Supply chain risk management modelling: A systematic literature network analysis review

被引:8
|
作者
Carvalho Fagundes, Marcus Vinicius [1 ,2 ,3 ]
Teles, Eduardo Oliveira [4 ]
Vieira de Melo, Silvio A. B. [1 ,5 ]
Mendonca Freires, Francisco Gaudencio [1 ]
机构
[1] Univ Fed Bahia, Grad Program Ind Engn, Salvador, BA, Brazil
[2] State Univ Southwest Bahia, Dept Appl Social Sci, Vitoria Da Conquista, BA, Brazil
[3] Univ Fed Bahia, Polytech Sch, Aristides Novis St 2,6 Floor, BR-40210630 Salvador, BA, Brazil
[4] Fed Inst Bahia, Camacari, BA, Brazil
[5] Univ Fed Bahia, Interdisciplinary Ctr Energy & Environm, Salvador, BA, Brazil
关键词
supply chain risk management; quantitative model; computer model; systematic literature review; citation network analysis; QUANTITATIVE MODELS; DISRUPTION RISKS; BIG DATA; MITIGATION; DESIGN; OPTIMIZATION; INFORMATION; UNCERTAINTY; PERFORMANCE; METHODOLOGY;
D O I
10.1093/imaman/dpaa019
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The modelling of supply chain risk management (SCRM) has attracted increasing attention from researchers and professionals. However, a systematic network analysis of the literature to understand the development of research over time is lacking. Therefore, this study reviews SCRM modelling and its evolution as a scientific field. We collected 566 papers published in the Scopus database and shortlisted 120 for review. We have analysed the field's performance, mapped the most influential studies, as well as the generative and evolutionary research areas, and derived future research directions. Using bibliometric methods and tools for citation network analysis to understand the field's dynamic development, we find that five generative research areas provide the fundamental knowledge for four evolutionary research areas. The interpretation of gaps and trends in these areas provides an SCRM modelling timeline with 14 future research directions, which should consider adopting a holistic SCRM approach and developing prescriptive and normative risk models. The holistic approach enables more research on key factors-like process integration, design, information risk, visibility and risk coordination-that directly impact industry, decision-makers and sustainability needs. Risk models with evolved prescriptive and normative typology should respect both business model strategies and actual supply chain performance.
引用
收藏
页码:387 / 416
页数:30
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