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In spite of the vast amount of studies on green supplier selection and related methods and approaches, the evaluation of green supply chain performance indicators aligned with classic measures is less investigated. Therefore, this research attempted to provide an integrated step by step procedure to consider both classical and green key performance indicators within the supplier selection framework. A literature survey was conducted and measures for assessing the green suppliers were extracted. Nominal Group Technique (NGT) is deployed to extract the most critical performance measures. Ten performance measures were selected as a substitute for green supplier selection. A Fuzzy Analytical Network Process (FANP) was then deployed to weight the extracted measures and determine their importance level.

With the global awareness of sustainability issues, sustainable development is being increasingly recognized by governments and industries. In addressing these issues, organizations worldwide have taken initiatives in adopting sustainability practices in their supply chain transferring it to sustainable supply chain management. In order to establish a responsible sustainable supply chain management, an effective way would be to make sure that the potential suppliers for procuring required components are precisely assessed and evaluated based on sustainable criteria. Therefore, this paper proposes a practical decision making approach to evaluate and select the most sustainable suppliers for an automotive spare part manufacturer licensed under a France-based automotive organization. Firstly, a requirement gathering approach, the audition check-list approach, is designed to facilitate the process of data gathering for supplier evaluation based on three pillars of sustainability. Next, the gathered data are processed using a proposed fuzzy inference system to remove impreciseness and vagueness in the gathered sustainability related data. The strength of this model falls into its applicability in data gathering phase which helps decision makers in manufacturing company to perform a fast audition of a typical supplier. Secondly, the final sustainable ranking of suppliers using the proposed fuzzy inference system provide a precise and less uncertain sustainability performance scoring which makes the developed approach a reliable system for making sustainable sourcing decisions. Comparison and sensitivity analysis are performed to evaluate the proficiency of the developed approach. Finally, theoretical and managerial implications together with conclusions of the study are presented.

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