This study focuses on evaluating potential raw material providers (RMPs) as one of the critical tasks of the logistics managers. In this regard, the literature showed that the simultaneous consideration of resilience, digitalization, and circular economy in the RMP selection problem (RMPSP) has been ignored by previous studies. Therefore, to cover the mentioned gap, this research attempts to study the RMPSP by considering other crucial concepts namely resilience and Circular Economy (CE). For this purpose, by considering a real-world case study in the steel industry, the current work first specifies the indicators of the research problem. Then, the indicators’ weights are measured using the stochastic Best-Worst Method (BWM). In the next step, the RMPs are prioritized by developing a novel approach called the stochastic Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In general, the main objective of this study is to evaluate the performance of the RMPs in the steel industry based on the CE, resilience, and digitalization aspects. According to the achieved results, “Reliability”, “Price”, “Quality”, “Reverse logistics and Waste management”, “Information systems usage”, and “Restorative Capacity”, are identified as the most desirable indicators. Moreover, the results confirm the effectiveness and validation of the developed method.
