基于博弈论组合赋权改进物元可拓模型的新能源汽车制造企业供应链绩效评价研究

Research on Supply Chain Performance Evaluation of New Energy Vehicle Manufacturing Enterprises Improved Matter-Element Extension Model Based on Game Theory Combined Weighting

摘要: 在全球气候变化与绿色发展的背景下，新能源汽车制造企业的供应链绩效评价对于提升运营效率、优化资源配置，实现可持续发展具有重要意义。针对现状供应链绩效评价研究在指标选取、理论框架和权重分配等方面的不足，本研究结合博弈论组合赋权与改进物元可拓模型，构建了一种新型的新能源汽车制造企业供应链绩效评价体系。首先，基于ESG理论及行业特点，从财务、顾客、运营、绿色环保和发展成长五个维度构建了包含15项指标的综合评价体系。其次，采用变异系数法和熵权法分别计算各指标权重，并运用博弈论进行组合优化，以平衡不同赋权方法的差异，提高权重分配的合理性。再次，将组合权重引入物元可拓模型，通过关联函数量化指标与绩效等级的匹配程度，实现绩效的动态评价。最后，以国内某知名新能源车企2018~2023年的数据为案例进行实证分析，结果表明：新能源汽车销售量、市场占有率和净资产收益率是影响供应链绩效的关键因素；绿色环保维度表现较弱，需重点关注；企业绩效随时间推移显著提升，验证了模型的有效性。

Abstract: Under the backdrop of global climate change and green development, the supply chain performance evaluation of new energy vehicle manufacturing enterprises is of great significance for enhancing operational efficiency, optimizing resource allocation, and achieving sustainable development. In response to the deficiencies in the current research on supply chain performance evaluation in terms of indicator selection, theoretical framework, and weight allocation, this study combines game theory-based combined weighting and an improved matter-element extension model to construct a novel supply chain performance evaluation system for new energy vehicle manufacturing enterprises. Firstly, based on ESG theory and industry characteristics, a comprehensive evaluation system consisting of 15 indicators is established from five dimensions: finance, customers, operations, green environmental protection, and development and growth. Secondly, the coefficient of variation method and entropy weight method are used to calculate the weights of each indicator, and game theory is applied for combined optimization to balance the differences among different weighting methods and improve the rationality of weight allocation. Thirdly, the combined weights are introduced into the matter-element extension model, and the matching degree between indicators and performance levels is quantified through the correlation function to achieve dynamic performance evaluation. Finally, an empirical analysis is conducted using the data of a well-known domestic new energy vehicle manufacturer from 2018 to 2023. The results show that new energy vehicle sales volume, market share, and return on net assets are the key factors influencing supply chain performance; the performance in the green environmental protection dimension is relatively weak and requires focused attention; and the enterprise performance has significantly improved over time, verifying the effectiveness of the model.