Knowledge transfer between supply chain partners

Int. J. Process Management and Benchmarking, Vol. 1, No. 3, 2006

Knowledge transfer between supply chain partners: a conceptual model Qile He Middlesex University Business School, The Burroughs, London NW4 4BT, UK E-mail: [email protected]

Abby Ghobadian and David Gallear* Brunel Business School, Brunel University, Elliott Jaques Building, Uxbridge, Middlesex UB8 3PH, UK E-mail: [email protected] E-mail: [email protected] *Corresponding author

Amrik Sohal Faculty of Business and Economics, PO Box 197, Caulfield East, Vic 3145, Australia E-mail: [email protected] Abstract: The opportunity to learn more effective practices from firms operating within a strategic supply chain partnership is viewed as critical to enhanced competitiveness. Despite the perceived importance of knowledge transfer in a strategic supply chain partnership there is a paucity of conceptual models depicting the variables that have an impact on transfer effectiveness. This paper presents such a model and discusses how the variables are inter-related, through systematically reviewing the literature. The model development process involved both induction and deduction. The authors contend that the proposed model contributes to the developing literature and is of relevance to both researchers and practitioners. Keywords: knowledge; knowledge transfer; supply chain; buyer-supplier partnership. Reference to this paper should be made as follows: He, Q., Ghobadian, A., Gallear, D. and Sohal, A. (2006) ‘Knowledge transfer between supply chain partners: a conceptual model’, Int. J. Process Management and Benchmarking, Vol. 1, No. 3, pp.231–262. Biographical notes: Qile He is a Research Associate at Middlesex University Business School. He received his first degree, a BA in Economics from the University of Colorado at Denver. Subsequently he gained an MSc in Financial Decision Management from the University of Luton and an MSc in Research Methods from Middlesex University. He is now pursuing his PhD at Middlesex University. His principal research interest is the knowledge transfer processes and practices in the context of firms’ supply chain management.

Copyright © 2006 Inderscience Enterprises Ltd.

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Q. He, A. Ghobadian, D. Gallear and A. Sohal Abby Ghobadian is Professor of Management at Brunel Business School and Visiting Professor at Warwick Business School. He is author/co-author of seven research monographs, two edited books, over 60 refereed journal papers, and numerous chapters in books and conference papers. His research interests lie in examining the reasons for heterogeneous organisational performance and how organisational performance can be improved. David Gallear is Senior Lecturer in Operations Management at Brunel Business School. His research interests include operations strategy, quality management and supply chain management. Current work focuses on examining the nature, form and determinants of supply chain purchasing strategy relationships. He has authored/co-authored two research monographs, two edited books and a significant number of papers. Amrik Sohal is a Professor in the Department of Management and Associate Dean, Research Development in the Faculty of Business and Economics at Monash University. He has authored or co-authored over 100 papers in refereed journals, as well as three books and a number of chapters contributed to books. His current research interests are in manufacturing/operations strategy, technology/information management, quality management, supply chain management, lean/agile production systems and electronic business.

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Introduction

Hyper competition has propelled supply chain partnerships to the forefront of practitioners’ and researchers’ agenda (for example, Harland, 1996; Christopher, 1998; Monczka et al., 1998). A supply chain is a network of actors that transform raw materials into distributed products (Bowersox et al., 1999). In some supply chains members seek to develop long-term collaborative relationships in pursuit of stability and predictability, however, to avoid inflexibility links are severed when needs change (Hult et al., 2004). The proponents of strategic supply chain partnerships argue that partnership enables the members to develop new solutions to complex problems by creating stability, enhancing synchronisation, improving coordination, increasing innovativeness, aiding information flow and encouraging learning (Hult et al., 2002, 2004). The outcome is faster cycle times, improved quality, better delivery performance, lower costs, higher market share and ultimately higher profitability and return on investment for members of the chain (Macbeth and Ferguson, 1994; Christopher, 1998; Monczka et al., 1998). In short, strategic supply chain partnership offers long-term competitive advantage in highly turbulent and low munificence environments coupled with ever more demanding customer expectations (Lemke et al., 2003). The attraction of this promise has led firms to invest vast sums to improve supply chain processes, for example, UPS spent $9 billion between 1986 and the late 1990s to improve its supply chain (Farhoomand and Ng, 2000). A number of prepositions have been advanced to explain why partnership results in improved performance. Lawrence et al. (2002) posit that through repeated interactions, groups of organisations develop common understandings and superior practices. On the other hand, Gray (1989) argued that collaborative relationships facilitate a greater level of innovation. The combination of these two propositions led (Lawrence et al., 2002) to theorise that collaboration results in new practices, technologies and rules, hence,

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improved performance. This point of view is supported by other scholars who argue that partnership can potentially act as a source of additional information and new ideas critical to the development of sustainable competitive advantage (Powell et al., 1996; Dyer and Singh, 1998; Inkpen, 1998; Dussauge et al., 2000). The above propositions and resulting theory are implicitly based on the assumption that the exchange of knowledge between the collaborating organisations goes beyond that which takes place in a typical market transaction. In fact, many scholars argue that the key incentive for businesses to form supply chain partnership, apart from stability and predictability, is the potential for exchange of knowledge and access to best practice (Contractor and Lorange, 1988; Lamming, 1993; Mody, 1993; Crossan and Inkpen, 1995; Mowery et al., 1996; Kale et al., 2000; Chen, 2004). Supply chain theory development is at an early stage and despite the recognised catalytic role of knowledge transfer within the strategic supply partnership there is a paucity of conceptual models depicting both the key factors influencing knowledge transfer between supply chain partners and the knowledge transfer mechanisms (Bessant et al., 2003; Hult et al., 2004). The aim of this paper is to address this gap by developing a conceptual model of knowledge transfer within strategic supply chain partnerships grounded in theory and empirical research. A three-stage process was used to develop the conceptual model presented in this paper. First, an initial inductive skeleton model was developed. To this end, the authors identified theories relevant to the knowledge transfer process in the context of strategic supply chain partnerships and used these to isolate appropriate variables from prior empirical studies. Second, a deductive process was used, by conducting an extensive review of the literature, to verify the relevance of these variables. Third, with the help of literature, the relationship between factors identified previously was examined, to develop a comprehensive conceptual model of knowledge transfer in the context of strategic supply chain partnership. The process used follows Ginsberg and Venkatraman’s recommendation, that “... an analytic review scheme is necessary for systematically discerning patterns from a widely differing set of studies and evaluating the contributions of a given body of research.” (Ginsberg and Venkatramans, 1985, p.422)

Moreover, the framework constitutes a well-specified model, which can help guide future research. The rest of the paper is organised into seven sections. Supply chain partnership literature is reviewed in the next section. This is followed by presentation of the initial skeleton model. Next the stages of knowledge transfer process are examined, followed by organisational factors influencing interfirm knowledge transfer. This is followed by an examination of relationships between the organisational factors and the stages of knowledge transfer, and an examination of relationships amongst these organisational factors. Next our comprehensive conceptual model is presented. In the final section our conclusions are elaborated.

