Knowledge effectiveness, social context and innovation

Knowledge effectiveness, social contextand innovation

Dimitris Brachos, Konstantinos Kostopoulos, Klas Eric Soderquist and Gregory Prastacos

Abstract

Purpose – The purpose of this paper is to conduct an investigation into knowledge-sharingmechanisms by empirically testing the role that context plays in the transfer of actionable knowledge,and, in turn, for innovation.

Design/methodology/approach – A multiple-respondents survey was performed in 72 business unitsof companies belonging to the ICT, pharmaceutical and food industries in Greece. In total, 295 usefulquestionnaires were collected using a multiple respondent strategy. All constructs were measured withmulti-item scales and validated using exploratory factor analyses. A total of seven hypotheses weregenerated following a literature review on the key determinants of context for effective knowledgesharing. The hypotheses were tested using ordinary least squares regression.

Findings – The research shows that when units pursue knowledge transfer between their differentactors, contextual factors such as trust, motivation to transfer knowledge, management support andlearning orientation are crucial for fostering knowledge transfer and innovation. This contribution isimportant since the need for developing an organizational context where knowledge transfer andinnovation flourish is constantly put forth in the business press, while the empirical and research basedevidence for its importance has been scarce.

Research limitations/implications – There is a research need in knowledge sharing theory to defineand identify an integrated model concerning the contextual factors that enable the knowledge sharingprocess. Having established a firm relationship between organizational context and innovation, theresearch also sets a foundation for further exploring the organization-environment link in terms ofleveraging organizational knowledge dynamics.

Originality/value – The research is a first attempt to show that the construct ‘‘perceived usefulness ofknowledge’’ is a critical proxy of knowledge transfer effectiveness, as well as to find support for itspositive relation to innovation.

Keywords Knowledge transfer, Knowledge management, Organizational culture, Innovation, Greece

Paper type Research paper

Introduction

A primary aim of knowledge management and knowledge-based social development is to

enable and encourage knowledge transfer among and between organizational entities such

as individuals, communities and units (Newell et al., 2002). Building on earlier

ground-breaking work on knowledge transfer and sharing (Kogut and Zander, 1995;

Szulanski, 1996), Argote and Ingram (2000, p. 151) argue that ‘‘the creation and transfer of

knowledge in organizations provide a basis for competitive advantage in firms’’. In a wider

social perspective, this knowledge-driven competitiveness is crucial for ensuring sustained

performance and growth in regions and industries alike (e.g. Feldman and Martin, 2005). So

far, the majority of empirical research has been concentrated on the types of knowledge that

enable or hinder knowledge transfer (Szulanski, 1996; Argote and Ingram, 2000; Reagans

and McEvily, 2003; Haas and Hansen, 2005), on the kind of organizational components that

support knowledge sharing – such as dyads (Szulanski, 1996; Levin and Cross, 2004),

ego-networks and inter-unit relationships (Hansen, 1999; Dyer and Nobeoka, 2000; Tsai,

DOI 10.1108/13673270710819780 VOL. 11 NO. 5 2007, pp. 31-44, Q Emerald Group Publishing Limited, ISSN 1367-3270 j JOURNAL OF KNOWLEDGE MANAGEMENT j PAGE 31

Dimitris Brachos andKonstantinos Kostopoulos,Management ScienceLaboratory, AthensUniversity of Economicsand Business, Greece.Klas Eric Soderquist,Assistant Professor ofInnovation and KnowledgeManagement in AthensUniversity of Economicsand Business, Greece.Gregory Prastacos,Professor of ManagementScience in AthensUniversity of Economicsand Business and Directorof the ManagementScience Laboratory,Greece.

An earlier version of parts of thispaper was presented at the2006 Annual Academy ofManagement Conference, 11-16August 2006, Atlanta, Georgia,USA. This Research is fundedby the Greek General Secretarialfor Research and Technology,Ministry of Development, by theEuropean Social Fund and bythe Commercial Bank of Greece,a member of the Credit AgricoleGroup.

2001; Hansen et al., 2005) and knowledge based value systems (Carrillo, 1997) – as well as

on the factors determining knowledge inflows and outflows in multi national corporations

(MNCs) and strategic business units (SBUs) (Gupta and Govindarajan, 2000).

The context where knowledge transfer takes places is an important factor that needs further

empirical development, as to what exactly is meant by context and what variables can be

conceived as proxies for context when it comes to knowledge sharing. Actually, contextual

parameters are important both at the organizational level, which is the focus of this paper,

and at the level of the wider social context where organizations operate. In addition, few

researchers have attempted to analyze, in depth, knowledge transfer effectiveness

(Reagans and McEvily, 2003), that is, the extent to which knowledge transfer actually leads

to positive innovation outcomes and other performance effects (Tsai, 2001; Smith et al.,

2005).

