Supply chain resilience: a systematic literature review and typological framework

• Published in: International journal of physical distribution & logistics management Vol. 48; no. 8; pp. 842 - 865
• Main Authors: Kochan, Cigdem Gonul, Nowicki, David R.
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 12.09.2018; Emerald Group Publishing Limited
• Subjects: Decision making; Integer programming; Keywords; Linear programming; Literature reviews; Logistics; Monte Carlo simulation; Research methodology; Resilience; Studies; Supply chain management; Supply chains; Systematic review; Supply chain vulnerability; Supply chain resilience; Supply chain risk; Systematic literature review
• ISSN: 0960-0035; 1758-664X
• DOI: 10.1108/IJPDLM-02-2017-0099

Purpose The study of supply chain resilience (SCRES) continues to gain interest in the academic and practitioner communities. The purpose of this paper is to present a focused review of the SCRES literature by investigating supply chain (SC) capabilities, their relationship to SCRES outcomes and the underpinning theoretical mechanisms of this relationship. Design/methodology/approach The paper uses the systematic literature review approach to examine 383 articles published between 2000 and 2017, ultimately down selecting to the most relevant 228 peer-reviewed studies. Context-interventions-mechanisms-outcomes (CIMO) logic is applied to organize and synthesize these peer-reviewed studies. A typological framework is developed from the CIMO-based classification of the SCRES literature. Findings The findings of this study outline the gaps in the SCRES literature and present an agenda for future research. Research limitations/implications This paper presents an exploratory research; therefore, the typological model presented is just one of the possible perspectives. Practical implications The typology of SCRES literature can help practitioners to understand SCRES and to measure and assess the resilience of SCs. Originality/value The paper provides clear definitions of SCRES constructs, develops a typological framework to further understand SCRES and identifies SCRES measures and assessment techniques.