Data-Driven Evaluation and Recommendations for Regional Synergy Innovation Capability

Keyan Zheng, Fagang Hu () and Yaliu Yang
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Keyan Zheng: School of Foreign Studies, Suzhou University, Suzhou 234000, China
Fagang Hu: Business School, Suzhou University, Suzhou 234000, China
Yaliu Yang: Business School, Suzhou University, Suzhou 234000, China

Sustainability, 2023, vol. 15, issue 14, 1-21

Abstract: Regional synergy innovation capability is an important driving force in promoting the sustainable and high-quality development of the regional economy. Taking the regional innovation development panel data of the Yangtze River Delta integration region from 2010 to 2019 as a sample, this study constructs an evaluation index system of regional synergy innovation capability, weights the index using the entropy weight method, and measures the capability of the Yangtze River Delta integration region (three provinces and one city) using the composite system synergy degree model. The empirical results show that the synergy of regional synergy innovation in the Yangtze River Delta integration has increased steadily, but there is still much room for improvement. Anhui has great potential for synergy innovation with Jiangsu, Zhejiang, and Shanghai. Therefore, this study proposes countermeasures and suggestions for the high-quality development of Anhui’s synergy innovation capability under the integration of the Yangtze River Delta. This study provides theoretical and methodological support for enhancing regional synergy innovation capability and provides decision support for the sustainable and high-quality development of the regional economy.

Keywords: Yangtze River Delta integration; regional synergy innovation capability; composite system synergy degree model; entropy weight method; data-driven (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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