The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals
Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes...
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MDPI AG
2025-01-01
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| author | Jiaojiao Yang Ting Wang Min Zhang Yujie Hu Xinran Liu |
| author_facet | Jiaojiao Yang Ting Wang Min Zhang Yujie Hu Xinran Liu |
| author_sort | Jiaojiao Yang |
| collection | DOAJ |
| description | Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices. |
| format | Article |
| id | doaj-art-fe0e28297d4e4dd59f9fb1d6a7932436 |
| institution | DOAJ |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj-art-fe0e28297d4e4dd59f9fb1d6a79324362025-08-20T02:44:39ZengMDPI AGSystems2079-89542025-01-011327810.3390/systems13020078The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment GoalsJiaojiao Yang0Ting Wang1Min Zhang2Yujie Hu3Xinran Liu4School of Management, Guizhou University, Guiyang 550025, ChinaSchool of Management, Guizhou University, Guiyang 550025, ChinaSchool of Management, Queen’s University Belfast, Belfast BT9 5EE, UKSchool of Management, Guizhou University, Guiyang 550025, ChinaSchool of Management, Guizhou University, Guiyang 550025, ChinaGiven the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices.https://www.mdpi.com/2079-8954/13/2/78economy–society–resource–environmentCRITIC (criteria importance though intercriteria correlation)–entropy weightTOPSIS (technique for order preference by similarity to ideal solution)coupling coordination degree model (CCDM)logarithmic mean divisia index (LMDI)obstacle degree model |
| spellingShingle | Jiaojiao Yang Ting Wang Min Zhang Yujie Hu Xinran Liu The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals Systems economy–society–resource–environment CRITIC (criteria importance though intercriteria correlation)–entropy weight TOPSIS (technique for order preference by similarity to ideal solution) coupling coordination degree model (CCDM) logarithmic mean divisia index (LMDI) obstacle degree model |
| title | The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals |
| title_full | The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals |
| title_fullStr | The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals |
| title_full_unstemmed | The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals |
| title_short | The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals |
| title_sort | coordinated development and identification of obstacles in the manufacturing industry based on economy society resource environment goals |
| topic | economy–society–resource–environment CRITIC (criteria importance though intercriteria correlation)–entropy weight TOPSIS (technique for order preference by similarity to ideal solution) coupling coordination degree model (CCDM) logarithmic mean divisia index (LMDI) obstacle degree model |
| url | https://www.mdpi.com/2079-8954/13/2/78 |
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