Supply chain risk management modelling: A systematic literature network analysis review
Author(s) -
Marcus Vinicius Carvalho Fagundes,
Eduardo Oliveira Teles,
Sílvio A.B. Vieira de Melo,
Francisco Gaudêncio Mendonça Freires
Publication year - 2020
Publication title -
ima journal of management mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 34
eISSN - 1471-6798
pISSN - 1471-678X
DOI - 10.1093/imaman/dpaa019
Subject(s) - computer science , systematic review , supply chain , field (mathematics) , knowledge management , supply chain risk management , scopus , risk management , risk analysis (engineering) , supply chain network , management science , supply chain management , process management , data science , business , engineering , service management , mathematics , medline , finance , marketing , political science , pure mathematics , law
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.
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