IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v198y2025ics0301421524004580.html
   My bibliography  Save this article

How to accurately evaluate and effectively improve the performance of provincial green development in China? An improved integrated method

Author

Listed:
  • Yang, Haidong
  • Zhang, Xiangle
  • Lao, Quanchu
  • Liu, Biyu

Abstract

Evaluating and improving the performance of green development (GD) is essential for the government to formulate sustainable development policies. This study first analyzes the connotation and structures of GD from systemic perspective. Secondly, based on the two-stage eco-inefficiency (TE) model, non-cooperative theory, the correlation coefficient and standard deviation, and fuzzy set qualitative comparative analysis method (fsQCA), an improved integrated method, i.e., ITNE-fsQCA, is proposed. Thirdly, the validity and accuracy of ITNE-fsQCA are verified using the data from 30 Chinese provinces in 2020, and the results are compared with those obtained from TE and two-stage non-cooperative eco-inefficiency (TNE). Finally, the driving types and configuration pathway are discussed based on ITNE-fsQCA. The results show that: (1) compared to TE and TNE, ITNE-fsQCA helps to avoid the overestimation/underestimation of inefficiency in complex systems; (2) there are 8 configuration pathways that can effectively improve GD performance in 30 Chinese provinces in 2020, and these pathways are categorized into 4 driving types; (3) the enhancement of green technology innovation plays a crucial role in provincial sustainable development; and (4) the provincial GD inefficiencies in China are manifest various combinatorial forms. These findings provide the government with innovative ideas and methodologies for formulating sustainable development policies.