Building on the knowledge transfer, organizational context and new product innovation

literature, the authors position the study in business units (marketing divisions), use the term

perceived usefulness of knowledge to operationalize knowledge transfer effectiveness, and

argue that an organizational context characterized by a combination of trust, motivation,

learning orientation, social interaction, and top management support facilitates knowledge

usefulness within business units. Further, the authors conceptualize that knowledge

usefulness mediates the relationship between these contextual factors and product

innovation. The conceptual framework is depicted in Figure 1. To test this model, 295

questionnaires were used and 72 marketing directors were interviewed from 65 medium- to

large-sized multinational enterprises located in Greece. Multiple regression analyses were

performed.

The remaining of this paper is organized as follows: First, the knowledge transfer and related

innovation literature is reviewed and the research hypotheses are formulated. Second, the

methodology with variables, measures and validation procedures is presented. In section

three the results are presented, and last implications, limitations and proposals for future

research directions are discussed.

Theory development and hypotheses

Making knowledge available is not equal to knowledge transfer. Knowledge also needs to be

used by the receiving part. Knowledge transfer actually occurs when received knowledge is

used by recipients and this use results in changing their behavior; in other words when

experience of one individual or unit influences another unit through changes in behavior

(Nelson and Winter, 1982; Argote and Ingram, 2000). Von Krogh (2003, p. 374) adds further

precision to the knowledge transfer/sharing processes, arguing that tacit knowledge sharing

is a ‘‘sequenced collective action and change. involving alteration and transformation in

cognition and action both of the sender and the receiver, whereas Argote and Ingram (2000)

point out that knowledge transfer can be measured through changes in knowledge or

changes in performance.

This specification of ‘‘true’’ knowledge transfer presents strong similarities to learning theory

where learning at the individual level occurs when an individual, as a result of learning,

modifies his or her mental models – which are representations of an individual’s explicit and

implicit understandings of the world (Senge, 1990). The learning literature supports the view

Figure 1 Knowledge sharing effectiveness and organizational performance

PAGE 32 j JOURNAL OF KNOWLEDGE MANAGEMENTj VOL. 11 NO. 5 2007

that organizations convert their past experience into promises for future action (Hargadon

and Fanelli, 2002). By following such a rationale, the authors adopt the view that knowledge

transfer can be seen as a building block of organizational learning (Argote, 1999), and,

consequently, knowledge is effectively transferred among actors when it is perceived as

useful by those actors.

The notion of perceived knowledge usefulness as a proxy of knowledge transfer

effectiveness is not new in knowledge theory. Menon and Varadarajan (1992), for

instance, define usefulness as a judgment made about knowledge from a particular source

in a particular context. More recently, Levin and Cross (2004) develop the construct receipt

of useful knowledge as an outcome variable to denote the concept of effective knowledge

transfer. Building on Hansen (1999), Hansen and Haas (2001) and Szulanski (1996) they

combine eight items to formulate this construct, indicating the extent to which received

knowledge hindered or promoted different aspects of project and business unit outcomes.

Four items related to project efficiency in terms of budget and time, and four items related to

business unit effectiveness – in terms of value, performance and quality – were measured in

these studies.

To sum up, perceived usefulness of knowledge is dependent on the extent to which the

concerned actors perceive knowledge as:

B Meaningful – knowledge should make sense to the users.

B Accurate – knowledge should be related to the tasks and problems facing the users and

to the processes and routines through which work gets done.

B Valid – knowledge should be action-oriented and proven applicable.

B Innovative – the use of knowledge should lead to something new (i.e. ideas, products,

deeper knowledge, etc).

Based on the above, the authors suggest that perceived usefulness of knowledge, which

prompts organizational actions, changes in behavior, and innovation outcomes, is an

adequate proxy of knowledge transfer effectiveness. Following Levin and Cross (2004), the

authors define and measure a unit’s perceived usefulness of knowledge as the extent to

which the knowledge which is shared, is perceived as meaningful, relevant, action-oriented,

and innovative.

Having analyzed and specified the notion of knowledge transfer, the particular context

where knowledge transfer actually occurs and in which knowledge is manifested as useful

needs to be examined. The knowledge transfer literature suggests that trust (Levin and

Cross, 2004), motivation (Osterloh and Frey, 2000), learning orientation (Baker and Sinkula,

1999), social interaction (Hansen, 1999) and management support (Vera and Crossan,

2004) are cornerstones of an organizational context that enables effective knowledge

sharing (Gibson and Birkinshaw, 2004). This context, which essentially is built up from

variables of social inter-personal nature, will affect the level of perceived usefulness of

knowledge, which, in turn, will affect new product and service introduction impacting also

the wider social context where the organization is located.

