarly, there was an association between the entrepreneurial skills, and ‘plural
activities’, of academics entrepreneurs, X2 (6, 276) = 34.43, p=0.000<0.05. The majority of
triple role entrepreneurs (59.6%) had ‘high’ entrepreneurial skills, while that of their single
role counterparts (68%) had ‘low’ entrepreneurial skills. There were two major groups
with respect to double role entrepreneurs, where 37.2% had ‘high’, and 42.3% had ‘low’,
entrepreneurial skills (Table 8.8). It was not possible to statistically test the difference
between entrepreneurs and non-entrepreneurs since none of the non- entrepreneurs had
‘very high’ business management or entrepreneurial knowledge and skills. The majority of
non-entrepreneurs were reported to have ‘low’ business management (69.7%), and
entrepreneurial (74.4%), knowledge and skills. Therefore, based on percentage values, it
was apparent that entrepreneurs have ‘higher’ business management and entrepreneurial
knowledge and skills than non-entrepreneurs.
In-depth interviews further confirmed the above results, by revealing that one of the major
reasons why single role academics were reluctant to diversify into ‘highly entrepreneurial’
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activities (e.g. company creation) was their lack of business management and
entrepreneurial knowledge and skills. The above analysis seems to suggest that academics
who have high business management and entrepreneurial knowledge and skills diversify
into all three entrepreneurial activities, while those who have low levels of these
knowledge and skills diversify only into teaching related entrepreneurial activities or do
not engage in any entrepreneurial activity. These results support the literature that has
argued that the level of business management (Dickson et al., 1998, Franklin et al., 2001),
and entrepreneurial (McMullan and Vesper, 1987, Henderson et al., 1998, Mowery et al.,
2002), knowledge and skills of academics influence academic entrepreneurship. On the
other hand, as discussed in the Section 6.3.2 of Chapter Six, it was also evident that
carrying out different entrepreneurial activities (e.g. triple role and double role activities)
improved their business management and entrepreneurial knowledge and skills. Hence, it
was apparent that, while the level of business management and entrepreneurial knowledge
and skills affected the ‘plural activity’ of academic entrepreneurs, causality can also run in
the opposite direction (i.e. the type of ‘plural activity’ determines the level of business
management and entrepreneurial knowledge and skills).
Table 8.8: The Effect of Entrepreneurial Knowledge and Skills of the Academic
Very low Low High Very high Total
Single Role A.E
Count 1 17 4 3 25 % within Academics 4.0% 68.0% 16.0% 12.0% 100.0% % within entrepreneurial skills 4.2% 18.1% 3.3% 8.6% 9.1%
Double Role A.E
Count 12 58 51 16 137 % within Academics 8.8% 42.3% 37.2% 11.7% 100.0% % within entrepreneurial skills 50.0% 61.7% 41.5% 45.7% 49.6%
Triple Role A.E
Count 11 19 68 16 114 % within Academics 9.6% 16.7% 59.6% 14.0% 100.0% % within entrepreneurial skills 45.8% 20.2% 55.3% 45.7% 41.3%
Total Count 24 94 123 35 276 % within Academics 8.7% 34.1% 44.6% 12.7% 100.0% % within entrepreneurial skills 100.0% 100.0% 100.0% 100.0% 100.0%
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8.2.6. The Relationship between the Social Network and Skills, and ‘Plural activities’,
of Academic Entrepreneurs
In order to measure the strength of the social network of respondents, academics were
asked to state to what extent they agreed or disagreed with following three statements, on a
four point Likert scale.
1. I have strong personal contacts with industrial partners,
2. I have access to industrial partners, through some contacts who have strong and direct
contacts with industry,
3. I am a member of a team that has strong contacts with the industry
Internal consistency and unidimentionality were tested to assess the possibility of
generating a single score (by aggregating the ratings of three statements) to represent the
strength of social network. Cronbach's Alpha for these three items was 0.853, which
indicated that there was a high level of internal consistency among three different items.
The unidimentionality of the scale was assessed with factor analysis. It was revealed that
the eigen value for the first component was larger than the second component (2.333 vs
.351), and the first component explained 77.8% of variance (Table 8.9). These results
confirmed the unidimensionality of the scale. Therefore, by averaging individual ratings of
the above stated three variables, one variable was created to represent the strength of social
networking of academics.
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Table 8.9: Test for Unidimentionality
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of
Variance Cumulative
% Total % of
Variance Cumulative
%
1 2.333 77.770 77.770 2.333 77.770 77.770
2 .351 11.704 89.474
3 .316 10.526 100.000 Extraction Method: Principal Component Analysis.
Component Matrixa
Component
1
I have very strong personal contacts with industrial partners .877
I have access to industrial partners through some of my contacts who have strong and direct contacts with industry
.890
I am a member of a team (s) that has very good contacts with industry .879
Extraction Method: Principal Component Analysis.
a. 1 components extracted.
An ANOVA test revealed that there was a significant association between the ‘plural
activities’, and strength of social network, of academics F (2, 395) = 34.101, 0.000<0.05.
A Tukey’s Posthoc test revealed that the strength of the social network of triple role
academic entrepreneurs (M= 3.2, SD=.64) was significantly higher than their single role
(M=2.4, SD=.65) and double role counterparts (M=2.7, SD=.63). Not surprisingly, it was
also evident that the strength of social networking of non-entrepreneurs (M=2.2, SD=.73)
was significantly less than entrepreneurs F (3, 334) = 28.322, 0.000<0.05. In-depth
interviews further confirmed these findings by revealing that a lack of strong contacts with
industry was a major barrier to single role entrepreneurs. Hence, it seemed that academics
who had stronger social networks diversified into a higher number of different
entrepreneurial activities (i.e. triple role), while those lacking such contacts diversified
only into teaching related entrepreneurial activities (i.e. single role) or did not engage in
any entrepreneurial activity. These findings supported the literature that has argued that the
strength of social network of academics influence academic entrepreneurship (Siegel et al.,
2007). On the other hand, Section 6.3.1 of Chapter Six has revealed that diversifying into
different activities enabled entrepreneurial academics (e.g. triple role and double role) to
develop a strong and diverse network of contacts. This implied that the ‘plural activities’ of
academic entrepreneurs influenced the strength of their social networks. Therefore, the
findings of this Section suggest that the causality between the social network, and ‘plural
181
activities’, of academics was present in both directions (i.e. the strength of social network
affect on ‘plural activity’ and vice versa).
The above analysis on the association between ‘plural activities’, and the personal
characteristics, of academics revealed that six out of eight personal characteristics had a
significant association with the ‘plural activities’ of academic entrepreneurs operating in
the resource constrained environment of Sri Lanka. These were position, gender, academic
discipline, business management and entrepreneurial knowledge and skills, and the
strength of social networks. Hence, in terms of these six characteristics, the Hypothesis 3.1,
which stated that there would be no relationship between the ‘plural activity’ of academic
entrepreneurs and their personal characteristics, was rejected. The two personal
characteristics which were not significantly associated with ‘plural activities’ were the age
and level of education of academics.
8.3. Analysis: The Relative Influence of Meso and Micro Level Factors on the ‘Plural
activities’ of Academic Entrepreneurs: A Multi-level Analysis
As discussed in the Section 8.1 of this Chapter, in addition to the personal characteristics
of academics, meso/university level factors might also influence ‘plural activities’. Hence,
this Section of the chapter has analysed whether it was micro- or meso- level variables that
had a higher influence on the propensity of academics to adopt specific ‘plural activity’
types. The dependent variable of this analysis was the ‘plural activities’ of academic
entrepreneurs, which was a nominal variable with three discrete categories (i.e. single role,
double role, and triple role). Micro/individual level independent variables were the
position, gender, academic discipline, business management and entrepreneurial
knowledge and skills, and strength of social network of academics. Meso university level
independent variables were the research strength, commercial orientation, and the resource
status of universities. Since independent variables were at two levels (i.e. micro and meso
levels), a multilevel analysis (using MLwiN software) was performed.
Initially the net influence of micro and meso level variables on the ‘plural activities’ of
academic entrepreneurs was investigated. This analysis revealed that the ‘plural activities’
of academics was influenced only by the individual level variables but not by the
university level variables (v0k = 0.000(0.000). Hence, the Hypothesis 3.2, which stated
that there would be no difference between the influence of micro and meso level factors on
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academic propensity to adopt specific ‘plural activity’ types, was rejected. This finding
was not surprising, since none of the universities in Sri Lanka had a policy on academic
entrepreneurship. Hence, as discussed in Section 7.2.3 of Chapter Seven of this thesis,
academic entrepreneurship was solely driven by academics. Furthermore, since all the Sri
Lankan universities suffered from resource scarcity, there might not be a significant
difference between universities.
8.4. Analysis: The Relationship between the Perceived Quality of Universities and
‘Plural Activities’
Even though it was apparent in the previous Section that there was no significant (real)
influence of universities on ‘plural activities’, the perception of academics regarding the
environment might influence their ‘plural activities’. Hence, this Section investigates
whether there is a statistical association between ‘plural activities’ and the perception of
academics regarding the quality of their universities. In order to investigate the perception
of academics, they were asked to rate the quality of five aspects of their universities. These
five aspects were the ‘research strength of university’, ‘research strength of department’,
‘commercial orientation of university’, ‘commercial orientation of department’, and
‘resource status of university’.
ANOVA tests revealed that the perceived quality of four of five factors significantly
associated with the ‘plural activities’ of academic entrepreneurs (Table 8.10). Triple role
academic entrepreneurs, when compared with single and double role colleagues, rated the
‘research strength of their department’, ‘commercial orientation of their universities’,
‘commercial orientation of their departments’, and ‘resource status of their universities’
more highly. Hence, in terms of these four characteristics of universities, the Hypothesis
3.3, which stated that, there would be no relationship between the ‘plural activity’ of
academic entrepreneurs and their perception of university quality, was rejected.
Since it was revealed that the ‘plural activities’ of academics was not influenced by the
objective measures of the qualities of their universities, the above identified significant
relationships must be only due to the perception of academics. Therefore, these results
support the literature which has stated that the perception of entrepreneurs regarding their
environment shapes their entrepreneurial behaviours (Stevenson and Jarillo, 1990, Binks
and Vale, 1990).
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Table 8.10: The Effect of Perceived Quality of University and Department
Meso level factors F statics p Mean rank Single role
Double role
Triple role
1. Research strength of the department 10.1 (2, 286) .006 101.78 142.95 153.89 2. Research strength of the university 1.97(2, 285) .373 125.33 142.22 148.06 3. The commercial orientation of department
6.45 (2, 279) .040 113.63 135.18 151.60
4. The commercial orientation of university
9.27 (2, 283) .010 133.84 129.97 158.38
5. The resources status of the university 6.30 (2, 284) .043 135.76 132.73 155.94
8.5. Analysis: An Aggregated Model: Factors Affecting the ‘Plural Activities’ of
Academic Entrepreneurs
It was initially decided to use a multilevel analysis to investigate how each micro and meso
level variable influenced the ‘plural activities’ of academic entrepreneurs. However, since
it was found in the Section 8.3 that only micro level factors had an effect, it was apparent
that a multilevel analysis was not appropriate. Hence, it was decided to perform a
regression analysis to examine how each micro level independent variable influenced the
‘plural activities’ of academic entrepreneurs. Thus, the personal characteristics of academic
entrepreneurs were used as independent variables. Additionally, since there was no
significant (real) variation between universities, any variation in terms of the perceived
quality of universities was considered solely attributed to individuals (i.e. their
perceptions) (See the Section 8.4 of this chapter for the relevant analysis). Therefore, in
addition to personal characteristics, the perceived qualities of their universities were also
used as independent variables.
Accordingly, the dependent variable of this aggregated model was the ‘plural activities’ of
academic entrepreneurs, which was a nominal variable with three discrete categories.
Micro level variables that were found to have a significant association with the ‘plural
activities’ of academic entrepreneurs (in previous analyses presented in Sections 8.2 and
8.4 of this Chapter) were used as independent variables. There were ten independent
variables; namely, the ‘gender’, ‘business and management knowledge and skills’,
‘entrepreneurial knowledge and skills’, ‘position’, ‘academic discipline’, ‘the strength of
social network’, as well as ‘perceived quality of the commercial orientation of department’,
‘perceived quality of the commercial orientation of university’, ‘perceived quality of the
research strength of department’, and ‘perceived quality of the resource status of
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university’. As illustrated in Table 8.11, some of these independent variables were
categorical, while others were continuous. The literature has suggested the use of a
discriminant or multinomial logistic regression for an analysis with a categorical
independent variable and a mix of continuous and categorical independent variables (Bulla
and Donner 1987)
Discriminant analysis uses linear functions, while multinomial logistic regression uses
nonlinear functions (since it applies maximum likelihood estimates) (Cohen et al., 2003).
Therefore, discriminant analysis requires meeting normality and homoscedacity
assumptions, whilst multinomial logistic regression is free from these restrictive
assumptions (Reyment et al., 1984, Manly, 1994, Howitt, 2008, Tabachnick and Fidell,
2001, Press and Wilson, 1978). Furthermore, discriminant analysis is also reported to be
sensitive to uneven group sizes (i.e. number of respondents who have adopted each ‘plural
activity’ type) (Reyment et al., 1984, Manly, 1994). In contrast, multinomial logistic
regression analysis is not sensitive to uneven group sizes, and could be used for relatively
small sample sizes as long as each group size is larger than the number of predictor
variables (Long and Freese, 2001). Considering the above stated comparison, this study
decided to use a multinomial logistic regression analysis since the group sizes of the
dependent variable were uneven (i.e. single role – 30, double role – 150, triple role- 122)
and some independent variables did not meet normality tests.
The model fitting statistics revealed that the model is statistically significant X2(30) =
113.27, p=0.000<0.05. Instead of R2 in a linear regression analysis (which explained the
extent to which the variance of dependent variable is explained by independent variables),
the literature on multinomial logistic regression analysis has recommended the calculation
of a classification accuracy rate and compare it with a proportional by chance accuracy
criterion (Pampel, 2000). In this model, the classification accuracy rate was 70.6%, and it
was greater than the proportional by chance accuracy criterion of the model, which was
53.09%. Hence, the model was acceptable. Furthermore, the standard errors of each of the
10 independent variables were less than 2 (See Appendices 8.1 and 8.2). This indicated
that there was no multicollinearity. Moreover, the standard residual of each variable being
less than 2 also indicate that there were no outliers, which is not surprising considering the
nature of independent variable being either categorical or ordinal with less variability
(Field, 2005). Additionally, the ratio between the number of valid cases and the number of
independent variables of this model was 24:1, which was almost equal to the preferred
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ratio of 20:1, which further suggested that this model was suitable for the intended analysis
(Leech et al., 2005). Since multinomial logistic regression is free from normality and
homoscedacity assumptions, these were not tested (Reyment et al., 1984, Manly, 1994,
Howitt, 2008, Tabachnick and Fidell, 2001, Press and Wilson, 1978).