Suggested Citation

  • Yang, Haidong & Zhang, Xiangle & Lao, Quanchu & Liu, Biyu, 2025. "How to accurately evaluate and effectively improve the performance of provincial green development in China? An improved integrated method," Energy Policy, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:enepol:v:198:y:2025:i:c:s0301421524004580
    DOI: 10.1016/j.enpol.2024.114438
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421524004580
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2024.114438?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. Zhao, Jinkai & Zhou, Na, 2021. "Impact of human health on economic growth under the constraint of environment pollution," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Zhu, Bangzhu & Zhang, Mengfan & Zhou, Yanhua & Wang, Ping & Sheng, Jichuan & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "Exploring the effect of industrial structure adjustment on interprovincial green development efficiency in China: A novel integrated approach," Energy Policy, Elsevier, vol. 134(C).
    3. Du, Kerui & Cheng, Yuanyuan & Yao, Xin, 2021. "Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities," Energy Economics, Elsevier, vol. 98(C).
    4. Shi Yin & Yudan Zhao, 2024. "Digital green value co-creation behavior, digital green network embedding and digital green innovation performance: moderating effects of digital green network fragmentation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    5. Chen, Yao & Cook, Wade D. & Li, Ning & Zhu, Joe, 2009. "Additive efficiency decomposition in two-stage DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1170-1176, August.
    6. Dierk Herzer, 2022. "An Empirical Note on the Long-Run Effects of Public and Private R&D on TFP," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(4), pages 3248-3264, December.
    7. Li, Ye & Cui, Qiang, 2017. "Carbon neutral growth from 2020 strategy and airline environmental inefficiency: A Network Range Adjusted Environmental Data Envelopment Analysis," Applied Energy, Elsevier, vol. 199(C), pages 13-24.
    8. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    9. Pan, Xianyou & Shen, Zhiyang & Song, Malin & Shu, Yalin, 2023. "Enhancing green technology innovation through enterprise environmental governance: A life cycle perspective with moderator analysis of dynamic innovation capability," Energy Policy, Elsevier, vol. 182(C).
    10. Hamid Kiaei & Reza Farzipoor Saen & Reza Kazemi Matin, 2023. "Cross-efficiency evaluation and improvement in two-stage network data envelopment analysis," Annals of Operations Research, Springer, vol. 321(1), pages 281-309, February.
    11. Lin, Boqiang & Zhou, Yicheng, 2022. "Measuring the green economic growth in China: Influencing factors and policy perspectives," Energy, Elsevier, vol. 241(C).
    12. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    13. 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.
    14. Yuan, Huaxi & Feng, Yidai & Lee, Chien-Chiang & Cen, Yan, 2020. "How does manufacturing agglomeration affect green economic efficiency?," Energy Economics, Elsevier, vol. 92(C).
    15. Wang, Yizhong & Jeong, Sujong & Hang, Ye & Wang, Qunwei, 2024. "Multi-sector environmental efficiency and productivity: A general Leontief optimization method," Omega, Elsevier, vol. 126(C).
    16. Shi Yin & Yudan Zhao, 2024. "An agent-based evolutionary system model of the transformation from building material industry (BMI) to green intelligent BMI under supply chain management," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    17. Camanho, Ana Santos & Silva, Maria Conceicao & Piran, Fabio Sartori & Lacerda, Daniel Pacheco, 2024. "A literature review of economic efficiency assessments using Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 315(1), pages 1-18.
    18. Lee, Chien-Chiang & He, Zhi-Wen & Yuan, Zihao, 2023. "A pathway to sustainable development: Digitization and green productivity," Energy Economics, Elsevier, vol. 124(C).
    19. Jie Wu & Dacheng Huang & Zhixiang Zhou & Qingyuan Zhu, 2020. "The regional green growth and sustainable development of China in the presence of sustainable resources recovered from pollutions," Annals of Operations Research, Springer, vol. 290(1), pages 27-45, July.
    20. Pappas, Ilias O. & Woodside, Arch G., 2021. "Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing," International Journal of Information Management, Elsevier, vol. 58(C).
    21. Chen, Liang & Ma, Rui & Li, Jing & Zhou, Fengjiao, 2024. "Revolutionizing sustainable economic growth in China: Harnessing natural resources, green development, and fintech for a greener future," Resources Policy, Elsevier, vol. 92(C).
    22. Amirteimoori, Alireza & Kazemi Matin, Reza & Yadollahi, Amir Hossein, 2024. "Stochastic resource reallocation in two-stage production processes with undesirable outputs: An empirical study on the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    23. Ferreira, Fernando A.F. & Jalali, Marjan S. & Ferreira, João J.M., 2016. "Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables," Journal of Business Research, Elsevier, vol. 69(4), pages 1471-1478.
    24. Shabani, Mohadeseh & Kordrostami, Sohrab & Jahani Sayyad Noveiri, Monireh, 2023. "Renewable energy performance analysis using fuzzy dynamic directional distance function model under natural and managerial disposability," Applied Energy, Elsevier, vol. 352(C).
    25. Xiaowei Song & Muhammad Irfan & Ibrahim Alnafrah & Yu Hao, 2024. "Economic policy uncertainty and carbon neutrality in China: Do sustainable energy and eco‐innovation make a difference?," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(4), pages 4057-4070, August.
    26. Cheng, Manli & Wang, Junbo & Yang, Shanlin & Li, Qiang, 2024. "The driving effect of technological innovation on green development: From the perspective of efficiency," Energy Policy, Elsevier, vol. 188(C).
    27. Syed Abdul Rehman Khan & Yu Zhang & Anil Kumar & Edmundas Zavadskas & Dalia Streimikiene, 2020. "Measuring the impact of renewable energy, public health expenditure, logistics, and environmental performance on sustainable economic growth," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 833-843, July.
    28. Fare, Rolf, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    29. Thai-Ha Le & Youngho Chang & Donghyun Park, 2019. "Economic development and environmental sustainability: evidence from Asia," Empirical Economics, Springer, vol. 57(4), pages 1129-1156, October.
    30. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    31. Cropper, Maureen & Griffiths, Charles, 1994. "The Interaction of Population Growth and Environmental Quality," American Economic Review, American Economic Association, vol. 84(2), pages 250-254, May.
    32. Zhao, Xin & Shang, Yuping & Magazzino, Cosimo & Madaleno, Mara & Mallek, Sabrine, 2023. "Multi-step impacts of environmental regulations on green economic growth: Evidence in the lens of natural resource dependence," Resources Policy, Elsevier, vol. 85(PB).
    33. Cui, Qiang & Jin, Zi-yin, 2020. "Airline environmental efficiency measures considering negative data: An application of a modified network Modified Slacks-based measure model," Energy, Elsevier, vol. 207(C).
    34. 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.
    35. Zeng, Juying & Pagàn-Castaño, Esther & Ribeiro-Navarrete, Samuel, 2022. "Merits of Intercity Innovation Cooperation of Environment-friendly Patents for Environmental Regulation Efficiency," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    36. Yang, Lisha & Ni, Mengying, 2022. "Is financial development beneficial to improve the efficiency of green development? Evidence from the “Belt and Road” countries," Energy Economics, Elsevier, vol. 105(C).
    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. Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
    2. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    3. Arsen Benga & Glediana Zeneli (Foto) & María Jesús Delgado‑Rodríguez & Sonia Lucas Santos, 2025. "Company efforts and environmental efficiency: evidence from European railways considering market-based emissions," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 9977-10012, May.
    4. Qingyou Yan & Fei Zhao & Xu Wang & Tomas Balezentis, 2021. "The Environmental Efficiency Analysis Based on the Three-Step Method for Two-Stage Data Envelopment Analysis," Energies, MDPI, vol. 14(21), pages 1-14, October.
    5. Chu, Junfei & Shao, Caifeng & Emrouznejad, Ali & Wu, Jie & Yuan, Zhe, 2021. "Performance evaluation of organizations considering economic incentives for emission reduction: A carbon emission permit trading approach," Energy Economics, Elsevier, vol. 101(C).
    6. 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.
    7. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    8. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    9. Ma-Lin Song & Ron Fisher & Jian-Lin Wang & Lian-Biao Cui, 2018. "Environmental performance evaluation with big data: theories and methods," Annals of Operations Research, Springer, vol. 270(1), pages 459-472, November.
    10. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    11. Xiaohong Liu & Qingyuan Zhu & Junfei Chu & Xiang Ji & Xingchen Li, 2019. "Environmental Performance and Benchmarking Information for Coal-Fired Power Plants in China: A DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1287-1302, December.
    12. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    13. Cui, Qiang & Jin, Zi-yin, 2020. "Airline environmental efficiency measures considering negative data: An application of a modified network Modified Slacks-based measure model," Energy, Elsevier, vol. 207(C).
    14. Wu, Jie & Lv, Lin & Sun, Jiasen & Ji, Xiang, 2015. "A comprehensive analysis of China's regional energy saving and emission reduction efficiency: From production and treatment perspectives," Energy Policy, Elsevier, vol. 84(C), pages 166-176.
    15. Ma-Lin Song & Yuan-Xiang Zhou & Rong-Rong Zhang & Ron Fisher, 2017. "Environmental efficiency evaluation with left–right fuzzy numbers," Operational Research, Springer, vol. 17(3), pages 697-714, October.
    16. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    17. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    18. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    19. Afzalinejad, Mohammad, 2020. "Reverse efficiency measures for environmental assessment in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    20. Taleb, Mushtaq, 2025. "A general series network slacks-based measure approach for non-controllable inputs and undesirable outputs in mixed integer data envelopment analysis: An application to airport operations," Socio-Economic Planning Sciences, Elsevier, vol. 99(C).

    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:enepol:v:198:y:2025:i:c:s0301421524004580. 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.elsevier.com/locate/enpol .

    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.