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Q. He, A. Ghobadian, D. Gallear and A. Sohal

Strategic supply chain partnership: an overview

The nature of the relationship between actors in a supply chain varies along a continuum – at one end they operate at arms-length and at the other end they operate as a virtually vertically integrated entity (Spekman et al., 1998; Mentzer et al., 2000; Knemeyer et al., 2003; Moberg and Speh, 2003). In between there are different levels of cooperation. The extant literature suggests that supply chains characterised by a high level of cooperation are more effective than those relying on traditional market mechanisms and operating at arms-length from each other (for example, Macbeth and Ferguson, 1994; Lambert et al., 1996; Spekman et al., 1998; Dyer and Nobeoka, 2000). Collaboration is defined as a cooperative, interorganisational relationship that is negotiated in an ongoing communicative process and that relies on neither market nor hierarchical mechanisms of control (Heide, 1994; Lawrence et al., 1999; Phillips et al., 2000; Lawrence et al., 2002). In the supply chain context, cooperation is considered as a step towards partnership (for example, Spekman et al., 1998). The difference between cooperation and partnership is best summarised by a quote from Copacino (1996, p.60), “although it is challenging to develop true partnership relationship, the fact is that without strategic partnerships, it is impossible to manage the supply chain as a single entity”. The implication here is that strategic supply chain partnership is characterised by a high level of integration. Despite its popularity there is no commonly accepted definition of strategic partnership (Lemke et al., 2003). Table 1 depicts a range of definitions provided by supply chain researchers. These definitions, whilst different, share a number of important common characteristics. All the definitions imply a high level of interdependence characterised by shared: goals, information, reward, risk and practices. Implicit in all the definitions is the belief that the ultimate outcome of partnership is enhanced competitiveness. Table 1

Definitions of strategic supply chain partnership

Author(s) Mohr and Spekman (1994) Ellram (1995)

Lambert et al. (1999) Mentzer et al. (2000) Kotabe et al. (2003) Hult et al. (2004)

Definition Purposive strategic relationships between independent firms who share compatible goal, strive for mutual benefit, and acknowledge a high level of mutual interdependence An agreement between a buyer and a supplier that involves a commitment over an extended time period, and includes the sharing of information along with a sharing of the risks and rewards of the relationship A tailored business relationship based upon mutual trust, openness, shared risk and shared rewards that yield a competitive advantage, resulting in business performance greater than would be achieved by the firms individually An inter-organisational entity developed between two independent organisations in a vertical relationship within a supply chain Buyer-supplier relationship or partnership is set of practices and routines that support economic exchanges between the two firms Members of the chain are strategically, operationally, and technologically integrated

The importance of strategic supply chain partnership as a catalyst for knowledge transfer is acknowledged by many researchers (for example, von-Hippel, 1988; Love and


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Gunasekaran, 1999; Kotabe et al., 2003). On the other hand, because chain members are not part of the same organisation, knowledge sharing potentially plays an important coordinating function, and thus, it is central to effective functioning of the chain (Hansen, 2002). It is contended that effective sharing of knowledge among supply chain partners can potentially increase profitability because the flow of know-how, practices, and technology is a critical source of new ideas resulting in innovation and sustainable development of the entire supply chain (for example, Beecham and Cordey-Hayes, 1998; Kotabe et al., 2003; Lamming et al., 2004). Prior research also points to the importance of integration, for example, linking relationship and technology strategy together to facilitate technological innovations via links developed around supply chain nodes (Lamming, 1993). Dussauge et al. (2000) showed that ‘link alliances’ – that is to say, negotiated interorganisational partnerships which are formed by partners contributing differently but complementarily to the alliance – offer greater opportunities for learning. For example, customer-supplier relationship is more likely to lead to knowledge transfer than other forms of strategic alliances. The review of literature suggests that relatively few studies have addressed the interfirm knowledge transfer between strategic supply chain partners. Beecham and Cordey-Hays (1998) examined the knowledge transfer in a particular type of buyer-supplier partnership in the UK motor industry, which they referred to as technology partnering. They defined technology partnering as a relationship between supplier and customer that encourages the development of technology to meet the customer’s requirements. Dyer and Nobeoka (2000) examined Toyota’s knowledge transfer practices to demonstrate the role of supply chain partnership in strengthening effective learning and knowledge transfer. Kotabe et al. (2003) examined the influence of technical exchange and technological transfer between suppliers and buyers and how the exchange contributed to the supplier performance improvement in the automotive industry. The empirical studies, although few in number, demonstrate a positive link between knowledge transfer and improved performance. However, they do not provide a model showing the variables that potentially influence the effectiveness of knowledge transfer within a strategic supply chain partnership. The aim of this paper is to address this gap in the literature.

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Initial conceptual model of interfirm knowledge transfer

The definitions of strategic supply chain partnership presented in Table 1 and prior studies suggest that institutional theory, Resource-Based View (RBV), Knowledge-Based View (KBV), and organisational learning all play a role in explaining interorganisational knowledge transfer and its potential impact (for example, Hult et al., 2002, 2004; Lawrence et al., 2002). These theories were used to guide our examination of the prior empirical research investigating interfirm knowledge transfer. The review covered the period 1990–2004 and examined interfirm knowledge transfer within different types of partnership including that of strategic supply chain partnership. Table 2 depicts the outcome of this review along four dimensions of interest to this study – the type of interfirm relationship studied, method and unit of analysis, variables examined and outcomes of the study.

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Q. He, A. Ghobadian, D. Gallear and A. Sohal List of prior studies of interfirm knowledge transfer

Knowledge transfer between supply chain partners: a conceptual model Table 2

List of prior studies of interfirm knowledge transfer (continued)

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Q. He, A. Ghobadian, D. Gallear and A. Sohal List of prior studies of interfirm knowledge transfer (continued)

Knowledge transfer between supply chain partners: a conceptual model Table 2

List of prior studies of interfirm knowledge transfer (continued)

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The strategic alliances reviewed included both equity and non-equity type strategic alliances (Mowery et al., 1996; Simonin, 1997, 1999). Other studies examined knowledge transfer in the context of joint ventures established in Japan (Ritcher and Vettel, 1995). Research and Development (R&D) alliances provided the context for Powell et al.’s (1996) research. They examined knowledge transfer between a biotechnology firm and range of organisations such as hospitals, universities and government agencies. Yet another group of researchers concurrently examined knowledge transfer in the context of different types of partnership, for example, Cummings and Teng (2003) examined inter and intra firm knowledge transfer. More specifically they studied knowledge transfer between different R&D units of a firm, intra firm R&D-related knowledge transfer as a part of strategic alliance, and knowledge transfer flowing from equity acquisitions. Strategic supply chain partnership provided the context for three of the studies reviewed (Beecham and Cordey-Hayes, 1998; Dyer and Nobeoka, 2000; Kotabe et al., 2003). The studies examined view knowledge transfer as a learning process where knowledge is acquired from the source firm and exploited by the recipient firm to generate additional benefits (Cohen and Levinthal, 1990; Calantone et al., 2002; Cummings and Teng, 2003). However, they also highlight the importance of mutual learning by pointing out that a firm can simultaneously receive and transmit knowledge. The study by Mowery et al. (1996) showed that knowledge transfer is more effective in bilateral contract-based alliances (for example, technology sharing and joint development agreement) than in unilateral contract-based alliances (for example, licensing agreement). A similar point was made by Kotabe et al. (2003) in the context of strategic supply chain partnership. They argued that firms in a supply chain value bilateral knowledge exchange above that of unilateral knowledge flow. The studies examined also suggest that irrespective of the type of cooperation the resulting knowledge transfer is a source of both intangible and tangible benefits to the recipient of knowledge. The studies have concluded that effective knowledge transfer results in important intangible benefits such as enhanced innovation capabilities, improved future learning capacity, and better visibility (Powell et al., 1996; Calantone et al., 2002; Cavusgil et al., 2003). Moreover, that effective knowledge transfer yields improved efficiency, reduced cost, improved product quality, shorter cycle times, enhanced productivity, and enhanced competitiveness (Inkpen, 1998; Dyer and Nobeoka, 2000; Cavusgil et al., 2003; Kotabe et al., 2003). These studies also generally highlight the value of external knowledge to the recipient firms. Variables compatible with the theoretical underpinning of our study and pertinent to its aims are presented in italic in Table 2. We used this information and the relevant theories to construct an initial model (Figure 1). The model was then used to guide the conduct of the literature review, targeted at each link identified by the model. The aim was to ascertain further support for the links proposed by the initial skeleton model, identify how a particular variable may influence the knowledge transfer process, and establish the potential links between the different variables.

