Comprehensive Assessment of China's Coal Supply Chain Resilience: An Integrated Framework Based on an Improved Entropy Weight Method–TOPSIS–GRA.
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| Title: | Comprehensive Assessment of China's Coal Supply Chain Resilience: An Integrated Framework Based on an Improved Entropy Weight Method–TOPSIS–GRA. |
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| Authors: | Tang, Jiakuo1,2 (AUTHOR), Jin, Gang2,3 (AUTHOR), Zhang, Jinsuo2,3,4 (AUTHOR) zjs@yau.edu.cn |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 9, p2095. 30p. |
| Subject Terms: | *TOPSIS method, *Grey relational analysis, *Energy security, *Coal reserves, *Organizational resilience |
| Geographic Terms: | China |
| Abstract: | Against the backdrop of global energy landscape restructuring, the advancement of the "dual-carbon" goals, and escalating external uncertainties, coal, as the "ballast stone" of China's new energy system, faces new challenges in terms of supply chain stability and security. Therefore, scientifically assessing China's coal supply chain resilience (CSCR) is of significant theoretical and practical importance for systematically identifying its supply vulnerabilities and ensuring energy supply security under extreme conditions. In the paper, we construct a composite evaluation indicator system using national statistical data from 2010 to 2024. We operationalize resilience across the following four capacities: resistance, absorption, recovery, and adaptive capacity. Annual resilience levels are measured using an integrated framework. This framework combines an improved entropy weight method, TOPSIS, and gray relational analysis (GRA). We then use the indicator contribution degree and obstacle degree models to identify the most influential factors. The results indicate that China's CSCR followed a fluctuating upward, W-shaped trajectory during 2010–2024, with a marked acceleration after 2020. Resistance and absorption capacities display pronounced volatility. Recovery and adaptation capacities improve steadily. The dominant obstacle factors include the share of intelligent coal production capacity, labor productivity per employee, the scale of workforce security, and the working-capital turnover ratio. These findings provide empirical evidence and policy-relevant insights for strengthening China's CSCR and reinforcing national energy security. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | Against the backdrop of global energy landscape restructuring, the advancement of the "dual-carbon" goals, and escalating external uncertainties, coal, as the "ballast stone" of China's new energy system, faces new challenges in terms of supply chain stability and security. Therefore, scientifically assessing China's coal supply chain resilience (CSCR) is of significant theoretical and practical importance for systematically identifying its supply vulnerabilities and ensuring energy supply security under extreme conditions. In the paper, we construct a composite evaluation indicator system using national statistical data from 2010 to 2024. We operationalize resilience across the following four capacities: resistance, absorption, recovery, and adaptive capacity. Annual resilience levels are measured using an integrated framework. This framework combines an improved entropy weight method, TOPSIS, and gray relational analysis (GRA). We then use the indicator contribution degree and obstacle degree models to identify the most influential factors. The results indicate that China's CSCR followed a fluctuating upward, W-shaped trajectory during 2010–2024, with a marked acceleration after 2020. Resistance and absorption capacities display pronounced volatility. Recovery and adaptation capacities improve steadily. The dominant obstacle factors include the share of intelligent coal production capacity, labor productivity per employee, the scale of workforce security, and the working-capital turnover ratio. These findings provide empirical evidence and policy-relevant insights for strengthening China's CSCR and reinforcing national energy security. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 19961073 |
| DOI: | 10.3390/en19092095 |