Organizational context, knowledge transfer effectiveness, and performance

Davenport and Prusak (1998) argue that when knowledge transfer is the objective, the

method must always suit the organizational culture and social processes, while De Long and

Fahey (2000) advance that different contextual dimensions shape the individuals’ mindsets,

behavior and their corresponding relationships. Therefore, the organizational context

determines the way that knowledge is created, legitimated and diffused throughout the

organization. The authors position the research recognizing that the notions of organizational

context, culture and social climate represent overlapping perspectives on the same

phenomenon (Ashkanasy et al., 2000; Smith et al., 2005).

The factors that have been identified as influencing and characterizing the context for

knowledge transfer include social interaction (Hansen, 1999; 2002; Reagans and McEvily,

2003), trust (De Long and Fahey, 2000; Argote et al., 2003; Becerra and Gupta, 2003),

VOL. 11 NO. 5 2007 j JOURNAL OF KNOWLEDGE MANAGEMENTj PAGE 33

management support (Vera and Crossan, 2004), motivation (Gupta and Govindarajan, 1986;

2000; Osterloh and Frey, 2000; Argote et al., 2003) and learning orientation (Tsai and

Ghoshal, 1998; Baker and Sinkula, 1999, Crossan et al., 1999).

A key enabler for knowledge transfer is social interaction among organizational members

(e.g. participants in problem-solving teams) who rely on knowledge transfer for supporting

innovation and for driving performance (Ghoshal et al., 1994; Tsai, 2001; Reagans and

McEvily, 2003). Hansen (1999, p. 83) defines such relations as ‘‘regularly occurring contacts

between groups of people’’. Social interaction strengthens inter and intra-organizational

relationships by integrating actors’ activities in knowledge sharing processes and routines.

Key determinants of effective social interaction are closeness and communication frequency

(Ghosal et al., 1994; Tsai and Ghoshal, 1998; Tsai, 2001; Becerra and Gupta, 2003).

Social-related activities play an important role in the creation, development and cultivation of

a space where knowledge sharing takes place. Hansen (1999), in his study of 120

new-product development projects undertaken by 41 divisions within a large multinational

firm, shows that weak ties (i.e. distant and infrequent relationships) among business units

help project teams search for simple and useful codified knowledge in other business units,

whereas, in contrast, strong ties promote complex knowledge transfer. Additionally, Tsai and

Ghoshal (1998) emphasize the important role of social ties as channels of knowledge

sharing and resource flows, which influence positively the creation and diffusion of

innovations.

Thus, social interaction among individuals in organizational settings could improve

productivity (Reagans and Zuckerman, 2001), increase performance (Tsai, 2001), foster

innovation (Tsai, 2001), and stimulate knowledge transfer (Reagans and McEvily, 2003).

Taking the above into consideration, the following hypothesis related to social interaction

was formulated:

H1. Social interaction, as measured by closeness and communication frequency, will

have a positive impact on a business unit’s level of perceived knowledge

usefulness.

Although trust has been consistently theorized as an important aspect of organizational

context, its role in relation to knowledge transfer is rather ambiguous and underexplored.

Some studies, for example, argue that high levels of trust may inhibit monitoring and thereby

minimize collective action (Webb, 1996) whereas others argue that trust among participants

facilitates knowledge transfer (Argote et al., 2003) and emphasize the mediating role of trust

in perceived usefulness of knowledge (Levin and Cross, 2004). Harris et al. (1999) delineate

that developing relationships built upon trust is a vital aspect of knowledge transfer

effectiveness, although they recognize the difficulty of creating and maintaining high levels

of trust with associated implications for management. Thus, even though strong evidence

have been found for the supporting role of trust in effective knowledge transfer, the concept

still necessitates further specification especially when integrated in a broader explanatory

research model.

Giddens (1990, p. 34) identifies trust as being a property of both individuals and social

contexts. Effective knowledge transfer is characterized by a simultaneous high level of

mutual trust and trustworthiness among individuals in all processes and activities (Tsai and

Ghoshal, 1998; Von Krogh et al., 2000; Newell et al., 2002). The literature on trust comprises

‘‘ Making knowledge available is not equal to knowledgetransfer. ’’


strong evidence that trustful relationships are a key prerequisite for knowledge transfer

within and among business units (Dirks and Ferrin, 2001; Levin and Cross, 2004).

Taking the above into consideration, the following hypothesis related to trust was formulated:

H2. Trust will have a positive impact on a business unit’s level of perceived knowledge

usefulness.

