WO2022041267A1 - Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk - Google Patents

Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk Download PDF

Info

Publication number
WO2022041267A1
WO2022041267A1 PCT/CN2020/112713 CN2020112713W WO2022041267A1 WO 2022041267 A1 WO2022041267 A1 WO 2022041267A1 CN 2020112713 W CN2020112713 W CN 2020112713W WO 2022041267 A1 WO2022041267 A1 WO 2022041267A1
Authority
WO
WIPO (PCT)
Prior art keywords
risk
supply chain
rail transit
maintenance
logistics supply
Prior art date
Application number
PCT/CN2020/112713
Other languages
French (fr)
Chinese (zh)
Inventor
夏泽宇
方芳
夏钢
Original Assignee
苏州大成电子科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 苏州大成电子科技有限公司 filed Critical 苏州大成电子科技有限公司
Priority to PCT/CN2020/112713 priority Critical patent/WO2022041267A1/en
Publication of WO2022041267A1 publication Critical patent/WO2022041267A1/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/08Logistics, e.g. warehousing, loading or distribution; Inventory or stock management

Definitions

  • the present invention relates to a method for risk identification and assessment of rail transit operation and maintenance logistics supply chain, which belongs to the technical field of supply chain logistics.
  • BACKGROUND OF THE INVENTION With the rapid development of rail transit, the pressure on rail transit system operation and maintenance is increasing.
  • the risk of rail transit operation and maintenance logistics supply chain is related to all aspects of rail transit operation safety, punctuality and efficiency.
  • the rapid development of rail transit, the lack of experience in rail transit operation and maintenance, the relative imperfection of related operation and maintenance facilities and policies, and the resulting risk problems have become extremely acute. How to correctly identify the factors affecting the logistics risk of the rail transit operation and maintenance system, evaluate the risk results and propose improved risk response strategies are important research topics in this field.
  • the researchers' research on supply chain risk mainly focuses on the fragility, uncertainty factors, operation interruption, etc. of the supply chain, and then summarizes the research focus of supply chain risk factors in environmental risk, demand risk, interruption risk, policy risk, etc. .
  • Risk assessment is the most challenging work in risk management, mainly using scoring method, semi-quantitative method, frequency domain analysis method, etc. Identification of risk factors such as supply chain network disruption, endogenous and exogenous risks, profit distribution risk, etc., risk assessment methods such as principal-agent, Bayesian network, fuzzy comprehensive evaluation, coefficient of variation, etc.
  • qualitative research methods are more and quantitative methods are insufficient.
  • the analysis of logistics supply chain risk in rail transit operation and maintenance system cannot meet the needs of rail transit operation and maintenance risk management.
  • the technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a logistics supply chain risk identification and assessment method that can comprehensively assess the operational risk of the logistics supply chain of the rail transit operation and maintenance system.
  • the technical solution adopted in the present invention is: a method for identifying and evaluating the risk of rail transit operation and maintenance logistics supply chain, comprising the following steps: S01, the weight analysis of the AHP method, using the analytic hierarchy process, and inputting the relevant data according to the judgment of the manager, will calculate the efficiency, quality, cost, service level and Trust the relative weights of the five risk factors, respectively a, b, c, d, and e, where the sum of the five relative weights is 1; 502, the weight analysis process of the ANP method,; calculated using the AHP method in five The weights of the four risk dimensions under the risk factor.
