Cost efficiency and return to scale in a two-stage network supply chain: Case study of drink companies in Iran

Data Envelopment Analysis (DEA) is a powerful tool to evaluate the performance of decision-making units. Some of decision- making units consist of several parts or stages that make a network of sub-processes. Data Envelopment Analysis (DEA) is used to evaluate such type of units. Two different types of inputs (variable and quasi-constant inputs) are considered based on the framework of Network Data Envelopment Analysis. One of the characteristics of the quasi-consist input is that it is considered as the output of current stage, while it will be used as the input of the next stage. The network DEA can measure the independence between the two stages. The present study investigates its cost efficiency and returns to scale (RTS) as a two-stage process. Cost efficiency can use inputs, as well as their cost and values in order to calculate the efficiency. We investigate the cost efficiency of the stages and whole process, and we also determine returns to scale. One of the advantages of the models is the reduction of computational time. Green Supply Chain Management (GSCM) is an approach to improve environmental performance. GSCM will increase its economic and environmental performance. Hence, GSCM's assessment is very important for every company. One of the techniques which can be used to evaluate GSCM is Data Envelopment Analysis (DEA). In order to achieve our goals in this study, we use network Data Envelopment Analysis (DEA) to investigate 9 GSCM Iranian Drinking Company.