Motivation to transfer knowledge constitutes another key determinant for knowledge transfer

effectiveness. The motivation to learn is a powerful force driving participation in

organizational contexts (Argote et al., 2003). Motivated organizational members can deal

easier and more effectively with ill-structured situations and transfer knowledge faster.

Osterloh and Frey (2000) distinguish two forms of motivation: extrinsic motivation (pay,

incentives, awards and recognition) and intrinsic motivation (work-related factors and work

environment), which can motivate participants to share their knowledge. Extrinsic rewards

are those that are provided to participants by someone else, while intrinsic rewards are those

that individuals generate themselves as a result of accomplishing a task. Intrinsic motivation

refers to an undertaken activity for one’s need satisfaction. The ideal incentive system is in

the work content itself, which needs to be acceptable, satisfactory and fulfilling for

employees (Osterloh and Frey, 2000; Ferrin and Dirks, 2003).

Extrinsic motivation contributes to knowledge transfer, maneuvering actors to exploit

existing knowledge and explore new one. The behavioral theory of the firm emphasizes

intrinsic motivation in the form of identification with organizational strategy and shared

purposes. Intrinsic motivation is needed for tasks that require creativity in their execution,

and triggers the transfer of knowledge under conditions where extrinsic motivation fails

(Osterloh and Frey, 2000). Thus, members of a unit are more likely to transfer knowledge if

they are rewarded for utilizing internal knowledge (Argote et al., 2003; Menon and Pfeffer,

2003).

Taking the above into consideration, the following hypothesis related to motivation was

formulated:

H3. Motivation will have a positive impact on a business unit’s level of perceived

knowledge usefulness.

Learning orientation is an organizational characteristic, which affects a firm’s propensity to

use, create and share all kinds of knowledge (Baker and Sinkula, 1999). Organization-level

learning represents the translation of shared understandings and collective action into new

products, procedures, systems, and strategies (Crossan et al., 1999). Organizational

context influences knowledge transfer and learning through commitment to learning, open

mindedness, and shared vision that collectively make up the learning orientation construct

(Vera and Crossan, 2004; Baker and Sinkula, 1999).

Firms that are committed to learning, recognize the need to understand the cause and effect

of their actions, which, in turn, is necessary for firms to regularly detect and correct errors in

their theories in use (Crossan et al., 1999). The learning orientation comprises a set of

knowledge questioning values through which organizations proactively question long-held

routines, taken-for-granted assumptions and beliefs, resulting in processes of unlearning.

Hence, unlearning is at the heart of organization change and, in turn, open mindedness is an

organization value that is necessary for unlearning efforts to take place (Baker and Sinkula,

1999). The trading of know-how requires the existence of shared codes and vision within

firms (Dyer and Nobeoka, 2000; Tsai and Ghoshal, 1998).

Thus, a learning orientation in the business unit prevents participants from hiding and not

transferring valuable knowledge and, in parallel, protects from undesired situations (Tsai

and Ghosal, 1998). The authors view a learning orientation as a bonding mechanism that

helps different parts of a business unit to integrate or to combine knowledge.

Taking the above into consideration, the following hypothesis related to learning orientation

was formulated:


H4. Learning orientation, namely commitment to learning, open-mindedness and

shared vision, will have a positive impact on a business unit’s level of perceived

knowledge usefulness.

Management literature has emphasized the importance of top management style in

implementing and supporting an environment that fosters effective knowledge sharing and

innovation within business units (Van de Ven, 1986; Pan and Scarbrough, 1998; Vera and

Crossan, 2004). Top management involvement in knowledge sharing is fundamental, since

managers need to emphasize the importance of knowledge sharing by frequently urging

employees to share their knowledge with their colleagues and by developing, supporting

and sustaining the required organizational context.

Strategic leadership theorists (e.g. Hambrick and Mason, 1984) stipulate that decision

making at the top management level is critical to organization outcomes; ‘‘ultimately, it

accounts for what happens to organizations and business units’’ (Hambrick, 1989, p. 5). In

addition, strategic leadership is a key driving force for organizational learning (Vera and

Crossan, 2004) and for knowledge management (Nonaka et al., 2000). Nonaka et al. (2000)

asserts that leaders promote and develop knowledge sharing, create and energize ‘‘ba’’ –

the space in which knowledge is created – and trigger knowledge creation and use. The

way in which knowledge management practices are designed and implemented is a

reflection of corporate and business unit culture, which in turn, is a reflection of the

leadership (Pan and Scarbrough, 1998; Figallo and Rhine, 2002).

Taking the above into consideration, the following hypothesis related to management

support was formulated:

H5. Management support will impact on a business unit’s level of perceived knowledge

usefulness.