  • S02 specifically includes the following steps: Step 1: construct a judgment matrix of risk assessment dimensions and risk factors, calculate the eigenvector corresponding to the maximum eigenvalue of each judgment matrix, and perform normalization processing and consistency check. If the judgment matrix passes the consistency check, go to Step 2; if the judgment matrix fails the consistency check, go to Step 1 again; Step 2: Use the eigenvectors as the ranking vector of network risk factors to obtain ranking relative to other risk assessment factors Vector; Step 3: combine the ordering vectors of the mutual influence of all network layer risk assessment factors to obtain an unweighted supermatrix; Step 4: multiply the judgment matrix and the unweighted supermatrix to obtain a weighted supermatrix; Step 5: to reflect the risk Evaluate the dependence and feedback relationship between the factors, and perform stability processing on the weighted supermatrix; Step 6: On the basis of the weighted supermatrix, calculate the final weights of each evaluation factor of the aviation logistics supply chain risk.
  • S01 the evaluation opinions of researchers and managers are obtained in the form of telephone interviews or face-to-face interviews.
  • market sensitivity, information drive, process integration and logistics network connectivity are regarded as the four dimensions under the risk factors of Guangxi aviation logistics supply chain.
  • the market sensitivity is measured by four risk factors: Completeness (CD), Satisfaction (Os), On Time Rate (FPR) and Operational Ability (0A).
  • the logistics network connectivity means connectivity in spatial structure, which is measured by three risk factors: the number of cities (NCN), the number of operating companies (NC), and the density (FD).
  • the present invention provides a method for identifying and evaluating the risk of a rail transit operation and maintenance logistics supply chain, which studies the risk identification and evaluation method of the logistics supply chain of the rail transit operation and maintenance system from an overall perspective, and can provide an effective method for identifying and evaluating the risk of the rail transit operation and maintenance system.
  • Systematic logistics supply chain operation risk assessment can improve the operation ability and operation competitiveness of rail transit operation and maintenance enterprises.
  • Analytic Hierarchy Process AHP
  • ANP Analytic Hierarchy Process
  • the present invention uses the AHP method to solve the weights of the risk assessment factors with an independent relationship, and uses the ANP method to solve the weights of the risk factors with an interdependent relationship.
  • the specific process is as follows.
  • Step 1 construct a judgment matrix of risk assessment dimensions and risk factors, calculate the eigenvector corresponding to the maximum eigenvalue of each judgment matrix, and perform normalization processing and consistency check. If the judgment matrix passes the consistency check, go to step 2; if the judgment matrix fails the consistency check, go to step 1 again.
  • Step 2 Take the feature vector as the ranking vector of network risk factors, and obtain the ranking vector relative to other risk assessment factors.
  • Step 3 Combine the ordered vectors of interactions of all network layer risk assessment factors to obtain an unweighted supermatrix.
  • Step 4 Multiply the judgment matrix and the unweighted supermatrix to obtain a weighted supermatrix.
  • Step 5 In order to reflect the dependence and feedback relationship between the risk assessment factors, the stability processing is performed on the weighted supermatrix.
  • Step 6 On the basis of the weighted super matrix, calculate the final weights of each assessment factor of logistics supply chain risk.