Knowledge transfer between supply chain partners: a conceptual model Figure 1

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Initial model of interfirm knowledge transfer

The remainder of the paper is devoted to discussing each variable and its influence on the effectiveness of knowledge transfer with particular reference to strategic supply chain partnerships.

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The knowledge transfer process

The starting point for our in-depth literature review was the heart of the model presented in Figure 1, that is to say, the knowledge transfer process. The information processing model of organisation posits that a firm’s main task is to gather, process, and act on data from the environment (Daft and Weick, 1984). The proposed model of organisation overlays the organisational learning model. The organisational learning literature distinguishes between single-loop and double-loop learning (Argyris and Schon, 1978). The primary purpose of single-loop learning is to detect errors and keep the organisation on track while the purpose of double-loop learning is to reflect on the single-loop learning and investigate the underlying causes and assumptions. In the single-loop learning mode managers adjust the variables to attain the desired steady state. In the double-loop learning mode, on the other hand, managers ask why the steady state is what it is, and whether or not a different steady state may yield the desired output more efficiently and effectively. The authors theorise that effective knowledge transfer in the context of strategic supply chain management is mainly grounded in double-loop learning, that is to say, questioning the existing assumptions, norms and practices. The knowledge transfer literature is broadly agreed on the notion that transfer is a multi-step process. However, there is some division as to the nature of these steps. Table 3 depicts the steps proposed by different scholars.

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Table 3

The steps of knowledge transfer process

Author(s)

Steps

Cohen and Levinthal (1990)

Recognise Assimilate Apply

Huber (1991)

Knowledge acquisition Information distribution Information interpretation Organisational memory

Grant and Banden-Fuller (1995)

Acquiring Storing Applying

Grant (1996)

Transmit knowledge Receive knowledge

Lorange (1996)

Discover new knowledge Adapt new knowledge

Powell et al. (1996)

Access knowledge Utilise knowledge

Wiig (1997)

Create or import knowledge Organise and store knowledge Distribute and pool knowledge Apply knowledge

Crossan and Berdrow (2003)

Intuiting Interpreting Integrating Institutionalising

Cummings and Teng (2003)

Acquiring Internalising

The apparent differences between the knowledge transfer steps presented in Table 3 are often due to semantics rather than conceptual differences. The three steps that appear in most models of knowledge transfer are: acquisition, internalisation and utilisation. We adopted these three steps in building our conceptual model. Huber (1991) identified ‘organisational memory’ as a step in the learning process. As is discussed later, ‘organisational memory’ plays a fundamental role, consequently it is included as one of the organisational factors in our model. Each of the three steps in the learning process is examined separately in the following sections. However, prior to this review, it is important to note that a significant proportion of the empirical research reviewed in Table 2 conceptualised knowledge transfer as a single-stage process (Mowery et al., 1996; Simonin, 1999; Calantone et al., 2002; Cavusgil et al., 2003; Kotabe et al., 2003). A minority of studies used a multi-stage process explicitly’ to model knowledge transfer (Ritcher and Vettel, 1995; Cummings and Teng, 2003). In their examination of


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knowledge transfer between joint venture firms (Ritcher and Vettel, 1995) used three steps – perception, internalisation and abstraction – to model the knowledge transfer process. Cummings and Teng (2003) on the other hand used two steps – acquisition and internalisation – to model knowledge transfer. Overall, most empirical researchers tend to treat the knowledge transfer process as a black box, in that they only consider the input and output side of this process. Overall, it is believed that to view knowledge transfer as a black box is a weakness, because understanding the knowledge transfer process is essential to understanding what affects the effectiveness of the process.

4.1 Knowledge acquisition Knowledge acquisition is the first step in an improvement journey and the effective operation and coordination of a strategic supply chain partnership. The KBV posits that an organisation’s relative ability to acquire and develop knowledge differentiates high and low performance (Grant, 1996). Improvement is predicated on change, and the extant literature broadly agrees that recognition is a prerequisite for change (for example, Kotter, 1995; Weick and Quinn, 1999) and that recognition is a function of knowledge acquisition. In the context of strategic supply chain partnership, knowledge acquisition enhances the knowledge flow in each node of the supply chain (Hult et al., 2004). According to the KBV the flow of information will enhance each node’s ability to efficiently perform its role (Hult et al., 2004). The improvement in outcome is dependent on nodes making changes to ineffective processes and practices. Knowledge acquisition is concerned with how a firm identifies, accesses and acquires knowledge from the supply chain nodes. The process occurs at both individual and organisation level. The primary unit of knowledge acquisition, storage and application is an individual (Grant, 1996; Spender, 1996). In the context of a strategic supply chain partnership individuals build extensive contact with their counterparts in different nodes, are likely to develop understanding and trust-based relationship overtime, and therefore, could serve as agents of knowledge transfer. For example, Toyota exchanges employees with its suppliers in an attempt to create shared purpose and transfer knowledge (Dyer and Nobeoka, 2000). The key challenge for organisations is to capture and utilise this knowledge. At the firm level knowledge acquisition activities are organised on either a bilateral or multilateral basis (Dyer and Nobeoka, 2000). Bilateral knowledge acquisition involves transfer of knowledge between two firms. Normally in this type of situation one firm acquires knowledge from another firm. Examples include joint development agreement, technology exchange/sharing, inter-firm visit and joint employee training (for example, Appleyard, 1996; Lorange, 1996; Mowery et al., 1996; Beecham and Cordey-Hayes, 1998; Cummings and Teng, 2003). Multilateral knowledge acquisition is concerned with a network of firms where members have equal access to the knowledge available and the exchange of knowledge takes place simultaneously between several firms. Examples include industry association, joint management meetings, and joint problem solving teams (for example, Mody, 1993; Dyer and Nobeoka, 2000; Cummings and Teng, 2003; Kotabe et al., 2003). Both bilateral (Beecham and Cordey-Hayes, 1998; Kotabe et al., 2003) and multilateral (Dyer and Nobeoka, 2000; Kotabe et al., 2003) modes of knowledge transfer could exist within a strategic supply chain partnership. Moreover, both approaches can provide supply chain partners with effective means to access and acquire external knowledge. However, it is the opportunity for multilateral knowledge

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transfer that distinguishes strategic supply chain partnership from other forms of alliances (Pekar and Allio, 1994). For instance, Toyota has formed Kyohokai (supplier association) with its suppliers to create a forum for multilateral information exchange and to enhance network identity (Dyer and Nobeoka, 2000).

