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论文编号：	13154
作者编号：	2120202806
上传时间：	2022/6/6 23:39:51
中文题目：	智能网联汽车供应链风险评价与演化研究
英文题目：	Research on Risk Assessment and Evolution of Intelligent and Connected Vehicle Supply Chain
指导老师：	李勇建
中文关键字：	智能网联汽车；供应链；指标体系；风险评价；风险演化
英文关键字：	Intelligent and connected vehicle; Supply chain; Index system; Risk assessment; Risk evolution
中文摘要：	汽车产业是一个国家经济制造业的支柱产业。随着技术更新迭代，智能网联汽车的渗透率正在快速上涨，中国市场更是跻身于世界前列，智能化与自动化驾驶技术逐步应用到汽车上已经成为汽车产业未来发展的必然趋势。智能网联汽车的技术复杂性以及产业生态链的巨大变革等诸多特点决定了其供应链面临的风险形势更加复杂，风险后果更加严重。因此，本文全面把握了智能网联汽车供应链的风险系统构成、风险因素作用关系与风险演化过程，为风险的评价与控制提供理论依据。 首先，本文从两个维度的风险识别原则出发，通过研究文献、国家标准文件与行业权威报告，建设了智能网联汽车供应链风险评价的二级指标体系。一维是基于智能网联汽车的特点，对传统SCOR模型进行改进，将其扩展为计划、研发、采购、生产、配送、运维、逆向七个流程，并据此展开分流程的供应链风险因素分析。另一维是针对每个流程，依据全面风险管理理论涵盖的“人”、“物”、“环”、“管”四要素，分析各流程在这四个方面的风险。 基于所建设的指标体系及可拓物元理论，本文建立了智能网联汽车供应链的风险评价模型，并在指标权重确定上引入了变权概念，采用改进变权层次分析法，通过考虑指标的状态值对其权重变化的影响，降低了评价结果的主观性。研究发现当前我国智能网联汽车行业供应链处于较低风险水平，但偏向中风险，这主要源于研发、运维及采购流程中的宏观环境、车联网信息环境及供应商管理等因素处于中风险或较高风险状态。 最后，本文运用系统动力学方法建立了智能网联汽车供应链风险演化模型，梳理明确各流程子系统间的因果回路和作用机制，从风险演化趋势和风险控制干预两个角度进行仿真模拟。研究得出我国智能网联汽车行业供应链总风险及各流程风险的未来演化趋势，发现为供应链各流程设置风险预警值能够及时促进风险控制资源投入，从而有效控制系统风险量。风险预警值越低，对系统风险量的抑制作用越大，但风险预警值过低也会降低风险控制效率，造成投入资源的浪费。
英文摘要：	The automobile industry is the pillar industry of a country's economic manufacturing industry. With the iteration of technology update, the penetration rate of intelligent and connected vehicle is rising rapidly, and the Chinese market is at the forefront of the world. The gradual application of higher-level automatic driving technology to vehicles has become an inevitable trend of the future development of intelligent and connected vehicles. The technical complexity applied by intelligent and connected vehicle and the great change of the industrial ecological chain determine that the risk situation faced by its supply chain is more complex and the risk consequences are more serious. Therefore, this thesis comprehensively grasps the risk system composition, the action relationship of risk factors and the risk evolution process of intelligent and connected vehicle supply chain, so as to provide a theoretical basis for risk evaluation and control. Through the research of relevant literature and national standards, this thesis starts from two dimensions and constructs a secondary index system of intelligent and connected vehicle supply chain risk evaluation. One dimension is based on its characteristics to improve the traditional SCOR model into seven processes: plan, research and development, source, make, deliver, operation and maintenance and reverse, and carry out the analysis of supply chain risk factors by process. The other dimension is to analyze the risks existing in each process of the supply chain according to the four aspects of "human risk operation", "material risk state", "environmental threat" and "short board of management" of comprehensive risk management extended from the theory of total quality management. Based on the index system and extension matter-element theory, this thesis establishes the risk evaluation model of intelligent and connected vehicle supply chain, and uses the improved variable weight AHP to determine the weight of each index. By considering the influence of the state value of the index on its weight change, the subjectivity of the result brought by the fixed weight is reduced. It is found that the current domestic intelligent and connected vehicle supply chain is at a low risk level, but biased towards medium risk. This is mainly due to the fact that the macro environment, the information environment and supplier management are at a medium or high risk level. In the end, using the system dynamics method, this thesis establishes the risk evolution model of intelligent and connected vehicle supply chain, sorts out the causal circuit and action mechanism between each process subsystem, and carries out simulation from the perspective of risk evolution trend and risk influencing factor analysis. On the one hand, it obtains the total risk of intelligent and connected vehicle industry supply chain and the evolution level of each process risk. On the other hand, it is found that setting the risk early warning value for each process of the supply chain can timely promote the investment of risk control resources, so as to effectively control the amount of system risk. The lower the risk early warning value, the greater the inhibitory effect on the amount of system risk. However, the lower the risk early warning value will also reduce the efficiency of risk control and cause a waste of invested resources.
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