Table 8.11: Independent and Dependent Variables: Multinomial Logistic Regression
Variable Description (if categorical) N Marginal Percentage
Dependent Variable
Academic entrepreneurs Single role academic entrepreneur 21 8.8%
Double role academic entrepreneurs 116 48.7%
Triple role academic entrepreneur 101 42.4%
Independent Variables
1. Gender Male 181 76.1%
Female 57 23.9%
2. Business and Management Knowledge and Skills
Low 147 61.8%
High 91 38.2%
3. Entrepreneurial Knowledge and Skills
Low 103 43.3%
High 135 56.7%
4. Position of Academics Lecturer 72 30.3%
Senior Lecturer 124 52.1%
Professor 42 17.6%
5. Academic Discipline Social Sciences 41 17.2%
Architecture, Engineering 73 30.7%
Computing, Information Technology
10 4.2%
Medicine, Dentistry, Veterinary 11 4.6%
Agriculture 56 23.5%
Science 47 19.7%
6. Strength of Social Network
Ordinal variables – 1- very low, 2- low, 3- high, 4-very high
7. Perceived quality of the commercial orientation of department
8. Perceived quality of the commercial orientation of university
9. Perceived quality of the research strength of department
10. Perceived quality of the resource status of university
Valid 238 100.0%
Missing 107
Total 345
Subpopulation 222a
a. The dependent variable has only one value observed in 218 (98.2%) subpopulations. The model revealed that six of ten independent variables significantly affect the propensity
of academics to adopt specific ‘plural activity’ types. These factors were ‘gender’ (X2(2,
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238) = 10.338, p=0.006<0.05), ‘academic discipline’ (X2(10, 238) = 18.276, p=
0.050<0.05), ‘business management knowledge and skills’(X2(2, 238) = 6.906,
p=0.032<0.05), ‘entrepreneurial knowledge and skills’ (X2(2, 238) = 15.446,
p=0.000<0.05), ‘the strength of social network’ (X2(2, 238) = 21.309, p=0.000<0.05) and
‘the perceived quality of the commercial orientation of department’ (X2(2, 238) = 7.445,
p=0.024<0.05) (Table 8.12).
Table 8.12: Likelihood Ratio Tests
Effect
Model Fitting Criteria
Likelihood Ratio Tests
-2 Log Likelihood of Reduced Model
Chi-Square Df Sig.
Intercept 3.255E2 .000 0 .
1. Gender 335.872 10.338 2 .006
2. Position 331.017 5.483 4 .241
3. Academic Discipline 343.810 18.276 10 .050
4. Business Management Knowledge and Skills
332.441 6.906 2 .032
5. Entrepreneurial Knowledge and Skills
340.981 15.446 2 .000
6. Strength of Social Network 346.843 21.309 2 .000
7. Perceived Quality of the Commercial Orientation of department
332.980 7.445 2 .024
8. Perceived Quality of the Commercial Orientation of University
330.742 5.208 2 .074
9. Perceived Quality of the Research Strength of Department
327.907 2.372 2 .305
10. Perceived Quality of Resource Status of University
326.787 1.252 2 .535
The chi-square statistic is the difference in -2 log-likelihoods between the final model and a reduced model.
The reduced model is formed by omitting an effect from the final model. The Null-Hypothesis is that all
parameters of that effect are 0.
a. This reduced model is equivalent to the final model because omitting the effect does not increase the
degrees of freedom.
Parameter estimates were calculated to examine how these factors affect two types of
propensities; namely, the propensity to diversify into company creation in addition to
carrying out teaching and research related entrepreneurial activities (i.e. triple role vs.
double role) and the propensity to diversify into research related entrepreneurial activities
in addition to carrying out teaching related entrepreneurial activities (i.e. single role vs.
double role).
Parameter estimates suggested that the propensity to diversify into company creation, in
addition to carrying out teaching and research related entrepreneurial activities (i.e. triple
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role vs. double role), increased when the academic was a male than for a female (i.e. 4
times higher), and when the academic was a senior lecturer than a lecturer (i.e. 2 times
higher). Furthermore, this propensity increased when the academic specialised in
‘Computing and Information Technology’ (i.e. increased by 32 times) or ‘Agriculture’ (i.e.
by 4 times) than ‘Pure Sciences’. Additionally, this propensity was positively influenced
by the strength of social network (i.e. when the strength was increased by 1 unit the
propensity increased by 3 times), as well as entrepreneurial skills (i.e. propensity decreased
by 72.5% when skills were ‘low’ than ‘high’) and business management skills (i.e.
propensity decreased by 61.3 % when skills were ‘low’ than ‘high’) (Please refer to
Appendix 8.1 for parameter estimates).
Similarly, the propensity to diversify into research related entrepreneurial activities in
addition to carrying out teaching related entrepreneurial activities (i.e. single role vs.
double role) was positively influenced by the strength of social network of academics
(when the strength of social network of academics increased by one unit, propensity
increased by 3 times) as well as their perception of the commercial orientation of
department (when the perceived quality of the commercial orientation of department
increased by one unit, propensity increased by 4 times) (See Appendix 8.2 for parameter
estimates).
8.6. Analysis: University, Industry, and Government Interactions
8.6.1. Reasons for University Industry Interactions
Primary qualitative data gathered from in-depth interviews, as well as secondary data
collected from various policy documents, were analysed to understand how university,
industry, and government in the resource constrained environment of Sri Lanka interact
with each other. These qualitative data suggested that industry and universities in Sri
Lanka had a mutual dependence, which stimulated university-industry interactions. For
instance, in-depth interviews revealed that, even though the majority of Sri Lankan firms
were becoming increasingly interested in improving their product and services through
innovation, they lacked a strong research and development base. Hence, they consulted
academics to carry out research and development activities and to train their staff.
Furthermore, qualitative data analysis indicated that some small and medium enterprises
sought the expert advice of academics to solve problems faced by them in day to day
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operations (particularly engineering related issues). It was also reported that there were a
small number of Sri Lankan companies, who had research and development departments,
but these companies lacked capabilities in some specialized fields. Hence, they established
joint-research labs and engaged in different forms of collaboration (e.g. consultancy, joint
research projects, and employee training) with universities in order to make use of
university’s human resource capital.
These results on reasons why Sri Lankan industry collaborated with universities are in line
with the findings of research carried out in developed countries. For example, Meyer-
Krahmer and Schmoch (1998) have highlighted that capitalising on the knowledge and
skills of academics and receiving access to the laboratory facilities of universities were
some of the benefits industry received by interacting with universities. Hence, even though
the literature argued that an industry with a weak research and development base (e.g. Eun
et al 2006; Adesola 1991) may hamper the possibilities of university- industry interactions,
the above results seem to disagree with this view. However, differences between a strong
and a weak industry (in terms of research and development capabilities) may exist in terms
of the type of knowledge exchanged. For instance, it was found that, due to a lack of
research capacity of Sri Lankan industry, in most instances, the interactions between
university and industry did not involve advanced scientific knowledge.
Some reasons why academics collaborated with industry were the need to earn additional
personal and research income, to successfully carry out normal academic duties (Please
refer to Section 9.3 of Chapter 9 for more details), to improve the resource status of
universities, to strengthen the networks of contacts, to learn about new trends in industry,
and to develop new knowledge and skills. These results also corroborate the findings of
research conducted in developed countries (e.g. Siegel et al., 2004, D’Este and Patel,
2007). Hence, the above analysis has suggested that the reasons why academics and
industry in the resource constrained environment of Sri Lanka interact with each other are
more or less similar to those of developed countries.
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8.6.2. The Role of Government
Even though it was revealed in the previous Section that university and industry in Sri
Lanka actively interacted with each other, it was evident that these interactions were
different from developed countries in terms of how they were mediated. For example, it
was evident that Sri Lanka does not have a university or government policy, supportive
mechanisms, or formal institutional infrastructure to promote university-industry
interactions (at the time data was collected). As a result, university industry interactions
were initiated and carried out by individuals. Academics stated that, in most of the
instances, they had approached industry to propose possible collaborations. Therefore,
these interactions seemed to be scattered and random. It was apparent that due to these
reasons, it was not possible to have major investments (e.g. a science park), or to generate
huge economic benefits from, academic entrepreneurship. These findings corroborate
previous studies carried out in Sri Lanka (e.g. Esham 2008; Kumarasena 2007), which
have highlighted the need to establish infrastructure and institutional mechanisms to
support university industry interactions.
Furthermore, as a result of this dearth of formal supportive mechanisms, carrying out
entrepreneurial activities during the early stages of academic careers was reported to be
very difficult. Academics stated that they had to gradually develop a reputation by initially
engaging in teaching related entrepreneurial activities before diversifying into research
related entrepreneurial activities or company creation. Hence, academics believed that, the
creation of institutional frameworks and supportive mechanisms for university-industry
interactions would improve the extent of collaborations.
In addition to a lack of formal supportive mechanisms, some government policies were
reported to discourage academic entrepreneurship. For instance, the Sri Lankan
government policy does not allow the formation of university owned profit oriented
companies or engagement in competitive bidding to secure consultancy projects. Hence,
academics must arrange alternative mechanisms to carry out these entrepreneurial
activities. However, such initiatives were subject to government audits, as a result of which
some academics were discouraged from carrying out entrepreneurial activities. Academics
stated that they found it irritating to reply to government audits and inquiries, since these
processes implied that academics were carrying out illegal activities. Furthermore,
responding to government audits was reported to be time consuming.
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Hence, it was apparent that, even though universities and industry mutually benefit from
academic entrepreneurship, the absence of supportive mechanisms hindered potential
collaborations. Accordingly, the above discussion suggests that the nature of involvement
of government was the major difference between the interactions described in the Triple
Helix models and that of the resource constrained environment of Sri Lanka. Thus, the
Hypothesis 3.4, which stated that, interactions between university, industry and
government in a resource constrained environment would not differ from those in a
developed environment, was rejected.
8.7. Chapter Summary
This chapter has presented an analysis of the third of the four objectives of this thesis,
which was to investigate how multilevel causal factors affect the ‘plural activities’ of
academic entrepreneurs operating in the resource constrained environment of Sri Lanka. It
was evident that the personal characteristics of academic entrepreneurs, but not the
qualities of their universities, affected their ‘plural activities’. These personal
characteristics were the ‘gender’, ‘position’, ‘academic discipline’, ‘business management
and entrepreneurial knowledge and skills’, and ‘the strength of social network’ of
academic entrepreneurs.
It was apparent that male academics have a relatively high tendency to engage in a wider
array of entrepreneurial activities than female academics. Although not prominent, some
female academics have also diversified into all three entrepreneurial activities (i.e. teaching
and research related entrepreneurial activities and company creation). Furthermore, it was
evident that, when compared with lecturers, professors have a higher tendency to carry out
all three entrepreneurial activities. While the statistical analysis revealed that, position
influenced ‘plural activities’, qualitative data analysis suggested that causality occurs in
both the directions (i.e. position affects ‘plural activity’ and vice versa). This was due to
the finding that the diversification into all three activities positively influenced academic
promotions.
Furthermore, statistical analysis revealed that, academics specialising in applied
disciplines, tended to diversify into all three entrepreneurial activities, while those engaged
in pure sciences had less opportunities to perform company creation. Additionally, it was
also evident that academics in different disciplines tend to collaborate to carry out
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interdisciplinary projects, which enabled them to extract value from their constrained
environments. This strategy was also found to be useful in overcoming the dearth of
opportunities for entrepreneurship in some academic disciplines such as Social Sciences.
Moreover, statistical analysis revealed that academics with ‘high’ business management
and entrepreneurial knowledge and skills have a higher propensity to diversify into all
three activities than those with ‘low’ levels of these skills. While qualitative data analysis
further confirmed this, it also suggested that, causality may run in the opposite direction as
well (i.e. the type of ‘plural activity’ may determine the level of business management and
entrepreneurial knowledge and skills). This was due to the finding that carrying out a
higher number of different entrepreneurial activities (i.e. triple role) improved the business
management and entrepreneurial knowledge and skills of academics.
Similarly, both statistical and qualitative data analyses revealed that the strength of the
social network of academics influenced ‘plural activities’. Additionally, qualitative data
analysis revealed that causality might occur in the opposite direction as well (i.e. the
‘plural activities’ may influence the strength of social network). Whilst academics with
strong social networks had a high propensity to diversify into all three entrepreneurial
activities, this high level of diversification was found to enable triple role and double role
academics to develop a strong and diverse network of contacts.
This chapter also revealed that industry and universities in Sri Lanka had a mutual
dependence, which stimulated university-industry interactions. Sri Lankan companies that
lacked research and development capabilities tended to seek academic expertise to carry
out research and development activities for them, to train staff, to get problems faced by
them in day to day operations solved, and to overcome technical deficiencies. On the other
hand, academics collaborated with industry due to their need to earn additional personal
and research income, to successfully carry out normal academic duties, to improve the
resource status of universities, to strengthen the networks of contacts, to learn about new
trends in the industry, and to develop new knowledge and skills.
Even though universities and industry seem to be inclined to collaborate due to the above
discussed mutual benefits, Sri Lanka did not have a university or government policy,
supportive mechanisms, or formal institutional infrastructure for university-industry
interactions. Therefore, it was evident that these interactions were driven by individuals,
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and thus, were scattered and isolated. This lack of intervention by Sri Lankan government
was reported to be due to other government priorities linked to poverty. Hence, it seemed
that the way government contributed to university-industry interactions in the resource
constrained environment of Sri Lanka is different from the active involvement of
government elaborated in Triple Helix models. These results led to a conclusion that
interactions between university, industry and the government in this resource constrained
environment of Sri Lanka differ from those in developed countries.
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Chapter 9: The Impacts of Academic Entrepreneurial Engagement in a Resource
Constrained Environment
A considerable amount of literature has argued that academic entrepreneurship may have a
myriad of impacts on normal academic duties (Dasgupta and David, 1994, Rosenberg and
Nelson, 1994) and wider national economy (Pattyn, 2006, Etzkowitz, 1998). However,
most of these previous studies have been carried out in developed countries, and so far,
there has been little discussion about the impacts of academic entrepreneurship in
developing, resource constrained, environments. Hence, this chapter intends to fill this gap
in our knowledge by initially, briefly recalling the relevant literature that had been
discussed in detail in the Chapter Three and Four of the thesis. This is followed by
qualitative and quantitative data analysis, and finally, the chapter concludes with a
summary.
9.1. The Impacts of Academic Entrepreneurial Engagement
Some previous studies have argued that academic entrepreneurship can compensate for
meagre direct government funds available to higher education (Phan and Siegel, 2006,
Wright et al., 2006), since it generates additional income to academics and universities
(Wright et al., 2004). Furthermore, recent evidence suggests that academic
entrepreneurship improves the knowledge and skills (D'Este et al., 2010) and professional
networks of academics (Siegel et al., 2007). Additionally, these studies also argue that
academic entrepreneurship increases future opportunities for collaboration (D’Este and
Patel, 2007), mobility between academia and industry (Van Dierdonck et al., 1990), and
access to industrial resources (Siegel et al., 2004). In line with these arguments, some
previous studies have shown that there is a positive relationship between academic
entrepreneurship and normal academic duties (Calvert and Patel, 2003, Van Looy et al.,
2006, Lowe and Gonzalez-Brambila, 2007, Brooks and Randazzese, 1999).
However, the change of focus from basic science to applied science, and the use of limited
physical (Van Dierdonck and Debackere, 1988) and human resources (Bercovitz and
Feldman, 2003) in universities for academic entrepreneurship have been criticised for
causing negative impacts on the quality of non-practical teaching and research (Dasgupta
and David, 1994, Rosenberg and Nelson, 1994). The above literature, which has
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highlighted the positive and negative impacts of academic entrepreneurship on normal
academic duties, has mostly been derived from relatively resource rich environments. So
far, there has been little discussion of these impacts on normal academic duties carried out
in resource constrained environments. Hence, the first aim of this chapter is to investigate
how academic entrepreneurship in a resource constrained environment affects normal
academic duties (which relates to Hypothesis 4.1: The entrepreneurial engagements of
academics in resource constrained environments have no impact on their normal academic
duties).
As discussed in the Section 4.1 of Research Hypothesis Chapter, academics may adopt
different ‘plural activity’ types, depending on which, the impacts on normal academic
duties might vary. For instance, it could be argued that those who carry out activities
related to normal academic duties (e.g. training and seminars to industry personnel, joint
research, and external teaching etc.) may receive more benefits than those who engage in
activities distantly related to teaching and research (e.g. company creation). Therefore, the
second objective of this chapter is to examine whether impacts on normal academic duties
vary depending on the ‘plural activities’ of academic entrepreneurs (which relates to
Hypothesis 4.2: In resource constrained environments, there is no association between the
‘plural activity’ of academic entrepreneurs and their impact on normal academic duties).