4.2 Knowledge internalisation The theories that underpin our model place a significant emphasis on outcome. Knowledge acquisition is a necessary but not sufficient condition to enhance outcome in terms of improved individual firm efficiency or effectiveness of the whole of the supply chain network. As Mowery et al. (1996) pointed out, an interfirm alliance offers the opportunity to access knowledge, but knowledge that is not internalised is unlikely to enhance organisational capability. Knowledge internalisation is concerned with the ability of a firm to absorb the acquired knowledge so as to enhance its own internal capabilities. A firm’s ability to absorb knowledge influences whether or not the acquired knowledge can be successfully exploited (Cohen and Levinthal, 1990). This point of view is shared by Cummings and Teng (2003, p.42). They argued that “only when a recipient internalises knowledge can it be sufficiently understood and adapted by the recipient to allow for its effective re-creation and ultimately its use”. The internalisation of the knowledge has three main facets: storing knowledge, disseminating knowledge and combining the existing know-how with the new knowledge (Kogut and Zander, 1992; Wiig, 1997). The ability to grasp and store the acquired knowledge is the first stage of absorption. This requires experts to understand, interpret and capture the knowledge (Cohen and Levinthal, 1990) and adequate technology to store the knowledge (Wiig, 1997). Second, knowledge needs to be disseminated appropriately. It should, for example, flow to the relevant people or embedded into the appropriate part of the existing systems (Wiig, 1997). The greater the flow, the better timed and accurate targeting of knowledge the greater the level of improvement attained (Hult et al., 2004). Third, a firm needs to possess combinative capability (Kogut and Zander, 1992). This refers to the ability of a firm to transform the newly acquired knowledge into a compatible form and to combine it with the accumulated prior knowledge ready for use by the firm (Grant, 1996; Mowery et al., 1996). A number of different approaches are used to measure the effectiveness of a firm’s knowledge internalisation. Some researchers advocate the use of patent citation data to measure the extent of technological knowledge absorbed by a firm from other firms. They argue that change in technology patents tends to reflect the absorption of external knowledge (for example, Almeida, 1996; Mowery et al., 1996). Others recommend use of three different indicators, namely knowledge ownership (Mowday et al., 1979), satisfaction with transferred knowledge (Szulanski, 1996) and commitment to the knowledge (Pierce et al., 2001). Based on these indicators Cummings and Teng (2003) empirically assessed the extent of knowledge absorbed by a firm in strategic alliances.

4.3 Knowledge utilisation Knowledge utilisation forms the last stage of the knowledge transfer process. Here the knowledge acquired and absorbed into a firm’s internal systems is applied to improve processes, practices and products or services (Wiig, 1997). Moreover, a firm could use the knowledge to enhance its ‘dynamic learning capability’ (Dyer and Nobeoka, 2000) by


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improving its innovative capabilities and/or capacity for future knowledge creation (Calantone et al., 2002; Cavusgil et al., 2003). In the context of strategic supply chain partnership, effective knowledge acquisition, internalisation and utilisation results in significant tangible and intangible benefits. For example, Dyer and Nobeoka’s (2000) study revealed that effective knowledge transfer practices yielded significant productivity improvement for Toyota and its suppliers as well as a reduction in inventory levels. Similarly, Kotabe et al. (2003) showed that interfirm technical exchange and technology transfer improved suppliers’ operational performance along a number of dimensions including that of process design, product design, product quality and reduction in lead time. In the case of intangible benefits, supply chain partners could enhance their learning through knowledge transfer practice and improve internal capabilities to generate further innovations or simply learn more in the future (Calantone et al., 2002; Cavusgil et al., 2003).

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Organisational factors influencing interfirm knowledge transfer

The knowledge transfer process is affected by a range of factors. Guided by our underpinning theories and previous empirical research, Figure 1 has aided in the identification of key broad organisational factors that could potentially influence the knowledge transfer process. The starting point was the institutional theory. Through repeated interaction, nodes in a strategic supply chain partnership develop common understandings and practices that form the institutions that define the field, at the same time, these institutions shape the ongoing patterns of interaction from which they are produced (Lawrence et al., 2002). Institutions represent widely diffused and entrenched practices, technologies and rules. Partnership has an institutional effect because it represents an arena in which the process of structuration described by DiMaggio and Powell (1983) can be enacted: interorganisational interaction can increase in intensity, coalitions can form, information can be exchanged, and an awareness of involvement in a common enterprise can develop, giving rise to new practices, technologies and rules (Lawrence et al., 2002). The RBV posits that a firm’s competitive advantage is tied to its ability to capitalise on its strategic resources (Wernerfelt, 1984; Barney, 1991; Peteraf, 1993). Strategic resources are those resources that are rare, valuable and difficult to imitate (Barney, 1991). Culture is a strategic resource (Barney, 1986) and it can develop through interaction among supply chain members. For these reasons, learning intention and achieved memory were included in our initial skeleton model. The other three variables in this part of model are rooted in the KBV and learning theory. With the help of theoretical and empirical literature we discuss how these factors influence the nature of interfirm relationship and as the result affect the process of socialisation and structuration in the context of strategic supply chain partnership. Moreover, the impact of these factors on the knowledge transfer process are discussed.

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5.1 Nature of interfirm relationship The KBV implies that the coordinating network mechanisms tend to influence the effectiveness of interfirm knowledge transfer (Grant and Banden-Fuller, 1995). Moreover, the coordinating arrangements are heavily influenced by the nature of the relationship between firms (Grant and Banden-Fuller, 1995; Mowery et al., 1996). In this sense, the relationship interface, in other words how partner firms interact with each other, tends to determine the success of interfirm knowledge transfer. Dyer and Nobeoka (2000) argued that if a network can create a strong identity and coordinating rules, then the network could be more effective in creating and recombining knowledge than the individual member firms. Many of the studies reviewed examined the influence of the interfirm relationship on effectiveness of knowledge transfer. In their study, Mowery et al. (1996) focused on the effect of alliance structure on knowledge transfer, while Dyer and Nobeoka (2000) examined the role of network strength. Cavusgil et al. (2003) examined the influence of relationship strength and concluded that interfirm relationship strength affects the extent of tacit knowledge transfer. Kotabe et al. (2003) empirically tested the mediating effect of link duration and found that the length of the link enhanced the amount of technology transfer and the magnitude of supplier performance. Another related factor is the nature of communication in the strategic supply chain partnership. Cummings and Teng (2003) concluded that interactive interface and iterative communications between parties promotes knowledge transfer success. Similarly, Chen (2004) suggested that partner interaction in terms of trust and mutual adjustment have positive effects on knowledge transfer performance. Another dimension is the relative power of partners. Beecham and Cordey-Hayes (1998) argued that good partnering arrangements depend on the stable balance of power between the partners, and went on to demonstrate that failure of technology partnerships relates to relentless struggles for superiority, that is, power tussle (Beecham and Cordey-Hayes, 1998, p.203). On the other hand Dyer and Nobeoka (2000) study concluded that the powerful position of Toyota aided the process of knowledge transfer among its supply chain partners. Theory and the review of the literature led us to conclude that the nature of interfirm relationship in the context of strategic supply chain partnership is affected by its: strength, duration, balance of power and common understanding. The relationship strength is defined as “the extent or degree of closeness or strength of the relationship between or among organisations” (Golicic et al., 2003, p.61). According to Golicic et al. (2003), ‘strength’ helps to determine the nature of interfirm relationship. Strength of the relationship is a function of trust, commitment, interdependence, communication, investment and shared risks/rewards (Stuart, 1993; Lambert et al., 1996; Mentzer et al., 2000; Golicic et al., 2003; Knemeyer et al., 2003; Moberg and Speh, 2003). Duration is another important factor (Gadde and Snehota, 2000). Relationship duration basically refers to the length of time in which firms have been involved in the partnership (Monczka et al., 1995). The protagonists of this view argue that strength of a relationships is positively correlated with the duration of partnership (Monczka et al., 1995). Others argue that strength and durability are not necessarily correlated and they point to durable arms-length relationships between purchasers and suppliers (Dyer et al., 1998; Lemke et al., 2003).