Abstract

A method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk, comprising the following steps: S01: in AHP weighting analysis, using an analytic hierarchy process and inputting relevant data according to the evaluation opinion of a manager to calculate the relative weights of the five risk factors of efficiency, quality, cost, service level, and trust, respectively a, b, c, d, and e, in the overall goals for the identification and evaluation of the logistics supply chain risk of a rail transit operation and maintenance system, the total of the five relative weights being 1; and S02: during the ANP weighting analysis, using the ANP method to calculate the weights of four risk dimensions under the five risk factors. The present method comprehensively studies the logistics supply chain risk of a rail transit operation and maintenance system to evaluate risk and can thereby improve the operation and maintenance management capability and the operation and maintenance competitiveness of an operating company.

Description

 一种轨道交通运维物流供应链风险识别与评估方法A method for risk identification and assessment of rail transit operation and maintenance logistics supply chain
 
 
技术领域
本发明涉及一种轨道交通运维物流供应链风险识别与评估方法,属于供应链物流技术领域。
背景技术轨道交通快速发展,轨交系统运维压力越来越大,其中轨交运维物流供应链的风险关系到轨交运营的安全、正点和高效的方方面面。
轨交发展快速与轨交运维经验缺乏、相关运维设施设备和政策相对不完善,带来的风险问题也变得异常尖锐。如何正确识别影响轨交运维系统的物流风险的因素,评估风险结果和提出改进风险应对策略,是该领域研究的重要课题。
研究者对供应链风险的研究主要集中在供应链的脆弱性、不确定性因素、运行中断等,进而归纳了供应链风险因素的研究重点体现在环境风险、需求风险、中断风险、政策风险等。风险评估是风险管理中最具挑战性的工作,主要使用评分法、半定量化方法、频域分析方法等。风险因素识别如供应链网络破坏、内生风险和外生风险、利润分配风险等,风险评估方法如委托代理、贝叶斯网络、模糊综合评判、变异系数等。但是各种研究方法中定性研究方法较多而定量方法不足,特别对于轨交运维系统的物流供应链风险的分析仅仅不能满足对于轨交运维风险管理的需求。
发明内容
本发明要解决的技术问题是,克服现有技术的不足,提供一种可以全面对轨交运维系统的物流供应链运行风险进行评估的物流供应链风险识别与评估方法。
为解决上述技术问题,本发明采用的技术方案为:一种轨道交通运维物流供应链风险识别与评估方法,包括以下步骤:
S01,AHP方法的权值解析,运用层次分析方法,依据管理者的评判意见输入有关数据将计算得到轨交运维系统的物流供应链风险评估总目标下的效率、质量、成本、服务水平和信任五个风险因素的相对权值,分别为a、b、c、d和e,其中五个相对权值的总和为1;502,ANP方法的权重解析过程,;使用AHP方法计算在五个风险因素下的四个风险维度的权值。
S02具体包括下面几个步骤:
步骤1:构造风险评估维度和风险因子的判断矩阵,计算每个判断矩阵的最大特征值对应的特征向量,并做归一化处理和一致性检验。如果判断矩阵通过一致性检验,转到步骤2;如果判断矩阵没有通过一致性检验,重新进行步骤1;步骤2:将特征向量作为网络风险因子的排序向量,得到相对于其他风险评估因子的排序向量;步骤3:将所有网络层风险评估因子的相互影响的排序向量组合起来,得到未加权超矩阵;步骤4:判断矩阵与未加权超矩阵相乘得到加权超矩阵;步骤5:为反映风险评估因子间的依存和反馈关系,对加权超矩阵进行稳定性处理;步骤6:在加权超矩阵的基础上,计算航空物流供应链风险各个评估因子的最终权值。
S01中,采取电话访谈或面谈的形式获得研究者和管理者的评判意见。
S01中,将市场敏感性、信息驱动、流程集成和物流网络连通性作为广西航空物流供应链风险因素下的四个维度。
所述市场敏感性通过完整性(CD)、满意度(Os)、准时率(FPR)和作业能力(0A)四个风险因子衡量。
所述物流网络连通性意味着在空间结构上实现连通,通过城市数量(NCN)、运营公司数量(NC)和密度(FD)三个风险因子来衡量。


