越览（145）——精读博士论文的4.1引言4.2网络韧性研究指标构建

摘要：This issue of tweets will introduce 4.1 Introduction and 4.2 Construction of indicators for supply chain network resilience under

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“越览（145）——精读博士论文

《供应链网络结构视角下的产业链韧性研究》

的4.1引言和4.2随机与目标中断下

供应链网络韧性研究指标构建

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3.4 Analysis of supply chain network structure indicators

of "Yuelan (145)—— Intensive reading of

the doctoral dissertation

‘Research on the resilience of

the supply chain from the perspective of

supply chain network structure’".

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一、内容摘要（Summary of content）

本期推文将从思维导图、精读内容、知识补充三个方面介绍博士论文《供应链网络结构视角下的产业链韧性研究》的4.1引言和4.2随机与目标中断下供应链网络韧性研究指标构建。

This issue of tweets will introduce 4.1 Introduction and 4.2 Construction of indicators for supply chain network resilience under random and targeted disruptions of the doctoral thesis "Research on Industrial Chain Resilience from the Perspective of Supply Chain Network Structure" from three aspects: mind mapping, intensive reading content, and knowledge supplement.

二、思维导图（Mind mapping）

三、精读内容（Intensive reading content）

（一）引言（Introduction）

作者首先介绍了本部分的研究背景：在全球政治经济环境日益复杂的背景下，供应链全球化、关联化和精益化趋势不断加深，供应链中断问题日益突出。数据显示，企业平均每3.7年会遭遇一次持续1–2个月的中断事件，且风险呈上升趋势。网络攻击、财务风险和信息不透明已成为主要威胁，企业每年因此损失高达1.84亿美元。尤其在后疫情时代，中国企业仍面临生产中断、物流阻滞和需求下跌等挑战。

The author first introduced the research background of this part: Against the backdrop of an increasingly complex global political and economic environment, the globalization, interconnectedness, and leanness of supply chains have continued to deepen, and supply chain disruptions have become increasingly prominent. Data show that companies encounter an average of one to two months of disruption every 3.7 years, and the risk is on the rise. Cyber attacks, financial risks, and information opacity have become major threats, costing companies up to $184 million each year. Especially in the post-epidemic era, Chinese companies are still facing challenges such as production disruptions, logistics blockages, and falling demand.

接着介绍了大型或全球性供应网络常常面临自然灾害、地缘冲突等突发事件带来的中断风险，这些风险虽起始于局部节点，却可能通过网络结构放大，进而引发系统性故障，严重影响物流、信息流和资金流，导致成本上升和销售减少。因此，提升供应链网络的韧性已成为研究热点。

Then, it was introduced that large or global supply networks often face interruption risks caused by natural disasters, geopolitical conflicts and other emergencies. Although these risks start from local nodes, they may be amplified through the network structure, leading to systemic failures, seriously affecting logistics, information flow and capital flow, resulting in rising costs and reduced sales. Therefore, improving the resilience of supply chain networks has become a research hotspot.

作者还提到了目前的研究不足：已有研究表明，供应链网络结构对其韧性具有显著影响，但存在两个主要不足：一是多基于单一上下游关系构建的线性链条，难以反映现实产业中企业间复杂的网状结构；二是忽视企业在网络中的位置对风险传播的作用，导致结论与实际偏差较大，难以为实践提供有效指导。

The author also mentioned the shortcomings of current research: Existing studies have shown that the supply chain network structure has a significant impact on its resilience, but there are two major shortcomings: First, most of the linear chains built based on a single upstream and downstream relationship are difficult to reflect the complex network structure between enterprises in the real industry; second, the role of the enterprise’s position in the network in risk propagation is ignored, resulting in a large deviation between the conclusions and reality, making it difficult to provide effective guidance for practice.

