Multi-Criteria Decision-Making Methods in Digital Supply Chain

Abstract

This chapter investigates the potential of integrating multiple criteria decision-making (MCDM) techniques with decision support systems of digital supply chain management (DSCM) to achieve optimal outcomes. Digital supply chain (DSC) employs digital technologies (DTs) such as artificial intelligence (AI), Internet of Things (IoT), and big data analytics to provide extensive datasets and valuable insights pertaining to supply chain operations. MCDM techniques employ these realizations to facilitate informed decision-making through the assessment of multiple competing criteria. Usually MCDM approaches are used in the academic research with comparatively lesser application in industry. We argue that MCDM methodologies can play an instrumental role in DSCM, specifically in the areas of supplier selection, demand forecasting, and inventory management. Nevertheless, the integration of MCDM like AHP, ANP, DEMATEL, etc., with decision support systems presents several challenges, including concerns regarding the quality of data and the intricate task of assigning weights to various factors.

Citation

Mubarik, M.S. and Khan, S.A. (2024), "Multi-Criteria Decision-Making Methods in Digital Supply Chain", The Theory, Methods and Application of Managing Digital Supply Chains, Emerald Publishing Limited, Leeds, pp. 145-161. https://doi.org/10.1108/978-1-80455-968-020241010