Asking both university and industry actors about their engagement in knowledge transfer: What single-group studies of motives omit
Highlights
► We interview participants in five university-industry knowledge transfer initiatives. ► We show similarities and differences in motives of academic and practitioners. ► Both groups seek stability despite the de-stabilising nature of knowledge transfer. ► We explore the roles of technology translators in the intermediary organisations.
Introduction
The interest in university–industry relationships (UIRs) for knowledge transfer (D'Este and Patel, 2007, Lai, 2011, Liefner and Schiller, 2008, Tether and Tajar, 2008) stems from the belief that collaborative research by academia with industry can be a powerful source of innovation (Ambos et al., 2008, Mansfield, 1998) and governments’ concerns that academic research should be relevant to, and accessible by, industry (Tether and Tajar, 2008). We define ‘university–industry relationships (UIRs)’ as interactions between all parts of the higher educational system and the industrialising economy (Anon., 1974), while we define knowledge transfer broadly as any activities aimed at transferring technology or knowledge to help either the company or the university to further pursue its activities (Arvanitis et al., 2008). Perkmann et al. (2012) carried out a recent review of academic engagement in university–industry knowledge transfer activities; activities which they separated from commercialisation. They define academic engagement as “knowledge-related collaboration by academic researchers with non-academic organisations” while commercialisation involves “the patenting and licensing of inventions as well as academic entrepreneurship”. Based on their review we show that existing studies of academic engagement have a number of shortcomings. For example, they are heavily-biased to using quantitative methods to focus on academics. However, collaboration depends on mutuality between two parties; in this case academics and those in industry, and the predominant studies of one side of the collaboration (Arvanitis et al., 2008, D’Este and Perkmann, 2011) limit current research in this area. In our research we use a common framework to study simultaneously both sets of actors and to discover to what extent their motives coincide and hence potentially reinforce, or hinder, collaboration. In particular we concentrate on individuals rather than organisations, consistent with the belief that the former are important in initiating and sustaining collaboration. In addition we study collaborative situations where third parties, intermediaries called technology translators, are present to facilitate the collaboration between the two groups of collaborators. Their presence enables us to triangulate the responses of academics and industry actors and enhance the validity of the study. We use a qualitative approach which offsets the bias towards quantitative studies and contributes a richer picture of the study terrain. In addition to studying the motives of individual actors’ we investigate the outcomes of their collaborative relationships in terms of the benefits and drawbacks since, as George et al. (2002) noted, appreciating such benefits and drawbacks helps understand more completely how to manage such alliances. Our research question is: “how do the motives of, and outcomes for, individual actors in universities and industry correspond in government-sponsored UIRs for knowledge transfer?”
We choose as our research context large-scale projects sponsored by government thus reflecting the imperative stated in the opening sentence that governments are particularly concerned to foster university–industry knowledge transfer. We examined five major case studies of UIRs for knowledge transfer in the Faraday Partnership Initiative. This UK government-backed novel scheme of UI collaboration involving intermediaries was dedicated to improving the competitiveness of UK industry through research, development and knowledge transfer, and to exploiting science and technology (Acworth, 2008). Our interest in government-sponsored UIR stems from the move by many governments to increase sponsorship of research ties between publicly-funded organisations (in particular universities) and industry (Peters et al., 1998). Since the 1980s, many governments have implemented policies to promote and sustain UIRs (Fontana et al., 2006). Peters et al. (1998) explain that government sponsorships of these relationships make public sector organisations, such as universities, aware of the market demands and stimulate them to direct their knowledge development toward underpinning technological innovation. We focus on individual actors because, while analysis at the organisational level is clearly important, UIRs for knowledge transfer depend critically on the individual actors (Allen et al., 2007, Azagra-Caro, 2007). Several authors call for research at this level (Foss et al., 2009, Markman et al., 2008) since analysis at the individual level is relatively understudied (Allen et al., 2007, Azagra-Caro, 2007). The knowledge-sharing literature tends to be preoccupied with constructs, processes, and phenomena defined at a macro (i.e., collective, organisational) level and pays comparatively little attention to micro-level constructs (Foss et al., 2009).
