新能源汽车产业是国民经济的重要支柱，面对能源和环境问题的日益严峻，其发展是实现经济、环境、社会可持续的必然选择。2023 年中央经济会议指出，“要稳定和扩大传统消费，提振新能源汽车等大宗消费”。随着延续免征购置税和继续加严排放法规等政策利好，新能源汽车产业处在高速发展阶段。反馈到市场层面，新能源汽车已经形成了较大市场规模，但是尚未形成垄断格局，行业标准尚未统一，规模化生产仍面对不少挑战。新兴产业的转型 升级离不开与之相匹配的经营绩效评价方法，为企业经营者提供更加可靠的决策依据。

本文梳理提炼了学者们关于经济增加值（EVA，Economic Value Added）和平衡计分卡（BSC,Balanced Score Card）的相关理论研究，明确了 EVA 法和 BSC 法各自的优势和局限，从而选择 EVA 和 BSC 相结合的方法，构建新能源汽车公司的经营绩效评价体系。本文选取A 公司为研究对象，发现其当前的经营绩效评价存在侧重财务指标、和战略目标不匹配的等问题，所以应用 EVA-BSC 法进行经营绩效评价。接着本文以企业战略为导向，将战略目标细分到财务、客户、内部流程和学习与成长四个维度，选取与战略目标相匹配的经营绩效评价指标，其中，EVA 指标是财务指标的核心。本文运用层次分析法确定 EVA-BSC 经营绩效 评价指标权重，运用功效系数法设置经营绩效评价等级，构建出了 EVA-BSC 经营绩效评价体系并加以应用，得出 A 公司 2021-2023 年的经营绩效评价结果并对结果进行讨论研究。

评价结果显示：A 公司近三年经营绩效均为良好，且逐年向好。分析可知，A 公司市场份额连年攀升、技术创新成果显著，但是也反映出 A 公司财务表现方面不足欠佳，质量管理、售后管理流程也仍有提升空间，这可能是由于企业扩大经营、抢占国内外市场速度过快速度快导致的。为了更好推行 EVA-BSC 经营绩效评价体系，A 公司可以采取建立有效的数据管理系统、开展相关培训宣传以及建立绩效激励与约束制度等措施。

本文通过构建新能源汽车公司的经营绩效评价体系并以 A 公司为案例加以应用，旨在丰富 EVA-BSC 经营绩效评价方法的理论和实践研究，并且也为其他新能源汽车公司建立相匹配的经营绩效评价体系提供借鉴。

The new energy vehicle industry is a crucial pillar of the national economy. Confronting increasingly severe energy and environmental challenges, its development is an inevitable choice for achieving economic, environmental, and social sustainability. The 2023 Central Economic Conference emphasized that we should stabilize and expand traditional consumption and boost mass consumption such as new energy vehicles.With the continuation of the purchase tax exemption and the tightening of emissions regulations, the new energy vehicle industry is in rapid development. Despite significant progress in China's new energy vehicle industry guided by policy, there are still challenges such as unformed monopoly pattern, lack of unified industry standards and obstacles to large-scale production.The transformation and upgrading of emerging industries cannot be separated from the matching performance evaluation method, which provides more reliable decision-making basis for enterprise operators.

This paper synthesizes and distills scholarly research on EVA(Economic Value Added) and BSC(Balanced Score Card) theories, clarifying the strengths and limitations of each method. It proposes a combined EVA and BSC approach to develop an operational performance evaluation system for new energy vehicle companies. Using Company A as a case study, it identifies issues in the current performance evaluation, such as an overemphasis on financial indicators and misalignment with strategic goals. The paper then aligns strategic objectives with four dimensions — financial, customer, internal processes, and learning and growth — selecting performance indicators that match these goals. It employs the Analytic Hierarchy Process (AHP) to determine the weights of EVA-BSC performance indicators, uses the efficacy coefficient method to set performance evaluation levels, and constructs the EVA-BSC performance evaluation system. Finally, it applies this system to assess Company A's performance from 2021 to 2023.

The evaluation results show that Company A has had good operational performance over the past three years, and it has been improving annually. Analysis reveals that Company A's market share has been climbing year after year, and its technological innovations are significant. However, it also shows that Company A's financial performance is subpar, and there is still room for improvement in quality management and after-sales service processes. This may be due to the company expanding its operations and rapidly capturing markets at home and abroad too quickly. To better implement the EVA-BSC performance evaluation system, Company A could adopt measures such as establishing an effective data management system, conducting related training and publicity, and setting up performance incentives and restraint systems.

This paper aims to enrich the theoretical research on the EVA-BSC performance evaluation method by constructing a performance evaluation system for new energy vehicle companies and applying it to Company A as a case study. Additionally, it provides a reference for other new energy vehicle companies to establish a matching performance evaluation system.

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