Supply Chain Risk Management Measurements: A Critical Literature Review

Abstract

Supply Chain (SC) risk refers to any unwanted deviation from the expected SC outcome that can adversely affect SC operations and result in negative consequences for the focal firm. Supply Chain Risk Management (SCRM) measurements are effective tools for identifying, assessing, mitigating, and controlling SC risks. Hence, this paper aims to critically review the literature on existing SCRM measurements, identify their limitations, and outline future research directions. The review revealed that most scholars developed SCRM measurements based on risk identification assessment, ranking, and prioritization, combining qualitative and quantitative techniques, most of which require company-specific risk-related data. The majority employed traditional tools such as the risk matrix approach and the Analytic Hierarchy Process for risk assessment, while a few used more advanced hybrid and network-based models, machine learning, and optimization models for risk assessment, ranking, and prioritization. Despite numerous risk identification and assessment measurements, an extremely limited number of SCRM capability measurements were found in the existing literature. Furthermore, there is a lack of a standardized, universally applicable framework/measurement for SCRM that balances accuracy, usability, and context-specific applicability. This research has significant implications, as it consolidates recent literature on investigation in one place and enhances practitioners' awareness of the measurements.