In addition to the impacts on normal academic duties carried out in universities, it has also
been reported in the literature that the entrepreneurial activity of academics produces direct
economic benefits (Pattyn, 2006, Etzkowitz, 1998). For instance, previous studies have
argued that academic spin-offs generate wealth and create jobs (Birch, 1987). Moreover,
university-industry technology transfer provides opportunities for industry to capitalise on
the knowledge and skills of academics and to access the infrastructure facilities of
universities (Meyer-Krahmer and Schmock, 1998). However, several studies have revealed
that the extent of economic benefits varies with the type of academic entrepreneurial
activities. Some researchers have argued that university industry technology transfer
activities have a greater economic importance than spin-off firms (D’Este and Patel, 2007,
Cohen et al., 2002, Agrawal and Henderson, 2002). Additionally, Golob (2006) had shown
that spin-offs are also heterogeneous in terms of their economic importance, where spin-
offs that receive a greater support from their universities tend to generate more economic
value than those operating independently from their universities. Nevertheless, most of
these previous studies had been conducted in developed countries. Hence, the third aim of
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this chapter is to investigate whether the above noted differences between academic
entrepreneurial activities with respect to economic contribution, holds in the case of the
resource constrained environment of Sri Lanka (which relates to Hypothesis 4.3: There is
no difference among academic entrepreneurial activities with respect to the academic
perception of their national economic importance).
9.2. Analysis: The Impacts of Academic Entrepreneurship on Normal Academics
Duties
In order to test for the potential impacts (positive/negative) of academic entrepreneurship
on normal academic duties, the analysis used nine different aspects of normal academic
duties, identified from the literature (see Section 5.4.2.4 of Methodology Chapter for
details). In the online survey, academics were asked to rate, to what extent the carrying out
of academic entrepreneurial activities had resulted in positive or negative impacts on these
criteria. Additionally, personal income status was also included in the above list in order to
investigate how entrepreneurial engagements by academics affect their income status in
comparison to normal academic duties.
Analysis has indicated that the mean value of each aspect of normal academic duties was
more than 3.5 (Table 9.1), which suggested that academic entrepreneurship in the resource
constrained environment of Sri Lanka had positive impacts on normal academic duties (<3-
negative impacts, >3- positive impacts). An ANOVA test revealed a significant difference
between ten criteria with respect to the extent of positive influence F (10, 2568) = 34.725,
p= 0.000. Table 9.1 present the analysis of a Tukey’s Post Hoc test, which categorised
activities on the basis of their impacts on normal academic duties. The aspects of normal
academic duties that were most positively influenced by academic entrepreneurship were
‘knowledge and skills as an academic’ (M= 4.46, SD= 0.547), ‘professional network as an
academic’ (M=4.45, SD=0.577), ‘future opportunities for collaboration’ (M=4.38,
SD=0.582), ‘social status as an academic’ (M=4.11, SD=0.811), ‘the quality of teaching’
(M=4.32, SD=0.616), and ‘the quality of basic research’ (M=4.14, SD=0.634).
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Table 9.1: The Impacts of Academic Entrepreneurship on Normal Academics Duties
The aspects of normal academic duties N
Mean and standard deviation
1 2 3 4 5
1.The funding status of your university
230 3.69 (0.92)
2.Your income status as an academic 238 3.70 (0.87)
3.Your access to facilities/resources in the industry
224
3.92(0.79)
4.Your potential mobility between academia and industry
224
4.00(0.75) 4.00 (0.75)
5.Your social status as an academic 238 4.11(0.81) 4.11 (0.81) 4.11 (0.81)
6.The quality of your basic research 238 4.14 (0.63) 4.14 (0.63)
7.The quality of your teaching 237 4.32 (0.62) 4.32 (0.62)
8.Your future opportunities for collaboration
237
4.38 (0.58)
9.Your professional network as an academic
238
4.45 (0.58)
10.Your knowledge and skills as an academic
241
4.46 (0.55)
Sig. 1.00 .092 .576 .063 .560
Means for groups in homogeneous subsets are displayed.
Surprisingly, ‘personal income’ (M=3.69, SD =0.918) and ‘the funding status of
universities’ (M=3.70, SD=0.871) had the lowest positive influence. In-depth interviews
revealed that teaching related entrepreneurial activities generated only a limited amount of
extra income. Similarly, most of the research related activities, except consultancy, did not
provide academics with additional personal income. It was mainly company creation which
had generated high extra income (if the company was successful). On the other hand, it
was apparent that, since Sri Lankan universities did not have a policy on academic
entrepreneurship, entrepreneurial activities carried out by academics generated funding
mainly for individuals or for their departments. Hence, overall, academic entrepreneurship
had a low level of positive impact on the funding of universities.
Additionally, this chapter investigated whether there was an association between ‘plural
activities’ and the ‘impacts of academic entrepreneurship on normal academic duties’. This
analysis used three ‘plural activities’ adopted by academic entrepreneurs in Sri Lanka,
identified in the Section 6.2 of Chapter Six. These were ‘single role’, ‘double role’, and
‘triple role’. Single role academics had diversified only into teaching related
entrepreneurial activities, while their triple role counterparts diversified into teaching and
research related entrepreneurial activities as well as company creation. The engagement of
double role academics was positioned between that of single and triple role colleagues,
197
whereby they diversified into teaching and research related entrepreneurial activities, but
not into company creation.
ANOVA tests revealed that eight out of the possible nine impacts on normal academic
duties as well as the impacts on the personal income of academics had a significant
association with the ‘plural activities’ adopted by them (six criteria were significant at 0.05
level and the rest was at 0.1 level) (Table 9.2). Since all the mean values were higher than
3.5 (3> positive impacts, 3<negative impacts), it was the extent of positive impacts that
was found to differ depending on the ‘plural activities’ of academic entrepreneurs. A
Tukey’s Post-hoc test revealed that, the carrying out of all three types of entrepreneurial
activities (i.e. teaching and research related as well as company creation) generated more
positive impacts than engaging in only teaching related entrepreneurial activities (i.e.
single role entrepreneurship) or teaching and research related entrepreneurial activities (i.e.
double role entrepreneurship). The analysis of interviews, presented in the following
Sections, provided an in-depth understanding on these differences.
Table 9.2: The ‘plural activity’ of academic entrepreneurs and impacts on normal academic duties
The aspects of normal academic duties F statics p Mean
Single role
Double role
Triple role
1. Your income status as an academic F (2, 229) = 2.36 .097 3.211-3 3.72 3.751-3 2. Your social status as an academic F (2, 34) = 6.63 .004 3.211-3&1-2 4.091-2 4.281-3 3. The quality of your basic research F (2, 230) = 4.58 .011 3.711-3&1-2 4.111-2 4.231-3 4. The quality of your teaching F (2, 228) = 3.39 .036 3.931-3&1-2 4.311-2 4.381-3 5. Your knowledge and skills as an academic
F (2, 50) = 13.29 .000 4.071-3&1-2 4.441-2 4.521-3
6. Your professional network as an academic
F (2, 38) = 4.13 .024 4.151-3&1-2 4.43 4.501-3
7. Your future opportunities for collaboration
F (2, 38) = 2.79 .074 4.15 4.35 4.44
8. The funding status of your university F (2, 222) = .361 .697 3.45 3.70 3.70 9. Your access to facilities/resources in the industry
F (2, 215) = 1.74 .178 3.56 3.85 3.99
10. Your potential mobility between academia and industry
F (2, 215) = 6.76 .001 3.401-3&1-2 3.901-2 4.161-3
1-2 - A significant difference between single role and double role at 0.05
1-3 – A significant difference between single role and triple role at 0.05
2-3- A significant difference between double role and triple role at 0.05
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9.3. Analysis: The Positive Impacts of Academic Entrepreneurship on Normal
Academic Duties
9.3.1. The Positive Impacts of Academic Entrepreneurship on the Normal Academic
Duties of Single Role Academic Entrepreneurs
Single role academics had engaged in at least one out of four teaching related
entrepreneurial activities; namely, external teaching, initiating the development of new
degree programmes, placing students as trainees in industry, and conducting seminars and
training sessions for industry personnel. The majority of single role academics mentioned
that carrying out teaching related entrepreneurial activities enabled a better understanding
of new trends in industry and developing a professional network of contacts. They made
use of these to revise curriculum, to gain access to companies for normal academic duties
(e.g. industrial resources and company data for research and access to companies for
student visits), to secure training placements for students, and to invite industry personnel
for visiting lectures. One academic stated:
‘When conducting training and seminars for industry personnel, we get opportunities to
informally interact with them. These informal discussions enabled me to understand new
trends in the industry, which I incorporated into curriculum revisions’
The above quotation illustrates how carrying out teaching related academic entrepreneurial
activities improved the knowledge and skills of academics, which in turn, had positive
impacts on university curriculum. Another single role academic who specialised in Animal
Science stated that:
‘I often have to arrange field visits...... Students and alumni [of external teaching he
conducts], who are employees of industry, provide access to their companies for such
visits. Sometimes, they arrange short training programmes for my university
students.....there were few instance where I got access to data available in industry
through these contacts which was helpful for my research activities’
This quotation shows how the networks of contacts developed by engaging in teaching
related academic entrepreneurial activities had positive impacts on university teaching and
research. These results on the positive impacts of teaching related entrepreneurial activities
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are in line with the findings of other research carried out in developed countries, which
revealed that entrepreneurial engagements positively influenced the knowledge and skills
(D'Este et al., 2010) and professional networks (Siegel et al., 2007) of academics, which
were used by them to improve the quality of their university teaching (Shane, 2004).
However, it was evident that, since single role academics had engaged in only teaching
related entrepreneurial activities, they received lower benefits than their double and triple
role counterparts. Hence, the following Sections discuss extra positive impacts on normal
academic duties generated by diversifying into the additional activities such as research
related entrepreneurial activities and company creation.
9.3.2. The Positive Impacts of Academic Entrepreneurship on the Normal Academic
Duties of Double Role Academic Entrepreneurs
In addition to carrying out teaching related entrepreneurial activities, double role
academics had engaged in at least one activity categorised under research related
entrepreneurial activities; namely, working in the industry (research based), carrying out
research based consultancy for industry via their universities or privately (but without
forming a company), developing products or services with potential for commercialization,
acquiring research funding from government, non-governmental or international bodies,
collaborating with industry through joint research projects, and providing research related
assistance to small business owners.
Similar to single role academics, the entrepreneurial activity of their double role colleagues
was also reported to generate positive impacts on university teaching and research.
However, since double role academics had engaged in both teaching and research related
entrepreneurial activities, they were found to generate more positive impacts on normal
academic duties than their single role counterparts. For instance, one double role academic
explained how his engagements had positive impacts on teaching:
‘During my involvements with industry, particularly when carrying out joint-research and
conducting training programmes to employees of some companies, I got opportunities to
have informal discussions with them. As a result, I was able to receive feedback on how
our students [particularly alumni, who are employed by these companies] perform, which
was useful to improve my teaching [he was an expert in construction engineering].....
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‘Often, I use my experience in carrying out consultancy and joint-research projects with
industry to develop case studies to make students aware of practical aspects. I also make
use of these to explain the applications of some theoretical aspects.....The photographs I
took [e.g. defects in machinery, processes, and plants etc] while working in industry were
also used for teaching’
The above quotations demonstrate how the respondent used his experience of carrying out
both teaching and research related entrepreneurial activities for curriculum revisions, for
case-based teaching, and to develop teaching aids. In addition to the benefits for teaching,
the entrepreneurial activity of double role academics was also reported to have positive
impacts on their research. For example, one academic stated:
‘From this joint-research project with industry [a research in veterinary science], I was
able to provide 3 bursaries to research students. They work as research assistants in the
research project......the income gained from different consultancy assignments were used
to improve lab facilities.......[when he was asked why he used consultancy income to
improve labs, he answered] University does not have enough funds to upgrade labs, so I
had no alternative...... Without these external funds we wouldn’t have been able to conduct
research’
He further explained:
‘Recently we decided to form a research group to investigate a crucial matter [related to
animal pathology] prevailed in industry...we got to know about the severity of this issue as
a result of the informal discussions we had with industry personnel while carrying out
some consultancy work’
The above quotations show how double role academics made use of academic
entrepreneurship to generate positive benefits for teaching and research, by way of
improving lab facilities, recruiting research students, and identifying research gaps.
Moreover, the above quotes highlighted that, since universities were resource constrained,
without entrepreneurial engagements, the carrying out of research activities would be very
difficult. Another double role academic explained how entrepreneurial engagements (e.g.
joint research projects and applying for international funds) enabled improving her
research profile.
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‘Research funding is extremely constrained in Sri Lanka. Therefore, I often apply for joint
research funding with industry and non-governmental organizations. I also apply for
funding available in international bodies. From one of the recent project funds, I funded
three PhD students, who are now working in the project, and improved university
floriculture lab...... We published four papers’
As illustrated in the above comment, it was apparent that entrepreneurial activity generated
research funds, without which academics would not be able to carry out research.
Accordingly, the above results largely corroborate with the findings of research carried out
in developed nations, which highlights that entrepreneurial engagements improve the
quality of research carried out in universities (Siegel et al., 2004, Calvert and Patel, 2003)
(Van Looy et al., 2006, Lowe and Gonzalez-Brambila, 2007, Brooks and Randazzese,
1999). However, apart from this similarity, this analysis also suggests that, research
income acquired from research related academic entrepreneurial activities (i.e. from
industry, non-governmental organizations, and international bodies) was particularly
important, since the government and universities in Sri Lanka suffered from high resource
scarcity (see Section 2.2.1 of Chapter Two for more details on financial resource scarcities
in Sri Lanka). Furthermore, the above results highlight the fact that diversifying into both
teaching and research related entrepreneurial activities may generate more benefits for
normal academic duties than carrying out only teaching related entrepreneurial activities.
9.3.3. The Positive Impacts of Academic Entrepreneurship on Normal Academic
Duties: Triple Role Academic Entrepreneurs
In addition to engaging in teaching and research related entrepreneurial activities, triple
role academics carried out at least one activity involving company creation; namely, the
formation of joint ventures in which the university and industry were the joint partners,
joint ventures privately through collaborating with industry, new spin-off companies,
university centres designed to carry out commercialization activities, and privately owned
companies. Hence, besides the benefits of teaching and research related entrepreneurial
activities highlighted above, triple role academics generated extra positive impacts on
normal academic duties through their companies. For instance, in-depth interviews
revealed that spin-offs provided employment opportunities to graduates, training
placements for students, access to professional networks, and resources to carry out
university teaching and research. One academic stated:
202
‘I with two staff members of my department [the Department of Computer Engineering]
formed three companies. One company provides information security services....other two
companies are technology and consultancy services providers of computer engineering
[e.g. products and services are designed to enable on-line applications in all areas
including eGovernment, eCommerce, and eLearning]....we hire graduates, provide
training placements to students...we also formed a department fund for which a portion of
profit earned in companies goes into. We use this fund to improve infrastructure facilities
of our department....we also have a network of researchers working in our
companies.......Therefore, we could access them whenever we need assistance to carry out
teaching and research.....it is very difficult to find funds for university research, but since
we have resources in our companies, we successfully carry out research activities’
As illustrated in the above quotation, it was evident that spin-offs generated positive
benefits, such as employment opportunities for graduates, training placements for students,
resources to carry out research, and funding to improve the facilities of university
departments. Academics mentioned that, since the environment was resource constrained,
without these companies, academics would not have been able to successfully carry out
normal academic duties. Similarly, joint research labs with industry were also found to
provide resources to carry out teaching and research, to fund postgraduates, to provide
employment opportunities to students, and to carry out university research. For example,
one academic stated:
‘In our university, we have three joint research labs [attached to Electronics,
Telecommunications, and Chemical Engineering departments]. In addition to carrying out
joint-research activities [with industry], labs are also used to conduct university teaching
and research. For example, students are given opportunities to carry out their ‘practicals’,
we use lab facilities for university research ......University cannot afford to buy expensive
equipment. Therefore, these labs are very useful......We also fund postgraduate students.
