A Fuzzy Model Using Entropy Weight for Financial Risk Measurement and Analysis to Enhance Energy Performance: A Case Study of New Energy Vehicle in China
DOI:
https://doi.org/10.62270/jirmcs.v3i1.25Keywords:
Double carbon, New energy, Fuzzy comprehensive evaluation, Financial risk, automobile companyAbstract
With the tightening of government subsidies and the increasing thresholds for preferential policies, China’s new energy vehicle industry has entered a critical period of transformation from being “policy-driven” to “policy and market-driven.” As it becomes significantly more difficult for new energy vehicle enterprises to obtain government subsidies, they are likely to face heightened financial risks. This paper develops a financial risk evaluation index system based on four key aspects: financing risk, operational risk, investment risk, and income distribution risk. Using the entropy weighting method to calculate the weights and the fuzzy comprehensive evaluation method to assess the financial risks, the paper evaluates the financial risk of C Automobile Company. The findings reveal that the company’s current assets, such as inventory and accounts receivable, exhibit a weak turnover rate, suggesting a need to improve its current ratio. Moreover, the returns generated by its total assets are low, indicating poor operational efficiency, which calls for better asset management and enhanced use of funds. Additionally, C Automobile Company’s long-term equity investments are not sufficiently profitable, prompting a reassessment of the feasibility of these investment programs. Lastly, the company’s joint venture has incurred substantial losses, which have hampered its growth, emphasizing the need for a sound business strategy and a focus on strengthening brand value management. This paper provides an analysis of C Automobile Company's financial risk, offering a reference for other enterprises in the new energy vehicle industry as they seek to implement comprehensive and effective financial risk evaluation and control strategies.
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Copyright (c) 2024 Shi Yin, Aicong Liu, Yingying Zhang, Yuexia Wang, Jiachen Wang

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