Evidence-based resilience management for supply chain sustainability: An interpretive structural modelling approach

Abstract

The purpose of this study is to systematically identify and design improvement planning for supply chain resilience (SCRES) for a higher level of sustainability and a competitive advantage. Literature-based interpretive structural modelling (ISM), a pairing of the systematic literature review (SLR) and ISM approaches, is proposed for investigating and identifying a set of key performance measures of resilience for supply chain (SC) management. In line with previous research, we identified and updated 13 key SC capabilities out of 24 as core performance measures of supply network resilience. Furthermore, our findings categorised each capability and element into one of four types of influential power variables (drivers, dependent, autonomous, or linkage). This study (i) lends support to and updates previous research that examined the core capabilities of SCRES and (ii) provides complementary classifications for the influential powers of SCRES capabilities and elements. The literature indicates that there has been no research that has integrated SLR as a basis to ISM for an effective way to utilize existing studies for increasing awareness and developing managerial guidelines to achieve SCRES.