They work in our labs....Experience in working in these labs had improved the
employability of our students’
Academics also mentioned that, since universities did not have sufficient funds to build
university owned labs, without these labs they would not have been able to successfully
carry out teaching and research. Furthermore, academics stated that working with industry
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personnel in these labs promoted the exchange of tacit knowledge, which positively
influenced the quality of academic teaching and research.
Additionally, it was also evident that triple role academics made use of their strong
networks of contacts with industry to receive feedback on university curriculum and to
promote their degree programmes, which in turn, improved the quality of teaching and the
employability of their graduates. For instance, it was reported that triple role academics in
one university held monthly meetings with industry personnel in order to explore
opportunities to collaborate with industry and to receive feedback on university teaching
and research activities. As a result, they were able to streamline academic programmes to
produce graduates who were suitable to meet industry requirements and to design research
programmes to generate outputs to capitalise on gaps in industry.
Hence, the above analysis suggests that diversifying into all three entrepreneurial activities
generated more benefits to normal academic duties than carrying out only teaching and
research related entrepreneurial activities. However, since the above analysis was solely
based on the interviews carried out with academics, there seemed to be a probability of
result bias. Hence, a few informal discussions (N=21) were conducted with students to
obtain general viewpoints and opinions about the teaching quality of a few selected
academics. Therefore, each student was asked to compare and contrast the teaching quality
of two particular academics mentioned by the researcher. The researcher chose different
pairs of academics, where one was a triple role academic, while the other was a single role
academic. Interestingly, all the discussions with students suggested that triple role
academics were better teachers than their single role counterparts. For example, one
student said:
‘The lectures of the lecturer x [a single role academic entrepreneur] were mainly
theoretical, and we found these less useful than the lecturers of the lecturer y [a triple role
academic entrepreneur]. Lecturer y always brings examples from industry, and explains
how theoretical aspects are applied in practise........Lecturer y had several contacts with
industry. So, he found jobs for students.............the lecturer y organized a lot of field visits
and gave opportunities to engage in industry oriented research....... he [lecturer y] is
extremely good, No argument, he is better than lecturer x’
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Therefore, these observations support the view that academic entrepreneurship in the
resource constrained environment of Sri Lanka had positive impacts on normal academic
duties. As a result, Hypothesis 4.1, which stated that, the entrepreneurial engagements of
academics in resource constrained environments would have no impact on their normal
academic duties, was rejected. The analysis also suggested that, since the environment was
resource constrained, it was impossible to carry out normal academic duties without
academic entrepreneurship, which explained why academics did not perceive that
academic entrepreneurship had negative impacts on normal academic duties. Furthermore,
diversifying into all three entrepreneurial activities was reported to provide more benefits
to normal academic duties than carrying out only teaching and research related
entrepreneurial activities. Therefore, it was possible to reject Hypothesis 4.2 which stated
that, in resource constrained environments, there would be no association between the
‘plural activity’ of academic entrepreneurs and their impacts on normal academic duties.
9.4. Analysis: The National Economic Importance of Academic Entrepreneurship
As a common measure of economic importance, the perception of academic entrepreneurs
regarding the level of economic importance of each entrepreneurial activity to Sri Lanka
was used. The use of such a subjective measure has been recommended in the absence of
an objective measure (Dess and Robinson, 1984), which in this research is judged to be the
dearth of a common measure of national economic importance of different academic
entrepreneurial activities. Accordingly, the on-line survey asked academic entrepreneurs to
rate the level economic importance of each entrepreneurial activity to Sri Lanka.
The analysis revealed that there was a significant difference between the perceived national
economic importance of different entrepreneurial activities F (17, 5536)=61.496, p=0.000.
Table 9.3 illustrates the results of a Tukey’s Post-hoc analysis, which categorised different
activities based on their economic importance. Interestingly, the analysis suggested that
teaching and research related entrepreneurial activities had a significantly higher level of
economic importance than company creation. It was also evident that entrepreneurial
activities, privately carried out by academics (e.g. privately carried out research based
consultancy, the formation of academic owned companies, and the formation of joint
venture/(s) privately through collaborating with industry), had lower levels of economic
importance than those carried out via/with universities (e.g. research based consultancy for
industry through the university, contributing to the formation of joint ventures in which
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university and industry are the joint partners, and contributing to the formation of
university centres designed to carry out commercialization activities).
Table 9.3: The Economic Outcomes of Academic Entrepreneurial Engagement
Academic Entrepreneurial Activities N
Subset for alpha = 0.05
1 2 3 4 5 6 7 8 9
The formation of your own company/(s) 246 2.63
Contributing to the formation of one or more new spin-off companies
302
2.95
The formation of joint venture/(s) privately through collaborating with industry
269 3.07 3.07
Research based consultancy privately 306 3.23 3.23
Working in the industry on secondments 307 3.25 3.25 3.25
Contributing to the formation of university centres designed to carry out commercialization activities
318
3.38 3.38 3.38
Contributing to the formation of joint ventures in which university and industry are the joint partners
317
3.48 3.48 3.48
External teaching 321 3.49 3.49 3.49
Conducting training and seminars for industry personnel
321
3.62 3.62 3.62
Introducing new degree programmes 321 3.62 3.62 3.62
Developing products with the potential for securing patents
305
3.65 3.65
Assisting small business owners to commercialize their innovations
297
3.66 3.66
Acquiring funding from government, non-governmental or international bodies (those without collaborations with industry)
324
3.66 3.66
Collaborating with industry through joint research projects
320
3.72
Research based consultancy for industry through the university
322
3.73
Finding industrial placements for students 325 3.74
Sig. 1.00 .736 .053 .054 .065 .950 .069 .075 .714
Means for groups in homogeneous subsets are displayed.
It was also tested whether the perceived economic importance varied depending on the
type of academic entrepreneur. As illustrated in Table 9.4, triple role academics placed a
significantly higher value on nine out of 17 entrepreneurial activities than their single role
counterparts. However, interestingly, it was found that, regardless of the type of
entrepreneur, a higher economic value was placed on teaching and research related
academic entrepreneurial activities than company creation.
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Table 9.4: Perceived Economic Importance Vs. The Type of Academic Entrepreneurs
F statics p Mean
Single role
Double role
Triple role
The formation of your own company/(s) F (2, 226) = 9.814
0.000 2.5213 2.35 2.9313
Contributing to the formation of one or more new spin-off companies
F (2, 274) = 1.586
0.207 2.83 2.88 3.07
The formation of joint venture/(s) privately through collaborating with industry
F (2, 247) = 4.511
0.012 2.6212 and 13 3.1112 3.1213
Research based consultancy privately F (2, 277) = 8.495
0.000 2.7612 and 13 3.2412 3.3713
Working in the industry on secondments F (2, 282) = 6.987
0.001 3.14 3.13 3.46
Contributing to the formation of university centres designed to carry out commercialization activities
F (2, 291) = 08.734 0.000 3.0012 and 13 3.3312 3.5413
Contributing to the formation of joint ventures in which university and industry are the joint partners
F (2, 289) = 2.525 0.082 3.36 3.43 3.60
External teaching F (2, 294) = 2.184
0.114 3.39 3.40 3.60
Conducting training and seminars for industry personnel
F (2, 294) = 6.556
0.02 3.3212 and 13 3.6312 3.74 13
Introducing new degree programmes F (2, 294) = 5.581
0.004 3.2812 and 13 3.6812 3.6613
Developing products with the potential for securing patents
F (2, 282) = 3.136
0.045 3.5213 3.63 3.7413
Assisting small business owners to commercialize their innovations
F (2, 271) = 13.470
0.000 3.1812 and 13 3.7212 3.7413
Acquiring funding from government, non-governmental or international bodies (those without collaborations with industry)
F (2, 296) = 7.169 0.001 3.3612 and 13 3.6812 3.7612
Collaborating with industry through joint research projects
F (2, 292) = 1.703
0.184 3.64 3.76 3.81
Research based consultancy for industry through the university
F (2, 293) = 2.345
0.098 3.55 3.74 3.77
Finding industrial placements for students F (2, 298) = 0.096
0.908 3.72 3.76 3.75
13 – Significant difference between single role and triple role entrepreneurs
12 - Significant difference between single role and double role entrepreneurs
207
In-depth interviews further validated the findings of the above quantitative data analysis.
The qualitative data analysis suggested that teaching related entrepreneurial activities
contributed to the Sri Lankan economy by developing high-skilled human resources. For
instance, academics stated that industry placements enabled students to acquire skills on
the applications of theory and to gain working experience. Likewise, training and seminars
for industry personnel were reported to improve their technical capabilities. Similarly,
external teaching was also found to be important to the development of high-skilled human
resources. Furthermore, new degree programmes had generated long term economic
benefits, since academics had designed these to capitalize on human resource gaps in
industry. As illustrated in the Section 2.2.2 of Chapter Two, a lack of high-skilled human
resources was a major constraint in Sri Lanka. Therefore, the contribution of teaching
related entrepreneurial activities to overcome this issue was perceived by academics as
having a high economic importance.
On the other hand, as illustrated in the Section 8.6 of Chapter Eight, Sri Lankan industry
was found be weak in terms of research and development capabilities, and the government
had other priorities of poverty alleviation. Therefore, universities were reported to be the
major driving forces of national innovation. Hence, the outputs of research related
entrepreneurial activities were considered (by respondents) very important to country’s
innovation performance.
However, the majority of respondents believed that due to the small scale of operation,
companies formed by academics did not generate high economic benefits. Furthermore,
since university policy does not allow the forming of profit oriented companies, alternative
arrangements made by academics to establish such companies (see Section 6.3.4 of
Chapter Six for more details), did not receive support from their universities. Therefore, it
was reported that these companies had to overcome several barriers, which hampered
potential growth. In contrast, university centres designed to carry out commercialization
activities and university-industry joint venture labs (i.e. non-profit oriented), which
received support from universities, were considered to have higher economic importance
than companies solely owned by academics. Hence, academics mentioned that, had profit-
oriented companies received support from the government and universities, these would
have generated high economic benefits. These results corroborate Golob (2006), who
found that spin-offs that receive support from universities make a higher economic
contribution than those that do not. Nevertheless, academics also stated that, due to
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resource scarcities, without establishing companies, it would not be possible to
successfully carry out normal academic duties and teaching and research related
entrepreneurial activities. Therefore, although companies created by academics were
reported to generate less direct national economic benefits than teaching and research
related entrepreneurial activities, these results have indicated that spin-offs generate both
personal and university level benefits. This analysis led to a rejection of Hypothesis 4.3,
which stated that there would be no difference between academic entrepreneurial activities
with respect to their perceived national economic importance.
9.5. Chapter Summary
This chapter has presented an analysis of the final objective of this thesis, which was to
investigate the impacts of academic entrepreneurship in the resource constrained
environment of Sri Lanka. The analysis suggested that academic entrepreneurship
positively influences normal academic duties. The aspects of normal academic duties that
were highly positively influenced by academic entrepreneurship were ‘knowledge and
skills as an academic’, ‘professional network as an academic’, ‘future opportunities for
collaboration’, ‘social status as an academic’, ‘the quality of teaching’ , and ‘the quality of
basic research’. Surprisingly, ‘personal income’ and ‘the funding status of universities’ had
the least level of positive influence. The reason for this appeared to be that academics did
not earn very high incomes by carrying out teaching or research related entrepreneurial
activities, and thus, it was only through company creation (if companies were successful)
that academics earned high additional income. On the other hand, since there was no
university policy on academic entrepreneurship, the funding statuses of universities were
reported to have less positive impacts.
Interviews suggested that the carrying out of teaching related entrepreneurial activities
helped understanding new trends in industry and developing a professional network of
contacts. These were made use by academics to revise the curriculum, gain access to
companies for normal academic duties (e.g. industrial resources and company data for
research and access to companies for student visits), secure training placements for
students, and invite industry personnel for visiting lectures. Similarly, engaging in research
related entrepreneurial activities were reported to be of use for identifying research gaps,
developing academic research profiles, improving lab facilities, and recruiting research
students. The analysis also suggested that, unlike in developed countries, in the resource
209
constrained environment of Sri Lanka, funding acquired from industry and non-
governmental and international bodies through research related entrepreneurial activities
was of great importance in carrying out university research.
Spin-offs were also reported to generate several positive benefits to normal academic
duties by way of providing employment opportunities for graduates, training placements
for students, resources to carry out teaching and research, and funding to improve the
facilities of university departments. Academics mentioned that, since the environment was
resource constrained, without these companies, it would not be possible to successfully
carry out normal academic duties. Hence, not surprisingly, triple role academics, who
carried out all three types of entrepreneurial activities generated more positive impacts than
double or single role academics, who engaged in only teaching and/or research related
entrepreneurial activities.
The chapter also revealed that there was a significant difference between the perceived
national economic importance of different entrepreneurial activities. Interestingly, it
seemed that teaching and research related academic entrepreneurial activities had a
significantly higher level of economic importance than company creation. It was evident
that teaching related entrepreneurial activities developed high-skilled human resources, and
research related entrepreneurial activities contributed to national innovation, both of which
fulfilled two extreme resource scarcities in Sri Lanka. These results seem to explain why
academics placed a high national economic importance on such activities.
On the contrary, due to the small scale of operation, companies formed by academics did
not generate high economic benefits. However, results indicated that the perceived
economic importance of joint venture labs and university centres designed for
commercialization activities was higher than companies formed by academics themselves
(e.g. spin-off companies, companies or joint ventures formed by academics themselves). It
seemed that this difference was mainly associated with the disparity between these two
categories of companies in terms of the support received from their universities. It was
apparent that companies formed by academics themselves did not receive support from
their universities since Sri Lankan universities were not allowed to form profit oriented
companies. On the contrary, joint venture labs and university centres, which were non-
profit oriented companies, were reported to receive support from their universities. This
difference in terms of economic value is in line with Golob (2006), who found that spin-
210
offs that receive support from universities make a higher economic contribution than those
do not. Nevertheless, results suggested that due to resource scarcities, without companies
established by academics, it would not be possible to successfully carry out normal
academic duties and other academic entrepreneurial activities (i.e. personal and university
level impacts).
211
Chapter 10: Conclusions and Recommendations
The main purpose of this chapter is to provide a final synthesis of the research findings in
order to reflect upon the implications of this study for theory and policy as well as to
highlight limitations and future research avenues. The thesis has demonstrated that there
has been little discussion of academic entrepreneurship in low income developing
countries (Eun et al., 2006, Adesola, 1991) despite their increasing investments in higher
education in recent years (World Bank EdStat, 2011). It is also argued that, if developing
countries need to derive valuable outcomes from higher education investments, they should
adopt context specific strategies, rather than merely imitating developed nations
(Bernasconi, 2005, Eun et al., 2006). Similarly, a context specific understanding of
academic entrepreneurship is believed to be needed to develop domestic capacities, and to
carry out applied research, that would be necessary to achieve the economic growth
(Pardey et al., 2006), that will deliver positive social benefits (Patel, 2003). Therefore, the
current study has underscored the need for filling this gap in our knowledge about
academic entrepreneurship in low income developing countries (Bercovitz and Feldman,
2003).
The thesis then illustrated that developing countries, when compared with developed
nations, face relatively higher levels of resource scarcity that involve shortages of skills
(Alexander and Andenas, 2008, Griffith-Jones et al., 2003), finance (United Nations
Human Settlements Programme, 2005), physical infrastructure, technology (World Bank,
2010), and institutions (Claude and Weston, 2006) needed for innovation and
entrepreneurship. Hence, by emphasising differences between developed and developing
nations in terms of their resource statuses, the present study investigated academic
entrepreneurship in a resource constrained environment.