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The relative power of firms in a supply chain is considered by many scholars to be a key influence on the nature of the relationship (Lascelles and Dale, 1989; New, 1998; Cox, 1999; Cox et al., 2001; Watson, 2001). According to Cox (1999, p.171), a firm in a supply chain relationship is in a [relatively] powerful situation over others when the firm is able to “put (itself) in a position where neither customers, employees, competitors or suppliers can leverage value from (it), while putting (itself) in a position to leverage all of them”. Cox (1999) pointed out that power distribution between partner firms in a supply chain is imbalanced, and it is essential these differences are clearly understood because of their influence on the nature of the buyer-supplier relationship. Strategic supply chains partnerships will operate more effectively and efficiently if participants learn to think alike (Hult et al., 2004). In a supply chain each node depends on its adjoining node to perform its role (Thompson, 1967). This reciprocal interdependence means that common understanding is vital to successful operation of partner firms. Therefore, diverse views of concepts such as quality and timeliness need to be resolved so that effort can be focused on necessary activities (Handfield and Nichols, 2002).

5.2 Internal capacity The internal capability of a firm to acquire and exploit knowledge is frequently cited as a key factor in the effective transfer of interfirm knowledge (for example, Cohen and Levinthal, 1990; Mowery et al., 1996; Chen, 2004). Authors tend to use different terms to describe what in this paper we call ‘internal capacity’. Cohen and Levinthal (1990, p.128) coined the phrase ‘absorptive capacity’. They defined absorptive capacity as “the ability to evaluate and utilise outside knowledge”. According to them absorptive capacity is “largely a function of the level of prior related knowledge …(it) confers an ability to recognise the value of new information, assimilate it and apply it to commercial ends”. Hamel (1991) on the other hand used the word ‘receptivity’ to capture firm’s overall ability to absorb knowledge from its partner. Kogut and Zander (1992) used ‘combinative capabilities’ to describe firm’s ability to recombine existing knowledge with the acquired external knowledge to generate new knowledge. Simonin (1999) suggested using concept of ‘learning capacity’ to indicate firm’s ability to allocate appropriate resources to the knowledge transfer process. In our view despite semantic difference these authors refer to the same underlying concept, that is to say, a firm’s ability to learn new knowledge. According to the extant literature internal capacity has an intangible and a tangible dimension. The ability to learn new knowledge largely depends on the firm’s prior knowledge and capabilities (Cohen and Levinthal, 1990; Kogut and Zander, 1992; Trott et al., 1995; Mowery et al., 1996; Beecham and Cordey-Hayes, 1998). For example, to assimilate or use new technologies, a firm must possess a certain level of knowledge or capability, which is to complement the acquired external knowledge (Trott et al., 1995; Mowery et al., 1996). Another intangible concerns the development of internal capacity. Cohen and Levinthal (1990) argued that the development of absorptive capacity depends on the effectiveness of a firm’s channels of communication with the external environment, effectiveness of channels of communications between firm’s subunits, and the character and distribution of expertise within the organisation. According to this model the internal capacity embedded in an organisation is a function of interaction with the environment, interaction between the subunits within the organisation and individuals’ expertise. This is because effective information distribution helps each firm

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in the supply chain to gain a better understanding of how to efficiently operate within the chain as well as gaining a better understanding of other firms’ needs and preferences (Hult et al., 2002). As the result of the increased skills and awareness firms should be able to improve their performance. The empirical research shows that boundary-spanning activity, in general, has a positive impact on performance (for example, Dollinger, 1984). Moreover, information processing activities appear to influence performance (Thomas et al., 1993). The tangible dimension of internal capacity is concerned with the allocation of resources to boost a firm’s internal capacity, for example, investment in R&D, staff development and communication systems (Cohen and Levinthal, 1990; Mowery et al., 1996; Simonin, 1999). In other words, appropriate allocation of tangible resources, for example, human and support activities, helps to develop and enhance firm’s internal capacity (Simonin, 1999). In the same vein, quality of staff assigned to work with partner firm influences the effectiveness of the knowledge transfer process. Mowery et al. (1996) argued that “absorptive capacity results from a prolonged process of investment and knowledge accumulation within the firm…the current absorptive capacity is influenced by its historic participation in specific product markets, lines of R&D, and other technical activities.” (Mowery et al., 1996, p.80)

However, the extant literature is also clear that a firm can compensate for lack of existing knowledge by allocating greater resources to developmental activities and better deployment of existing resources (Simonin, 1999). In the context of strategic supply chain partnerships the difference in the skill levels of partner firms helps to determine what can be learned. Too large a difference between partner firms will inhibit effective learning (Crossan and Inkpen, 1995). Beecham and Cordey-Hayes (1998) reached a similar conclusion and pointed out that uneven capability of the partner firms could inhibit the knowledge transfer success and used the position of small suppliers in UK motor manufacturing industry to demonstrate the point.

5.3 Learning intention The extant literature suggests that culture in general and attitudes towards learning in particular have a major influence on the effectiveness of knowledge transfer. The cultural values of a firm directly impact on its learning intention and commitment to learn from partner firms (Cummings and Teng, 2003). It is important that values are embedded at the highest level and the strategic vision of the firm defines its attitude towards partnership and interfirm learning (Hamel, 1991; Inkpen, 1998; Calantone et al., 2002). Hamel (1991) argued that ‘intent’, which conveys the objectives of the organisation with respect to interfirm learning, is one of the key determinants of learning in international alliances. Beecham and Cordey-Hayes (1998) argued that the success of progressive technology partnering arrangements depends on the degree to which management possess the ‘right’ attitude towards sharing knowledge with others outside the firm. Love et al. argued that “to foster organisational learning, it is necessary to concentrate on both individual and group skills, the design of support structures and the creation of an overall organisational attitude that encourages learning.” (Love et al., 2002, p.8)


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A consistent attitude towards partnership and organisational learning is also an important factor. Beecham and Cordey-Hayes (1998) identified inconsistent managerial attitudes toward partnership as one of the main reasons for the failure of effective knowledge transfer between partner firms. On the other hand, Calantone et al. (2002) suggested that ‘learning orientation’ – that is to say, firms’ organisation wide activities of creating and using knowledge to enhance competitive advantage– is determined not only by firms’ commitment to learning, but also by shared vision, open-mindedness and intra-organisational knowledge sharing. The latter three variables largely reflect the consistency of attitude towards partnership and knowledge sharing. Scholars also point to the impact of differences in national culture on the interfirm knowledge transfer (Hamel, 1991; Mowery et al., 1996; Calantone et al., 2002; Cummings and Teng, 2003). National culture is cited by many as the reason for differential attitudes towards learning. For example, Japanese firms are often perceived to have a greater desire to learn from their partners compare to US firms. Hamel (1991, p.96) highlighted this difference in attitude by stating that when Japanese managers were asked why their firms’ learn more than their Western partners, they stated that “We have the attitude of students, and our Western partners the attitude of teachers”. Japanese firms, by offering incentives, adopt a more proactive stance towards learning vis-à-vis the US firms (Mody, 1993; Crossan and Inkpen, 1995; Mowery et al., 1996). Prior research indicates that firms with a more proactive and ambitious learning culture tend to practice knowledge transfer more effectively. For instance, Hamel (1991) showed that asymmetric knowledge acquisition capability between Japanese and US companies was due to Japanese firms’ more ambitious learning intention, which led Japanese companies to emerge from alliances stronger than their US partners. Likewise, Mowery et al. (1996) examined the strategic alliances between Japanese and US firms and showed that cultural differences were an obstacle to the effectiveness of knowledge transfer.

