IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v324y2025ics0360544225014744.html
   My bibliography  Save this article

Policy-driven analysis of carbon emission efficiency under uncertainty and its application in Chinese industry: Hybrid delta-slacks-based model and ordinal priority approach

Author

Listed:
  • Cui, Shutian
  • Wang, Renlong
  • Li, Xiaoyan
  • Bai, Xiuguang

Abstract

Regional differences in carbon emission efficiency arise from disparities in multiple factors, which are often influenced by government policy preferences. However, currently, most studies fail to consider the impact of government policy preferences and data uncertainty on carbon emission efficiency. To address the above limitations, this study proposes a hybrid model based on delta-slacks-based model and ordinal priority approach for measuring carbon emission efficiency driven by government policy preferences under data uncertainty. The proposed model incorporates constraints on the importance of inputs and outputs under different policy preference scenarios. It then develops the efficiency optimization model with Farrell frontiers and efficiency tapes to deal with the data uncertainty in inputs and outputs. This study demonstrates the proposed model by analyzing industrial carbon emission efficiency in Chinese provinces in 2021. It examines the carbon emission efficiency and corresponding clustering results of provinces under three types of policies with varying priority preferences. The results indicate that the carbon emission efficiency of the 30 provinces can mainly be categorized into technology-driven, development-balanced, and transition-potential types, with most provinces achieving optimal efficiency under the technology-dominant preferences. Ultimately, this study suggests policy recommendation for different provinces to work towards achieving the low carbon goal.