By referring to the entrepreneurship (e.g. Westhead et al 2005, Kodithuwakku and Rosa,
2002) and diversification literature (e.g. Alsos et al 2003; Rumelt 1982) this thesis has
argued that academics may engage in a combination of entrepreneurial activities as a
strategy to extract value from their limited resource environment. Hence, in order to
achieve the main objective, the current study decided to focus on the portfolio of
entrepreneurial activities carried out by academics, named in the thesis as ‘plural
activities’. On the basis of this central argument and some specific gaps in our knowledge,
four specific objectives are constructed, namely, to investigate the ‘plural activities’ of
212
academic entrepreneurs, to examine the motivations of academic entrepreneurs, to study
the effects of multilevel causal factors on ‘plural activities’, and to investigate the impacts
of academic engagement in entrepreneurial endeavour.
This research chose Sri Lanka as the study location and used a three stage sequential mixed
method design. During the first phase, context specific data were collected, which were
then used to design two subsequent major data gathering stages, namely, an on-line survey
and in-depth interviews. Qualitative and quantitative data analyses were conducted to test
hypotheses constructed in relation to each of the above mentioned four specific objectives.
Returning to the hypotheses posed at the beginning of this thesis, it is now possible to state
that results led to a rejection of all the null hypotheses (see Table 10.1).
213
Table 10.1: Results- Research Hypotheses
Objective 1 Investigating the ‘Plural Activity’ of Academic Entrepreneurs in a Resource Constrained Environment
Accept/ Reject
Null
Hypothesis
1.1
Being entrepreneurial is not a means of overcoming
resource barriers in a resource constrained environment
Reject
Null
Hypothesis
1.2
There is no association between the ‘plural activity’ of
academic entrepreneurs and the extent of synergistic effects
generated in a resource constrained environment
Reject
Objective 2 Investigating the Motivation of Academic Entrepreneurs in a Resource Constrained Environment
Null
Hypothesis
2.1
In resource constrained environments, there is no
association between the ‘plural activity’ of academic
entrepreneurs and their motivations
Reject
Null
Hypothesis
2.2
The motivations of academic entrepreneurs operating in
resource constrained environments do not change over their
entrepreneurial careers
Reject
Objective 3 Investigating the Influence of Multilevel Factors on the ‘Plural Activities’ of Academic Entrepreneurs in a Resource Constrained Environment
Null
Hypothesis
3.1
There is no relationship between the ‘plural activity’ of
academic entrepreneurs and their personal characteristics Reject
Null
Hypothesis3.2
There is no difference between the influence of micro and
meso level factors on academic propensity to adopt specific
‘plural activity’ types
Reject
Null
Hypothesis3.3
There is no relationship between the ‘plural activity’ of
academic entrepreneurs and their perception of university
quality
Reject
Null
Hypothesis
3.4
Interactions between university, industry and government in
a resource constrained environment do not differ from those
in a developed environment
Reject
Objective 4 The Impacts of Academic Entrepreneurial Engagement in a Resource Constrained Environment
Null
Hypothesis
4.1
The entrepreneurial engagements of academics in resource
constrained environments have no impact on their normal
academic duties
Reject
Null
Hypothesis
4.2
In resource constrained environments, there is no
association between the ‘plural activity’ of academic
entrepreneurs and their impact on normal academic duties
Reject
Null
Hypothesis
4.3
There is no difference among academic entrepreneurial
activities with respect to the academic perception of their
national economic importance
Reject
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10.1. Implications for Theory
This study has made theoretical contributions not only to academic entrepreneurship
literature, but also to general entrepreneurship and diversification/ portfolio
entrepreneurship literature. There are two major types of theoretical contributions of this
thesis. First, the current study demonstrated the extent to which academic entrepreneurship
in a resource constrained environment differs from, or is similar to, that of a resource-rich
environment. This comparison was performed mainly in terms of the type of
entrepreneurial engagements, the motivations of academics, and the influence of multilevel
factors on, and the outcomes of, academic entrepreneurial engagements. Second, it
introduced the term, the ‘plural activities’ of academic entrepreneurs (i.e. the portfolio of
entrepreneurial activities carried out by academics), a phenomenon that has not yet been
widely discussed in the literature in either developed or developing countries. The thesis
also investigated how motivations and multilevel factors shape, and normal academic
duties and national economy are affected by, ‘plural activities’. Hence, the following
Sections discuss how this study has filled important gaps in the literature by looking at
academic entrepreneurship in an hitherto neglected area.
10.1.1. Academic Entrepreneurship: Resource Constrained Environments vs.
Resource Rich Environments
Chapter Two of this thesis showed that Sri Lanka is a resource constrained environment,
which is somewhat similar to other low income developing nations in South Asia. These
similarities were particularly apparent in terms of financial, human, infrastructural,
technological, and institutional resources that are relevant to academic entrepreneurship.
However, this does not negate the fact that there are differences between resource meagre
nations. Nevertheless, as illustrated in Chapter Two, when compared with differences
between resource-rich and resource constrained countries, it seemed that resource
constrained nations are more or less similar in terms of the above mentioned resource
statuses. Hence, when concluding on the findings, this study believed that, to some extent,
it is possible to generalise the results of this thesis to similar environments that confront
resource barriers.
The current study revealed that being entrepreneurial is a means of overcoming resource
barriers in a resource constrained environment. This highlights a major difference between
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academic entrepreneurship in resource constrained and resource rich environments since
previous studies, focused on resource rich environments, have argued that resources are a
means of becoming entrepreneurial (e.g. Etzkowitz and Leydesdorff 2000, Siegel et al.,
2004). Conversely, one of the original contributions of this thesis to the academic
entrepreneurship literature is that resource constraints can stimulate entrepreneurial
behaviour in relatively impoverished environments (e.g. Kodithuwakku and Rosa 2002;
Gilad and Levine 1986). This finding is largely in line with general entrepreneurship
literature which argues that the unavailability of resources is not critically damaging, and
that, entrepreneurs creatively overcome resource barriers (e.g. Hart et al., 1995, Kirzner,
1973, Saylor, 1987).
The findings also indicated that the engagement in each type of academic entrepreneurial
activity (i.e. teaching related academic entrepreneurial activities, research related academic
entrepreneurial activities and company creation) was initially motivated by push factors.
Over time the influence of push factors declined, while the impact of pull motives
increased. This highlights the importance of understanding the dynamism of
entrepreneurial motivation, which has been largely neglected in the academic
entrepreneurship literature in both developed and developing countries. Additionally, this
finding supports the general entrepreneurship literature, that has found a similar pattern of
change in the motivations of entrepreneurs over the growth of their ventures in both
developed (e.g. Schjoedt and Shaver 2007) and developing countries (e.g. Rosa et al.,
2006, De Silva and Kodithuwakku, 2011)
It appears that, in Sri Lanka, due to resource barriers, entrepreneurial engagement was the
major source that provided academics with the additional funding and physical resources
needed to achieve their pull motivations. Hence, even though pull motives have been
defined as the attractive reasons why entrepreneurs decide to form new ventures (Gilad and
Levine, 1986), this thesis has demonstrated that, in resource barren environments, pull
motives can be shaped by a need to overcome resource barriers, which becomes a push
motive.
On the other hand, some findings of this study support research from developed nations,
which stated that the individual characteristics of academics have a greater impact on
determining entrepreneurial behaviour than the characteristics of their academic
departments or universities (D’Este and Patel, 2007, Ambos et al., 2008, Clarysse et al.,
216
2011). Regardless of the above stated similarity, resource constrained environments
seemed to have context specific reasoning for this lack of impacts of universities on
academic entrepreneurship. For instance, it was apparent that, in Sri Lanka, due to the
absence of an overall university policy or support mechanisms to promote academic
entrepreneurship, it was solely driven by individual academics. Furthermore, since all the
Sri Lankan universities suffered from resource scarcities, there was no significant
difference between universities.
It was also evident that the carrying out of interdisciplinary projects in collaboration with
colleagues from different disciplines has enabled academics in Sri Lanka to overcome a
lack of resources and opportunities in some university disciplines. Hence, the involvement
in interdisciplinary projects appears to be another entrepreneurial strategy to overcome
resource barriers. On the other hand, this propensity towards decreased demarcations
between disciplines illustrates the importance of caution when comparing the influences of
different academic disciplines on entrepreneurial engagements.
Moreover, this study has demonstrated that industry and universities in Sri Lanka have a
mutual interdependence, which stimulates university-industry interactions. Sri Lankan
companies that lacked research and development capabilities tended to seek academic
expertise to assist innovation related activities. Hence, even though the literature has
argued that an industry with a weak research and development base (e.g. Eun et al 2006;
Adesola 1991) may hamper the possibilities of university-industry interactions, the above
results disagree with this view. However, due to a lack of research capacity in Sri Lankan
industry, in most instances, the interactions between university and industry did not
involve advanced scientific knowledge.
Even though universities and industry are inclined to collaborate due to mutual benefits,
Sri Lanka does not have a university or government policy, supportive mechanisms, or
formal institutional infrastructure to promote university-industry interactions. This lack of
intervention by the Sri Lankan government was argued to be due to other government
priorities linked to poverty. Therefore, university industry interactions were driven by
individuals, and thus, were scattered and isolated. These results support the findings of
similar research carried out in Latin America (Arocena and Sutz, 2001) but disagree with
the Triple Helix models that have mainly focused on developed nations (Etzkowitz and
Leydesdorff, 2000). Since a dearth of institutional frameworks for innovation and
217
entrepreneurship was found to be one of the characteristics of a resource constrained,
developing nation (See the Sections 2.2.4 and 2.1 of Chapter Two for details), the above
findings on university-industry-government interactions possibly might be generalized to
other similar countries.
The results on the impacts of academic entrepreneurship are in line with research from
developed countries, which revealed that entrepreneurial engagements positively influence
the knowledge and skills (D'Este et al., 2010) and professional networks (Siegel et al.,
2007) of academics. These positive impacts have contributed to the improvement of the
quality of university teaching (Shane, 2004) and research (Siegel et al., 2004, Calvert and
Patel, 2003, Van Looy et al., 2006, Lowe and Gonzalez-Brambila, 2007, Brooks and
Randazzese, 1999). Interestingly, these positive influences of academic entrepreneurship
on university teaching and research were extremely important to Sri Lanka, since the
government and universities suffered from high resource scarcity. Therefore, in meagre
resource environments, academic entrepreneurship seems to enable the overcoming of
resource barriers to university teaching and research.
The results have also demonstrated that there is a significant difference between the
perceived national economic importance of different entrepreneurial activities (by
academics, which carried out these activities). Interestingly, teaching and research related
entrepreneurial activities had been perceived as having a significantly higher level of
national economic importance than company creation. This was due to the contribution of
teaching and research related activities to overcoming resource scarcities such as high
skilled human labour and national innovation capacities. In contrast, spin-off companies
were small, and thus, academics (even those who have formed companies) perceived that
these have lower national level economic impacts. This finding is in line with the research
carried out in developed nations, which has argued that university-industry technology
transfer activities have a greater economic importance than spin-off firms (D’Este and
Patel, 2007, Cohen et al., 2002, Agrawal and Henderson, 2002).
Nevertheless, results suggested that due to physical resource scarcities in universities,
without companies established by academics, it would not be possible to successfully carry
out normal academic duties and other academic entrepreneurial activities. Therefore, it is
possible to conclude that, even though companies formed by academics were reported to
218
have low impacts on the national economy, they generate benefits both to individual
academics and to their universities.
10.1.2. The ‘Plural Activities’ of Academic Entrepreneurs
The results indicated that the majority of academics engaged in a combination of
entrepreneurial activities as a strategy to extract value from their limited resource
environments. This appears to represent ‘diversification’ discussed in the portfolio
entrepreneurship and strategic management literature (e.g. Alsos et al 2003, Rumelt 1982,
Westhead et al 2005). Hence, this thesis made an in-depth investigation of the diversity of
entrepreneurial activities of academics. This, to the knowledge of the author, has not been
studied before in either developed or developing country contexts.
The findings showed that academic entrepreneurial diversification is a process whereby
academics started their entrepreneurial careers by engaging in teaching related
entrepreneurial activities, and then, some of them diversified into research related
entrepreneurial activities and company creation. On the basis of the combinations of
entrepreneurial activities carried out by academics in Sri Lanka, three ‘plural activity’
types were identified namely, ‘single role’, ‘double role’, and ‘triple role’. Single role
academics had diversified only into teaching related entrepreneurial activities, while
double role academics had diversified into teaching and research related entrepreneurial
activities. Their triple role counterparts have diversified into teaching and research related
entrepreneurial activities, as well as company creation.
In addition to the types of activities, the results on the number of activities categorised into
each type of entrepreneurial activity revealed that triple role academics engaged in a
significantly higher number of teaching, and research, related entrepreneurial activities
than their single or double role counterparts. Therefore, it was considered that single role
academics diversified into a limited number of similar activities (i.e. a lower number of
teaching related activities), while their triple role colleagues diversified into a higher
number of diverse activities (i.e. a higher number of teaching and research related activities
as well as company creation). The engagement of double role academics was positioned
between that of single and triple role academics, whereby they diversified into different
activities to an average level (i.e. the number of teaching and research related activities was
less than triple role academics, but higher than single role academics). The highlighting of
219
this heterogeneity with respect to the ‘plural activities’ of academic entrepreneurs is
another original contribution of this thesis.
Furthermore, this study went some way towards the investigation of the synergies of
carrying out a combination of academic entrepreneurial activities. This, to the knowledge
of the author, has not been fully captured in the academic entrepreneurship literature. It
was apparent that academic entrepreneurial diversification generates synergistic effects in
terms of knowledge and skills, social networking, input-output flows, and physical
resources. Moreover, it seemed that synergistic effects were of great importance when
overcoming resource barriers in a limited resource environment. The above results, to
some extent, corroborate the diversification and portfolio entrepreneurship literature,
which has argued that the carrying out of several entrepreneurial activities provides
additional benefits, due to the synergies that, can develop between activities (Westhead et
al., 2005, Alsos et al., 2003). Hence, another original contribution of this thesis is to extend
the theoretical concepts of diversification and portfolio entrepreneurship to academic
entrepreneurship that is particularly focused on resource constrained environments.
The results further suggested that the extent of synergistic effects observed varied
depending on the complexity of ‘plural activities’, in which, diversifying into a higher
number of diverse activities (e.g. triple role academics) generated more synergistic effects
than diversifying into a limited number of similar activities (e.g. single role academics).
This finding does not agree with the literature which has stated that diversifying into
similar activities (e.g. diversifying only into teaching related activities) generates more
synergistic effects (since similar activities allows sharing common resources and
competencies) (Markides and Williamson, 1996). In a resource constrained environment,
there were not enough opportunities to diversify into similar activities extensively.
Therefore, the creation of resources, and minimizing resource conflicts by engaging in
diverse activities, was more important than sharing common resources, which led to the
argument that engaging in a higher number of diverse activities is an effective strategy for
extracting value from a resource constrained environment.
Nevertheless, there remained synergies between those who adopted different
diversification strategies, which emphasized the importance of having different and clear
role identities (Jain et al., 2009) by which academics and their universities might extract
value from a resource constrained environment.
220
This thesis also revealed that the motives of academics influence the types of ‘plural
activities’ adopted by them. However, the dynamism of entrepreneurial motivation from
‘push’ to ‘pull’ did not change depending on the nature of ‘plural activities’. The current
study also investigated how the personal characteristics of academic entrepreneurs
influenced ‘plural activities’ adopted by them. ‘Gender’, ‘position’, ‘academic discipline’,
‘business management and entrepreneurial knowledge and skills’, and ‘the strength of
social network’ of academic entrepreneurs were all the factors that significantly affected
their propensity to adopt different ‘plural activity’ types.
Moreover, the results demonstrated that, in the resource constrained environment of Sri
Lanka, university level factors did not have a significant influence on the ‘plural activities’
of academic entrepreneurs. However, the perception of academics on the quality of their
universities significantly varied, depending on the ‘plural activities’ adopted by them.
