Data-Driven Coupling Coordination Development of Regional Innovation EROB Composite System: An Integrated Model Perspective

Yaliu Yang, Yuan Wang, Yingyan Zhang and Conghu Liu
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Yaliu Yang: Business School, Suzhou University, Suzhou 234000, China
Yuan Wang: Business School, Suzhou University, Suzhou 234000, China
Yingyan Zhang: Business School, Suzhou University, Suzhou 234000, China
Conghu Liu: School of Mechanical and Electronic Engineering, Suzhou University, Suzhou 234000, China

Mathematics, 2022, vol. 10, issue 13, 1-25

Abstract: To promote coupling coordination development for regional innovation environment-resource-output-benefit (EROB) composite systems, we propose a data-driven integrated model method for measurement, evaluation, and identification. First, we construct an evaluation indicator system of coupling coordination development of regional innovation EROB composite systems. Second, we apply the entropy method to measure indicator weights and comprehensive development indices of regional innovation composite systems. The coupling coordination degree model is used to calculate and evaluate four subsystems’ coupling coordination development levels. The obstacle degree model is used to identify the main obstacle factors affecting coupling coordination development. Finally, using panel data of the Yangtze River Delta region (three provinces and one city) between 2014–2019 as a case study, we test the integrated model method. The results show that the comprehensive development level of the regional innovation EROB composite system in the Yangtze River Delta region maintained a stable growth trend; the coupling coordination development level among four subsystems continuously improved, with the main obstacle being the innovation resource subsystem. Accordingly, targeted policy suggestions are put forward. This study not only provides theoretical and methodological support for evaluating and optimizing regional innovation composite systems but also provides decision-making support for sustainable and high-quality development of regional economies.

Keywords: data-driven; regional innovation; integrated model; decision-making support (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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