TY - JOUR
T1 - Modeling the industry perspective of university-industry collaborative innovation alliances
T2 - Player behavior and stability issues
AU - Song, Yang
AU - Berger, Ron
AU - Rachamim, Matti
AU - Johnston, Andrew
AU - Fronzetti Colladon, Andrea
N1 - Publisher Copyright:
© The Author(s) 2022.
PY - 2022/5
Y1 - 2022/5
N2 - 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.
AB - 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.
KW - University-Industry links
KW - innovation efficiency
KW - knowledge complementary
KW - knowledge spillovers
KW - stochastic evolutionary game
UR - http://www.scopus.com/inward/record.url?scp=85131153005&partnerID=8YFLogxK
U2 - 10.1177/18479790221097235
DO - 10.1177/18479790221097235
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AN - SCOPUS:85131153005
SN - 1847-9790
VL - 14
JO - International Journal of Engineering Business Management
JF - International Journal of Engineering Business Management
ER -