FIELD OF THE INVENTION The present invention relates to a method for risk identification and assessment of rail transit operation and maintenance logistics supply chain, which belongs to the technical field of supply chain logistics.
BACKGROUND OF THE INVENTION With the rapid development of rail transit, the pressure on rail transit system operation and maintenance is increasing. The risk of rail transit operation and maintenance logistics supply chain is related to all aspects of rail transit operation safety, punctuality and efficiency.
The rapid development of rail transit, the lack of experience in rail transit operation and maintenance, the relative imperfection of related operation and maintenance facilities and policies, and the resulting risk problems have become extremely acute. How to correctly identify the factors affecting the logistics risk of the rail transit operation and maintenance system, evaluate the risk results and propose improved risk response strategies are important research topics in this field.
The researchers' research on supply chain risk mainly focuses on the fragility, uncertainty factors, operation interruption, etc. of the supply chain, and then summarizes the research focus of supply chain risk factors in environmental risk, demand risk, interruption risk, policy risk, etc. . Risk assessment is the most challenging work in risk management, mainly using scoring method, semi-quantitative method, frequency domain analysis method, etc. Identification of risk factors such as supply chain network disruption, endogenous and exogenous risks, profit distribution risk, etc., risk assessment methods such as principal-agent, Bayesian network, fuzzy comprehensive evaluation, coefficient of variation, etc. However, among various research methods, qualitative research methods are more and quantitative methods are insufficient. Especially, the analysis of logistics supply chain risk in rail transit operation and maintenance system cannot meet the needs of rail transit operation and maintenance risk management.
SUMMARY OF THE INVENTION The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a logistics supply chain risk identification and assessment method that can comprehensively assess the operational risk of the logistics supply chain of the rail transit operation and maintenance system.
In order to solve the above-mentioned technical problems, the technical solution adopted in the present invention is: a method for identifying and evaluating the risk of rail transit operation and maintenance logistics supply chain, comprising the following steps:
S01, the weight analysis of the AHP method, using the analytic hierarchy process, and inputting the relevant data according to the judgment of the manager, will calculate the efficiency, quality, cost, service level and Trust the relative weights of the five risk factors, respectively a, b, c, d, and e, where the sum of the five relative weights is 1; 502, the weight analysis process of the ANP method,; calculated using the AHP method in five The weights of the four risk dimensions under the risk factor.
S02 specifically includes the following steps:
Step 1: construct a judgment matrix of risk assessment dimensions and risk factors, calculate the eigenvector corresponding to the maximum eigenvalue of each judgment matrix, and perform normalization processing and consistency check. If the judgment matrix passes the consistency check, go to Step 2; if the judgment matrix fails the consistency check, go to Step 1 again; Step 2: Use the eigenvectors as the ranking vector of network risk factors to obtain ranking relative to other risk assessment factors Vector; Step 3: combine the ordering vectors of the mutual influence of all network layer risk assessment factors to obtain an unweighted supermatrix; Step 4: multiply the judgment matrix and the unweighted supermatrix to obtain a weighted supermatrix; Step 5: to reflect the risk Evaluate the dependence and feedback relationship between the factors, and perform stability processing on the weighted supermatrix; Step 6: On the basis of the weighted supermatrix, calculate the final weights of each evaluation factor of the aviation logistics supply chain risk.
In S01, the evaluation opinions of researchers and managers are obtained in the form of telephone interviews or face-to-face interviews.
In S01, market sensitivity, information drive, process integration and logistics network connectivity are regarded as the four dimensions under the risk factors of Guangxi aviation logistics supply chain.
The market sensitivity is measured by four risk factors: Completeness (CD), Satisfaction (Os), On Time Rate (FPR) and Operational Ability (0A).
The logistics network connectivity means connectivity in spatial structure, which is measured by three risk factors: the number of cities (NCN), the number of operating companies (NC), and the density (FD).