5.4 Knowledge type The nature of knowledge to be transferred has attracted the attention of many researchers. The difference between explicit and tacit knowledge is commonly highlighted (for example, Inkpen, 1998; Simonin, 1999; Cavusgil et al., 2003). According to Polanyi (1962) the explicit knowledge is codified, which is transmittable in formal and systematic language. Explicit knowledge is revealed through its communication (Grant, 1996). It is more discrete or ‘digital’ and can be captured in records of the past, such as libraries, archives and databases (Nonaka, 1994). Because it is easily articulated and communicated, it is easier to transfer (Grant and Banden-Fuller, 1995; Grant, 1996). On the other hand, tacit knowledge has personal quality, which is hard to formalise and communicate, and is rooted in action, commitment, and involvement in a specific context (Polanyi, 1962). Contrary to explicit knowledge, tacit knowledge is regarded as a continuous activity of knowing (Nonaka, 1994). It is revealed through its application, because it is difficult to codify and can only be observed through its application and acquired through practice and experiences (Nelson and Winter, 1982; Nonaka, 1994; Conner and Prahalad, 1996; Grant, 1996). Consequently, it is more difficult to transfer (Grant, 1996; Cavusgil et al., 2003). In contrast to explicit knowledge, tacit knowledge is more ‘personal’ since it is part of an individual’s cognition, and hence it is difficult to communicate (Grant and Banden-Fuller, 1995). However, the ‘personal’ characteristic of

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tacit knowledge does not mean that tacit knowledge exists only in individuals. Tacit knowledge could also be held collectively, for instance collective tacit knowledge could reside in top management teams, organisational consensus on past collaborative experiences, firm routines, firm culture and professional culture (Cavusgil et al., 2003). Although tacit knowledge is more difficult to articulate, communicate and transfer, compared to explicit knowledge, tacit knowledge is considered to be more critical to the competitive advantage of the firm. Tacit knowledge is more difficult to imitate. This is referred to as inertness of the knowledge (Kogut and Zander, 1992). In this sense, tacit knowledge is more likely to result in sustainable advantage (Nonaka, 1994). According to Cavusgil et al. (2003), tacit knowledge contributes significantly to the firm’s ability to develop innovative capability. This is because tacit knowledge or embedded knowledge facilitates creativity and new product development (Madhavan and Grover, 1998). Innovation capability in turn determines the product performance of the firm (Cooper, 1984; Cavusgil et al., 2003). Therefore, firms tend to be differentiated from each other because of the differences in embedded tacit knowledge. The results of prior studies tend to agree upon the hindrance of tacitness on effective knowledge transfer. For instance, the empirical study of Simonin (1999) suggested that knowledge tacitness tended to increase the knowledge ambiguity which inhibits the effective interfirm knowledge transfer. Likewise, Cavusgil et al. (2003) suggested that tacit knowledge is more difficult to transfer and deploy across borders, and Cummings and Teng (2003) indicated that knowledge embeddedness has negative effects on successful transferability. Moreover, Chen’s (2004) study revealed that knowledge explicitness will positively affect the knowledge transfer performance of strategic alliances. Overall, one might expect the effectiveness of knowledge transfer to be different in the case of tacit and explicit knowledge.

5.5 Achieved memory According to Huber (1991) memory targets knowledge acquisition activities in a certain direction. Here, achieved memory refers to the amount of knowledge, experience, and familiarity with the supply chain process (Hult et al., 2004). The effect of memory in a strategic supply chain partnership is not to influence direction but to encourage more acquisition (Hult et al., 2004). Members in a chain possessing significant memory are aware that knowledge coordination across firms reduces duplication, waste, and redundancy (Handfield and Nichols, 2002). This recognition is likely to lead the nodes in the chain to seek out more knowledge than chains that lack memory. That is to say, the more knowledge the chain members possess, the greater their awareness that additional knowledge can ultimately enhance outcomes (Hult et al., 2004). Strategic supply chain partnerships require continuous information distribution so as to maintain strategic, operational, and technological integration (Hult et al., 2004). A partnership, according to the RBV, is valuable if it results in a rare, valuable, and inimitable source of knowledge and coordination (Grant, 1996). In this context both volume and accurate targeting of information are important. Retained memory in terms of past success and failure not only makes the need for information circulation clear (Bowersox et al., 1999), but it also suggests where a certain piece of information is likely to have a positive impact on the outcome and so determines which entities will receive the information (Huber, 1991; Hult et al., 2004).


6

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Organisational factors and multiple stages of knowledge transfer

A model is a pattern, physical entity, or mathematical formulation that can represent an actual process, system, scenario, or object. It can represent either the process or its results. The aim of our conceptual model is to show the pattern of interaction between organisational factors and between these factors and stages of knowledge transfer. The initial model (Figure 1) provided a skeleton in that the patterns of relationship were not explicitly identified. The authors used the skeleton model, grounded in theory and prior empirical studies, to review the literature to further justify the inclusion of the organisational variables it identifies. In this section the authors go a step further and attempt to identify the pattern and direction of interaction between the organisational variables and between these variables and the three stages of knowledge transfer.

6.1 Nature of interfirm relationship and knowledge transfer The extant literature suggests that the strength of relationship influences all of the three stages of knowledge transfer. A stronger relationship tends to engender higher levels of trust and commitment and this in turn enhances the communication and interaction between partner firms. Mody (1993) suggested that trust could augment the capability to search for and share new knowledge between partner firms. Similarly, Kraatz (1998) indicated that strong ties are more likely to promote in-depth communications and to facilitate the exchange of detailed information between organisations. Inkpen (1998, p.74) argued that “as trust increases and mutual partner understanding develops, alliance knowledge should become more accessible”. Cavusgil et al. (2003) suggested that a close relationship tends to enhance the opportunities for people in the partner firms to share feelings, emotion, and collaborative experiences, and mental models through physical face-to-face contacts. Moreover, Dyer and Nobeoka (2000) pointed out that stronger relationship between supply chain partners tends to promote firms to develop a wider variety of mechanisms to transfer knowledge and best practices between each other. To summarise, strong relationship has a significant and positive impact on the opportunity to acquire knowledge. It helps to improve communications, intensify contacts, and increase potential alternatives for knowledge acquisition. A strong relationship can potentially enhance firms’ ability to absorb knowledge. For example, Dyer and Nobeoka (2000) found that strong ties between Toyota and its suppliers as well as offering better access to knowledge also assisted knowledge internalisation. Cummings and Teng (2003) pointed out that strength of social ties, free-flow of communication, consistency in administrative controls, and level of trust between source and recipient of knowledge were also positively associated with knowledge internalisation. Evidence suggests that a strong relationship between supply chain partners has a positive impact on knowledge utilisation. The study by Dyer and Nobeoka (2000) showed that Toyota’s strong relationship with its suppliers lay behind efforts to provide them with active assistance during the adoption and implementation of new systems. Wiig (1997) argued that strong relationship creates commitment and openness, hence, partner organisations will be more willing to review previous knowledge transfer, and make adjustment to the process so as to facilitate a more effective knowledge acquisition, internalisation, and utilisation.