The introduction of new products and services is an important precursor of organization

performance (Damanpour, 1991) and new value creation (Tsai and Ghoshal, 1998). The rate

of new product introduction can mirror a firm’s capacity of managing, sharing, creating and

combining new and existing knowledge (Smith et al., 2005).

The innovation literature explains the processes through which firms create differentiated

added value through novelty in products, services and procedures. Innovation can be

defined as the generation and development of new products, services or processes

(Damanpour, 1991), as ‘‘the creation and exploitation of new ideas’’ (Kanter, 1988, p. 170), or

as ‘‘the development and implementation of new ideas (Van de Ven, 1986, p. 590). From an

innovation perspective, knowledge provides firms with the raw material for innovation, and

knowledge sharing enables a potential of combining shared, but previously disparate ideas,

insights and information conductive to the creation of new products, services, and

processes (Cohen and Levinthal, 1990; Kogut and Zander, 1992).

The knowledge transfer theory is concerned with analyzing, predicting and prescribing the

ability and means of an organizational entity to effectively transfer knowledge across its

constituting members. Business units need to provide paths and flows where knowledge is

deliberately distributed. Moreover, they need to make full use of their knowledge (Levin and

Cross, 2004) so as to support innovative activities (Tsai, 2001).

‘‘ The learning organization comprises a set of knowledgequestioning values through which organizations proactivelyquestion long-held routines, taken-for-granted assumptionsand beliefs, resulting in processes of unlearning. ’’


Taking the above into consideration, the following hypothesis related to new product and

services introduction was formulated:

H6. The level of perceived knowledge usefulness of a business unit is associated with

the number of new products and services it introduces.

Overall, the authors have argued that a context characterized by a combination of trust,

motivation, learning orientation, social interaction, and top management support fosters the

perceived usefulness of knowledge within business units and that perceived usefulness of

knowledge will, in turn, positively affect the level of new products and services introduction

as well as the creation of wealth from a wider social perspective. Accordingly, the authors

expect perceived usefulness of knowledge to be an important prerequisite to the innovation

process.

Taking this into consideration, the following hypothesis was formulated:

H7. The level of perceived knowledge usefulness of a business unit mediates the

relationship between the business unit’s context and number of new products and

services.

Method

The majority of past studies on knowledge sharing and its consequences has either adopted

a case study method or has relied on a single informant to answer questions on behalf of an

entire organization. Both these approaches have certain limitations. In this paper, the

authors use multiple respondents’ methodology to evaluate business units on context,

perceived usefulness of knowledge, and innovation output. They then aggregate the

multiple responses to create unit– level measures. This was done in 72 marketing divisions in

business units of 65 Greek Firms, each of which had distinct context and market orientation.

Procedures and sample

Data were collected in two ways, through:

1. two detailed questionnaires, one distributed to the senior management of each marketing

division and the other to selected knowledge workers; and

2. a structured interview with the marketing director or senior deputy of each unit was

conducted to obtain a more complete picture of the organizational context variables.

The authors contacted all 194 medium to large enterprises, which employed more than 100

people, from the Greek ICT, pharmaceutical and food industries. These firms constitute the

research population. Of the 194 firms contacted, 112 firms agreed to participate in the study

(representing a 57.7 percent participation rate). In this paper, preliminary findings of 72

marketing divisions (business units) from 65 of those firms are presented. The total number

of survey respondents was 312 including senior, middle and line management. Because of

missing data on some measures, 295 questionnaires were used for analyses. In order to

mitigate the problem of common method variance or same–source bias (Podsakoff and

Organ, 1986), different levels of respondents for the independent variables and the

dependent variables were used (Gibson and Birkinshaw, 2004). That is, for the independent

variables (i.e. social interaction, trust, motivation, learning orientation, and management

support) responses only from those who identified themselves as line management and

middle management were aggregated. By contrast, for the dependent variables (i.e.

knowledge sharing effectiveness and business unit performance) the authors aggregated

only those respondents who identified themselves as senior management.

Driven from multilevel theory (Klein and Koslowski, 2000), it is critical to aggregate variables

to statistically demonstrate within-unit agreement and between-units differences. Several

analyses to ensure this were conducted. First, the ‘‘interrater agreement score’’ (rwg(j))

(James et al., 1993) was calculated for each variable. This measure ranges from 0 (‘‘no

agreement’’) to 1 (‘‘total agreement’’). Glick (1985) suggested 0.60 as the cutoff for

acceptable interrater agreement values. Mean (median) interrater agreement was above


0.70 for all variables. The intraclass correlation coefficients – ICC(1) and ICC(2) – were also

calculated, using one-way analysis of variance (ANOVA) on the individual level data.

