Journal of Chaohu University ›› 2024, Vol. 26 ›› Issue (4): 40-50.doi: 10.12152/j.issn.1672-2868.2024.04.006

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Research on Pathways to High Regional Innovation Performance Driven by Regional Innovation Ecosystem Configuration Effects

WANG Cheng-jun,ZHANG Kai,XU Ya-qin:School of Business Administration, Anhui University of Finance and Economics   

  1. School of Business Administration, Anhui University of Finance and Economics, Bengbu Anhui 233030
  • Received:2023-11-21 Online:2024-07-25 Published:2025-01-15

Abstract: Constructing a regional innovation ecosystem has become a pivotal strategy for achieving regional collaborative innovation and bolstering national innovation capacities. This study, grounded in the perspective of innovation ecology, selects 31 provinces and cities in China as case study subjects. By integrating Necessary Condition Analysis (NCA) and Qualitative Comparative Analysis (QCA), it examines the relationship between the regional innovation ecosystems and regional innovation performance from a configurational perspective. The findings reveal that: A comprehensive network of technological innovation entities is a necessary condition for driving high regional innovation performance; There are three pathways to achieving high regional innovation performance: "Knowledge Innovation Entity–Balanced Type", "Technological Innovation Entity–Balanced Type", and "Collaborative Symbiosis–Balanced Type", and five pathways leading to non-high regional innovation performance, with an asymmetric relationship between them; Under certain conditions, there exists a substitution relationship among innovation entities, and between innovation entities and the market environment. Furthermore, this study provides strategic insights and potential measures for optimizing regional innovation layouts, creating regional economic growth poles, and exploring the types of regional innovation ecosystems that can more effectively enhance regional innovation performance, thereby facilitating high-quality development in different cities.

Key words: regional innovation ecosystem, fuzzy set qualitative comparative analysis, necessary condition analysis, regional innovation performance

CLC Number: 

  • G321