Academics who believed that the quality of their universities was ‘high’ tended to engage
in a higher number of diverse entrepreneurial activities (i.e. triple role academics). In
contrast, those who believed that the quality of their universities is ‘low’ tend to adopt a
limited number of similar activities (i.e. single role academics). Therefore, these results
support the general entrepreneurship literature, which has argued that the perceptions of
entrepreneurs regarding their environment shape their entrepreneurial behaviour
(Stevenson and Jarillo, 1990, Binks and Vale, 1990).
Furthermore, this research has indicated that diversifying into a greater number of different
activities (e.g. triple role entrepreneurs) generated significantly higher positive impacts on
normal academic duties than diversifying into a limited number of similar activities (i.e.
double role and single role entrepreneurs). However, the engagement in a greater number
of different activities would not have been possible without support received from those
who carried out a limited number of similar activities. This highlights the importance of
having a team of different activity types of academic entrepreneurs, who complement each
other.
10.2. Implications for Policy
In addition to the theoretical contributions highlighted above, this thesis has also provided
some implications for academics, universities, and policy makers, particularly for those
operating in resource constrained environments (e.g. low income developing countries and
221
South Asian countries). The findings of this study have revealed that being entrepreneurial
is a means of overcoming resource barriers in a resource constrained environment.
Interestingly, it was evident that academic entrepreneurship had positive impacts on
normal academic duties (e.g. university teaching and research) as well as the national
economy. These results have important policy implications for resource constrained
environments, since introducing incentives and support mechanisms for entrepreneurship,
as well as university-industry interactions, appear to improve university and national
performance. In addition to overcoming resource barriers, academics used entrepreneurial
engagements to achieve personal and academic goals. Hence, this study also suggests that
academics and universities in resource constrained environments should capitalise on
academic entrepreneurship as a strategy to pursue university and personal goals.
Although, traditionally, the worth of spin-off companies is gauged on the basis of the
amount of profit generated, this study suggests that spin-off companies provide a myriad of
other indirect benefits. Some of these indirect benefits involve improving the resource
status of universities, enhancing opportunities to engage in other entrepreneurial activities,
and overcoming institutional inefficiencies. This highlights the importance of taking into
account both direct and indirect benefits of spin-offs when valuing their worth. Moreover,
not only company creation, but also teaching and research related academic entrepreneurial
activities are used by academics to pursue personal and academic goals, which is also in
line with the findings of research conducted in developed countries (D'Este and Perkmann
2011). This emphasises the importance of recognising the value of teaching and research
related academic entrepreneurial activities, which are currently undervalued when
compared with the importance attributed to company creation.
It was also noted that academic entrepreneurship is a process in which academics start their
entrepreneurial engagements by engaging in teaching related activities, while some of them
subsequently diversify into research related activities and company creation. Furthermore,
the results indicate that, in this process, academics make use of teaching and research
related entrepreneurial activities to develop business management and entrepreneurial
skills, a network of contacts and physical resources, which are then capitalised on when
creating companies. This illustrates how academics, particularly those in resource meagre
environments, should benefit from such activities. On the other hand, the ability of this
phenomenon to overcome resource barriers underscores the need to nurture this process,
rather than merely pressing academics to create new business ventures.
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Furthermore, the thesis highlighted the importance of synergies between activities. Hence,
encouraging academic entrepreneurial diversification should be a strategy adopted by
universities in resource constrained environments. It is also worth noting that the amount
of synergistic effects generated varied depending on the complexity of the ‘plural activity’
of academics. Diversifying into a higher number of diverse activities was found to generate
more synergistic effects and positive impacts on normal academic duties than diversifying
into a limited number of similar activities. Nevertheless, at a university level, there were
synergies between entrepreneurs who adopt both these ‘plural activity’ types. This
underlines the importance of having different and clear role identities for academics by
which universities might extract value from a resource constrained environment.
Since each type of academic entrepreneurial activity, carried out in the resource
constrained environment of Sri Lanka, was motivated by specific pull- and push-factors
(monetary as well as nonmonetary), there is, therefore, a need to incorporate these findings
when designing rewarding schemes for academics in similar environments. Furthermore,
the findings of this study have highlighted the importance of taking into account the
dynamic nature of entrepreneurial motivations, when they change from push to pull. While
a constrained environment provides initial push motives, university managers and policy
makers can influence the entrepreneurial process by introducing new incentives and
support mechanisms for entrepreneurship, as well as improved university-industry
interactions.
The results also indicated that the ‘plural activities’ of academic entrepreneurs are affected
by the demographic characteristics of academic entrepreneurs, such as gender, position,
academic discipline, and their level of education. Hence, it is possible for university
managers to consider position, academic discipline, and the level of education in their
selection processes. Furthermore, it was found that academics, who have ‘high’ business
management and entrepreneurial knowledge and skills and strong networks of contacts,
tend to carry out a higher number of diverse activities (e.g. triple role academics). In
limited resource environments, these entrepreneurs generate more benefits for universities
than those who carry out a limited number of entrepreneurial activities (i.e. single role
academics). Hence, providing entrepreneurship education for academics and introducing
measures to strengthen their networks of contacts might pave the way for the reaping of
high benefits from academic entrepreneurship. Furthermore, this highlights the importance
223
of universities establishing intermediary institutions that connect academics with industry,
which enable academics to overcome a lack of contacts with industry.
It also appears that interdisciplinary projects have enabled academics to extract value from
their constrained environments as well as to overcome the dearth of entrepreneurial
opportunities in some disciplines. Hence, this suggests that academics should consider
collaborating with colleagues from different disciplines as a strategy to overcome
opportunity or resource shortages. Similarly, university managers should facilitate such
collaborations, by way of identifying opportunities for interdisciplinary projects, the
forming of project teams to capitalise on perceived opportunities, and encouraging a
culture that promotes interactions among disciplines.
High mutual dependence between universities and industry in Sri Lanka indicated that the
weak research and development capabilities of industry do not hinder academic
entrepreneurship. Instead, such circumstances bring opportunities for universities and
industry to mutually benefit. Hence, similar resource constrained environments should seek
to identify opportunities for university industry interactions, which might not be the same
as opportunities in resource-rich environments. Even though, these interactions were
mutually beneficial, the results also demonstrated that Sri Lanka did not have a university
or government policy, supportive mechanisms, or formal institutional infrastructure for
university-industry interactions. Therefore, these interactions were driven by individuals,
and thus, were scattered and isolated, which hindered the potential benefits of academic
entrepreneurship. This highlighted the importance of providing a support infrastructure that
promotes academic entrepreneurship in order for resource constrained environments to
reap maximum benefits. On the other hand, some government policies actually discourage
academic entrepreneurship. One such example is the government not allowing universities
to form profit-oriented companies. It was also evident that spin-off companies that
received support from universities (i.e. in Sri Lanka - non-profit organizations) had a
higher perceived economic importance than those that did not.
The above problems highlight the importance of university managers, in Sri Lanka and
other similar nations, taking initiatives to introduce supportive mechanisms and a
conducive policy environment that support the entrepreneurial engagements of academics.
However, unless government actively engages in this process, it might not be possible for
‘scattered and isolated’ academic entrepreneurial activities to make a national level impact.
224
Based on these findings, the following are some of the recommendations that the Sri
Lankan government should consider in order to promote academic entrepreneurship. Even
though these suggestions are mainly specific to Sri Lanka, they might provide a list of
aspects to be considered by any similar government (e.g. those with resource meagre
environments).
The creation of institutions to promote collective efforts for academic entrepreneurship -
As discussed above, in Sri Lanka, academic entrepreneurship is mainly achieved by
individual academics. Hence, it was apparent that academics are unable to generate high
economic value. As a result, collective and organized efforts towards academic
entrepreneurship, via the formation of relevant institutions, are needed. These will enable
academic entrepreneurship to be incorporated into the development goals of the country, as
a result of which, academic entrepreneurship will generate wider economic benefits. Some
examples of such institutions in developed countries are Technology Transfer Offices
(TTO) (Powers and McDougall, 2005) and intermediary institutions such as ANGLE
Technology Limited, UK (Franklin et al., 2001). However, it is important to create
institutions which are specific to the context, while the experience of such initiatives in
developed nations will provide useful insights. Furthermore, in addition to these
institutions that are mainly dealing with commercialization at the university level, it is also
important to establish national institutions that broadly facilitate collaborations between
university, industry, and government.
Creating a conducive policy environment – The findings of this thesis have indicated that
Sri Lanka does not have a conducive policy environment for academic entrepreneurship.
Hence, the government should evaluate how to amend existing university and industry
policies, and to introduce new policies, in order to encourage academic entrepreneurship.
Higher Education Innovation Fund in the UK, which funds knowledge transfer in
Universities and other Higher Education institutions, is one such example.
Facilitating and promoting technological learning – As discussed, Sri Lankan firms are
weak in terms of research and development capabilities, and thus, the exchange of
knowledge between industry and universities is limited to less-advanced scientific
knowledge. Therefore, promoting and supporting technological learning among Sri Lankan
companies is believed to enhance local demand for academic entrepreneurship, which will
induce the exchange of advanced scientific knowledge and the reaping of high benefits.
225
Promoting international partnerships and attracting foreign direct investments – The
results showed that, since Sri Lankan government suffers from financial resource scarcity,
academics rely on international funds. Therefore, promoting international research
alliances, and attracting foreign companies who are interested in carrying out research and
development activities in Sri Lanka would promote academic entrepreneurship and enable
academics to generate more benefits.
10.3. Limitations of the Study and Future Research Avenues
The findings of this study are subject to a few limitations, which might be addressed by
future research initiatives. First, the study was conducted only in Sri Lanka. Even though
this study has considered the possibility of generalising results to other similar resource
constrained environments, its replication in other similar and different contexts would
allow more robust theory development through a wider empirical comparisons. Second, to
the knowledge of the author, the ‘plural activity’ of academic entrepreneurs has not been
widely explored in the academic entrepreneurship literature in either developed or
developing countries. Therefore, this single country focus offers limited possibilities for
theory development. Hence, future research might conduct multi-national research in both
developed and developing countries for a better understanding of academic
entrepreneurship in differing national contexts.
Third, due to cost, time, and data concerns, this study adopted a cluster sampling technique
to select a sample for the on-line survey. Even though cluster sampling requires clusters
(i.e. in this case, universities) to be homogenous, there was no statistical evidence, before
collecting data, to show universities are homogeneous. Therefore, this study, in order to
reduce potential sampling errors, chose a representative sample of universities on the basis
of their age, size, and location. Nevertheless, interestingly, the findings of this research
confirm that universities did not have a significant influence on academic entrepreneurship,
which suggested that universities in this study context are homogeneous. However, for
future research, it would be advisable to use a stratified random sampling technique, which
has less sampling errors, if the above stated cost, time, and data issues could be overcome.
Fourth, since there was no common measure to gauge the impacts of different academic
entrepreneurial activities, this study asked academics to rate these on a Likert scale.
226
Therefore, future research could concentrate on developing a more accurate measure, so
that, impacts could be objectively measured. While this might improve the academic rigour
of similar research, it will provide a basis for policy makers to evaluate the impacts of
different academic entrepreneurial activities.
Fifth, this research has demonstrated that, at a university level, there were synergies
between entrepreneurs who adopt different ‘plural activity’ types (i.e. single role, double
role, and triple role). The results also suggested that, without these synergies, triple role
academics would not be able to successfully manage their engagements in all three types of
entrepreneurial activities. However, this study did not perform an in-depth analysis of the
synergies between different academic entrepreneurs. Hence, it should be a future research
objective to investigate what is the best combination of ‘plural activity’ types that a
university might seek in order to ensure achieving optimum benefits from academic
entrepreneurship.
Sixth, results on the dynamism of entrepreneurial motivation indicated that, initially,
academics are motivated by push factors, which are mainly associated with resource
scarcities. Over time, the significance of push motives declines, while that of pull motives
increases. However, this study did not investigate in detail, when this shift occurs and what
other circumstances influence this shift. Hence, further research might conduct a detailed
investigation of this phenomenon.
227
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Appendix 5.1: Initial Data Gathering
Academic
Entrepreneurial
Activities
Reference Initial findings Categorization
by
respondents*
1. External
teaching
Jones-Evans
1997
It was revealed that the teaching workload of
academics in Sri Lankan universities consists of
only undergraduate teaching. There are
independent institutions within universities for
postgraduate studies, and thus, academics
received additional payments for teaching in these
institutions. It was also revealed that, academics
tend to engage in teaching in other universities,
and private institutions. However, it was revealed
that there was no consensus with respect to the
use of the term ‘external teaching’. Therefore, it
was decided to explicitly describe the boundary of
the external teaching in the questionnaire (please
refer Questionnaire 2.1. (a).
Teaching related
2. Initiating the
development of
new degree
programmes
Laredo 2007 Interviews confirmed that academics have
engaged in the initiation of new degree
programmes, for undergraduates, and
postgraduates. Some academics have also
engaged in designing new degree programmes for
newly established universities and for private
institutes.
Teaching related
3. Placing
students as
trainees in the
industry
(D’Este and
Patel, 2007)
Interviews revealed that most of the degree
programmes has an element of in-plant training.
Even though there were separate bodies within
universities which dealt with arranging such
industrial placements, academics have contributed
to this task by way of finding placements, and
supervising students during placements.
Teaching related
4. Conducting
seminars and
training sessions
for industry
D’Este and
Patel 2007;
Schmoch 1997
Interviews confirmed that academics conduct
seminars and training sessions for both private
and public sector corporations.
Teaching related
5. Working in the
industry (research
based)
(Lashley,
2011, Arlett et
al., 2010)
It was revealed that some academics work in the
industry on secondments, which are mostly
research based.
Research related
244
Academic
Entrepreneurial
Activities
Reference Initial findings Categorization
by respondents
6. Research based
consultancy for
industry through
university centres
7. Research based
consultancy
privately
Glassman et al
2003; Jones-
Evans 1997;
Louis et al
1989;
Goldfarb and
Henrekson
2003
Interviews revealed that some academics carry
out consultancy through university centres while
others offer their consultancy services privately.
Those who engage in consultancy privately
sometimes do these via their own companies.
Therefore, it was decided to explicitly state these
in the questionnaire (Questionnaire No 2.1 (c),
and (d)). Carrying out consultancy through
academics owned companies is considered under
company formation.
Research related
8. Collaborating
with industry
through joint
research projects
Louis et al
1989
It was revealed that, the contribution of industry
to joint research project was mostly in terms of
funding, and providing access to industrial
resources. There were certain instances, in which
industrial representatives actively engaged in
carrying out projects collaboratively.
Research related
9. Acquiring
research funding
from government,
non-
governmental or
international
bodies (those
without
collaborations
with industry)
Lockett et al
2005
It was revealed that, besides industrial funding,
academics apply for funding provided by
government, nongovernmental organizational and
international bodies. Furthermore, due to limited
research funding provided by the government
academics mostly rely on international funding to
carry out their research. Since the industrial
funding is captured in the activity No. 8, it was
excluded in this activity.
Research related
10. Developing
products or
services which
have potential for
commercializatio
n.
Glassman et al
2003; Jones-
Evans 1997;
Siegel et al
2004
It was revealed that most of the new product
developments were done to find out cheap
technological alternatives with locally available
raw materials. However, the majority was
reluctant to obtain Sri Lankan IPR owing to the
lack of protection. Even though they believe that
it’s worthwhile to obtain foreign IPR they
couldn’t afford for these.
Research related
11. Research
related assistance
to small business
owners.
Wani et al
(2003)
Research related assistance to small business
owners has been mostly been informal which has
later resulted in some formal arrangements such
as consultancy, or joint ventures.
Research related
245
Academic
Entrepreneurial
Activities
Reference Initial findings Categorization-
respondent
12. Contributing
to the formation
of joint ventures
in which
university and
industry are the
joint partners.
13. The formation
of joint
venture/(s)
privately through
collaborating
with industry
Louis et al
1989;
Goldfarb and
Henrekson
2003; Hall et
al., 2001
It was revealed that the formation of joint
ventures with industry is done by academics by
themselves or via their universities. The
universities in Sri Lanka didn’t have technology
transfer offices, and thus, academics actively
engaged in these activities.