本发明的有益效果:本发明提供的一种轨道交通运维物流供应链风险识别与评估方法,从整体角度研究轨交运维系统的物流供应链风险识别和评估方法,可以对轨交运维系统物流供应链运行风险进行评估,能够提高轨交运维企业经营能力和运营竞争能力。Beneficial effects of the present invention: The present invention provides a method for identifying and evaluating the risk of a rail transit operation and maintenance logistics supply chain, which studies the risk identification and evaluation method of the logistics supply chain of the rail transit operation and maintenance system from an overall perspective, and can provide an effective method for identifying and evaluating the risk of the rail transit operation and maintenance system. Systematic logistics supply chain operation risk assessment can improve the operation ability and operation competitiveness of rail transit operation and maintenance enterprises.
具体实施方式detailed description
下面本发明作进一步描述,以下实施例仅用于更加清楚地说明本发明的技术方案,而不能以此来限制本发明的保护范围。The present invention is further described below, and the following examples are only used to illustrate the technical solutions of the present invention more clearly, and cannot be used to limit the protection scope of the present invention.
在层次分析方法(AHP)基础上系统地的网络层次分析法(ANP),该方法更准确地描述了客观事物之间相互依赖和反馈决策的关系,构建了基于利益、机会、成本和风险的决策模式。因此,本文结合AHP和ANP方法处理问题时各自的优势,建立物流供应链风险评估组合模型。On the basis of the Analytic Hierarchy Process (AHP), the Analytic Hierarchy Process (ANP) of the network is systematically used, which more accurately describes the relationship between the interdependence and feedback decision-making between objective things, and constructs a network based on benefits, opportunities, costs and risks. decision mode. Therefore, this paper combines the respective advantages of AHP and ANP methods to deal with the problem, and establishes a combined model of logistics supply chain risk assessment.
本发明对具有独立关系的风险评估因素的权重使用AHP方法求解,对具有相互依赖关系的风险因子权重使用ANP方法求解,具体过程如下。The present invention uses the AHP method to solve the weights of the risk assessment factors with an independent relationship, and uses the ANP method to solve the weights of the risk factors with an interdependent relationship. The specific process is as follows.
1、AHP方法的权值解析。运用层次分析方法,依据管理者的评判意见输入有关数据,采取电话访谈或面谈的形式,将市场敏感性、信息驱动、流程集成和物流网络连通性作为物流供应链风险因素下的四个维度。其中市场敏感性是对实际需求的快速反映,通过货物的完整性(CD)、货主满意度(Os)、准时率(FPR)和作业能力(OA)四个风险因子衡量。物流网络连通性意味着物流在空间结构上实现连通,通过城市数量(NCN)、运营公司数量(NC)和密度(FD)三个风险因子来衡量。将计算得到物流供应链风险评估总目标下的效率、质量、成本、服务水平和信任五个风险因素的相对权值,分别为a、b、c、d和e,其中五个相对权值的总和为1。1. Weight analysis of AHP method. Using the analytic hierarchy process, input relevant data according to managers' judgments, take the form of telephone interviews or face-to-face interviews, and take market sensitivity, information drive, process integration and logistics network connectivity as the four dimensions of logistics supply chain risk factors. Among them, market sensitivity is a rapid reflection of actual demand, which is measured by four risk factors: cargo integrity (CD), owner satisfaction (Os), on-time rate (FPR) and operational capability (OA). Logistics network connectivity means that logistics are connected in spatial structure, which is measured by three risk factors: the number of cities (NCN), the number of operating companies (NC), and the density (FD). The relative weights of the five risk factors of efficiency, quality, cost, service level and trust under the overall objective of the logistics supply chain risk assessment will be calculated, which are a, b, c, d and e respectively. The sum is 1.
2、ANP方法的权重解析过程。在相同的风险维度下的各风险因子之间具有相互依存和反馈关系,因此使用AHP方法计算在五个风 险因素下的四个风险维度的权值,具体步骤详细如下:2. The weight analysis process of ANP method. The risk factors under the same risk dimension have interdependence and feedback relationship. Therefore, the AHP method is used to calculate the weights of the four risk dimensions under the five risk factors. The specific steps are as follows:
步骤1:构造风险评估维度和风险因子的判断矩阵,计算每个判断矩阵的最大特征值对应的特征向量,并做归一化处理和一致性检验。如果判断矩阵通过一致性检验,转到步骤2;如果判断矩阵没有通过一致性检验,重新进行步骤1。Step 1: construct a judgment matrix of risk assessment dimensions and risk factors, calculate the eigenvector corresponding to the maximum eigenvalue of each judgment matrix, and perform normalization processing and consistency check. If the judgment matrix passes the consistency check, go to step 2; if the judgment matrix fails the consistency check, go to step 1 again.
步骤2:将特征向量作为网络风险因子的排序向量,得到相对于其他风险评估因子的排序向量。Step 2: Take the feature vector as the ranking vector of network risk factors, and obtain the ranking vector relative to other risk assessment factors.
步骤3:将所有网络层风险评估因子的相互影响的排序向量组合起来,得到未加权超矩阵。Step 3: Combine the ordered vectors of interactions of all network layer risk assessment factors to obtain an unweighted supermatrix.
步骤4:判断矩阵与未加权超矩阵相乘得到加权超矩阵。Step 4: Multiply the judgment matrix and the unweighted supermatrix to obtain a weighted supermatrix.
步骤5:为反映风险评估因子间的依存和反馈关系,对加权超矩阵进行稳定性处理。Step 5: In order to reflect the dependence and feedback relationship between the risk assessment factors, the stability processing is performed on the weighted supermatrix.
步骤6:在加权超矩阵的基础上,计算物流供应链风险各个评估因子的最终权值。Step 6: On the basis of the weighted super matrix, calculate the final weights of each assessment factor of logistics supply chain risk.
以上所述仅是本发明的优选实施方式,应当指出:对于本技术领域的普通技术人员来说,在不脱离本发明原理的前提下,还可以做出若干改进和润饰,这些改进和润饰也应视为本发明的保护范围。The above is only the preferred embodiment of the present invention, it should be pointed out: for those skilled in the art, under the premise of not departing from the principle of the present invention, several improvements and modifications can also be made, and these improvements and modifications are also It should be regarded as the protection scope of the present invention.

