智能网联新能源汽车供应链韧性评估方法

程茜伶; 王礼刚; 蔡晓禹; 陈坚

doi:10.16503/j.cnki.2095-9931.2025.03.005

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交通运输研究 ›› 2025, Vol. 11 ›› Issue (3) : 43-54. DOI: 10.16503/j.cnki.2095-9931.2025.03.005

理论与方法

智能网联新能源汽车供应链韧性评估方法

程茜伶 ¹ ,
王礼刚 ²^,^* ,
蔡晓禹 ³ ,
陈坚 ¹

作者信息 +

Resilience Evaluation Method for Intelligent Connected and New Energy Vehicle Supply Chain

CHENG Xiling ¹ ,
WANG Ligang ²^,^* ,
CAI Xiaoyu ³ ,
CHEN Jian ¹

Author information +

文章历史 +

摘要

为衡量智能网联新能源汽车供应链面对外部干扰时保持稳定性的能力，提出了供应链韧性评估方法。首先，考虑智能网联新能源汽车供应链研发、供应、生产、销售、售后等5个环节的抗风险能力，从单一环节抵抗能力与多环节协调能力两个维度提出供应链韧性测度框架；然后，采用熵权-TOPSIS法、耦合协调模型、K-means聚类算法进行供应链韧性的量化评价和等级划分，并基于12个地区的发展数据开展实证研究；最后，通过指标障碍度模型分析供应链韧性的主要影响因素。结果表明：各地区供应链韧性水平总体差距较大，广东、江苏、上海、浙江在供应链各环节的表现领先；高韧性地区与低韧性地区的差距主要来源于供应链上游环节，两者在零部件配套方面的差距最为显著，但在后市场服务保障方面的差距较小；大多地区的供应链处于濒临失衡及以下状态，且足够强的风险抵抗能力伴随着较强的协调能力；维修保养企业聚集密度、经销商聚集密度、专利发布数量、零部件供应商数量、新能源汽车产量是影响供应链韧性的主要因素。因此，各地区在扩大产业规模的同时要注重各环节能力的协调互补，避免因供应链失衡而阻碍供应链效能的提升。

Abstract

To measure the ability of the intelligent connected and new energy vehicle supply chain to maintain stability in the face of external disturbances, a supply chain resilience assessment method is proposed. Firstly, considering the risk resistance capability of the five links of research and development, supply, production, sale, and after-sale in the intelligent connected and new energy vehicle supply chain, a supply chain resilience measurement framework is proposed from two dimensions: single link resistance capability and multi link coordination capability. Then, the entropy weight TOPSIS method, coupled coordination degree model, and K-means clustering algorithm are used to quantitatively evaluate and classify the resilience of the supply chain. And based on the development data of 12 regions, case analysis is conducted. Finally, the main influencing factors of supply chain resilience are identified through the indicator obstacle degree model. The results indicate that there is a significant overall gap in the resilience level of supply chains among different regions, with Guangdong, Jiangsu, Shanghai, and Zhejiang showing leading performances in various links of the supply chain; the gap between high resilience areas and low resilience areas mainly comes from the upstream links of the supply chain, with the most significant difference in component matching between the two, but the gap in post market service guarantee is small; the supply chain in most regions is on the brink of imbalance or below, and strong risk resistance is accompanied by strong coordination ability; the main factors affecting the resilience of the supply chain are the clustering density of maintenance and repair enterprises, the clustering density of dealers, the number of patent publications, the number of component suppliers, and the output of new energy vehicles. Therefore, while expanding the industrial scale in various regions, attention should be paid to the coordination and complementarity of capabilities in each link, in order to avoid hindering the improvement of supply chain efficiency due to supply chain imbalance.

导出引用

程茜伶, 王礼刚, 蔡晓禹, 等. 智能网联新能源汽车供应链韧性评估方法[J]. 交通运输研究. 2025, 11(3): 43-54 https://doi.org/10.16503/j.cnki.2095-9931.2025.03.005

CHENG Xiling, WANG Ligang, CAI Xiaoyu, et al. Resilience Evaluation Method for Intelligent Connected and New Energy Vehicle Supply Chain[J]. Transport Research. 2025, 11(3): 43-54 https://doi.org/10.16503/j.cnki.2095-9931.2025.03.005

中图分类号： U491.1

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