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

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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.

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Notes

  1. The 'cost' for seeking information is relative to the specificity and importance of the information needed and to what needs to be disclosed or shared with the other side. Obviously, consultation is not always cheap and getting access to most knowledgeable people is not an easy task, thus there is a range of 'costs' and 'values' for various consultations. In our study, we examine a closed circle of experts joining under one contractual arrangement. Since all involved experts are in the same area of R&D, we propose that the cost of forming a consultation relationship is relatively low since accessibility is high and motivation to share advice and information is also relatively high.

  2. We also fitted the models after a maximum transformation, so that a tie exists between actors i and j if one actor named the other as a partner on KX relationship k, and we formulated the more complex, directional model. Results were overall similar to those presented. The non-directed matrices strongly matched the directed networks, with simple matching coefficients of .887 and .929 for the consultation and joint projects networks, respectively. This indicates that the transformation did not cause a loss of information. Moreover, using the non-directed networks leads to an easier interpretation of results by greatly reducing the number of parameters in the model. Given that little information was lost and results were overall similar in the directed and non-directed networks, we present the simpler, non-directed model. The goodness of fit statistics, as well as the model with specifications corresponding to a directed network, can be received from the first author upon request.

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Funding

This research was funded by grants from the Israeli Science Foundation (709–11) and from the Israeli Ministry of Science and Technology (0398884).

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Authors and Affiliations

  1. Coller School of Management, Tel Aviv University, Tel Aviv, Israel

    Yuval Kalish

  2. Department of Sociology, Hebrew University of Jerusalem, Jerusalem, Israel

    Amalya L. Oliver

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  1. Yuval Kalish
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Correspondence to Yuval Kalish.

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Appendices

Appendix 1

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Table 4 Full ERG models for Study 1
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4.

Appendix 2

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Table 5 Correlations between in- and outdegrees, by network and timepoint
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5.

Appendix 3: Full SAO models for Study 2

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Table 6 Simplified SAO model parameter estimates (and standard errors, in brackets) for joint project and consultation networks
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6.

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Kalish, Y., Oliver, A.L. Reducing the cost of knowledge exchange in consortia: network analyses of multiple relations. J Technol Transf 47, 775–803 (2022). https://doi.org/10.1007/s10961-021-09858-1

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