Indication of convergence within units is an ICC(1) greater than zero and that F was

significant (Kenny and La Voie, 1985). In all cases ICC(1) was greater than zero and F was

significant. The ICC(2) values, namely the indication of the reliability of the unit mean were,

also, strong and above 0.65 (described below).

Measures

All constructs were measured with multi-item scales. Scores on these measures were

mean-computed across items. Survey items from published scales were used when

possible, while in some cases, original items to capture Greek firms peculiarities were

developed. These scales were validated with an expert panel of academics and senior

managers and a pretest on a sample of ten business units was conducted as well.

Subsequently, exploratory factor analyses with principle component method was employed

to further validate measures (described below).

Social interaction. The authors measured social interaction, in terms of closeness and

communication frequency, with six items in a seven-point Likert scale. The first item –

closeness of the working relationship – was adapted from Hansen (1999). Respondents, in

the first item were asked to assess their closeness (1 ¼ ‘‘very distant’’ to 7 ¼ ‘‘very close’’)

within their division. Items of communication frequency were adapted by Gupta and

Govindarajan (2000), Hansen (1999), Becerra and Gupta(2003). Respondents were asked

to assess their communication frequency (1 ¼ ‘‘once every three months’’ to 7 ¼ ‘‘once a

day’’) within their division. All items loaded on a single factor having eigenvalue of 2.56 and

accounting for 42.8 percent of the variance. Internal reliability was (a ¼ 0:72) and supported

aggregation (ICCð1Þ ¼ 0:21, ICCð2Þ ¼ 0:65).

Trust. From the many different existing scales of trust-based concepts, the authors adapted

four items from Levin and Cross (2004). Two dimensions of trust were measured

(benevolence and competence trust). Respondents were asked to assess their perceived

trustworthiness (1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly agree’’) within their division. All

items loaded on a single factor having eigenvalue of 2.76 and accounting for 69.1 percent of

the variance. Internal reliability was high (a ¼ 0:84) and supported aggregation

(ICCð1Þ ¼ 0:57, ICCð2Þ ¼ 0:84).

Motivation. Motivation for knowledge transfer was measured with five items of which two

were adapted from Bock et al. (2005). The remaining three were developed by the

authors[1]. Respondents were asked to assess their agreement (1 ¼ ‘‘strongly disagree’’ to

7 ¼ ‘‘strongly agree’’) concerning their motivation to transfer knowledge within their unit.

Items were emphasizing intrinsic motivation, without, however, overlooking extrinsic

motivation. All items loaded on a single factor having eigenvalue of 2.81 and accounting for

65.2 percent of the variance. Internal reliability was high (a ¼ 0:83) and supported

aggregation (ICCð1Þ ¼ 0:39, ICCð2Þ ¼ 0:76).

Learning orientation. The authors measured learning orientation with items based on Baker

and Sinkula (1999). Ten items were used for the three dimensions of learning orientation –

commitment to learning, open-mindedness, shared vision. Ten further items were

aggregated to generate the learning orientation variable. Following Baker and Sinkula

(1999), high correlations among the three dimensions suggest that they can be included in a

‘‘ When units pursue knowledge transfer between their differentactors, contextual factors such as trust, motivation to transferknowledge, management support and learning orientation arecrucial for fostering knowledge transfer and innovation. ’’


common construct. Internal reliability was high (a ¼ 0:92) and supported aggregation

(ICCð1Þ ¼ 0:51, ICCð2Þ ¼ 0:91).

Management support. The authors measured management support with five items adapted

by Vera and Crossan (2004). Respondents were asked to assess their agreement

(1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly agree’’) concerning the extent to which leadership

facilitates knowledge transfer within their division. All items loaded on a single factor having

eigenvalue of 3.5 and accounting for 71.5 percent of the variance. Internal reliability was

high (a ¼ 0:89) and supported aggregation (ICCð1Þ ¼ 0:62, ICCð2Þ ¼ 0:89).

Perceived usefulness of knowledge. The authors combined six items, from Levin and Cross

(2004), Hansen (1999), Szulanski (1996) to create the scale for perceived usefulness of

knowledge. Respondents were asked to evaluate (1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly

agree’’) the extent to which knowledge transfer within the business unit was useful for

business unit’s operation. Principle component analysis demonstrated that all items loaded

on a single factor having eigenvalue of 2.59 and accounting for 64.9 percent of the variance.

Factor loadings were above 0.7. Internal reliability was high (a ¼ 0:81) and supported

aggregation at the unit– level of analysis (ICCð1Þ ¼ 0:45, ICCð2Þ ¼ 0:77).

