Alliance network configurations and the co-evolution of firms' technology profiles: An analysis of the biopharmaceutical industry
Jacob,J. Duijsters,Geert
Jacob,J.
Duijsters,Geert
Abstract
Many inter-organizational networks exhibit small-world properties in that they consist of close-knit sub-networks or blocks, along with sparse ties spanning those blocks, so that an average firm in the network has short connections to a wide range of partners. While extant literature has shown that networks exhibiting these properties outperform those that do not, little empirical research exists on the process of knowledge exchanges among firms within and across blocks in a network. This paper aims to fill this gap in the context of inter-firm technology alliance networks in the biopharmaceutical industry. Adopting an intertemporal perspective, we examine how particular alliance relationships within a network affect learning and information flows and therefore the co-evolution and similarity of the firms' technology profiles. Results of a Quasi-Maximum Likelihood analysis on a 10-year panel data set consisting of 217 firms reveal that firms in blocks tend to develop similar technology profiles over time. The results further demonstrate that firms located closer to each other in a network (shorter path length) display higher levels of resemblance compared with firms that are farther apart. However, perhaps more importantly and contrary to expectations, our results also show that the length of ties between two firms has a smaller effect on the similarity between their profiles when firms are not members of the same block.
Description
Date
2017-07
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
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Journal Issue
Keywords
technology alliances, alliance block, path length, technology profile, network embeddedness, technological distance
Citation
Jacob, J & Duijsters, G 2017, 'Alliance network configurations and the co-evolution of firms' technology profiles : An analysis of the biopharmaceutical industry', Technological Forecasting and Social Change, vol. 120, pp. 90-102. https://doi.org/10.1016/j.techfore.2017.04.010
License
info:eu-repo/semantics/closedAccess