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A Two-Stage Data Envelopment Analysis Approach Incorporating the Global Bounded Adjustment Measure to Evaluate the Efficiency of Medical Waste Recycling Systems with Undesirable Inputs and Outputs

Author

Listed:
  • Wen-Jing Song

    (Transportation Institute, Inner Mongolia University, Hohhot 010030, China)

  • Jian-Wei Ren

    (Transportation Institute, Inner Mongolia University, Hohhot 010030, China)

  • Chun-Hua Chen

    (College of Economics and Management, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Chen-Xi Feng

    (Transportation Institute, Inner Mongolia University, Hohhot 010030, China)

  • Lin-Qiang Li

    (Transportation Institute, Inner Mongolia University, Hohhot 010030, China)

  • Chong-Yu Ma

    (Transportation Institute, Inner Mongolia University, Hohhot 010030, China)

Abstract

With the ever-increasing focus on sustainable development, recycling waste and renewable use of waste products has earned immense consideration from academics and policy makers. The serious pollution, complex types, and strong infectivity of medical waste have brought serious challenges to management. Although several researchers have addressed the issue by optimizing medical waste management networks and systems, there is still a significant gap in systematically evaluating the efficiency of medical waste recycling systems. Therefore, this paper proposes a two-stage data envelopment analysis (DEA) approach that combines the virtual frontier and the global bounded adjustment measure (BAM-VF-G), considering both undesirable inputs and outputs. In the first stage, the BAM-G model is used to evaluate the efficiency of medical waste recycling systems, and the BAM-VF-G model is used to further rank super-efficient medical waste recycling systems. In the second stage, two types of efficiency decomposition models are proposed. The first type of models decompose unified efficiency into production efficiency (PE) and environment efficiency (EE). Depending upon the system structure, the second type of models decompose unified efficiency into the efficiency of the medical waste collection and transport subsystem (MWCS) and the efficiency of the medical waste treatment subsystem (MWTS). The novel approach is used to measure the efficiency of the medical waste recycling systems in China’s new first-tier cities, and we find that (1) Foshan ranks the highest in efficiency, followed by Tianjin and Qingdao, with efficiency values of 0.386, 0.180, and 0.130, respectively; (2) the EE lacks resilience and fluctuated the most from 2017 to 2022; and (3) the efficiency of MWCSs has always been lower than that of MWTSs and is a critical factor inhibiting the overall efficiency of medical waste recycling systems.

Suggested Citation

  • Wen-Jing Song & Jian-Wei Ren & Chun-Hua Chen & Chen-Xi Feng & Lin-Qiang Li & Chong-Yu Ma, 2024. "A Two-Stage Data Envelopment Analysis Approach Incorporating the Global Bounded Adjustment Measure to Evaluate the Efficiency of Medical Waste Recycling Systems with Undesirable Inputs and Outputs," Sustainability, MDPI, vol. 16(10), pages 1-33, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4023-:d:1392555
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    References listed on IDEAS

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    1. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Yang, Junwen & Chen, Bin, 2021. "Energy efficiency evaluation of wastewater treatment plants (WWTPs) based on data envelopment analysis," Applied Energy, Elsevier, vol. 289(C).
    4. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    5. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Xiaodong Chen & Anda Guo & Jiahao Zhu & Fang Wang & Yanqiu He, 2022. "Accessing performance of transport sector considering risks of climate change and traffic accidents: joint bounded-adjusted measure and Luenberger decomposition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 115-138, March.
    8. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    9. Khalil al-Sulbi & Pawan Kumar Chaurasia & Abdulaziz Attaallah & Alka Agrawal & Dhirendra Pandey & Vandna Rani Verma & Vipin Kumar & Md Tarique Jamal Ansari, 2023. "A Fuzzy TOPSIS-Based Approach for Comprehensive Evaluation of Bio-Medical Waste Management: Advancing Sustainability and Decision-Making," Sustainability, MDPI, vol. 15(16), pages 1-21, August.
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