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

Yuval Kalish*, Amalya L. Oliver

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageAmerican English
Pages (from-to)775-803
Number of pages29
JournalJournal of Technology Transfer
Volume47
Issue number3
DOIs
StatePublished - Jun 2022

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • ERG models
  • Information search model
  • Knowledge exchange
  • Multiple networks
  • Network structure
  • SAO models
  • Triadic closure

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