Suggested Citation

  • Cui, Shutian & Wang, Renlong & Li, Xiaoyan & Bai, Xiuguang, 2025. "Policy-driven analysis of carbon emission efficiency under uncertainty and its application in Chinese industry: Hybrid delta-slacks-based model and ordinal priority approach," Energy, Elsevier, vol. 324(C).
    • Handle: RePEc:eee:energy:v:324:y:2025:i:c:s0360544225014744
    DOI: 10.1016/j.energy.2025.135832
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225014744
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.135832?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. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Sang, Meiyue & Shen, Liyin, 2024. "An international perspective on carbon peaking status between a sample of 154 countries," Applied Energy, Elsevier, vol. 369(C).
    3. Meng, Conghui & Du, Xiaoyun & Zhu, Mengcheng & Ren, Yitian & Fang, Kai, 2023. "The static and dynamic carbon emission efficiency of transport industry in China," Energy, Elsevier, vol. 274(C).
    4. Papaioannou, Grammatoula & Podinovski, Victor V., 2024. "A single-stage optimization procedure for data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1119-1128.
    5. Fang, Tao & Fang, Debin & Yu, Bolin, 2022. "Carbon emission efficiency of thermal power generation in China: Empirical evidence from the micro-perspective of power plants," Energy Policy, Elsevier, vol. 165(C).
    6. Cui, Lixin & Dong, Ruxue & Mu, Yunguo & Shen, Zhiyang & Xu, Jiatong, 2022. "How policy preferences affect the carbon shadow price in the OECD," Applied Energy, Elsevier, vol. 311(C).
    7. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    8. Arabmaldar, Aliasghar & Hatami-Marbini, Adel & Loske, Dominic & Hammerschmidt, Maik & Klumpp, Matthias, 2024. "Robust data envelopment analysis with variable budgeted uncertainty," European Journal of Operational Research, Elsevier, vol. 315(2), pages 626-641.
    9. Tian, Zhiguang & Mu, Xianzhong, 2024. "Towards China's dual-carbon target: Energy efficiency analysis of cities in the Yellow River Basin based on a “geography and high-quality development” heterogeneity framework," Energy, Elsevier, vol. 306(C).
    10. Amin Mahmoudi & Mehdi Abbasi & Xiaopeng Deng, 2022. "Evaluating the Performance of the Suppliers Using Hybrid DEA-OPA Model: A Sustainable Development Perspective," Group Decision and Negotiation, Springer, vol. 31(2), pages 335-362, April.
    11. Shaoze Li & Zhibin Deng & Cheng Lu & Junhao Wu & Jinyu Dai & Qiao Wang, 2023. "An efficient global algorithm for indefinite separable quadratic knapsack problems with box constraints," Computational Optimization and Applications, Springer, vol. 86(1), pages 241-273, September.
    12. Mahmoudi, Amin & Sadeghi, Mahsa & Deng, Xiaopeng & Mardani, Abbas, 2024. "A sustainable approach for exploiting cross-border nonrenewable resources using hybrid Game Theory and Ordinal Priority Approach," Resources Policy, Elsevier, vol. 88(C).
    13. Li, Rongrong & Han, Xinyu & Wang, Qiang, 2023. "Do technical differences lead to a widening gap in China's regional carbon emissions efficiency? Evidence from a combination of LMDI and PDA approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    14. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    15. Zhang, Sheng & Yu, Ran & Wen, Zuhui & Xu, Jiayu & Liu, Peihan & Zhou, Yunqiao & Zheng, Xiaoqi & Wang, Lei & Hao, Jiming, 2023. "Impact of labor and energy allocation imbalance on carbon emission efficiency in China's industrial sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    16. Dariush Khezrimotlagh & Shaharuddin Salleh & Zahra Mohsenpour, 2014. "A new method for evaluating decision making units in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(5), pages 694-707, May.
    17. Xiaohong Jiang & Jianxiao Ma & Huizhe Zhu & Xiucheng Guo & Zhaoguo Huang, 2020. "Evaluating the Carbon Emissions Efficiency of the Logistics Industry Based on a Super-SBM Model and the Malmquist Index from a Strong Transportation Strategy Perspective in China," IJERPH, MDPI, vol. 17(22), pages 1-19, November.
    18. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    19. Wang, Qiang & Zhang, Chen & Li, Rongrong, 2022. "Towards carbon neutrality by improving carbon efficiency - A system-GMM dynamic panel analysis for 131 countries’ carbon efficiency," Energy, Elsevier, vol. 258(C).
    20. Shaojian Qu & Yuting Xu & Ying Ji & Can Feng & Jinpeng Wei & Shan Jiang, 2022. "Data-Driven Robust Data Envelopment Analysis for Evaluating the Carbon Emissions Efficiency of Provinces in China," Sustainability, MDPI, vol. 14(20), pages 1-26, October.
    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. Shutian Cui & Renlong Wang, 2024. "A Novel {\delta}-SBM-OPA Approach for Policy-Driven Analysis of Carbon Emission Efficiency under Uncertainty in the Chinese Industrial Sector," Papers 2408.11600, arXiv.org, revised Dec 2024.
    2. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    3. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    4. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    5. Nikos Chatzistamoulou & Kostas Kounetas, 2023. "Tracing green growth through industrial resource efficiency patterns: The role of competitiveness and clean technologies," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(7), pages 4011-4026, October.
    6. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    7. Xushuai Li & Jiayu Zhang & Xiang Chen & Ching‐Cheng Lu, 2023. "Evaluation of innovation efficiency in China's cultural industry: A meta‐frontier with non‐radial directional distance function approach," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(5), pages 3709-3720, October.
    8. Färe, Rolf & Fukuyama, Hirofumi & Grosskopf, Shawna & Zelenyuk, Valentin, 2015. "Decomposing profit efficiency using a slack-based directional distance function," European Journal of Operational Research, Elsevier, vol. 247(1), pages 335-337.
    9. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
    10. Magdalena Kapelko, 2018. "Measuring inefficiency for specific inputs using data envelopment analysis: evidence from construction industry in Spain and Portugal," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(1), pages 43-66, March.
    11. Zhang, Ning & Kong, Fanbin & Choi, Yongrok, 2014. "Measuring sustainability performance for China: A sequential generalized directional distance function approach," Economic Modelling, Elsevier, vol. 41(C), pages 392-397.
    12. Fujii, Hidemichi & Managi, Shunsuke & Matousek, Roman, 2014. "Indian bank efficiency and productivity changes with undesirable outputs: A disaggregated approach," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 41-50.
    13. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    14. Kapelko, Magdalena & Oude Lansink, Alfons, 2017. "Dynamic multi-directional inefficiency analysis of European dairy manufacturing firms," European Journal of Operational Research, Elsevier, vol. 257(1), pages 338-344.
    15. Aparicio, Juan & Mahlberg, Bernhard & Pastor, Jesus T. & Sahoo, Biresh K., 2014. "Decomposing technical inefficiency using the principle of least action," European Journal of Operational Research, Elsevier, vol. 239(3), pages 776-785.
    16. Siying Hu & Shangkun Lu & Huiqiu Zhou, 2023. "Public Investment, Environmental Regulation, and the Sustainable Development of Agriculture in China Based on the Decomposition of Green Total Factor Productivity," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    17. Liu, Guangtian & Wang, Bing & Zhang, Ning, 2016. "A coin has two sides: Which one is driving China’s green TFP growth?," Economic Systems, Elsevier, vol. 40(3), pages 481-498.
    18. Gang Tian & Jian Shi & Licheng Sun & Xingle Long & Benhai Guo, 2017. "Dynamic changes in the energy–carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach," 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. 89(2), pages 585-607, November.
    19. Yun Tian & Rui Wang & Minhao Yin & Huijie Zhang, 2023. "Study on the Measurement and Influencing Factors of Rural Energy Carbon Emission Efficiency in China: Evidence Using the Provincial Panel Data," Agriculture, MDPI, vol. 13(2), pages 1-16, February.
    20. Nabavieh, Alireza & Gholamiangonabadi, Davoud & Ahangaran, Ali Asghar, 2015. "Dynamic changes in CO2 emission performance of different types of Iranian fossil-fuel power plants," Energy Economics, Elsevier, vol. 52(PA), pages 142-150.

    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:eee:energy:v:324:y:2025:i:c:s0360544225014744. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.