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The extant literature suggests that the length of partnership will have a positive influence on all three stages of knowledge transfer. A number of studies concluded that the duration of a partnership increased knowledge acquisition activity (Love and Gunasekaran, 1999; Simonin, 1999; Kotabe et al., 2003). The study of Toyota’s supply chain showed that it was necessary to develop network identity and knowledge transfer mechanisms before suppliers could effectively acquire knowledge, and this takes time (Dyer and Nobeoka, 2000). A similar point was made by Crossan and Inkpen (1995). They suggested that learning is an incremental process and it takes time for organisations to build up appropriate mechanisms to transfer knowledge. Mody (1993) proffered a slightly different explanation by pointing out that past experience and the history of the network influences the nature of future contacts and interaction, and hence, the knowledge acquisition activities. An alternative explanation was provided by Powell et al. (1996). They argued that experience with collaborative networks offers a fertile ground for both further formal partnerships and an expanding array of informal relationships. This in turn results in greater boundary spanning activity and opportunity to acquire knowledge. The literature review suggests that as the length of relationship increases partner firms tend to establish more intensified mechanisms to acquire knowledge. As a relationship continues, supply chain firms tend to gain more experiences interacting with their partners and to absorb knowledge acquired from external sources (Kale et al., 2000). The greater the duration of the relationship the more opportunity for partner firms to continuously assess and adjust their learning behaviour, and hence, institutionalise more knowledge (Levinson and Asahi, 1996). Thus, the duration of supply chain partnership also enhances the firm’s ability to internalise knowledge. Inevitably there is a time lag between acquiring, internalising, and utilising knowledge. The duration of partnership influences the opportunities for acquiring, internalising and utilising knowledge as well as receiving support during implementation (Kogut and Zander, 1992). The point made by Levinson and Asahi (1996) and discussed in the previous paragraph equally applies to the utilisation stage. Overall, the extant literature supports the proposition that increasing length of partnership enables partner organisations to more effectively recombine the existing knowledge with new knowledge to generate new applications. There is a broad consensus within the extant literature that relative power influences all three stages of knowledge transfer. However, there are divergences of views with regard to the type of power relationship that might have either a positive or negative impact on the knowledge transfer. Some scholars argue that a powerful firm could restrict the flow of knowledge to protect its core proprietary assets or market position (for example, Albino et al., 1999). Interestingly, these authors also offer an alternative perspective by arguing that a powerful leader firm in an industrial district could use knowledge transfer as a tool to develop interfirm relationship. Another group of scholars posit that a powerful firm within a supply chain partnership can act as a catalyst and help to increase knowledge acquisition, internalisation, and utilisation (Dyer and Nobeoka, 2000; Bessant et al., 2003). This is because a powerful partner can impose sanctions to prevent the ‘free rider’ problem and act as a role model for transferring practices that can improve efficiency and effectiveness (Dyer and Nobeoka, 2000). Cox (1999) refers to this as the “hierarchy of structural dominance”, where a leading partner is able to act as coordinator and promoter of effective supply chain learning (Bessant et al., 2003). Yet others argue that balanced power tends to enhance interfirm partnership, and therefore, knowledge acquisition, internalisation and utilisation (Beecham and


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Cordey-Hayes, 1998). The evidence supports a general proposition that relative power influences all three stages of knowledge transfer, but opinion is divided on the direction of influence of a powerful partner and the benefits of balanced power. The development of common understanding requires intensive contact and interaction (Daft and Lengel, 1986). This is why FedEx holds an annual conference with its strategic suppliers (Farhoomand and Ng, 2000). Such activities in turn provide familiarity and the opportunity to develop both trust and common-mind set (Hult et al., 2004). These, in turn, will influence knowledge acquisition, internalisation, and utilisation. The outcome is a virtuous circle. The effort to create common mind-set results in greater knowledge transfer and this in turn strengthens the common mind-set.

6.2 Internal capacity and knowledge transfer As discussed earlier, the literature suggests that both tangible and intangible dimensions of internal capability will affect a firm’s ability to learn from others effectively (for example, Cohen and Levinthal, 1990; Mowery et al., 1996; Simonin, 1999). The literature review suggests that all facets of knowledge transfer are influenced by internal capacity. Firms with higher internal capacity tend to have more qualified personnel and higher levels of expertise to acquire knowledge from partner firms (Mody, 1993). The effectiveness of knowledge internalisation depends on the ability of the firm to store, disseminate, and combine existing know-how with new knowledge. Firms with higher internal capacity tend to possess more effective systems for storing and disseminating knowledge and more importantly have the competency to recombine existing knowledge with new knowledge (Kogut and Zander, 1992). This point is supported by other researchers. For example, Trott et al. (1995) concluded that firms with higher internal capacity are better able to assimilate knowledge. At the knowledge utilisation stage, firms with higher internal capacity will also possess greater level of expertise and financial capabilities to put the internalised knowledge into more effective and appropriate use (Chen, 2004). It is through effective implementation of the new knowledge that firms improve their performance and enhance their competitive advantage.

6.3 Learning intention and knowledge transfer The extant literature, as was discussed previously, suggests that learning intention influences the knowledge transfer process. In this section the authors will go a step further and demonstrate with the help of prior studies that learning intention primarily influences the acquisition and internalisation stages. Many researchers argue that firms with stronger learning intentions will have greater incentive to learn from others (Mody, 1993; Crossan and Inkpen, 1995). According to Mody (1993) this is because these firms will invest more energy into relationships that will enable them to acquire knowledge from external sources. Inkpen suggested that “even though alliance knowledge is deemed useful, a firm will not necessarily actively seek to acquire the knowledge … in some alliances, partners aggressively seek to acquire alliance knowledge while in others, the partners take a more passive approach to knowledge acquisition.” (Inkpen, 1998, p.72)

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He argued that the difference lies in the attitude towards learning. According to Lorange (1996) positive learning intentions will enhance the ability of the organisation to acquire new knowledge, because these firms also display a degree of open-mindedness and encourage people in the organisation to innovate and treat mistakes as a learning opportunity. Overall evidence suggests that learning intention has a positive effect on firm’s ability to acquire knowledge from its supply chain partners. Inkpen (1998) distinguished between acquisition and internalisation. He pointed out that firms in a strategic alliance may seek collaborative access to partner firms’ knowledge, but will not necessarily internalise the knowledge. The internalisation depends on the attitude towards learning. A similar point was made by Lorange (1996). He argued that attitude towards learning influences a firm’s willingness to internalise and incorporate new knowledge. Likewise, Cummings and Teng argued that “retention of knowledge cannot be taken for granted… recipients with an extensive set of routines and learning competencies designed to retain and nurture transferred knowledge – with learning culture – may achieve greater knowledge transfer success.” (Cummings and Teng, 2003, p.49)

Therefore, adequate learning intention or culture is critical for the firm to internalise knowledge that is acquired from external sources.

6.4 Knowledge type and knowledge transfer In this section the authors examine the potential impact of knowledge type (the nature of knowledge) on the different stages of knowledge transfer. Inkpen (1998, p.74) stated that, “the more tacit the knowledge that an alliance partner seeks to acquire, the more difficult the acquisition”. He went on to argue that knowledge embedded in the culture or history of the partner firm is particularly more difficult to acquire. Similarly, Cummings and Teng (2003) posited that knowledge embeddedness has a negative effect on knowledge transfer success, not least because it is difficult to acquire in the first instance. According to the authors, embedded knowledge transfer may require transfer of knowledge reservoirs and associated sub-networks (for example, employees and group of individuals). Our review suggests that although tacit knowledge is likely to be highly valuable it is also inherently more difficult to transfer and acquire. Tacit knowledge also has a negative impact on internalisation. Successful knowledge internalisation involves diffusion and assimilation of knowledge within the organisation. Tacit knowledge is more difficult to articulate, teach, and learn, therefore, it is more difficult to disseminate and consequently internalise (Cummings and Teng, 2003). Moreover, knowledge internalisation often requires firms to ‘unlearn’ existing knowledge or practices to accept new knowledge (Hamel, 1991). Since tacit knowledge is likely to be embedded deeply into the culture or routines of the organisation it would be more difficult to unlearn in order to assimilate new knowledge. This in turn may result in more painful decisions or higher resistance from inside the organisation. Therefore, tacit knowledge is likely to be more difficult to be internalised.

