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This paper aims to determine the key factors and provide an effective model to enhance the performance of sustainable supply chain management (SSCM).

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.

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.

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.

Organizations experience various issues with the optimum use of data. This study is qualitative research to identify and provide a helpful pattern for increasing the performance of sustainable supply chain management (SSCM).

The statistical population in the qualitative section includes managers and experts in the supply chain (SC) and food production. The data were collected via semi-structured interviews, and data saturation happens after the tenth interview. Then, the data were coded using grounded theory and qualitative research analysis. 384 questionnaires were distributed among employees via random sampling. SmartPLS software is used to investigate and analyze the relationships in the mentioned model through 13 core categories.

The findings indicate that organizational productivity and SC deficiencies are among the effective factors in the SSCM primarily identified by this study. Moreover, the findings propose that industry SC, macro policies, organizational performance, social factors, economic factors, organizational factors, political factors, technological factors, production and customer are likely to positively impact the SSCM, which have previously been documented by studies.

The model and concepts extracted from the responses of research participants show well that there are reasons and motivations for increasing the performance of SSCM. Also, the designed model shows well that the motives and reasons for turning to this system are satisfied due to its implementation.