Data-Driven Modeling and Evaluating the Enablers for Implementation of Sustainable Supply Chain Management : Combining the Interpretive Structural Modeling and Bayesian Network Approach

In recent years, sustainability in supply chains is becoming increasingly more important, and deploying accurate enablers for achieving sustainability is a considerable issue. In this study, a data-driven method is employed to effectively select the enablers of the sustainable supply chain (SSC). Therefore, the enablers are used in the ISM to perceive their inter-relationships. Additionally, Bayesian network is separately established in TBL of SSC due to provide a superior insight. The final results show that the government regulations in the social and economic and supplier's ISO 14000 certification in environmental dimension have the strongest positive impacts on achieving the SSC