最后介绍了本文的研究目的：本研究基于彭博数据库构建真实的汽车产业供应链网络，采用社会网络分析方法，模拟随机网络与无标度网络下的随机与目标中断情景，分析其韧性差异，并提出相应的网络重构策略，以提升整体网络的抗风险能力。

Finally, the research purpose of this paper is introduced: This study constructs a real automotive industry supply chain network based on the Bloomberg database, uses social network analysis methods to simulate random and target disruption scenarios under random networks and scale-free networks, analyzes their resilience differences, and proposes corresponding network reconstruction strategies to enhance the overall network's risk resistance.

（二）指标提出与网络构建（Indicator proposal and network construction）

1. 韧性指标构建（Resilience index construction）

网络韧性指在部分结构或功能失效的情况下，网络仍能保持运行和连通的能力。具备韧性的供应链网络在面临中断时仍能维持物资供应和正常运作。通过对比图示案例可见，不同结构的供应链在节点中断时表现出不同的韧性水平，部分结构能保障资源持续流动，部分则可能导致供应中断。因此，为更科学评估供应链网络韧性，本文引入三类四个衡量指标。

Network resilience refers to the ability of a network to remain operational and connected when some structures or functions fail. A resilient supply chain network can maintain material supply and normal operation in the face of disruptions. By comparing the illustrated cases, it can be seen that supply chains with different structures show different levels of resilience when nodes are interrupted. Some structures can ensure the continuous flow of resources, while others may cause supply disruptions. Therefore, in order to more scientifically evaluate the resilience of supply chain networks, this article introduces three categories and four measurement indicators.

（1）供应链可用性（Supply chain availability）

供应链可用性反映网络中节点是否能获得维持运行所需的物资供应。不同于以往将供应网络视为无向网络并将节点限定为供应商或客户的假设，本文考虑真实供应链中物资流动的有向性以及企业兼具供应与需求角色的特点，采用具有入度（即能获取物资）的节点数量占总节点数的比例作为可用性的衡量标准，并基于节点集合V和边集合E建立相应的计算模型。

Supply chain availability reflects whether nodes in the network can obtain the supplies needed to maintain operation. Different from the previous assumption that the supply network is an undirected network and the nodes are limited to suppliers or customers, this paper considers the directional nature of material flow in the real supply chain and the characteristics of enterprises playing both supply and demand roles. The proportion of nodes with in-degree (i.e., able to obtain materials) to the total number of nodes is used as the measure of availability, and a corresponding calculation model is established based on the node set V and the edge set E.

（2）供应链连通性（Supply chain connectivity）

供应链连通性反映网络中节点间的整体连接程度，是衡量韧性的重要指标。传统研究常用网络规模或密度评估连通性，但这无法准确反映节点之间的可达性。为更真实地衡量供应链的联通程度，本文采用最大连通子图的规模作为指标。在最大连通子图中，任意两个节点之间均可达，能较好体现网络在部分节点中断后的整体连通能力。

Supply chain connectivity reflects the overall degree of connection between nodes in the network and is an important indicator for measuring resilience. Traditional studies often use network size or density to evaluate connectivity, but this cannot accurately reflect the accessibility between nodes. In order to more realistically measure the connectivity of the supply chain, this paper uses the size of the largest connected subgraph as an indicator. In the largest connected subgraph, any two nodes can be reached, which can better reflect the overall connectivity of the network after some nodes are interrupted.

（3）供应链可达性（Supply chain accessibility）

供应链可达性反映网络中资源传递的效率，与可用性不同，侧重衡量传递的速度与成本。为此，本文借鉴Latora & Marchiori（2001）的路径效率思想，采用平均路径长度和最大路径长度两个指标，路径越短代表网络传输效率越高，资源和信息传递越快捷，供应链越具韧性。

Supply chain accessibility reflects the efficiency of resource transfer in the network. Unlike availability, it focuses on measuring the speed and cost of transfer. To this end, this paper draws on the path efficiency idea of Latora & Marchiori (2001) and uses two indicators: average path length and maximum path length. The shorter the path, the higher the network transmission efficiency, the faster the transfer of resources and information, and the more resilient the supply chain.

