TY - JOUR

T1 - Literature review on disruption recovery in the supply chain

AU - Ivanov, Dmitry

AU - Dolgui, Alexandre

AU - Sokolov, Boris

AU - Ivanova, Marina

N1 - Funding Information: This research was supported by Russian Science Foundation [Project No. 16-19-00199]. The authors thank two anonymous reviewers for their valuable comments that greatly improved the manuscript. Publisher Copyright: © 2017 Informa UK Limited, trading as Taylor & Francis Group. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2017/10/18

Y1 - 2017/10/18

N2 - Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on the other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.

AB - Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on the other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.

KW - supply chain design

KW - supply chain dynamics

KW - supply chain engineering

KW - supply chain resilience

KW - supply chain risk management

UR - http://www.scopus.com/inward/record.url?scp=85020231825&partnerID=8YFLogxK

U2 - 10.1080/00207543.2017.1330572

DO - 10.1080/00207543.2017.1330572

M3 - Article

AN - SCOPUS:85020231825

VL - 55

SP - 6158

EP - 6174

JO - International Journal of Production Research

JF - International Journal of Production Research

SN - 0020-7543

IS - 20

ER -