New product and services. This was measured as the number of new products that the

marketing division had introduced during the last year (Smith et al., 2005). This measure was

significantly correlated with the number of unit personnel (r ¼ 0:50, p , 0:01).

Control variables. Business unit size, market share, market growth and competition intensity

were used as control variables. Size was measured using the natural logarithmic

transformation of a unit’s number of full-time employees. Each of the rest variables were

adopted and measured with one item in a seven-point Likert scale.

Results

Means, standard deviation and correlations among the variables are reported in Table I. The

hypotheses were tested using ordinary least squares (OLS) regression. Table II reports the

results of regression analyses, where perceived usefulness of knowledge and new products

and services are the corresponding dependent variables. Four models, illustrated in Table II,

were produced. Model 1 presents the relationship between the dependent (new products

and services) and the mediator (perceived usefulness of knowledge). Model 2 tests the

effect of the independent variables (business unit context characteristics) to the mediator

(perceived usefulness of knowledge). Model 3 relates the independent variables (business

unit context characteristics) to the dependent variable (new products and services) and in

Model 4 the effect of independent variables and the mediator to the independent variable is

tested.

Regarding the impact of business unit context to perceived usefulness of knowledge,

(Model 2; H1-H5), social interaction was unrelated to perceived usefulness of knowledge,

while trust has positive and significant influence to perceived usefulness of knowledge

Table I Descriptive statistics and correlationsa

Variableb Mean s.d. 1 2 3 4 5 6 7 8

1. Trust 5.87 0.792. Motivation 5.35 0.97 0.45**3. Shared vision 5.81 1.18 0.74 0.52**4. Open-mindedness 5.64 0.95 0.72** 0.33** 0.62**5. Commitment to learning 5.63 0.98 0.62** 0.62** 0.69** 0.59**6. Management support 5.54 0.86 0.63** 0.49** 0.55** 0.60** 0.57**7. Social interaction 6.06 0.75 0.50** 0.29** 0.53** 0.40** 0.38** 0.40**8. Perceived usefulness of knowledge 6.14 0.65 0.45** 0.51** 0.42** 0.30** 0.56** 0.18 0.22*9. New products and services 3.61 3.97 0.03* 0.01* 0.06 0.08 0.02 0.07 0.07 20.05

Notes: an ¼ 72 (business units); blearning orientation includes shared vision, open-mindedness and commitment to learning; *p , 0.05;**p , 0.01


(b ¼ 0:31, p , 0:05), thus supporting H2. Motivation was also found positively related to

perceived usefulness of knowledge (b ¼ 0:22, p , 0:05), supporting H3 and learning

orientation – namely shared vision, open-mindedness, commitment to learning – was

marginally positively to perceived usefulness of knowledge (b ¼ 0:26, p , 0:05), hence

confirming H4. Management support has strong and significant relation with perceived

usefulness of knowledge (b ¼ 20:33, p , 0:001), thus providing support for H5.

Consistent with H6, a unit’s level of perceived usefulness of knowledge was significantly

associated to its number of new products and services (b ¼ 20:11, p , 0:05). In addition,

unit size (b ¼ 0:50, p , 0:01), competition intensity (b ¼ 0:16, p , 0:01), and market share

(b ¼ 0:04, p , 0:10) were directly related to innovation as expected, whereas market growth

was unrelated.

It was also expected that perceived usefulness of knowledge would mediate the

relationships between the independent variables (trust, motivation, management support,

social interaction and learning orientation) and the number of new products and services.

Following Baron and Kenny (1986) the mediation analysis includes three steps. The first step

is to ensure and examine the existence of a relationship between independent variables

(here trust, motivation, management support, social interaction and learning orientation) and

the mediator (here perceived usefulness of knowledge). As shown in model 2 (see Table II),

with the exception of social interaction, all of the variables were significantly related with the

mediator. The second step is to analyze whether a significant relationship between the

independent variables and the dependent variable (here new products and services) exists.

In model 3 (Table II) this is found for the management support variable. As a final third step,

the previously significant relationships between dependent variable (here new products and

services) and independent variables (here management support) from model 4 were no

longer significant when a business unit’s level perceived usefulness of knowledge was

entered in the equation.

Discussion

This study is a first attempt to show that the construct ‘‘perceived usefulness of knowledge’’

is a critical proxy of knowledge transfer effectiveness, as well as to find support for its

positive relationship with innovation. The research attempted to answer two basic questions:

first, how do factors of a business unit context affect the level of perceived usefulness of

knowledge; and second, how does the unit’s level of perceived knowledge usefulness

influence innovation-related outputs?

