Author
Listed:
- Binbin He
- Qiang Mei
- Mao-Min Jiang
- Miladin Stefanović
Abstract
Based on the evolutionary game theory, this study aimed to explore the decision-making behavior of the enterprise when it adopted the open innovation model from the perspective of organizational distance. The evolutionary game theory is an important method to study the enterprise’ decision-making under bounded rationality. It applies to describe the trend of decision-making based on the enterprises’ open innovation choices in industrial clusters. This paper employs open innovation and institutional theory, utilizes industrial clusters as the research object, and measures the geographical proximity of enterprises in high-tech industrial clusters employing organizational distance. Within the analytical framework of the duopoly model, the impact of organizational distance and patent licensing fees on the innovative performance of a high-tech industrial cluster is studied. The findings indicate that the export-oriented open innovation model is more appropriate for the innovation of high-tech industry clusters. There is a significant relationship between organizational distance and the R&D spillovers of businesses. Increased patent fees can encourage industry clusters to adopt an open innovation model with an outward orientation if they are located in close proximity to each other. Further research analyzed the effect of organizational distance on the selection of an open innovation mode employing an evolutionary game model and indicated that geographical proximity would encourage enterprises to adopt open innovation export strategies. The conclusion of this study has both theoretical and practical ramifications for the independent innovation of high-tech industry clusters.
Suggested Citation
Binbin He & Qiang Mei & Mao-Min Jiang & Miladin Stefanović, 2022.
"Evolutionary Game Analysis on Impacts of Organization Distance on Open Innovation Mode Selection of High-Tech Industrial Clusters,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, August.
Handle:
RePEc:hin:jnlmpe:9109763
DOI: 10.1155/2022/9109763
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