Network proximity evolution of open innovation diffusion: A case of artificial intelligence for healthcare

Abstract

Open innovation diffusion is of great significance to industrial transformation and up-grading, forming an open innovation ecosystem based on the patent publication. However, patent applicants contribute much knowledge to the public domain, and the communication channel, which is network proximity, does not receive much attention. This study aimed to explore the key driving factors of open innovation diffusion by constructing a theoretical framework that includes four proximity dimensions in the context of a global industrial chain. By taking artificial intelligence for healthcare as an example, this study applied the quadratic assignment procedure model to conduct an empirical analysis with a sample containing 62 patent applicants. The empirical result verified that the key drivers are from the proximity dimensions and the interactions. Technological proximity plays the leading role in innovation diffusion, while organizational and temporal proximities play secondary roles. In addition, the significant moderating effects suggest that the proximity dimensions interact in innovation activities. Moreover, the proximity framework provides an overview of innovation management and policy implication.