Efficiency evaluation of green supply chains based on fuzzy chance constrained three-stage DEA model

Abstract

Nowadays, environmental pollution and resource waste are in the way of economic development of companies. Hence, it is vital to balance the relationship of economy, society and environment. Based on this, green supply chain management comes into being. Efficiency evaluation, being a main premise of implementing green supply chain management, not only can get knowledge of the overall performance of a company, but also can discover the inefficient parts. In a word, evaluating the performance of green supply chain is a hot topic in recent years. Traditional DEA model treats DMU as a "black box", which makes the efficiency value higher than that of actual one. Based on it, we study deeper into every subsystems of the overall supply chain, accompanied by multi objective programming model and network DEA model. In the process of coping with the proposed multi objective network DEA, we apply AHP method to determine the weights of each subsystem. In addition, considering the data observed is not always crisp and precise, therefore, we describe them with fuzzy data, and then apply chance constrained possibility programming to cope with it. In the case study, taking 10 enterprises for example, we calculate the overall efficiency and each subsystem's efficiency value, and propose managerial insights.