Methods for mitigating disruptions in complex supply chain structures: a systematic literature review

被引:135
作者
Bier, Tobias [1 ]
Lange, Anne [2 ]
Glock, Christoph H. [1 ]
机构
[1] Tech Univ Darmstadt, Dept Law & Econ, Darmstadt, Germany
[2] Univ Luxembourg, Luxembourg Ctr Logist & Supply Chain Management, Luxembourg, Luxembourg
关键词
supply chain; risk management; supply chain disruption; systematic literature review; network theory; resilience; network structure; SOCIAL NETWORK ANALYSIS; RISK-MANAGEMENT; ADAPTIVE SYSTEMS; DECISION-MAKING; NEXUS SUPPLIER; GRAPH-THEORY; RESILIENCE; PERFORMANCE; UNCERTAINTY; IDENTIFICATION;
D O I
10.1080/00207543.2019.1687954
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Supply chain risk management is extremely important for the success of a company. Due to the increasing complexity of supply chains, avoiding and mitigating the effects of disruptions is very challenging. This article presents the results of a systematic literature review and content analysis in order to provide a comprehensive overview of the methods that are currently used for mitigating supply chain disruptions. The results of the review indicate that research in this field is interdisciplinary and that no common modelling language has emerged thus far. Prior research mostly redraws to graph theory and/or social network analysis, although a few methods have been developed recently specifically for supply chain risk management. We observe that prior contributions addressed risk and structure mostly separately and that only a few works focused on their intersection. The results of this review are consolidated in a research agenda that calls for research on the risk-structure-interface and the development of proxy methods.
引用
收藏
页码:1835 / 1856
页数:22
相关论文
共 122 条
[1]   The impact of supply network characteristics on reliability [J].
Adenso-Diaz, Belarmino ;
Mena, Carlos ;
Garcia-Carbajal, Santiago ;
Liechty, Merrill .
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL, 2012, 17 (03) :263-276
[2]   Supply Chain Risk Identification Using a HAZOP-Based Approach [J].
Adhitya, Arief ;
Srinivasan, Rajagopalan ;
Karimi, Iftekhar A. .
AICHE JOURNAL, 2009, 55 (06) :1447-1463
[3]  
Aguila J. O., 2018, INT J PROD RES, V56, P6701, DOI DOI 10.1080/00207543.2018.1489158
[4]   Statistical mechanics of complex networks [J].
Albert, R ;
Barabási, AL .
REVIEWS OF MODERN PHYSICS, 2002, 74 (01) :47-97
[5]  
[Anonymous], 2019, INT J PROD RES, DOI DOI 10.1080/00207543.2019.1627438
[6]  
[Anonymous], 2016, DW
[7]   Modeling topologically resilient supply chain networks [J].
Arora V. ;
Ventresca M. .
Applied Network Science, 3 (1)
[8]   Supply chain risk management research agenda: From a literature review to a call for future research directions [J].
Bak, Ozlem .
BUSINESS PROCESS MANAGEMENT JOURNAL, 2018, 24 (02) :567-588
[9]   Computational Analysis and Visualization of Global Supply Network Risks [J].
Basole, Rahul C. ;
Bellamy, Marcus A. ;
Park, Hyunwoo ;
Putrevu, Jagannath .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (03) :1206-1213
[10]   Visual analysis of supply network risks: Insights from the electronics industry [J].
Basole, Rahul C. ;
Bellamy, Marcus A. .
DECISION SUPPORT SYSTEMS, 2014, 67 :109-120