6.5 Achieved memory and knowledge transfer The literature suggests that achieved memory has a positive impact on knowledge acquisition and internalisation. Simonin (1999) argued that the level of prior experience


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of the knowledge seeker with the underlying knowledge domain, is negatively related to the ambiguity of knowledge, which contributes to the determination of the extent of interfirm knowledge transfer. According to Hult et al. (2004) the level of achieved memory has a positive influence on the knowledge acquisition activities. They argued that supply chains where nodes possess high level of retained memory would have a higher level of knowledge acquisition activity because chain members are more aware of the benefits of knowledge acquisition. The relationship resembles an amplifying loop, memory enhances knowledge acquisition and vice versa (Lindsley et al., 1995). Achieved memory facilitates knowledge internalisation by helping to direct the acquired information to the appropriate parts of the organisation and by providing a better understanding of the likely impact of the information on outcomes (Bowersox et al., 1999; Hult et al., 2002, 2004). Furthermore, memory enables firms to assess the acquired knowledge and adapt the more pertinent know-how (Lorange, 1996).

7

A conceptual model of interfirm knowledge transfer

An important final stage in the analysis prior to modifying the initial skeleton model in light of our findings, was to consider the interactions of the organisational factors discussed in the previous section. The evidence suggests that there is a two-way interaction between internal capacity and learning intention. Simonin (1999) pointed out that both voluntary and involuntary transfers of knowledge are possible in strategic alliances, however, the amount of knowledge transferred partly depends on the extent that partners protect knowledge and on the intent of the knowledge seeker. According to the author, the appropriateness of resources allocated to the process signifies intent. For example, the quality of staff assigned to the partnership related activities. As such, internal capability overlaps with the learning intention. On the other hand, learning intention could also influence the internal capacity of the firm. According to Hamel (1991), receptivity thrives as long as the top management continues to express an active interest in the process. Moreover, Cohen and Levinthal (1990, p.149) concluded: “Absorptive capacity is more likely to be developed and maintained as a byproduct of routine activity when the knowledge domain that the firm wishes to exploit is closely related to its current knowledge base. When however, a firm wishes to acquire and use knowledge that is unrelated to its ongoing activity, then the firm must dedicate effort exclusively to creating absorptive capacity. In this case absorptive capacity may not even occur to the firm as an investment alternative.”

The extant literature suggests that the higher learning intention of Japanese firms enhances their learning capacity (Mody, 1993; Crossan and Inkpen, 1995). The evidence from the literature supports the proposition that internal capacity influences learning intentions and vice versa. The relationship between interfirm relationship and learning intention was examined next. As Inkpen (1998, p.73) argued, “if alliance partners are competitors or potential competitors it seems reasonable to suggest that a firm would have a limited incentive to share knowledge”. Love et al. (2002) argued that factors such as honesty, trust, openness to new ideas, and commitment from senior management, are all critical to learning culture development. More importantly, Dyer and Singh (1998) pointed out that a trust-based interfirm relationship will provide alliance partners with an appropriate

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incentive to share valuable knowledge with each other. Lack of trust between partner firms is very likely to diminish firm’s intention to share knowledge, due to the fear that the other firm will make their core competencies obsolete. The length of prior relationship also influences the cooperative actions of partners (Heide and Miner, 1992). According to them firms’ stable patterns of attitude towards learning and knowledge sharing is formed over time. Furthermore, Ganesan (1994) suggested that asymmetric dependence in a buyer-seller partnership is related with firms’ long-term orientation, which in turn determines firms’ attitudes toward knowledge sharing. Thus, relative power of supply chain partners could affect the learning intention. Both organisational information processing theory (for example, Daft and Weick, 1984) and empirical research (Thomas et al., 1993; Gioia and Thomas, 1996) suggest that shared meaning is a catalyst for encouraging commonly directed efforts among members of a network. Hult et al. (2004) adapted this concept to the case of strategic supply chain partnership and suggested that development of shared meaning brings higher level of integration and improved learning intentions. The evidence from the literature supports the proposition that interfirm relationship influences learning intentions. Ganesan (1994) argued that satisfaction with past outcomes may positively affect retailer’s long-term orientation in the buyer-seller partnership. The implication is that achieved memory tends to influence the learning intention of supply chain partners. Additionally, Cohen and Levinthal (1990) argued that firms’ absorptive capacity is largely a function of prior related knowledge. Therefore, achieved memory helps to develop appropriate internal capacity for absorbing know-how because it provides a frame of reference or a cognitive map (Corner et al., 1994; Hult et al., 2004). Based on the review of the literature presented in the above sections, the initial skeleton model (Figure 1) was modified to show more comprehensively the relationships between the learning stages and the organisational factors, and between the organisational factors themselves. The resulting conceptual model depicting the process of knowledge transfer between nodes in a strategic supply chain partnership is presented in Figure 2. Figure 2

Conceptual model of interfirm knowledge transfer


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The model depicted in Figure 2 shows the process of knowledge transfer between two firms. It suggests that knowledge transfer between partner firms can take place simultaneously and benefits flow in both directions. That is to say, knowledge transfer is not sequential and partner firms can acquire knowledge from each other at the same time. In the context of a strategic supply chain partnership the number of nodes will be much higher and the model repeated for all participating firms. Knowledge transfer is not restricted to buyer and supplier firms. A key purchaser can, and some do, encourage knowledge transfer between their suppliers (Dyer and Nobeoka, 2000; Farhoomand and Ng, 2000). The model equally applies to the second and third tier suppliers, however in reality, knowledge transfer beyond first-tier partnership is less evident (Bessant et al., 2003).

8

Conclusion

With the help of theory and the prior empirical research the factors that could potentially influence the effectiveness of knowledge transfer within a strategic supply chain partnership were initially identified. These variables were used to develop an initial skeleton model (Figure 1). The initial skeleton model guided the second stage of literature review. The aim here was to confirm the relevance of the factors identified to the process of knowledge transfer within a strategic supply chain partnership. Following this confirmatory stage the authors reviewed the literature to examine the relationship between organisational factors and the stages of knowledge transfer, as well as the potential relationships between the organisational factors. This process yielded a more comprehensive model depicting the process of knowledge transfer between two partner firms operating within a strategic supply chain partnership (Figure 2). The conceptual model makes a number of contributions to the existing literature. First, our model treats knowledge transfer in the context of supply chain partnership as a multi-stage process. Many of the previous empirical researchers have treated the knowledge transfer process as a single stage phenomenon. Information is important but in itself it does not result in better performance or understanding. The assigned meaning is more valuable than information (Daft and Weick, 1984; Grant, 1996), and still more important is action arising from the assigned meaning (Hult et al., 2002, 2004). This is why it is imperative to break up the knowledge transfer process into stages and understand how each stage might be influenced by organisational factors. We argue that it is only through this understanding that mangers can improve knowledge transfer. Second, we have identified organisational factors that might influence the effectiveness of knowledge transfer process and have assigned meaning to each factor. Third, we show the relationship among organisational factors. Again, without understanding such interrelationships, it would be difficult for managers to improve the process of knowledge transfer. The proposed conceptual model attempts to fill a gap in existing literature by providing a more holistic understanding of interfirm knowledge transfer. The model offers a starting point for the future empirical researchers to test and develop the model further. This in turn requires scale development to operationalise the model’s variables. We contend that the model offers managers a systematic model that can guide their efforts to improve knowledge transfer, and therefore, operating efficiency and

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effectiveness. However, we acknowledge that the model needs to be verified by practitioners. The conceptual model presented potentially suffers from a number of limitations. It does not address the potential impact of contingency factors (for example, sector, operating environment, product life cycle) on the knowledge transfer process. These factors may be important and need to be considered in the future developments of the model. Moreover, size is dealt with implicitly in the context of internal capacity, but it needs to be considered explicitly.

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