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Research on the Risk Assessment of New Energy Automobile Industry Based on Entropy Weight-Cloud Model in China’s Jiangsu Province

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  • Yanqiu Cao
  • Yijie Bian
  • Rong Wang
  • Lingjun Wang

Abstract

The development of the new energy vehicle industry is necessary for its advantages of saving energy and reducing greenhouse-gas emissions. However, the industry is currently facing risks with regard to, for example, technology, market, and the policy. Most existing studies of industry risk focused on analyzing and evaluating risk factors and summarizing and interpreting risk phenomena. In this study, systematic classification and quantitative analysis for the risk of the new energy vehicle industry were investigated, in which the entropy weight method and cloud model were combined to evaluate and quantify the industry risk. The formation mechanism of the industry risk from endogenous and exogenous perspectives was analyzed to screen out risk-evaluation factors. Combining the expert-investigation and fuzzy-statistics methods, a risk-evaluation index system with six primary indicators and twenty-four secondary indicators was constructed. On the basis of the entropy weight-cloud model, the risk of the new energy automobile industry of Jiangsu province in July 2019 was evaluated. Results indicated that the impact of exogenous risk on the industry was greater than that of endogenous risk, and industry risk was higher than medium risk, which was close to a higher medium level. A series of suggestions are given for preventing industry risk, such as improving the industry’s own ability to resist risk and building the industry’s soft environment.

Suggested Citation

  • Yanqiu Cao & Yijie Bian & Rong Wang & Lingjun Wang, 2021. "Research on the Risk Assessment of New Energy Automobile Industry Based on Entropy Weight-Cloud Model in China’s Jiangsu Province," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-20, June.
  • Handle: RePEc:hin:jnlmpe:4714681
    DOI: 10.1155/2021/4714681
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    Cited by:

    1. Chih-Hung Hsu & Xu He & Ting-Yi Zhang & An-Yuan Chang & Wan-Ling Liu & Zhi-Qiang Lin, 2022. "Enhancing Supply Chain Agility with Industry 4.0 Enablers to Mitigate Ripple Effects Based on Integrated QFD-MCDM: An Empirical Study of New Energy Materials Manufacturers," Mathematics, MDPI, vol. 10(10), pages 1-35, May.

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