By addressing the research question, we believe our study contributes in several main ways. Our study employs Oliver’s (1990) theoretical framework of six critical determinants to compare and contrast the motives of university and industry actors, thereby enabling a high-level view of what can be a diverse and detailed set of motives. As a consequence the study extends the empirical relevance of his framework to UIRs for knowledge transfer. Developing such a formal codification scheme helps us understand these relationships more strategically and thus fill a current knowledge gap. We demonstrate empirically that the motives of university actors and industry actors using Oliver’s theoretical framework are consistent at the determinant (i.e., summary) level but differ markedly at a lower (i.e., more detailed) level. Similarly, we show the correspondence between beneficial outcomes at a high level. In addition, we highlight the drawbacks in these relationships, although these appear to be limited. Particular points of interest include the academics’ lack of emphasis on mutual collaboration as a motive and both groups of actor’s emphasis on beneficial outcomes for individual institutions while according minimal emphasis to outcomes beneficial on a broader, societal dimension. We highlight the significance of the bridging or brokering function of intermediaries by demonstrating how they accurately predict the actors’ motives and beneficial outcomes, but fail to do this with drawbacks.
The rest of this paper is organised as follows. The next section reviews the literature on motives, benefits and drawbacks of UIRs. We then describe the context of the study, i.e., the UK Faraday Partnership Initiative. Next we present the method employed for the case studies. Then we present and discuss the findings, highlight the study’s contribution and implications, and close by mentioning the study’s limitations along with suggestions for future research.
Section snippets
Literature review
In this section we discuss the literature on motives and outcomes of UIRs for knowledge transfer with respect to both university and industry individual actors. Motives are conceived as underlying reasons for engaging in UIRs and the framework of Oliver (1990) is used to organise them. While motives can be construed as anticipated benefits, outcomes are taken to be composed of actual benefits and drawbacks (i.e., dis-benefits). Clearly connections between motives and outcomes are to be
Empirical background
We selected the Faraday Partnership Initiative as the context for addressing our research question. This government-sponsored UIR aimed at changing fundamentally knowledge transfer in the UK between universities (and other public research organisations) on the one hand, and industry on the other hand (Anon., 2004). The Partnership Initiative focused on science-based technologies, in which university–industry interaction has been found to be important (Bekkers and Freitas, 2008).
Method
We employed exploratory qualitative in-depth case studies in this study (Ghauri et al., 1995, Yin, 2009). Siegel et al. (2004) argue that qualitative research suits many of the issues associated with knowledge transfer since these issues are both ambiguous and highly contentious. Our methodology relies on semi-structured interviews with industry and university actors as a key component; however, the tables presented in the study summarise the data quantitatively and the length of the paper
Findings
First we present our findings under the motives of university and industry actors, and second the outcomes of the relationships in terms of the benefits and drawbacks to the university and industry actors.
Discussion
Table 7 summarises the findings to facilitate the discussion. Our study’s contributions are discussed below under the respective headings: motives of university and industry actors, beneficial outcomes and drawbacks.
Contribution
Our study contributes to the literature by establishing the extent of correspondence between the motives (and outcomes) of individual academic and industry actors engaged in UI knowledge transfer. Current studies focus predominantly on academics and the limited studies that do focus on both groups do not apply a common framework to a common context. We use a common framework of motivational determinants (Oliver, 1990) to study both groups of actors when collaborating concurrently within a
Conclusion
This research has yielded a number of conclusions, which should prove useful for theory, practice and policy-making including the design of public policies aimed at facilitating and fostering university–industry knowledge transfer. In this study, we have sought to examine the motives of university and industry individuals involved in knowledge transfer relationships, and the outcomes of the relationships in terms of benefits and drawbacks. We have employed Oliver's (1990) theoretical framework
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