Table II Results of regression analysisa

Model 1:dependent variable,new products and

services

Model 2:dependent variable,perceived usefulness

of knowledge


services


servicesVariables b t b t b t b t

No. of employees 0.40 2.48* 0.51 1.70** 0.43 2.48* 0.50 2.93**Competition 0.14 3.15* 0.12 1.47 0.14 3.01** 0.16 3.43**Market growth 0.01 0.50 0.02 0.43 0.02 0.80 0.03 0.94Market share 0.06 2.63* 20.03 20.70 0.05 1.81b 0.04 1.67b

Trust 0.31 2.32* 0.05 0.60 0.09 1.19Motivation 0.22 2.60* 20.09 21.81b 20.05 21.11Management support 20.33 23.40*** 0.02 0.32 20.03 20.53Social interaction 20.02 20.23 0.02 0.44 0.02 0.39Learning orientation 0.26 2.06* 20.01 20.02 0.04 0.51Perceived usefulness of knowledge 20.11 22.02* 20.15 22.10*R2 0.33 0.48 0.33 0.38Adjusted R2 0.28 0.40 0.23 0.29F 6.525*** 6.320*** 3.425** 3.697**

Notes: an ¼ 72 business units; bp , 0.10; *p , 0.05; **p , 0.01; ***p , 0.001


The research shows that when units pursue knowledge transfer between their different

actors, contextual factors such as trust, motivation to transfer knowledge, management

support and learning orientation are crucial for fostering knowledge transfer and innovation.

This contribution is important since the need for developing an organizational context where

knowledge transfer and innovation flourish is constantly put forth in the business press, while

the empirical and research based evidence for its importance has been scarce. The analysis

further reveals that perceived usefulness of knowledge leads to innovation, measured by

new product introduction. In turn, the authors showed that perceived usefulness of

knowledge fully mediates the relationship between management support and the number of

new products and services, which is a contribution to innovation theory and its relation to

knowledge.

These results can also have a wider implication at the spatial level. Over the last three years,

the Attica region in Greece has scored very high in terms of innovation in the IT services

sector (European Commission, 2006), one of the sectors analyzed in this research. It is clear

that the emergence of such a knowledge intensive industry in a country that traditionally has

been characterized as an innovation follower depends on the extent to which individual

organizations can leverage knowledge dynamics. This knowledge exploitation must be

rooted in the deeper social processes with the organization. Having established a firm

relationship between organizational context and innovation, this research sets a foundation

for further exploring the organization-environment link in terms of leveraging organizational

knowledge dynamics to create and maintain regional competitiveness and knowledge

clusters.

The study has limitations that should be acknowledged. In the research it was assumed that

knowledge transfer has occurred within business units if the unit’s outcomes are reported to

have improved as a result of perceived usefulness of knowledge. Hence it is assumed

beforehand that some process of knowledge transfer occurs within the organizational unit.

Moreover, the study required respondents to report on their perceptions within business

units. To overcome this problem and minimize perception bias, besides using a

multiple-respondent research design, the authors prompted respondents to answer

questions beginning with ‘‘to the best of your knowledge, regardless of whether or not you

had a prior relationship with this person . . . ’’.

Note

1. The steps followed to develop these three items were: extensive literature review; in-depth

interviews with both academics and business experts (face and content validity); pretest of the

survey for clarity and appropriateness; and exploratory factor analysis.

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About the authors

Dimitris Brachos is a research fellow at the Management Science Laboratory (MSL) inAthens University of Economics and Business (AUEB). He holds a PhD from AthensUniversity of Economics and Business, Greece. His research concentrates on knowledgemanagement, knowledge sharing and innovation. He is the corresponding author and canbe contacted at: [email protected] (www.msl.aueb.gr)

Konstantinos Kostopoulos is a research fellow at MSL, AUEB from where he also holds hisPhD in Innovation Management. His research concentrates on innovation and learning, andknowledge management.

Klas Eric Soderquist is an Assistant Professor and head of the MSL’s Innovation andKnowledge Management Unit at (AUEB). He holds and MSc from the Royal Institute ofTechnology in Stockholm, Sweden and a DBA from Brunel Univeristy. He is also a VisitingProfessor at the Grenoble Ecole de Management, France. His research concentrates onknowledge management, R&D and innovation management, and he has published in theJournal of Product Innovation Management, Long Range Planning, R&D Management andOmega, among others.

Gregory Prastacos is a Professor and Director of the Management Science Laboratory at theAthens University of Economics and Business. He holds a PhD from Columbia University,USA. His research concentrates on management science, information technology, and theiruse for business transformation in the information society. He has published in ManagementScience, Operations Research, Long Range Planning, Journal of Knowledge Management,Journal of Innovation Management, among others.


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