Comparative assessment over the selection of lean supply chain practices through fuzzy integrated principal component analysis, gray relational analysis, and complex proportional assessment approaches

Abstract

Due to the competitive market, the organizations look for performance improvement in their supply chain activities. Lean principles aim to reduce waste, and many research works have explored their effectiveness in the supply chain. Yet, industries face the problem of selecting appropriate lean supply chain management practices for their present environment. The present study performed a detailed literature study to identify majorly adapted lean supply chain management practices and generalize the most important ones with lesser implementation issues. For this purpose, the multi-criteria decision-making approaches, namely, gray relational analysis and complex proportional assessment of alternatives, are used to rank the identified lean supply chain management practices. Principal component analysis was used to generate criteria weights for computations. Out of 28 selected lean supply chain management practices from the literature, seven high-priority lean supply chain management practices are recommended as a generalized list as a result of prioritization by multi-criteria decision-making approaches such as total quality management, just-in-time production, pull system/kanban, 5S, information technology, work standardization, and customer relationship management. This study will benefit the practitioners to quickly identify suitable lean supply chain management practices to enhance their supply chain network, which can result in substantial cost savings.