Cost, Revenue and Profit Efficiency Evaluation in Downstream Petrochemical Industries with Data Envelopment Analysis Approach with Fuzzy Data

Authors

  • Nader Shateri Department of Industrial Engineering, Tehran-center Branch, Islamic Azad University, Tehran, Iran. https://orcid.org/0009-0006-2489-0900
  • Masoud Saneie Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Hilda Saleh Department of Mathematics, Tehran-center Branch, Islamic Azad University, Tehran, Iran.

Keywords:

Data envelopment analysis, Cost, Revenue and profit efficiency, Fuzzy data, α-cut

Abstract

One of the applications of data envelopment analysis is the calculation of cost, revenue and profit efficiency, which is used in the financial analysis of organisations. This analysis makes the managers of the organisations make better decisions against the fluctuations caused by the changes in the prices of production inputs in the competitive market, investment risk and other factors effecting their business. In the real world, not all data related to inputs, outputs and their corresponding prices are accurate. Therefore, in order to determine their value, it is necessary to use fuzzy concepts for imprecise data. The purpose of this research is to calculate the cost, revenue and profit efficiency of the production lines of the polymer pipe manufacturing plant from the downstream petrochemical industries with full fuzzy data of the type of triangular fuzzy numbers with an α-cut approach. So that each of the 7 existing production lines is considered as a DMU, this performance evaluation is based on the variety of production lines, product size and limitation in the problem using the data envelopment analysis technique, and then the proposed FDEA model is converted into a family of crisp models to calculate the upper and lower bounds and is ranked based on interval data rules.

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Published

2025-02-28

How to Cite

Cost, Revenue and Profit Efficiency Evaluation in Downstream Petrochemical Industries with Data Envelopment Analysis Approach with Fuzzy Data. (2025). Annals of Optimization With Applications, 2(1), 41-56. https://anowa.reapress.com/journal/article/view/34