The role of network characteristics in facilitating research impact: a knowledge transfer perspective

Abstract

Companies invest in research and development (R&D) with the expectation of boosting theirinnovation pipeline to achieve growth and profitability. In addition, many companies seeking toenhance their internal R&D capability adopt an open innovation strategy and engage withexternal entities. One form of external engagement is through collaborative research projects(CRPs) where the company joins a consortium composed of universities, public agencies andother companies to collaboratively work on and tackle complex research problems of commoninterest. Anecdotal evidence, however, suggests mixed outcomes of collaborative researchprojects in terms of achieving corporate research impact.Corporate research teams participating in CRPs have the dual tasks of (1) working withdiverse collaborative research project team members from different organisations to createnovel knowledge and (2) identifying and transferring high-potential knowledge into thecompany’s innovation funnel for further commercial development, through a process called asthe “fuzzy front end” (FFE) of innovation. Achievement of corporate research impact requiresthe achievement of both tasks. This study focuses on how the interplay of networkcharacteristics and knowledge processes within the collaborative research project networksand across the corporate-internal networks influences the achievement of research impact.This study posits that knowledge transfer among network stakeholders is a facilitatingmechanism in generating research impact. This study further posits that the structural andrelational characteristics of the network influence knowledge transfer, which in turn facilitatesresearch impact. To test these hypotheses, this study examines the social networks ofseveral collaborative research projects in which the corporate research department of a globalsoftware company participated. Based on the data collected from collaborative researchproject teams, their interactions with corporate research team and corporate internal networksand drawing on network theory, this study aims to examine how network characteristicsinfluence the knowledge transfer processes that facilitate research impact.This thesis uses a multi-method and multi-level design. Study 1 investigates the effect of thestructural characteristics of the global network of collaborative research projects on researchimpact. Studies 2 and 3 involve the analyses of collaborative research project networks inAustralia and Europe. Both studies aim to understand how the characteristics of project-level network (i.e., networks of project stakeholders) influence the knowledge transfer processesthat drive the creation of research impact. Finally, Study 4 involves the qualitative study ofproject stakeholders’ perspectives on research impact and knowledge transfer. Insights fromthis study contribute to deeper understanding of the dynamic interplay between networkcharacteristics and knowledge transfer that ultimately results in research impact.The findings indicate that at the global project network (i.e., network of all projects) level ofanalysis, the structural network characteristic (centrality) has significant effect on researchimpact. Furthermore, at the local project level of analysis (i.e., network of project stakeholdersfor each project), the relational network characteristic (tie strength) has a greater significanteffect on knowledge transfer than structural network characteristics (network range andcentrality). There is mixed support for the effect of network range on knowledge transfer andthere is no support for the effect of centrality on knowledge transfer. In addition, ourqualitative study results indicate a strong relationship between knowledge transfer andresearch impact.This research makes a number of contributions to knowledge. First, this study contributes tothe literature on the project management area of knowledge-intensive projects, such ascollaborative research projects. The application of a network perspective to analyse projectnetworks at multiple levels enables better understanding of how knowledge transferprocesses at the micro-level (network of project stakeholders) contribute to the achievementof research impact at the macro-level (network of projects). Deeper understanding ofknowledge collaboration within CRPs from a network perspective enables the visualization ofknowledge processes and dynamics within CRPs. The quantitative study results areenhanced by insights from qualitative study on the research impact construct and itsrelationship with knowledge transfer. Second, this study contributes to the literature oninnovation by conceptualising the knowledge transfer processes within CRPs and across tocompany-internal networks as the early stage fuzzy front end (FFE) of the innovation process.This study adapted a theoretical model of the FFE and translated its social network-relatedpropositions into testable hypotheses, which were then empirically validated in the context ofthe CRP networks. From a corporate research perspective, the study findings provideguidance on how to improve collaboration between industry and academic partners in CRPsettings. Third, understanding how knowledge workers collaborate within and across CRP networks can provide input into the design of effective collaboration-centric and knowledgebasedsocial networking information systems that can facilitate this collaboration, therebyopening up a new avenue of research. Finally, this study contributes to research methods innetwork analysis by implementing mixed methods and network analyses at multiple levelsthat complement each other to provide a holistic understanding of the knowledge processesand research impact creation in these CRP networks.