With increasing globalization and international cooperation, the importance of sustainability management across supply chains has received much attention by companies across various industries. Companies therefore strive to implement effective and integrated sustainable supply chain management initiatives to improve their operational and economic performance while also minimizing unnecessary damage to the environment and maintaining their social reputation and images. The paper presents an easy-to-use decision-support approach based on multiple-criteria decision-making (MCDM) methodologies that aim to help companies develop effective models for timely decision-making involving sustainable supply chain management strategies. The proposed approach can be used by practitioners to ultimately build a comprehensive Analytic Network Process model that will adequately capture and reveal all the interrelationships and interdependency among the elements in the problem, which is often a very difficult task. To facilitate and simplify this complex process, we propose that hierarchical thinking be used first to structure the essences of the problem capturing only the major issues, and an Analytic Hierarchy Process (AHP) model be built. Users can learn from the modeling process and gain much insight into the problem. The AHP can then be extended to an Analytic Network Process (ANP) model so as to capture the relationships and interdependencies among the elements. Our approach can reduce the sustainable expertise, effort and information that are often needed to build an ANP model from scratch. We apply our approach to the evaluation of sustainable supply chain management strategies for the fashion industry. Three main dimensions of sustainability—environmental, economic and social—are considered. Based on the literature, we identified four alternative supply chain management strategies. It was found that the Reverse Logistics alternative appears to be the recommended solution by the AHP model. However, the Socially Leagile Supply Chain is recommended by the ANP model, thereby demonstrating the necessity and importance of considering interdependencies in the model.
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