Claims (6)

  1. 一种轨道交通运维物流供应链风险识别与评估方法,其特征在于:包括以下步骤:A method for risk identification and assessment of rail transit operation and maintenance logistics supply chain, characterized by comprising the following steps:
    S01,AHP方法的权值解析,运用层次分析方法,依据管理者的评判意见输入有关数据将计算得到轨交运维系统物流供应链风险评估总目标下的效率、质量、成本、服务水平和信任五个风险因素的相对权值,分别为a、b、c、d和e,其中五个相对权值的总和为1;S01, the weight analysis of the AHP method, using the analytic hierarchy process, and inputting the relevant data according to the judgment of the manager, the efficiency, quality, cost, service level and trust under the overall goal of the logistics supply chain risk assessment of the rail transit operation and maintenance system will be calculated. The relative weights of the five risk factors, respectively a, b, c, d, and e, where the sum of the five relative weights is 1;
    S02,ANP方法的权重解析过程,;使用AHP方法计算在五个风险因素下的四个风险维度的权值。S02, the weight analysis process of the ANP method, using the AHP method to calculate the weights of the four risk dimensions under the five risk factors.
  2. 根据权利要求1所述的一种轨道交通运维物流供应链风险识别与评估方法,其特征在于:S02具体包括下面几个步骤:A rail transit operation and maintenance logistics supply chain risk identification and assessment method according to claim 1, characterized in that: S02 specifically includes the following steps:
    步骤1:构造风险评估维度和风险因子的判断矩阵,计算每个判断矩阵的最大特征值对应的特征向量,并做归一化处理和一致性检验。如果判断矩阵通过一致性检验,转到步骤2;如果判断矩阵没有通过一致性检验,重新进行步骤1;Step 1: Construct the judgment matrix of risk assessment dimensions and risk factors, calculate the eigenvector corresponding to the maximum eigenvalue of each judgment matrix, and perform normalization processing and consistency check. If the judgment matrix passes the consistency check, go to step 2; if the judgment matrix fails the consistency check, go to step 1 again;
    步骤2:将特征向量作为网络风险因子的排序向量,得到相对于其他风险评估因子的排序向量;Step 2: Take the feature vector as the ranking vector of network risk factors, and obtain the ranking vector relative to other risk assessment factors;
    步骤3:将所有网络层风险评估因子的相互影响的排序向量组合起来,得到未加权超矩阵;Step 3: Combine the ranking vectors of the mutual influence of all network layer risk assessment factors to obtain an unweighted supermatrix;
    步骤4:判断矩阵与未加权超矩阵相乘得到加权超矩阵;Step 4: Multiply the judgment matrix and the unweighted supermatrix to obtain a weighted supermatrix;
    步骤5:为反映风险评估因子间的依存和反馈关系,对加权超矩阵进行稳定性处理;Step 5: In order to reflect the dependence and feedback relationship between the risk assessment factors, the weighted supermatrix is stabilized;
    步骤6:在加权超矩阵的基础上,计算轨交运维系统物流供应链风险各个评估因子的最终权值。Step 6: On the basis of the weighted super matrix, calculate the final weights of each evaluation factor of the logistics supply chain risk of the rail transit operation and maintenance system.
  3. 根据权利要求1所述的一种轨道交通运维物流供应链风险识别与评估方法,其特征在于:S01中,采取电话访谈或面谈的形式获得研究者和管理者的评判意见。The method for identifying and evaluating the risk of rail transit operation and maintenance logistics supply chain according to claim 1, characterized in that: in S01, the evaluation opinions of researchers and managers are obtained in the form of telephone interviews or face-to-face interviews.
  4. 根据权利要求1所述的一种轨道交通运维物流供应链风险识别与 评估方法,其特征在于:S01中,将市场敏感性、信息驱动、流程集成和物流网络连通性作为轨交运维系统物流供应链风险因素下的四个维度。A rail transit operation and maintenance logistics supply chain risk identification and assessment method according to claim 1, characterized in that: in S01, market sensitivity, information drive, process integration and logistics network connectivity are used as the rail transit operation and maintenance system Four dimensions of logistics supply chain risk factors.
  5. 根据权利要求4所述的一种轨道交通运维物流供应链风险识别与评估方法,其特征在于:所述市场敏感性通过货物的完整性(CD)、货主满意度(Os)、准时率(FPR)和作业能力(OA)四个风险因子衡量。A method for identifying and evaluating risks in rail transit operation and maintenance logistics supply chain according to claim 4, characterized in that: the market sensitivity is determined by the integrity of the goods (CD), the satisfaction of the owner (Os), the on-time rate ( FPR) and operational ability (OA) are measured by four risk factors.
  6.  
    根据权利要求4所述的一种轨道交通运维物流供应链风险识别与评估方法,其特征在于:所述物流网络连通性意味着物流在空间结构上实现连通,通过城市数量(NCN)、运营公司数量(NC)和运营密度(FD)三个风险因子来衡量。

