An integrated decision framework for resilient sustainable waste electric vehicle battery recycling transfer station site selection

This study is driven by a company engaged in renewable resource recovery. As the company's battery recycling market continuous continues to grow, the existing recycling facilities are unable to cope with the demand for sorting and storage. As a result, there is an urgent need to identify a suitable electric vehicle battery recycling transfer station (EVBRTS) to alleviate the strain on the recycling plant. The issue of electric vehicle battery recycling location has received scant attention in previous research, with a notable absence of studies focusing on EVBRTS location. Thus, the primary objective of this study is to establish an integrated decision-making framework using the best worst method (BWM) and cumulative prospect theory (CPT) to determine the optimal EVBRTS location. To achieve this goal, a panel of experts representing various sectors was assembled to formulate five primary criteria and fifteen secondary sub-criteria across the economic, social, environmental, technological, and resilience domains, drawing on existing literature and expert insights. The BWM method was employed to determine the criteria weights, followed by a ranking of the alternatives using the CPT approach. Furthermore, an integrated analytical model for the EVBRTS site selection evaluation index system was developed herein. A sensitivity and comparative analysis was carried out to demonstrate the practicality and robustness of the proposed method. A notable finding highlighted in this study is the significant impact that the order in which the expert ratings information was aggregated had on the ranking results. Undoubtedly, this study offers a fresh perspective based on resilience and sustainability for battery recycling managers to make informed strategic decisions on site selection, thereby enhancing resilience in the context of EVBRTS site selection.