Mathematical Model for Estimation of Return to Scale in Four-Level Green Supply Chain by using Data Envelopment Analysis

Today, focusing on gaining a competitive edge in the global business market lies in enhancing supply chain performance. This study endeavors to examine the attainment of Returns To Scale (RTS) within a four-level green supply chain framework through the application of Data Envelopment Analysis (DEA). To achieve this objective, the Banker, Charnes, and Cooper (BCC) multiplicative model are employed to determine the return to scale at each level within the complete supply chain, ultimately culminating in estimating the overall return to scale for the entire supply chain. The statistical population for this applied research, aligned with its objectives, comprises ۴۲ cement companies. The assessment of returns to scale in these companies, featuring a four-level chain encompassing suppliers, manufacturers, distributors, and customers, is measured. The outcomes of the model reveal that return to scale remains constant in ۲۸ companies, exhibits a decreasing trend in ۱۴ companies, and conversely demonstrates an increasing trajectory in ۲ companies within the supplying sector, one company in manufacturing, and ۱۴ companies in distribution. The findings underscore that an increasing return to scale renders the expansion of Decision-Making Units (DMUs) economically viable. Conversely, a diminishing return to scale suggests a rational limitation of DMUs.

Keywords:

Data Envelopment Analysis , Return to Scale , four-level Green Supply Chain , cement companies