    The method for identifying and evaluating risks in rail transit operation and maintenance logistics supply chain according to claim 4, characterized in that: said logistics network connectivity means that logistics is connected in spatial structure, through the number of cities (NCN), operation The number of companies (NC) and the density of operations (FD) are three risk factors to measure.
PCT/CN2020/112713 2020-08-31 2020-08-31 Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk WO2022041267A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2020/112713 WO2022041267A1 (en) 2020-08-31 2020-08-31 Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2020/112713 WO2022041267A1 (en) 2020-08-31 2020-08-31 Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk

Publications (1)

Publication Number Publication Date
WO2022041267A1 true WO2022041267A1 (en) 2022-03-03

Family

ID=80354403

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/112713 WO2022041267A1 (en) 2020-08-31 2020-08-31 Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk

Country Status (1)

Country Link
WO (1) WO2022041267A1 (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114386884A (en) * 2022-03-24 2022-04-22 广东电网有限责任公司东莞供电局 Lean evaluation method for power grid dispatching operation
CN114936786A (en) * 2022-06-07 2022-08-23 中交机电工程局有限公司 Comprehensive efficiency evaluation method of road traffic energy self-consistency system
CN115081918A (en) * 2022-07-07 2022-09-20 北京交通大学 Rail transit risk point prediction method and system based on data driving
CN115577960A (en) * 2022-10-25 2023-01-06 北京思维实创科技有限公司 Method and device for evaluating dynamic service level of urban rail transit network equipment

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105930981A (en) * 2016-05-10 2016-09-07 大连理工大学 Supply chain financing platform capable of risk quantification and real-time automatic processing
CN107784451A (en) * 2017-11-10 2018-03-09 苏州大成电子科技有限公司 A kind of Air Logistics SC risk identification and appraisal procedure
US20190009923A1 (en) * 2014-11-10 2019-01-10 Federal Express Corporation Risk assessment framework
CN109544062A (en) * 2018-10-30 2019-03-29 长沙理工大学 A kind of Fast Packet vanning information processing system and method suitable for Air Logistics
CN110598984A (en) * 2019-08-09 2019-12-20 清华大学 Combined selection method and device for safety management measures in construction of super high-rise building
CN111177649A (en) * 2019-12-11 2020-05-19 交通运输部水运科学研究所 Ship-borne packaged cargo transportation risk assessment method based on big data fusion

