LAPSE:2023.0796
Published Article

LAPSE:2023.0796
Coupling Coordination Analysis of Regional IEE System: A Data-Driven Multimodel Decision Approach
February 21, 2023
Abstract
Coordinating regional innovation−economy−ecology (IEE) systems is an important prerequisite for overall continuous regional development. To fully understand the coordination relationship among the three, this study builds a data-driven multimodel decision approach to calculate, assess, diagnose, and improve the regional IEE system. First, the assessment indicator system of the regional IEE system is established. Secondly, the range method, entropy weight method, and weighted summation method are employed to calculate the synthetic developmental level. Thirdly, a multimodel decision approach including the coupling degree model, the coordination degree model, and the obstacle degree model is constructed to assess the spatiotemporal evolution characteristics of the regional IEE system coupling coordination and diagnose the main obstacles hindering its development. Finally, the approach is tested using Anhui Province as a case study. The results show that the coupling coordination degree of the Anhui IEE system presents a stable growth trend, but the coupling degree is always higher than the coordination degree. The main obstacle affecting its development has changed from the original innovation subsystem to the current ecology subsystem. Based on this, some countermeasures are put forward. This study, therefore, offers decision support methods to aid in evaluating and improving the regional IEE system.
Coordinating regional innovation−economy−ecology (IEE) systems is an important prerequisite for overall continuous regional development. To fully understand the coordination relationship among the three, this study builds a data-driven multimodel decision approach to calculate, assess, diagnose, and improve the regional IEE system. First, the assessment indicator system of the regional IEE system is established. Secondly, the range method, entropy weight method, and weighted summation method are employed to calculate the synthetic developmental level. Thirdly, a multimodel decision approach including the coupling degree model, the coordination degree model, and the obstacle degree model is constructed to assess the spatiotemporal evolution characteristics of the regional IEE system coupling coordination and diagnose the main obstacles hindering its development. Finally, the approach is tested using Anhui Province as a case study. The results show that the coupling coordination degree of the Anhui IEE system presents a stable growth trend, but the coupling degree is always higher than the coordination degree. The main obstacle affecting its development has changed from the original innovation subsystem to the current ecology subsystem. Based on this, some countermeasures are put forward. This study, therefore, offers decision support methods to aid in evaluating and improving the regional IEE system.
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Keywords
coupling coordination, decision support methods, multimodel decision, regional IEE system
Subject
Suggested Citation
Yang Y, Hu F, Ding L, Wu X. Coupling Coordination Analysis of Regional IEE System: A Data-Driven Multimodel Decision Approach. (2023). LAPSE:2023.0796
Author Affiliations
Yang Y: Business School, Suzhou University, Suzhou 234000, China [ORCID]
Hu F: Business School, Suzhou University, Suzhou 234000, China
Ding L: Business School, Suzhou University, Suzhou 234000, China
Wu X: Business School, Suzhou University, Suzhou 234000, China
Hu F: Business School, Suzhou University, Suzhou 234000, China
Ding L: Business School, Suzhou University, Suzhou 234000, China
Wu X: Business School, Suzhou University, Suzhou 234000, China
Journal Name
Processes
Volume
10
Issue
11
First Page
2268
Year
2022
Publication Date
2022-11-03
ISSN
2227-9717
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Original Submission
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PII: pr10112268, Publication Type: Journal Article
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LAPSE:2023.0796
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https://doi.org/10.3390/pr10112268
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Feb 21, 2023
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