A Two-Phase Network DEA Strategy for Performance Benchmarking in the Petrochemical Sector

The petrochemical industry is a key sector in Iran, playing a crucial role in the country's economic growth. Given the industry's reliance on scarce and non-renewable raw materials, evaluating the performance of petrochemical companies is essential for ensuring efficiency and sustainability. The organizational structure of these companies is often complex, necessitating advanced analytical methods for performance assessment. Network Data Envelopment Analysis (NDEA) is particularly suitable for this purpose, as it evaluates the efficiency of Decision-Making Units (DMUs) with interconnected sub-processes linked by intermediate products. These intermediate products serve as both outputs of one sub-process and inputs to another, creating interdependencies that can impact overall efficiency. An increase in output from one sub-process may inadvertently reduce the efficiency of another, highlighting the need for a more nuanced evaluation method. To address this challenge, this study presents a novel approach within the Slack-Based Measure (SBM) framework. The proposed method classifies intermediate products into two subsets — “input-type” and “output-type” — to account for their excesses and shortfalls, thereby directly influencing efficiency scores. This refined approach enhances the accuracy of performance assessments, providing valuable insights for analysts and decision-makers. The proposed model is applied to ۱۴ petrochemical companies listed on Iran’s stock exchange, and its results are compared with existing models from the literature. Findings indicate that the proposed approach offers improved discriminatory power, allowing for more precise differentiation among companies' efficiency levels.

کلیدواژه ها:

Network Data Envelopment Analysis (NDEA) ، Slack-Based Measure (SBM) ، intermediate products ، petrochemical companies ، efficiency evaluation