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190009923A1 (en) * 2014-11-10 2019-01-10 Federal Express Corporation Risk assessment framework
CN105930981A (en) * 2016-05-10 2016-09-07 大连理工大学 Supply chain financing platform capable of risk quantification and real-time automatic processing
CN107784451A (en) * 2017-11-10 2018-03-09 苏州大成电子科技有限公司 A kind of Air Logistics SC risk identification and appraisal procedure
CN109544062A (en) * 2018-10-30 2019-03-29 长沙理工大学 A kind of Fast Packet vanning information processing system and method suitable for Air Logistics
CN110598984A (en) * 2019-08-09 2019-12-20 清华大学 Combined selection method and device for safety management measures in construction of super high-rise building
CN111177649A (en) * 2019-12-11 2020-05-19 交通运输部水运科学研究所 Ship-borne packaged cargo transportation risk assessment method based on big data fusion

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114386884A (en) * 2022-03-24 2022-04-22 广东电网有限责任公司东莞供电局 Lean evaluation method for power grid dispatching operation
CN114936786A (en) * 2022-06-07 2022-08-23 中交机电工程局有限公司 Comprehensive efficiency evaluation method of road traffic energy self-consistency system
CN114936786B (en) * 2022-06-07 2024-04-26 中交机电工程局有限公司 Comprehensive efficiency evaluation method of road traffic energy source consistent system
CN115081918A (en) * 2022-07-07 2022-09-20 北京交通大学 Rail transit risk point prediction method and system based on data driving
CN115577960A (en) * 2022-10-25 2023-01-06 北京思维实创科技有限公司 Method and device for evaluating dynamic service level of urban rail transit network equipment
CN115577960B (en) * 2022-10-25 2023-07-14 北京思维实创科技有限公司 Dynamic service level assessment method and device for urban rail transit network equipment

Similar Documents

Publication Publication Date Title
WO2022041267A1 (en) Method for identifying and evaluating rail transit operation and maintenance logistics supply chain risk
Qian et al. Financial analyst coverage and corporate social performance: Evidence from natural experiments
Zhai Risk prediction and response strategies in corporate financial management based on optimized BP neural network
Seifbarghy et al. Analyzing the supply chain using SCOR model in a steel producing company
Kartika et al. The Role Of Intellectual Capital And Good Corporate Governance Toward Financial Performance
Liu et al. An integrated method of supply chains vulnerability assessment
Wang et al. Supplier Measurement of Fresh Supply Chain in Sustainable Environment.
Chen et al. GI-TOPSIS based on combinational weight determination and its application to selection of reverse logistics service providers
Valinejad et al. A hybrid model for supply chain risk management based on five-dimensional sustainability approach in telecommunication industry
Alamri et al. An Optimized Method for Accounting Information in Logistic Systems.
Swamy et al. Assessment and prioritization of Supply Chain Risk: Development of AHP model in Aerospace Industry.
Altin et al. CEO Overconfidence and Risk-Taking Behaviour in Indonesian Banking Sectors
CN107292569A (en) Purchasing of consumables management method for judicial expertise/forensic science mechanism
Zhou et al. How To Assess Accounting Materiality Amid Economic Crisis
Xiaofang Construction of Enterprise Economic Benefit Evaluation System Based on Fuzzy Clustering Algorithm
Orio et al. Blockchain and Supply Chain Financing: Innovations and Potential Disruptions
Tahir A Comprehensive Study on Risk Expense Evaluation
Xu et al. Construction and Evaluation of Risk Index System for Intelligent Transportation System Development Project
Banik et al. Leveraging Blockchain for Traceability and Product Authentication in Supply Chains
Xia et al. Analysis and Evaluation of Enterprise Performance Appraisal Index Based on Fuzzy AHP Model
Smith et al. Assessing the ROI of Blockchain Integration in Supply Chain Processes
Tahir et al. A Brief and Comprehensive Study on Risk Avoidance Structure
Purohit et al. Integrating IoT and Blockchain for Real-Time Monitoring and Control in Supply Chains
Xu et al. Multicriteria ABC Inventory Classification Using a Group Decision Making Method with Individual Preferences
Khoza et al. Supply Chain Management Strategies of the Private Residential Construction Sector in South Africa

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20950936

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20950936

Country of ref document: EP

Kind code of ref document: A1