Performance Evaluation in Green Supply Chain Using BSC, DEA and Data Mining

Efficiency is regarded as an important factor for both managers in different companies and organizations and customers who are interested in using the services related to these companies and organizations. However, the biggest challenges managers are coping with include an increase in the competition, an increase in the efficiency of production, and finding suitable suppliers. This study aimed to investigate the efficiency of green supply chain by using Data Envelopment Analysis (DEA) based on Malmquist Productivity Index (MPI) according to the input and output indicators of the Balanced Scorecard (BSC) model and accordingly providing some rules using the decision tree. To this aim, the efficiency of 15 manufacturer firms of automotive parts in Iran was evaluated. Finally, the implicit rules in the data were extracted by using the decision tree. The results indicated that the proposed model had a high degree of accuracy and interpretation in evaluating performance compared to previous models and helps managers to make better decisions.