IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i19p11060-d650974.html
   My bibliography  Save this article

Performance Measurement for the Recycling Production System Using Cooperative Game Network Data Envelopment Analysis

Author

Listed:
  • Huang-Chu Huang

    (Department of Telecommunication Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 82445, Taiwan)

  • Cheng-Feng Hu

    (Department of Applied Mathematics, National Chiayi University, Chiayi 600355, Taiwan)

Abstract

Resources scarcity and environmental degradation have made sustainable resource utilization and environmental protection necessary worldwide. The development of the circular economy is considered an approach for more appropriate economic and environmental management. This work introduces a cooperative game network data envelopment analysis model for evaluating the implementation effect of recycling production systems from a closed loop and centralized control perspective. The factor efficiency analysis of the involved inputs and outputs is presented to provide guidance for the factor dominance of subsystem efficiencies. An application for assessing the circular economy of EU countries is provided to illustrate the validation of the proposed method. Our results show that the average performance of the production subsystem is superior to that of the recycling subsystem in EU countries. Furthermore, factor efficiency analysis reveals that the inefficient environmental treatment input is the culprit in worse performance of the recycling subsystem. A comparison of the proposed method with recent studies for circular economy performance evaluation is also included.

Suggested Citation

  • Huang-Chu Huang & Cheng-Feng Hu, 2021. "Performance Measurement for the Recycling Production System Using Cooperative Game Network Data Envelopment Analysis," Sustainability, MDPI, vol. 13(19), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11060-:d:650974
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/19/11060/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/19/11060/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Kaoru Tone & Miki Tsutsui, 2014. "Slacks-Based Network DEA," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 231-259, Springer.
    3. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    4. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    5. Li, Haitao & Chen, Chialin & Cook, Wade D. & Zhang, Jinlong & Zhu, Joe, 2018. "Two-stage network DEA: Who is the leader?," Omega, Elsevier, vol. 74(C), pages 15-19.
    6. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    7. Cook, Wade D. & Liang, Liang & Zhu, Joe, 2010. "Measuring performance of two-stage network structures by DEA: A review and future perspective," Omega, Elsevier, vol. 38(6), pages 423-430, December.
    8. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "DEA-like models for the efficiency evaluation of hierarchically structured units," European Journal of Operational Research, Elsevier, vol. 154(2), pages 465-476, April.
    9. Zha, Yong & Liang, Liang, 2010. "Two-stage cooperation model with input freely distributed among the stages," European Journal of Operational Research, Elsevier, vol. 205(2), pages 332-338, September.
    10. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
    11. Jie Wu & Junfei Chu & Qingyuan Zhu & Pengzhen Yin & Liang Liang, 2016. "DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 5990-6007, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lei Li & Ruizeng Zhao & Feihua Huang, 2023. "Environmental Performance of China’s Industrial System Considering Technological Heterogeneity and Interaction," Sustainability, MDPI, vol. 15(4), pages 1-17, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antonio Peyrache & Maria C. A. Silva, 2022. "Efficiency and Productivity Analysis from a System Perspective: Historical Overview," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 173-230, Springer.
    2. Joe Zhu, 2022. "DEA under big data: data enabled analytics and network data envelopment analysis," Annals of Operations Research, Springer, vol. 309(2), pages 761-783, February.
    3. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    4. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    5. Antonio Peyrache & Maria C. A. Silva, 2019. "The Inefficiency of Production Systems and its decomposition," CEPA Working Papers Series WP052019, School of Economics, University of Queensland, Australia.
    6. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    7. Chen, Kun & Zhu, Joe, 2020. "Additive slacks-based measure: Computational strategy and extension to network DEA," Omega, Elsevier, vol. 91(C).
    8. An, Qingxian & Wen, Yao & Ding, Tao & Li, Yongli, 2019. "Resource sharing and payoff allocation in a three-stage system: Integrating network DEA with the Shapley value method," Omega, Elsevier, vol. 85(C), pages 16-25.
    9. Hadi Ghafoorian & NikIntan Norhan & Mohammed Ndaliman Abubakar & Fazel Mohammadi Nodeh, 2013. "Efficiency Considering Credit Risk in Banking Industry, Using Two-stage DEA," Journal of Social and Development Sciences, AMH International, vol. 4(8), pages 356-360.
    10. Ang, Sheng & Liu, Pei & Yang, Feng, 2020. "Intra-Organizational and inter-organizational resource allocation in two-stage network systems," Omega, Elsevier, vol. 91(C).
    11. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    12. Li, Yongjun & Chen, Yao & Liang, Liang & Xie, Jianhui, 2012. "DEA models for extended two-stage network structures," Omega, Elsevier, vol. 40(5), pages 611-618.
    13. Kao, Chiang, 2019. "Inefficiency identification for closed series production systems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 599-607.
    14. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    15. Kao, Chiang, 2016. "Efficiency decomposition and aggregation in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 255(3), pages 778-786.
    16. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    17. Santos Arteaga, Francisco J. & Tavana, Madjid & Di Caprio, Debora & Toloo, Mehdi, 2019. "A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution," European Journal of Operational Research, Elsevier, vol. 278(2), pages 448-462.
    18. Junhee Bae & Yanghon Chung & Hyesoo Ko, 2021. "Analysis of efficiency in public research activities in terms of knowledge spillover: focusing on earthquake R&D accomplishments," 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. 108(2), pages 2249-2264, September.
    19. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    20. Jun-Fei Chu & Jie Wu & Ma-Lin Song, 2018. "An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application," Annals of Operations Research, Springer, vol. 270(1), pages 105-124, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11060-:d:650974. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.