Proposing a new integrated MEREC‐NDEA algorithm for assessing and selecting the optimal sustainable suppliers: a case study

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AbstractIn recent decades, choosing sustainable suppliers (SS) within a supply chain (SC) has posed a significant challenge for management. The evaluation and selection of the optimal SS from a pool of suppliers in the SC stands as a pivotal factor in maintaining competitiveness in the market. Hence, decision‐makers must seek the most effective method to identify key selection criteria for SS. This study aims to introduce a novel hybrid algorithm for the selection and assessment of the best SSs, encompassing varied criteria such as economic, environmental, sustainability, and human health considerations. The innovative algorithm combines the MEthod based on the Removal Effects of Criteria (MEREC) technique with network data envelopment analysis (NDEA). The enhanced NDEA model incorporates undesirable outputs and environmental emissions like CO2. Initially, leveraging the MEREC approach, criteria weights are determined in two distinct groups: cost and benefit. Subsequently, inputs, intermediate products, and outputs are defined based on these weights, with NDEA models devised accordingly. The NDEA models effectively identify top suppliers based on efficiency. An efficient supplier is considered the best choice. The NDEA model highlights areas for improvement for inefficient suppliers while also leveraging insights from efficient ones. This leads to a comprehensive ranking of all suppliers, from which the best are selected. A case study at Shahriar Plast Company involving 10 suppliers and 11 criteria demonstrates the methodology's effectiveness. Results indicate that this hybrid algorithm is a reliable solution for supplier selection across various SCs. A comparative analysis with existing models further confirms the stability and reliability of the proposed algorithm, yielding consistent outcomes.