Solving voting system by data envelopment analysis for assessing sustainability of suppliers

Recently, sustainable supply chain management has attracted the attention of scholars and practitioners. Data envelopment analysis (DEA) is a useful tool for evaluating sustainability of suppliers. Ranking a system of voting is an important topic in DEA. Many firms apply voting systems to rank candidates. Generally, these kinds of methods rank candidates by their associated weights. In this paper, to increase discrimination power among candidates, a novel model for obtaining a suitable value of discriminating factor is proposed. Then, using the optimal value of the discriminating factor, a new model for calculating preference scores of candidates is presented. This model evaluates candidates based on different set of weights. To evaluate candidates based on common set of weights, using concept of ideal point, two new multiple objective programming models are proposed. The proposed method is applied for selecting the most sustainable suppliers that supply self-supporting cable for a power distribution company. Results show that candidates might be affected by changing the set of weights. Using our proposed models, full rankings are obtained.