Revenue Efficiency and the Detection and Analysis of Congestion in Pharmaceutical Companies: A Two-Stage Framework

Authors

  • Maryam Outougari * Department of Mathematics, Faculty of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Farhad Hosseinzadeh Lotfi Department of Mathematics, Faculty of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran. https://orcid.org/0000-0001-5022-553X
  • Mohsen Rostamy-Malkhalifeh Department of Mathematics, Faculty of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran. https://orcid.org/0009-0009-6372-8983
  • Tofigh Allahviranloo Department of Mathematics, Faculty of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran. https://orcid.org/0000-0002-6673-3560

https://doi.org/10.22105/ahse.v2i4.55

Abstract

This study proposes an integrated two-stage Data Envelopment Analysis (DEA) framework for evaluating Revenue Efficiency (RE) and identifying congestion in Decision-Making Units (DMUs). By incorporating both discretionary and non-discretionary inputs, as well as desirable and undesirable outputs, the proposed framework reflects real-world DEA applications more accurately. In the first stage, a revenue-based DEA model is employed to measure the RE of DMUs while explicitly accounting for non-discretionary inputs. Efficient units are subsequently identified and selected as benchmark reference units. In the second stage, a method is introduced to detect and quantify congestion in inefficient DMUs relative to the efficient reference units. Congestion refers to situations in which the excessive utilization of discretionary and non-discretionary inputs leads to a deterioration in unit performance. The proposed framework is empirically applied to pharmaceutical companies. The results indicate that revenue inefficiency is not always attributable to poor management; rather, some inefficient DMUs experience substantial congestion. In such cases, increasing input levels worsens performance instead of improving it. Furthermore, the extent of congestion is quantified, providing a clear distinction between managerial inefficiency and structural congestion.The proposed approach offers a benchmark-based method for congestion identification and integrates efficiency evaluation and congestion analysis within a unified DEA framework.

Keywords:

Revenue efficiency, Data envelopment analysis, Congestion, Non-discretionary inputs, Undesirable outputs

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Published

2025-12-23

Issue

Vol. 2 No. 4 (2025): Annals of Healthcare Systems Engineering

Section

Articles

How to Cite

Outougari, M., Hosseinzadeh Lotfi, F., Rostamy-Malkhalifeh, M., & Allahviranloo, T. (2025). Revenue Efficiency and the Detection and Analysis of Congestion in Pharmaceutical Companies: A Two-Stage Framework. Annals of Healthcare Systems Engineering, 2(4), 262-274. https://doi.org/10.22105/ahse.v2i4.55

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