Company
creation
14. Contributing
to the formation
of one or more
new spin-off
companies
15. The formation
of your own
company/(s)
16. Contributing
to the formation
of university
centres designed
to carry out
commercializatio
n activities
Radosevich
1995; Samson
and Gurdon
1993; Daniels
and Hofer
1993
It was revealed that the university system in Sri
Lanka doesn’t allow the formation of profit-
oriented companies, and thus, university centres
designed for commercialization activities were
mainly in the form of non-for profit organizations.
However, it seems that academics have
introduced alternative models to create profit
oriented organizations, which acted as external
arms of universities when interacting with
industry. Such entities, attached to universities
were considered spin-off companies in this study.
Some academics have privately formed their own
companies, which were different from the above
stated two types.
Company
creation
17. Contributing
to the
establishment of
university
incubators and/or
science parks
Mian (1996);
Phan et al
(2003)
It was revealed that academics are in the process
of forming these.
Company
creation
* There was 100% consensus among 8 respondents with respect to this categorization
246
Appendix 5.2: Sampling
Name of the University
Year of establishment
Urban(1) Rural (2)
Closer to Colombo (1)/not (2)
% of students 1
% of academics2
No. of Academics
University of Colombo
1942 1
1 11
12 496
University of Peradeniya
1942 1 2 10
17 716
University of S’Jayewardenepura
1959 1 1 10 11 474
University of Kelaniya,
1959 1 1 12 13 577
University of Moratuwa
1972 1 1 5 7 284
University of Jaffna
1974 5 7 310
University of Ruhuna
1978 2 2 6 10 418
Open University of Sri Lanka
1978 1 1 26 7 277
Eastern University of Sri Lanka
1981 2 2 3 4 153
Sabaragamuwa University of Sri Lanka
1991 2 2 2 4 160
Rajarata University
1995 2 2 4 3 108
South Eastern University of Sri Lanka
1995 2 2 2 2 92
Wayamba University of Sri Lanka
1999 2 2 2 2 107
Uva Wellassa University
2005 2 2 1 1 43
1 no of students in each university/total number of students in all the universities
2 no of academics in each university/total number of academics in all the universities
247
Appendix 5.3: Non-Response Bias of the on-line Survey
Conducting non-response bias tests with respect to known characteristics is a strategy
recommended in the literature to test the influence of non-respondents (Armstrong and
Overton, 1977). Therefore, in this study, chi-square tests were conducted to test whether
respondents significantly differ from non respondents with respect their universities,
gender, academic discipline, and positions. As illustrated in the following Table, it was
revealed that there was no significant difference between respondents and non-respondents
with respect to their universities X2(5, 1182) = 2.976 p=.704 > 0.05.
Testing Non-response Bias with respect to University
Name of the University
No. of Non-Respondent
s
% Non-respondent
s
No. of Respondent
s
% Respondent
s
Total
% Total
1. University of Colombo
130 15.8% 47 13.1% 177 15.0%
2. University of Peradeniya
216 26.2% 107 29.9% 323 27.3%
3. University of Moratuwa
194 23.5% 82 22.9% 276 23.4%
4. University of Ruhuna
144 17.4% 66 18.4% 210 17.8%
5. Sabaragamuwa University of Sri Lanka
76 9.2% 32 8.9% 108 9.1%
6. Wayamba University of Sri Lanka
64 7.8% 24 6.7% 88 7.4%
824 100% 358 100% 1182 15.0%
Similarly, as illustrated in the Table below, there was no significant difference between
respondents and non-respondents with respect to their gender X2(1, 1182)= 3.674
p=.06>.05.
Testing Non-response Bias with respect to Gender
Gender No. of Non-Respondents
% Non-respondents
No. of Respondents
% Respondents
Total % Total
Male 528 64.1% 250 69.8% 778 65.8% Female 296 35.9% 108 30.2% 404 34.2% 824 100% 358 100% 1182 100%
248
Likewise, as demonstrated in the following Table, there was no significant difference
between respondents and non-respondents with respect to their position X2(2, 1182)= 1.015
p=.602>.05.
Testing Non-response Bias with respect to University
Position No. of Non-Respondents
% Non-respondents
No. of Respondent
s
% Respondents
Total % Total
Professor 123 14.9% 57 15.2% 180 15.2% Senior Lecturer 452 54.9% 185 53.9% 637 53.9% Lecturer 249 30.2% 116 30.9% 365 30.9% 824 100% 358 100% 1182 100%
Similarly, as shown in the Table below, it was confirmed that there was no significant
difference between respondents and non-respondents with respect to their academic
discipline X2(7, 1182)= 10.410 p=.167>.05 (Table 5.20).
Testing Non-response Bias with respect to Academic Discipline
Academic Discipline No. of Non-Respondent
s
% Non-respondents
No. of Respondent
s
% Responde
nts
Total % Total
Arts 52 6.3% 9 2.5% 61 5.2% Social Sciences 128 15.5% 58 16.2% 186 15.7% Architecture 31 3.8% 12 3.4% 43 3.6% Engineering 198 24.0% 85 23.7% 283 23.9% Computing, Information Technology
34 4.1% 19 5.3% 53 4.5%
Medicine, Dental, Veterinary
62 7.5% 23 6.4% 85 7.2%
Agriculture 147 17.8% 78 21.8% 225 19.0% Science 172 20.9% 74 20.7% 246 20.8% 824 100% 358 100% 1182 100%
Accordingly, the above analysis led to conclude that in this study there was no significant
non-response bias.
1. Personal Characteristics
PLEASE NOTE: ALL THE INFORMATION GIVEN IN RESPONSE TO THIS QUESTIONNAIRE WILL BE TREATED IN THE STRICTEST CONFIDENCE I would like to thank you in advance for participating in this survey which will be havimmense policy implications for Sri Lanka. A copy of findings of this survey will be made available to you. 1.1. Please select your year of birth
1.2. If you have obtained following qualifications (or equivalents) please select the academic discipline. If you have obtained more than one in any category please select these different academic disciplines.
Diploma
Bachelor’s degree
Masters degree
Doctoral
1.3. Please rate your level of compet
1. Business Management knowledge and skills 2. Entrepreneurial skills
1.4. Please state to what extent you agree/disagree with following statements
1. I have very strong personal contacts with industrial partners 2. I have access to industrial partners through some of my contacts who have strong and direct contacts with industry3. I am a member of a team (s) that has very good contacts with industry
I'm extremely grateful to you. Y
Appendix 5.4: Survey Questionnaire
1. Personal Characteristics
PLEASE NOTE: ALL THE INFORMATION GIVEN IN RESPONSE TO THIS QUESTIONNAIRE WILL BE TREATED IN THE STRICTEST CONFIDENCE
I would like to thank you in advance for participating in this survey which will be havimmense policy implications for Sri Lanka. A copy of findings of this survey will be made
1.1. Please select your year of birth
1.2. If you have obtained following qualifications (or equivalents) please select the academic discipline. If you have obtained more than one in any category please select these different academic disciplines.
Academic Discipline Academic Discipline more than one qualification in any category)
1.3. Please rate your level of competency on following attributes Extrem
ely low Low
1. Business Management knowledge and skills
2. Entrepreneurial skills
1.4. Please state to what extent you agree/disagree with following statements Strongly
disagree Disagr
ee
1. I have very strong personal contacts with
2. I have access to industrial partners through some of my contacts who have strong and direct contacts with industry
I am a member of a team (s) that has very good contacts with industry
Arts, Social Sciences, Science, Engineering, Architecture, ComputingMedicine, DentalVeterinary Medicine, Agriculture, Other
I'm extremely grateful to you. You have already completed 25% of the
249
PLEASE NOTE: ALL THE INFORMATION GIVEN IN RESPONSE TO THIS QUESTIONNAIRE WILL BE TREATED IN THE STRICTEST CONFIDENCE
I would like to thank you in advance for participating in this survey which will be having immense policy implications for Sri Lanka. A copy of findings of this survey will be made
1.2. If you have obtained following qualifications (or equivalents) please select the academic discipline. If you have obtained more than one in any category please select
Academic Discipline (if you have more than one qualification in any
High Extremely
high
N/A
1.4. Please state to what extent you agree/disagree with following statements Agree Strongly
agree N/A
Arts, Social Sciences, Science, Engineering, Architecture, Computing &Information Technology Medicine, Dental Science,
terinary Medicine, Agriculture, Other
ou have already completed 25% of the survey
2. Academic Entrepreneurial Activities The following tables illustrate different activities identified as academic entrepreneurial activities in the literature. (a)Please state to what extent you consider these are economically important in the Sri Lankan context. (b)Please state if you have engaged in any of these activities
2.1. Training and Consultancy (Please select)(a) Placing students as trainees in the industry (the term industry is used to indicate the 'business world')
(b) Conducting seminars and training ses
(c) Research based consultancy for industry through the university
(d) Research based consultancy privately (but without forming a company)
2.2. The Formation of Companies by University (Please select)(a) Contributing to the formation of university centres designed to carry out commercialization activities
(b) Contributing to the formation of joint ventures in university and industry are the joint partners
(c) Contributing to the formation of one or more new spincompanies (university is the owner of these companies)
(d) Contributing to tand/or science parks
2.3. The formation of your own Company/ies in which University has no shares (Please select) (a) The formation of joint venture/(s) privately through collaborating with industry
(b) The formation of your own company/(s)
2.4. Other Forms of Collaboration with Industry (Please select)(a) Collaborating with industry through joint research projects
(b) Developing products or services which have potential for commercialization
(c) Research related assistance to small business owners. (d) Working in the indu
the university
Not important at all Slightly important Important Very important
2. Academic Entrepreneurial Activities The following tables illustrate different activities identified as academic entrepreneurial activities in the literature.
state to what extent you consider these are economically important in the Sri Lankan context. (b)Please state if you have engaged in any of these activities
Level of economic importance in the Sri Lankan context
2.1. Training and Consultancy (Please select) (a) Placing students as trainees in the industry (the term industry is used to indicate the 'business world')
(b) Conducting seminars and training sessions for industry
(c) Research based consultancy for industry through the
(d) Research based consultancy privately (but without forming
.2. The Formation of Companies by University (Please select)(a) Contributing to the formation of university centres designed to carry out commercialization activities
(b) Contributing to the formation of joint ventures in which university and industry are the joint partners
(c) Contributing to the formation of one or more new spin-off companies (university is the owner of these companies)
(d) Contributing to the establishment of university incubators
2.3. The formation of your own Company/ies in which University has no shares
(a) The formation of joint venture/(s) privately through ing with industry
(b) The formation of your own company/(s)
2.4. Other Forms of Collaboration with Industry (Please select)(a) Collaborating with industry through joint research projects
(b) Developing products or services which have potential for
(c) Research related assistance to small business owners.
Working in the industry (research based) while being attached to
No, never, Yes, engaged in during last 5 years Yes, engaged in before 1st January 2005, Yes, engaged in both before and during last 5 years
250
The following tables illustrate different activities identified as academic
state to what extent you consider these are economically important in the Sri Lankan context. (b)Please state if you have engaged in any of these activities
Level of economic importance in the
Lankan context
Have you personally engaged in these activities?
.2. The Formation of Companies by University (Please select)
2.3. The formation of your own Company/ies in which University has no shares
2.4. Other Forms of Collaboration with Industry (Please select)
2.5. Academic entrepreneurial activities toward basic research and teaching (Please select) (a) External teaching (excluding that for industry) for which you are paid in addition to the basic salary
(b) Initiating the development of new degree programmes
(c) Acquiring funding from government, noninternational bodies (those without cindustry) If you have engaged in any other activity/ies beyond your workload AND/OR for which
you are paid in addition to the basic salary please state
3. In order to direct you to the appropriate next question can you please state whether you
have engaged in any of the activities mentioned above (After answering this question
please click NEXT)
Yes
No
3. Academic Entrepreneurial Motive
3.1. Academics could be motivated be entrepreneurial in order to overcome a range of
existing negative circumstances. Please state the level of effect of the following factors on
your decision to engage in academic ent
1. Insufficient income 2. Job related dissatisfaction 3. Not having an industrial partner capable of commercializing the new product/technology4. Lack of resources within universitiesuniversity Others, if any (please state up to three)
I'm extremely grateful to you. You have already comple
2.5. Academic entrepreneurial activities toward basic research and teaching (Please
(a) External teaching (excluding that for industry) for which e paid in addition to the basic salary
(b) Initiating the development of new degree programmes
(c) Acquiring funding from government, non-governmental or international bodies (those without collaborations with
If you have engaged in any other activity/ies beyond your workload AND/OR for which
you are paid in addition to the basic salary please state
der to direct you to the appropriate next question can you please state whether you
have engaged in any of the activities mentioned above (After answering this question
3. Academic Entrepreneurial Motive (Those who said ‘yes’ to question 3)
3.1. Academics could be motivated be entrepreneurial in order to overcome a range of
existing negative circumstances. Please state the level of effect of the following factors on
your decision to engage in academic entrepreneurial activities.
Extremely low
Low
1. Insufficient income
2. Job related dissatisfaction
3. Not having an industrial partner capable of commercializing the new product/technology
of resources within universities within
Others, if any (please state up to three)
Those who clicked ‘Yes’ were directed to the question 3,
and those who said ‘No’ were directed to the question 5.
I'm extremely grateful to you. You have already completed 60
251
2.5. Academic entrepreneurial activities toward basic research and teaching (Please
If you have engaged in any other activity/ies beyond your workload AND/OR for which
der to direct you to the appropriate next question can you please state whether you
have engaged in any of the activities mentioned above (After answering this question
(Those who said ‘yes’ to question 3)
3.1. Academics could be motivated be entrepreneurial in order to overcome a range of
existing negative circumstances. Please state the level of effect of the following factors on
High Extremely
high
N/A
Those who clicked ‘Yes’ were directed to the question 3,
and those who said ‘No’ were directed to the question 5.
ted 60% of the survey
3.2. Academics could be motivated to be entrepreneurial in order to receive some positive
outcomes or due to certain external influences. Pleas
following factors on your decision to engage in academic entrepreneurial activities.
1. In order to achieve career development 2. In order to acquire new knowledge and 3. In order to capitalise on the opportunity PERCEIVED BY YOU4. In order to capitalise on the opportunity PERCEIVED BY YOUR UNIVERSITY5. In order to provide a service to students (e.g. lab equipments industry placements employmopportunities and other opportunities for students etc) 6. In order to make use of industrial resources
7. Desire for wealth
8. For personal satisfaction (e.g. associate with people outside the university, and independence, social status, challenge seeking nature etc)9. As result of role models 10. The belief that it will not interfere with my academic Career Others, if any (please state up to three)
3.2. Academics could be motivated to be entrepreneurial in order to receive some positive
outcomes or due to certain external influences. Please state the level of effect of the
following factors on your decision to engage in academic entrepreneurial activities.
Extremely low
Low
1. In order to achieve career development
2. In order to acquire new knowledge and skills
3. In order to capitalise on the opportunity PERCEIVED BY YOU
4. In order to capitalise on the opportunity PERCEIVED BY YOUR UNIVERSITY
5. In order to provide a service to students (e.g. lab equipments industry placements employment opportunities and other opportunities for students
6. In order to make use of industrial resources
8. For personal satisfaction (e.g. associate with
outside the university, and independence, social
challenge seeking nature etc)
9. As result of role models
10. The belief that it will not interfere with my
Others, if any (please state up to three)
252
3.2. Academics could be motivated to be entrepreneurial in order to receive some positive
e state the level of effect of the
following factors on your decision to engage in academic entrepreneurial activities.
