ACADEMIC ENTREPRENEURSHIP IN A RESOURCE CONSTRAINED ...

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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


7.2.3. Pull Motives that have no Significant Association with the ‘Plural activities’ of


7.2.4. Pull Motives that have a Significant Association with the ‘Plural activities’ of


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


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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


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


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


34

Figure 2.6.2: The Number of Patent Applications by Residents: with High


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.

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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


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



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



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



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



– 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



0.67%) (OECD, 2010). On the other hand, since Sri Lankan universities provide



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



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



0.67%) (OECD, 2010). On the other hand, since Sri Lankan universities provide



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



-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).


technology Exports (% of manufactured exports): w

Source: The World Bank (2011)

-technology Exports (% of manufactured exports): with High



applications by residents in Sri Lanka, in which the figures are significantly lower than that


South Asian and lower middle income countries (Figure 2.6.1).

33


xports (% of manufactured exports): without High

of manufactured exports): with High


e figures are significantly lower than that


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:


Figure 2.6.2: The Number of Patent Applications by Residents: with High Income


internet usage, which is considered an important indicator


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


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


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


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)


even though there were several initiatives to form research and development



lished in 1968, after which the first policy document, namely, the ‘National Science


this policy due to financial constraints and other priorities linked to poverty allev


year in which the ‘Science and Technology Development Act

successfully implemented. As a result of this act, the National Science and Tec


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


even though there were several initiatives to form research and development



namely, the ‘National Science


this policy due to financial constraints and other priorities linked to poverty alleviation. As


Science and Technology Development Act No. 11 of 1994’ was

successfully implemented. As a result of this act, the National Science and Technology


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.

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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

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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

63

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.

64

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).

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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

67

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

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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

I U

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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).


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


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


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

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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


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

92

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:

93


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


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

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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

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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

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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

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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).

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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



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


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


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


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


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


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


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

120

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.


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

121

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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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


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


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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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


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


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


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


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


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


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



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).

166

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


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 Position 1.8% 8.4% 12.8% 8.7%

Double Role Academic Entrepreneurs

Count(N) 30 77 43 150


% within Position 52.6% 43.0% 39.4% 43.5%

Triple Role Academic Entrepreneurs

Count(N) 24 69 29 122


% within Position 42.1% 38.5% 26.6% 35.4%

Total Count(N) 57 179 109 345


% 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 Gender 8.5% 9.1% 8.7%

Double Role Academic Entrepreneurs

Count(N) 101 49 150


% within Gender 41.1% 49.5% 43.5%

Triple Role Academic Entrepreneurs

Count(N) 100 22 122


% within Gender 40.7% 22.2% 35.4%

Total Count(N) 246 99 345


% 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


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%


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%


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%


18.5% 34.2% 38.2% 35.4%

Total Count 27 111 207 345

% within Academics

7.8% 32.2% 60.0% 100.0%


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 Business and Management Skills

38.5% 55.9% 46.9% 45.7% 49.6%

Triple Role A.E

Count 7 27 65 15 114



53.8% 26.5% 50.8% 42.9% 41.0%

Total

Count 13 102 128 35 278



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


Triple Role A.E


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


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.


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


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,

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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


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

199

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.


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].....

200

‘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

203

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

205

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


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


297

3.66 3.66


324

3.66 3.66


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


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


F (2, 271) = 13.470

0.000 3.1812 and 13 3.7212 3.7413


F (2, 296) = 7.169 0.001 3.3612 and 13 3.6812 3.7612


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

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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

208

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.


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

215

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

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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

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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

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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

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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.

222

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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243

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


3. Academic Entrepreneurial Motive (Those who said ‘yes’ to question 3)



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


(Those who said ‘yes’ to question 3)



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)


outcomes or due to certain external influences. Please state the level of effect of the


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


e state the level of effect of the


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


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


survey

5. The Perception of Academics (Those who said ‘No’ to


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



254

5. The Perception of Academics (Those who said ‘No’ to question 3)


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: [email protected]

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)?


(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?


(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



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


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


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)

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