2. 网络构建（Network construction）

为更全面刻画汽车产业链结构特征，本文在2021年构建的三级供应链网络基础上，进一步延伸采集核心汽车企业的二级主要供应商与客户信息，以及一级供应商中上市企业的上下游关系，最终建立了包含16,024个节点和39,239条边的五级汽车产业供应链网络。

In order to more comprehensively characterize the structural characteristics of the automobile industry chain, this article further extends the collection of information on the second-level major suppliers and customers of core automobile companies, as well as the upstream and downstream relationships of listed companies among the first-level suppliers, based on the three-level supply chain network constructed in 2021, and finally established a five-level automobile industry supply chain network with 16,024 nodes and 39,239 edges.

为深入分析网络结构对供应链韧性的影响，本文同时构建了一个随机网络和两个无标度网络用于对比分析。随机网络模拟在完全市场竞争下企业关系随机形成的网络结构，节点数和边数与真实网络一致，采用Python语言实现。无标度网络则反映政策或外力干预下由少数龙头企业主导的网络结构，构建时分别设定新节点连接边数为2和3，生成的网络具有幂律分布特征，边数分别为32,044和48,063。

In order to deeply analyze the impact of network structure on supply chain resilience, this paper constructs a random network and two scale-free networks for comparative analysis. The random network simulates the network structure formed randomly by enterprise relationships under perfect market competition. The number of nodes and edges is consistent with the real network and is implemented in Python. The scale-free network reflects the network structure dominated by a few leading enterprises under policy or external intervention. The number of edges connecting new nodes is set to 2 and 3 respectively during construction. The generated network has power-law distribution characteristics, with 32,044 and 48,063 edges respectively.

通过比较真实网络、随机网络与无标度网络在不同中断情境下的韧性变化，本文旨在为汽车产业供应链结构优化与韧性提升提供理论依据。

By comparing the changes in resilience of real networks, random networks, and scale-free networks under different disruption scenarios, this paper aims to provide a theoretical basis for optimizing the supply chain structure and improving resilience in the automotive industry.

四、知识补充

遗传算法是一种基于自然选择和遗传机制的优化与搜索算法，属于进化计算的一种。它通过模拟达尔文生物进化论中的“适者生存”原理，逐步逼近问题的最优解，常用于求解复杂问题的全局最优解。

Genetic algorithm is an optimization and search algorithm based on natural selection and genetic mechanism, which belongs to a kind of evolutionary computing. It gradually approaches the optimal solution of the problem by simulating the "survival of the fittest" principle in Darwin's theory of biological evolution, and is often used to solve the global optimal solution of complex problems.

遗传算法将问题的可能解表示为染色体（个体），组成一个种群，然后通过以下过程不断“进化”：

Genetic algorithms represent possible solutions to a problem as chromosomes (individuals), forming a population, which then evolves through the following process:

1. 初始化：随机生成一定数量的个体作为初始种群。

1. Initialization: Randomly generate a certain number of individuals as the initial population.

2. 适应度评估：通过适应度函数评估每个个体解的优劣。

2. Fitness evaluation: The fitness function is used to evaluate the quality of each individual solution.

3. 选择：选择适应度高的个体进入下一代。

3. Selection: Select individuals with high fitness to enter the next generation.

4. 交叉：将两个个体的“基因”片段交换，生成新个体。

4. Crossover: Exchange the "gene" fragments of two individuals to generate a new individual.

5. 变异：对个体基因进行随机微调，增加多样性。

5. Mutation: Randomly tweak individual genes to increase diversity.

6. 迭代：重复上述过程，种群不断进化，直到满足终止条件（如达到最大迭代次数或解满足精度）。

6. Iteration: Repeat the above process and the population continues to evolve until the termination condition is met (such as reaching the maximum number of iterations or the solution meets the accuracy).

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