Low High
Extremely
high
N/A
253
4. Outcomes of Academic Entrepreneurial Engagement (Those who said
‘yes’ to question 3)
Please state the degree to which academic entrepreneurial activities has influenced the following
Extremely negative
Negative No effect
Positive
Extremely positive
N/A
1. Your income status as an academic
2. Your social status as an academic
3. The quality of your basic research
4. The quality of your teaching
5. Your knowledge and skills as an academic
6. Your professional network as an academic
7. Your future opportunities for collaboration
8. The funding status of your university
9. Your access to facilities/resources in the industry
10. Your potential mobility between academia and industry
I'm extremely grateful to you. You have already completed 90% of the survey
survey
5. The Perception of Academics (Those who said ‘No’ to
5.1. To what extent are the following statements true with respect to you?
1. I do not have enough time to engage in other activities other than my workload2. I believe that academic careinterfered as a result of engaging in entrepreneurial activities3. There are no opportunities to engage in activities other than the workloadIf you have not engaged in academic entrepreneurial activities and if the aboveare not true with respect to you please state the main reason as to why you have not engaged in academic entrepreneurial activities
5.2. Based on your perception please state the degree to which academic entrepreneurial activities influence the following
1. Your income status 2. Your social status as an academic 3. The quality of your basic research 4. The quality of your teaching 5. Your knowledge and skills as an academic 6. Your professionaacademic 7. Your future opportunities for collaboration 8. The funding status of your university 9. Your access to facilities/resources in the industry 10. Your potential mobility betweacademia and industry
I'm extremely grateful to you. You have already completed 90
survey
5. The Perception of Academics (Those who said ‘No’ to
5.1. To what extent are the following statements true with respect to you?
Extremely low
Low
1. I do not have enough time to engage in other activities other than my workload
2. I believe that academic career would be interfered as a result of engaging in entrepreneurial activities
3. There are no opportunities to engage in activities other than the workload
If you have not engaged in academic entrepreneurial activities and if the aboveare not true with respect to you please state the main reason as to why you have not engaged in academic entrepreneurial activities
5.2. Based on your perception please state the degree to which academic entrepreneurial activities influence the following
Extremely negative
Negative effect
1. Your income status as an academic
2. Your social status as an academic
3. The quality of your basic research
4. The quality of your teaching
5. Your knowledge and skills as an
6. Your professional network as an
7. Your future opportunities for
8. The funding status of your university
9. Your access to facilities/resources in
10. Your potential mobility between academia and industry
I'm extremely grateful to you. You have already completed 90
254
5. The Perception of Academics (Those who said ‘No’ to question 3)
5.1. To what extent are the following statements true with respect to you?
High Extremely
high
N/A
If you have not engaged in academic entrepreneurial activities and if the above statements are not true with respect to you please state the main reason as to why you have not engaged
5.2. Based on your perception please state the degree to which academic entrepreneurial
No effect
Positive
Extremely positive
N/A
I'm extremely grateful to you. You have already completed 90% of the survey
255
6. The Perception/Experience of Academic (for all the academics)
4.1. Please state how the following factors affect on your propensity to engage in academic entrepreneurial activities
Extremely negative
Negative No effect
Positive
Extremely positive
N/A
1. Your University's policy towards academic entrepreneurship
2. Your universities’ reward system
3. The management system of your university
4. The location of your university
4.2. Based on your experience at a national level please rate your university in terms of the following attributes
Extremely low
Low High
Extremely
high
N/A
1. Research strength of your DEPARTMENT
2. Research strength of your UNIVERSITY
3. The commercial orientation of your DEPARTMENT
4. The commercial orientation of your UNIVERSITY
5. The resources status of your university
I would like to convey my sincere gratitude to you for completing this survey.
My Email address: Lasandahasi.desilva@postgrad.mbs.ac.uk
256
Academic Entrepreneurship – Semi Structured Questionnaire - Academics
1. Whether the academic has engaged in these activities or not (Yes/No) will be filled before the interview based on the responses of the on-line survey. According to the type of activities in which the respondent has engaged in the respective questions will be asked. If the academic has not engaged in any please go to question No. 14.
The nature of engagement
Yes/ No * During last 5 years
(interactions among activities
will be explored)
1.1 1.2 Why did you engage in/diversify into this activity? Has the motivation changed over years? If so how?
1.3. What were the outcomes (positive/negative)?
Teaching related academic entrepreneurial activities
(1) External teaching Where?/ No. of hours (if possible)
(2) Initiating the development of new degree programmes
No. of degree programmes/ Your contribution? Did you obtain input from industry and if yes how?
(3) Placing students as trainees in the industry
No of groups/No. of students? What was your contribution?
(4) Conducting seminars and training sessions for industry
No. of times?/ Income?
Research related academic entrepreneurial activities
(5) Working in the industry
No. of years? The nature of work? How did you find the opportunity?
(6) Research based consultancy for industry through the university
Income earned (university/Personal)? How did you find the opportunity?
(7) Research based consultancy privately (but without forming a company)
Income earned? How did you find the opportunity? Why didn’t you have it via university?
(8) Developing intellectual property rights
How many? How many have been commercialised? How have you collaborated with industry?
(9) Collaborating with industry through joint research projects
Amount of funds? What kind of projects? How long? What was your contribution?
Appendix 5.5: Questionnaire-In-depth Interviews
257
The nature of engagement
Yes/No *
During last 5 years
1.2 Why did you engage in/ diversify into this activity? Has the motivation changed over years? If so how?
1.3. What were the outcomes (positive/negative)?
Research related academic entrepreneurial activities (10) Assisting small business owners to commercialize their innovations
How many? In which ways?
(11) Acquiring funding from government, non-governmental or international bodies (those without collaborations with industry)
Amount of funds? For what? From which institutes?
The Formation of companies (12) Contributing to the formation of joint ventures in which university and industry are the joint partners
How did you contribute? How many? Profit? No. of employees?
(13) The formation of joint venture/(s) privately through collaborating with industry
How did you engage in? How many? Profit? No. of employees? Why didn’t you establish this via university?(if they have not contributed to university ones)
(14) Contributing to the formation of one or more new spin-off companies
How did you engage in/contribute to? How many companies? No. of employees? Profit? Only Own one – Why didn’t you establish it via university?
(15) Contributing to the establishment of university incubators and/or science parks
(16) Contributing to the formation of university centres designed to carry out commercialization activities
(17) The formation of your own company/(s)
*before the interview tick the box if the person has engaged in these activities
258
2. 1. How does the engagement affect on your traditional job role?
Role Status 1. The quality of teaching
Improved Enabled to (1) Incorporate practical aspects (Y/N) (2) Improve the syllabus based on the needs of the industry (Y/N) (3) Provide employment opportunities to students (Y/N) (4) Fund industrial placements to students (Y/N) (5) Provide opportunities for students to carryout industrial related final year projects (Y/N) Other;
Degraded
Indifferent
2. The quality of research
Improved Enabled to (1) Identify research problems (Y/N) (2) Enhance opportunities for research via industrial funding (Y/N) (3) Use industrial resources (Y/N) (4) Strengthen social network which was used for later research collaborations (Y/N)
Degraded
Indifferent
3. Resource status
Improved Enabled to (1) Improve laboratory facilities (2) Improve other infrastructure (3) Hire research staff
Conflicts owing to the lack of resources to share
Indifferent
5. Other (please state)
2.2. How did you manage engagement in academic entrepreneurial activities while engaging in normal academic duties?
259
3. How many research publications have you had during last five years? How many of these are in indexing journals?
4.
4.1. You have mentioned your business and management skills as (low/high) in the online survey, [Interviewer - Please fill this before the interview]
4.1.1. Those who said high - how did you make use of your skills when engaging in these activities? (one example)
4.1.2. Those who said low – Did it act as a constraint in engaging in specific type/s of academic entrepreneurial activity/ies?
4.2. You have mentioned your entrepreneurial skills as (low/high) in the online survey, [Interviewer - Please fill this before the interview]
4.2.1. Those who said High - how did you make use of your skills when engaging in these activities? (one example)
4.2.2. Those who said low – Did it act as a constraint in engaging in specific type/s of academic entrepreneurial activity/ies?
5.
5.1. How does university reward system acknowledge academics’ engagement in entrepreneurial activities in comparison to engagement in traditional job role?
Relatively low Equal recognition Relatively high
5.2. Has it motivated you to engage in these activities?
Yes/No
260
5.3. Should it be changed through acknowledging academic entrepreneurial activities? (Yes/No) If Yes, How should it be changed?
Please tick
Provide incentives on certain academic entrepreneurial activities which are not specified in the scheme
Please state types of activities
Reduce the pressure on publications
Other
5.4. How does other university policies affect on your engagement?
5.5. How does the location of your university affect on your engagement?
6. How does university management system affect on your engagement?
How?* If possible, any example to elaborate
Teaching related academic entrepreneurial activities
Research related academic entrepreneurial activities
The formation of companies
*Select from the following table
Encouraged 1 Indifferent 2 Discouraged 3
261
7.Only for 111or 110. If not please move to Question 9.
7.1. What made you have joint collaborations with industry?
Please tick Lack of management and entrepreneurial skills In order to make use of industrial resources In order to share the risk Other
7.2. How did you get to know about industrial partners?
Please tick Industrial Partner approached you You approached industrial partner Through intermediary (if yes, who?) Other
7.3. How difficult/easy was it to collaborate with them?
Please explain Agreeing on objectives
Sharing resources
Managing cultural differences
Other
262
8. Only for 110- If not move to question 10
Why haven’t you engaged in forming companies?
Please tick and explain whenever possible Lack of time Lack of interest Lack of business management, and entrepreneurial skills
Lack of incentives Lack of autonomy Lack of resources Lack of support from university management system
Lack of opportunities Constraints owing to the academic discipline
The pressure on publications avoided engagement
Didn’t want to dilute the quality of the primary role (teaching and research)
Risk averter Other,
Move to Question 10.
9. Only for 100, –
Why haven’t you engaged in research related academic entrepreneurial activities?
Please tick and explain whenever possible Lack of time Lack of interest Lack of incentives Lack of business management, and entrepreneurial skills
Lack of autonomy Lack of resources Lack of support from university management system
Lack of opportunities Constraints owing to the academic discipline
The pressure on publications avoided engagement
Didn’t want to dilute the quality of the primary role (teaching and research)
Risk averter No having appropriate industrial partners Other,
263
10. What was the major contributing factor of you which enabled you to interact with others (e.g. funding agency and the partner of joint collaborations etc...)?
10.1.If the other partner is Government or international research body
Please tick The research profile of the academic Strength of the social network of the academic The quality of the previous work carried out by the academic in collaboration with respective organizations
Status of the academic (professor/ senior lecturer/lecturer) 10.2. If the other partner is Private sector body
Please tick The research profile of the academic Strength of the social network of the academic The quality of the previous work carried out by the academic in collaboration with respective organizations
The image of the academic in the industry Status of the academic (professor/senior lecturer/lecturer)
11. How does government policy affect on your engagement? Do you have any suggestions to change the government policy?
Effect Please tick Restrict engagement
Encourage engagement
Indifferent Suggestions for Improvements Please tick and explain whenever
possible Should have different policies based on the type of academic entrepreneurial activity
Should have higher level of involvement by the government
Other
12. Do you perceive that Sri Lanka could adapt the conceptualizations developed in developed countries in order to improve academic engagement in entrepreneurial activities?
If yes How?
If no Why? Any other ways ?
264
13. Only for those who have not engaged in any activity
Why didn’t you engage in any academic entrepreneurial activity? (Investigate in-depth – barriers for engagement)
Lack of time Lack of interest Lack of incentives Lack of autonomy Lack of resources Lack of support from university management system
Lack of opportunities, owing to the academic discipline
The pressure on publications avoided engagement
Not having appropriate industrial partners Didn’t want to dilute the quality of the primary role (teaching and research)
Other,
265
Appendix 8.1: Parameter Estimates: Triple role academic entrepreneur in
comparison to double role academic entrepreneur
Independent Variables B Std.
Error Wald df Sig. Exp(B)
95% Confidence Interval for
Exp(B)
Lower Bound
Upper Bound
Tri
ple
ro
le
aca
dem
ic
entr
epre
neu
rs
in
com
pa
riso
n
to
do
ub
le
role
a
cad
emic
Intercept -5.213 1.228 18.014 1 .000 Gender=male 1.317 .433 9.256 1 .002 3.733 1.598 8.721 Gender=female 0b . . 0 . . . . Position = Professor .478 .509 .881 1 .348 1.612 .595 4.371 Position = Senior Lecturer .754 .381 3.923 1 .048 2.126 1.008 4.486 Position = Lecturer 0b . . 0 . . . . Discipline = Social Sciences .772 .585 1.747 1 .186 2.165 .689 6.808 Discipline = Architecture, Engineering
.817 .542 2.270 1 .132 2.263 .782 6.549
Discipline = Computing, Information Technology
3.481 1.346 6.686 1 .010 32.497 2.322 454.819
Discipline = Medicine, Dentistry, Veterinary
.675 .883 .585 1 .444 1.964 .348 11.086
Discipline =Agriculture 1.304 .532 6.004 1 .014 3.683 1.298 10.451 Discipline =Science 0b . . 0 . . . . Business Management=Low -.949 .414 5.250 1 .022 .387 .172 .872 Business Management=High 0b . . 0 . . . . Entrepreneurial Skills=Low -1.290 .383 11.360 1 .001 .275 .130 .583 Entrepreneurial Skills=High 0b . . 0 . . . . Strength of Social Network 1.046 .305 11.777 1 .001 2.847 1.566 5.174 Commercial Orientation of Department
-.475 .275 2.988 1 .084 .622 .363 1.066
Commercial Orientation of University
.473 .306 2.391 1 .122 1.604 .881 2.921
Research Strength of Department
.032 .242 .017 1 .896 1.032 .643 1.657
Resource Status of University
.280 .265 1.118 1 .290 1.323 .787 2.224
b. This parameter is set to zero because it is redundant (i.e. these were the reference categories)
266
Appendix 8.2: Parameter Estimates: Double role academic entrepreneur in
comparison to single role academic entrepreneur
Independent Variables B Std.
Error Wald df Sig. Exp(B)
95% Confidence Interval for
Exp(B)
Lower Bound
Upper Bound
Do
ub
le r
ole
aca
dem
ic e
ntr
epre
neu
r in
co
mp
ari
son
to
sin
gle
ro
le a
cad
emic
en
trep
ren
eur
Intercept -1.471 1.976 .554 1 .457 Gender=male -.576 .631 .832 1 .362 .562 .163 1.937 Gender=female 0b . . 0 . . . . Position= Professor 1.249 1.255 .991 1 .319 3.488 .298 40.791 Position = Senior Lecturer .177 .659 .072 1 .789 1.193 .328 4.346 Position = Lecturer 0b . . 0 . . . . Discipline = Social Sciences
.168 .840 .040 1 .842 1.183 .228 6.141
Discipline = Architecture, Engineering
.232 1.028 .051 1 .821 1.262 .168 9.463
Discipline = Computing, Information Technology
-3.322 1.425 5.434 1 .020 .036 .002 .589
Discipline = Medicine, Dentistry, Veterinary
-.469 1.153 .165 1 .685 .626 .065 6.003
Discipline =Agriculture .150 .981 .023 1 .878 1.162 .170 7.953 Discipline =Science 0b . . 0 . . . . Business Management=Low
-.483 .638 .574 1 .449 .617 .177 2.153
Business Management=High
0b . . 0 . . . .
Entrepreneurial Skills=Low
-.716 .659 1.182 1 .277 .488 .134 1.778
Entrepreneurial Skills=High
0b . . 0 . . . .
Strength of Social Network
1.046 .507 4.260 1 .039 2.848 1.054 7.692
Commercial Orientation of Department
1.376 .651 4.468 1 .035 3.960 1.105 14.189
Commercial Orientation of University
-1.153 .629 3.356 1 .067 .316 .092 1.084
Research Strength of Department
.666 .458 2.120 1 .145 1.947 .794 4.775
Resource Status of University
-.256 .486 .277 1 .599 .774 .299 2.007
b. This parameter is set to zero because it is redundant (i.e. these were the reference categories)