Artículo

Decision-making models and support systems for supply chain risk: literature mapping and future research agenda

Resumen

Supply chain disruptions have serious consequences for society and this has made supply chain risk management (SCRM) an attractive area for researchers and managers. In this paper, we use an objective literature mapping approach to identify, classify, and analyze decision-making models and support systems for SCRM, providing an agenda for future research. Through bibliometric networks of articles published in the Scopus database, we analyze the most influential decision-making models and support systems for SCRM, evaluate the main areas of current research, and provide insights for future research in this field. The main results are the following: we found that the identity of the area is structured in three groups of risk decision support models: (i) quantitative multicriteria decision models, (ii) stochastic decision-making models, and (iii) computational simulation/optimization models. We mapped six current research clusters: (i) conceptual and qualitative risk models, (ii) upstream supply chain risk models, (iii) downstream supply chain risk models, (iv) supply chain sustainability risk models, (v) stochastic and multicriteria decision risk models, and (vi) emerging techniques risk models. We identified seven future research clusters, with insights from further studies for: (i) tools to operate SCRM data, (ii) validation of risk models, (iii) computational improvement for data analysis, (iv) multi-level and multi-period supply chains, (v) agrifood risks, (vi) energy risks and (vii) sustainability risks. Finally, the future research agenda should prioritize SCRM’s holistic vision, the relationship between Big Data, Industry 4.0 and SCRM, as well as emerging social and environmental risks. (C) 2020 AEDEM. Published by Elsevier Espana, S.L.U.
Jrade, Ahmad (12804778900); Jalaei, Farnaz (57212026747); Zhang, Jieying Jane (59228484300); Jalilzadeh Eirdmousa, Saeed (59228444800); Jalaei, Farzad (54894358100)
Potential Integration of Bridge Information Modeling and Life Cycle Assessment/Life Cycle Costing Tools for Infrastructure Projects within Construction 4.0: A Review
2023
10.3390/su152015049
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199226134&doi=10.3390%2fsu152015049&partnerID=40&md5=b503d960a132c3df787b4cb99ad749dc
Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, ON, Canada; National Research Council Canada, Government of Canada, Ottawa, K1A 0R6, ON, Canada
All Open Access; Gold Open Access
Scopus
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