Generic Integration of Lean, Agile, Resilient, and Green Practices in Automotive Supply Chain

Abstract

Performance measures of supply chain have been investigated through recent scholar works and different tools have been proposed to follow, monitor, and analyse them. This research addresses the embedded uncertainty as well as mutual dependency among supply chain performance measures and proposes employing Bayesian network (BN) to monitor them. BN has been successfully used in related areas, however, in this particular context it is lacking in published literature. In addition, a framework is proposed to provide researchers and practitioners with step by step procedure of developing BN to monitor the performance measures of their supply chain. Finally, a case study is presented, which takes advantage of proposed methodology and follows the framework.