Benchmark Approach for Efficiency Improvement in Green Supply Chain Management with DEA Models

Abstract

Nowadays, concerns about environmental issues are increasing. Therefore, companies and producers are under pressure from government rules and regulations on one hand, and on the other hand, maintaining customer satisfaction concerning cares about the environment. Green supply chain management (GSCM) is a procedure to increase efficiency and decrease environmental effects for companies that collaborate with customers and suppliers. According to GSCM, there is some research about applying green aspects of purchasing, design, manufacture, distribution, packaging, marketing, and reverse logistics of supply chains to improve their company’s performance regarding environmental issues. Moreover, recently, DEA as a nonparametric model is used to evaluate the efficiency and performance of supply chains as decision-making units (DMUs). However, previous studies on efficiency improvement in GSCM did not investigate the effect of some economic and environmental factors together such as service level, emissions (CO2), and size of the supply chains (arcs) on the efficiency of the whole supply system. These factors are essential as they can affect the manager’s ability to distinguish the true performance of a green supply chain. Thus, evaluating the efficiency of GSCM by DEA models and imposing the green principles to find out the efficient ones for increasing management performance is vital. Fulfilling the mentioned research gap, this paper developed a benchmark approach to verifying efficient DMUs and potential efficient DMUs which may improve costs and efforts to become efficient. In the case study, the benchmarks and potentially efficient DMUs are found by DEA standard models and slight adjustment is conducted for potentially efficient DMUs to change their status to efficient DMUs. Moreover, the effect of some green principles on the efficiency value of DMUs is verified using Tobit regression before and after the mentioned modification. A set of realistic results provided for the priority of potential DMUs modification confirmed the applicability of the proposed procedure.