Modeling the industry perspective of university-industry collaborative innovation alliances: player behavior and stability issues

SONG, Yang, BERGER, Ron, RACHAMIM, Matti, JOHNSTON, Andrew and COLLADON, Andrea Fronzetti (2022). Modeling the industry perspective of university-industry collaborative innovation alliances: player behavior and stability issues. International Journal of Engineering Business Management, 14.

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Abstract

Many firms find it challenging to develop innovations, evidenced by the ever-mounting number of university-industry research alliances. This study examines the strategic choices of actors who participate in collaborative innovation alliances involving partnerships between industry and universities (U-I) based on a stochastic evolutionary game model. White noise was introduced to reflect uncertainty and the stochastic interferences caused by the differences between actors. Using the Itô stochastic differential equation theory, we analyze stability issues of player behaviors in the evolution of a collaborative innovation alliance. The results illustrate that improvements in innovation efficiency can contribute to U-I collaborative innovation alliances. High knowledge complementarity appears to be unbeneficial to the stability of these alliances, and controlling knowledge spillovers may suppress free-rider problems from both sides of the game. Our study contributes to innovation research by providing a decision-making reference for the design of U-I cooperation.

Item Type:	Article
Additional Information:	** Embargo end date: 25-05-2022 ** From SAGE Publishing via Jisc Publications Router ** Licence for this article starting on 25-05-2022: https://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 1847-9790 **Article IDs: publisher-id: 10.1177_18479790221097235 **History: published_online 25-05-2022; accepted 11-04-2022; submitted 11-02-2022
Uncontrolled Keywords:	Research Article, University-Industry links, innovation efficiency, knowledge complementary, knowledge spillovers, stochastic evolutionary game
Identification Number:	https://doi.org/10.1177/18479790221097235
SWORD Depositor:	Colin Knott
Depositing User:	Colin Knott
Date Deposited:	27 May 2022 16:22
Last Modified:	27 May 2022 16:22
URI:	https://shura.shu.ac.uk/id/eprint/30268

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