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Hybrid model for evaluating the transformation of China’s resource-based cities

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  • Pu, Song
  • Xia, Chang

Abstract

This paper constructs a new and proposes a novel hybrid model combining multi-criteria decision making (MCDM) model and variability for multi-periods as well as the approaches to select the best specific hybrid model. A case study based on 17 RBCs in three provinces of southwest of China for 2012–2020 indicates that the transformation efficiency of most RBCs is between 0.400 and 0.600. More specifically, 12 out of 17 RBCs have a positive variability direction with the biggest variability value less than 0.039. Sichuan has an obvious downward trend with a decreased rate of 9.13%, while Yunnan and Guizhou increase by 10.50% and 6.43%, respectively. The transformation efficiency of mature cities is the worst, while the only recession city is the best. The transformation efficiency of RBCs has the highest correlation with the freight volume, other indicators including unemployment rate, ratio of GDP growth, fiscal revenue, average annual population and unemployment rate are high correlation with the transformation efficiency.

Suggested Citation

  • Pu, Song & Xia, Chang, 2024. "Hybrid model for evaluating the transformation of China’s resource-based cities," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    • Handle: RePEc:eee:soceps:v:95:y:2024:i:c:s0038012124001460
    DOI: 10.1016/j.seps.2024.101947
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    References listed on IDEAS

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    1. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
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    1. Liang, Ye & Zhou, Chuanyu & Wu, Yunfeng, 2025. "The emerging driving force of green transformation in resource-based cities: Does the digital economy work?," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 1858-1880.
    2. Chao Gao & Jiayu Fang, 2025. "The Green Effect of Digital Intelligence in Chinese Cities: An Empirical Investigation Based on Big Data and Machine Learning Methods," Sustainability, MDPI, vol. 17(15), pages 1-20, July.

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