IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v27y2025i6d10.1007_s10668-023-04447-8.html
   My bibliography  Save this article

Network data envelopment analysis for carbon emission abatement allocation in a recycling production system

Author

Listed:
  • Fung-Bao Liu

    (I-Shou University)

  • Cheng-Feng Hu

    (National Chiayi University)

  • Cheng-Kai Hu

    (Taiwan Steel University of Science and Technology)

Abstract

Appropriate measurement of emission allowances is of great significance for sustainable energy management. This work considers the carbon emission abatement (CEA) allocation in a recycling production system with cyclical factors. A centralized CEA allocation model pursuing the maximization of total outputs among decision making units is proposed under the framework of network data envelopment analysis (DEA). To increase the advisability of the proposed allocation model, a compensation policy is employed to achieve a win-win situation. A real-world application to the CEA allocation among European Union (EU) countries is investigated. The main results are: (a) more than half of the EU countries are allowed to increase their carbon emissions to achieve the maximal total GDP level; (b) more than two-third of EU countries need to buy $$CO_2$$ C O 2 emissions to compensate for the increment in the carbon emissions from those with positive CEA contributions. Compared with conventional DEA-based allocation models, the proposed model considers the environmental treatment process with cyclical factors, which promotes the sustainable development while achieving energy allocation and emission reduction.

Suggested Citation

  • Fung-Bao Liu & Cheng-Feng Hu & Cheng-Kai Hu, 2025. "Network data envelopment analysis for carbon emission abatement allocation in a recycling production system," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(6), pages 13639-13658, June.
  • Handle: RePEc:spr:endesu:v:27:y:2025:i:6:d:10.1007_s10668-023-04447-8
    DOI: 10.1007/s10668-023-04447-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-023-04447-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-023-04447-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    2. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2014. "Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition," Energy Policy, Elsevier, vol. 66(C), pages 630-644.
    3. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    4. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    5. 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.
    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. Zhao, Jiqiang & Wu, Xianhua & Guo, Ji & Gao, Chao, 2022. "Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model," Applied Energy, Elsevier, vol. 325(C).
    8. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    9. Huang, Qian & Xu, Jiuping, 2020. "Bi-level multi-objective programming approach for carbon emission quota allocation towards co-combustion of coal and sewage sludge," Energy, Elsevier, vol. 211(C).
    10. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    11. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    12. Fang, Kai & Zhang, Qifeng & Long, Yin & Yoshida, Yoshikuni & Sun, Lu & Zhang, Haoran & Dou, Yi & Li, Shuai, 2019. "How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance," Applied Energy, Elsevier, vol. 241(C), pages 380-389.
    13. Sun, Tao & Zhang, Hongwei & Wang, Yuan, 2013. "The application of information entropy in basin level water waste permits allocation in China," Resources, Conservation & Recycling, Elsevier, vol. 70(C), pages 50-54.
    14. Feng, Chenpeng & Chu, Feng & Ding, Jingjing & Bi, Gongbing & Liang, Liang, 2015. "Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA," Omega, Elsevier, vol. 53(C), pages 78-89.
    15. Pekka Korhonen & Mikko Syrjänen, 2004. "Resource Allocation Based on Efficiency Analysis," Management Science, INFORMS, vol. 50(8), pages 1134-1144, August.
    Full references (including those not matched with items on IDEAS)

    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. Zhao, Jiqiang & Wu, Xianhua & Guo, Ji & Gao, Chao, 2022. "Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model," Applied Energy, Elsevier, vol. 325(C).
    2. Kao, Chiang & Liu, Shiang-Tai, 2025. "A compromise solution approach for efficiency measurement with shared input: The case of tourist hotels in Taiwan," European Journal of Operational Research, Elsevier, vol. 321(3), pages 895-906.
    3. Sun, J. & Wen, W. & Wang, M. & Zhou, P., 2022. "Optimizing the provincial target allocation scheme of renewable portfolio standards in China," Energy, Elsevier, vol. 250(C).
    4. 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.
    5. Ha Che-Ngoc & Thach Nguyen-Ngoc & Thao Nguyen-Trang, 2025. "A Novel Window Analysis and Its Application to Evaluating High-Frequency Trading Strategies," Computational Economics, Springer;Society for Computational Economics, vol. 65(2), pages 795-818, February.
    6. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    7. Svetlana V. Ratner & Artem M. Shaposhnikov & Andrey V. Lychev, 2023. "Network DEA and Its Applications (2017–2022): A Systematic Literature Review," Mathematics, MDPI, vol. 11(9), pages 1-24, May.
    8. Wang, Yizhong & Hang, Ye & Wang, Qunwei, 2024. "Multi-pollutants allocation and compensation schemes: A new approach considering materials balance principle," Ecological Economics, Elsevier, vol. 224(C).
    9. Xi Jin & Bin Zou & Chan Wang & Kaifeng Rao & Xiaowen Tang, 2019. "Carbon Emission Allocation in a Chinese Province-Level Region Based on Two-Stage Network Structures," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    10. Reza Feizabadi & Mehri Bagherian, 2023. "Identifying the Influential Factors in Increasing the Efficiency of Network Systems: A Mixed Binary Linear Programming," SN Operations Research Forum, Springer, vol. 4(4), pages 1-14, December.
    11. Shiping Mao & Marios Dominikos Kremantzis & Leonidas Sotirios Kyrgiakos & George Vlontzos, 2022. "R&D Performance Evaluation in the Chinese Food Manufacturing Industry Based on Dynamic DEA in the COVID-19 Era," Agriculture, MDPI, vol. 12(11), pages 1-19, November.
    12. Lívia Torres & Francisco S. Ramos, 2024. "Allocating Benefits Due to Shared Resources Using Shapley Value and Nucleolus in Dynamic Network Data Envelopment Analysis," Mathematics, MDPI, vol. 12(5), pages 1-23, February.
    13. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    14. Justyna Kujawska, 2021. "Health System Efficiency in European Countries: Network Data Envelopment Analysis Approach," European Research Studies Journal, European Research Studies Journal, vol. 0(2 - Part ), pages 1095-1117.
    15. repec:ers:journl:v:xxiv:y:2021:i:2:p:1095-1117 is not listed on IDEAS
    16. Jiawei Yang & Lei Fang, 2022. "Average lexicographic efficiency decomposition in two-stage data envelopment analysis: an application to China’s regional high-tech innovation systems," Annals of Operations Research, Springer, vol. 312(2), pages 1051-1093, May.
    17. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    18. Mohammad Tavassoli & Mahsa Ghandehari & Masoud Taherinia, 2023. "Rang-adjusted measure: modelling and computational aspects from internal and external perspectives for network DEA," Operational Research, Springer, vol. 23(4), pages 1-34, December.
    19. Ruchuan Zhang & Aijun Li & Davo Ayuba Dahoro, 2024. "A new approach for vehicle-health system measurement by network data envelopment analysis and an application in the USA," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(6), pages 14693-14727, June.
    20. Tao Ding & Ya Chen & Huaqing Wu & Yuqi Wei, 2018. "Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach," Annals of Operations Research, Springer, vol. 268(1), pages 497-511, September.
    21. Sungwook Jung & Jaeho Shin & Changhee Kim, 2025. "A study on the operational and competitive efficiency of National Oil Companies using two-stage network DEA model," Operations Management Research, Springer, vol. 18(1), pages 269-283, March.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:endesu:v:27:y:2025:i:6:d:10.1007_s10668-023-04447-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.