Presenting a model for enhancing the performance of sustainable supply chain management using a data-driven approach

Purpose This paper aims to determine the key factors and provide an effective model to enhance the performance of sustainable supply chain management (SSCM). Design/methodology/approach Data were collected using a semi-structured interview technique, a snowball sampling method and qualitative study method. For this purpose, ten supply chain and food production managers and experts were interviewed semi-structured. The data were analyzed using open, central and selective coding methods with grounded theory approach. In the proposed model, 13 principal codes have been specified, including organizational productivity, sustainable supply chain (SSC), industry supply chain, macro policies, organizational performance, social factors, economic factors, organizational factors, political factors, technology, manufactured products, customer and supply chain failures. Findings The model and concepts obtained from the participants clearly show that several reasons and motivations are involved in increasing the performance of SSCM. Moreover, the designed model indicates that the motives and reasons for turning to this system are satisfactory when implemented. Originality/value The distinctive and knowledge-enhancing feature of this paper compared to previous studies is the focus on the selected background, intervening and causal factors with the influence of strategies designed to achieve a new and local model for the SSC model and assess its impact on organizational performance and productivity. The proposed components of this paper have not been investigated so far.