A supply chain risk management maturity model and a multi-criteria classification approach

Purpose The purpose of this paper is to propose a supply chain risk management (SCRM) maturity model combined with a fuzzy TOPSIS classification method to evaluate and sort an organization into a pre-defined maturity level. Design/methodology/approach An axiomatic and prescriptive research method guided this study. Therefore, it proposes a prescriptive approach of maturity classification based on a theoretical SCRM maturity model combined with a multi-criteria decision technique. Findings The results of a pilot application indicated a consistent classification and the value of the model for diagnosing flaws and pointing directions for improving operational and disruption risk management. Its comprehensiveness allows applying it to supply chains of several industry sectors. Research limitations/implications The proposed model does not include all possible risks and could be revised in further developments. Also, adjustment of the maturity profiles of the multi-criteria decision-making (MCDM) model requires a learning process from practical applications. Practical implications The adoption of the risk management maturity grid by practitioners may bring the benefit of a more objective and comprehensive evaluation of risk management processes in the supply chain context. Social implications An immediate social implication derives from the improvement actions that may result from the diagnosis of risk management vulnerabilities identified in the pilot application. In general, the proposed model has the potential to reduce risks, improve results and contribute to economic sustainability. Originality/value The maturity grid and decision model integrate overall aspects of risk management, bringing together managerial concepts to deal with a variety of supply chain operational risks. The combined multi-criteria classification procedure to sort the maturity level of an organization is also a novelty.

Automated summary

This paper introduces a supply chain risk management maturity model with a fuzzy TOPSIS classification method to evaluate and sort organizations. The research method is axiomatic and prescriptive, proposing a prescriptive approach based on a theoretical SCRM maturity model. The model has the potential to improve risk management processes and contribute to economic sustainability.