Reducing the cost of knowledge exchange in consortia: network analyses of multiple relations

Yuval Kalish () and Amalya L. Oliver ()
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Yuval Kalish: Tel Aviv University
Amalya L. Oliver: Hebrew University of Jerusalem

The Journal of Technology Transfer, 2022, vol. 47, issue 3, No 9, 775-803

Abstract: Abstract Valuable knowledge exchanged in networks is associated not only with benefits but also with tensions and costs. This paper offers a new structural approach to knowledge exchange relations within consortia through integrating Information Search Model (ISM, Borgatti & Cross, 2003) with social network theory. This integration explains explain how organizational actors mitigate the costs associated with knowledge exchange (KX) relationships by using network structure. We examine ISM at the dyadic level of explanation and add triads and other complex configurations of multiple types of KX relationships. Using a multi-study approach, we conduct one inductive study and two network studies—one cross-sectional and one longitudinal in university-industry science consortia. The analyses, based on Exponential Random Graph models and Stochastic Actor Based models, show that organizational actors optimize the benefits and reduce the costs of KX through utilizing KX relationships of various types and network structures.

Keywords: Information search model; Multiple networks; Network structure; Triadic closure; Knowledge exchange; ERG models; SAO models (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10961-021-09858-1

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