IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v145y2021ics1364032121004196.html
   My bibliography  Save this article

Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration

Author

Listed:
  • Li, Ye
  • Chen, Yiyan

Abstract

China has created the rapid development of the economy, but it has also negatively impacted the ecosystem. In China's affluent and innovative pearl river delta urban agglomeration (PRDUA), how to balance the relationship between economic development and environmental protection is related to the realization of local green development strategy. Consequently, to carry out green development more accurately and scientifically, the primary task is to conduct scientific research and judge the relationship among regional resources, environment, and economy. Therefore, it's of tremendous significance to study the green total factor productivity (GTFP) of the PRDUA, including resources and environmental factors. Combining the fixed Malmquist-Luenberger (ML) index and the slack based measure (SBM) model with undesirable output, this paper proposes a novel method, called slack based measure-Malmquist-Luenberger (SBM-ML) model, to measure GTFP. This method was used to measure the GTFP of the PRDUA from 2005 to 2018 and analyzes its changes from time and space dimensions. The results show that: from the perspective of time, the GTFP of all cities in the PRDUA increased in a wavelike increasing trend during the sample period, and the change of the annual average GTFP of the PRDUA can be roughly divided into four stages. From the perspective of space, the GTFP of Shenzhen has been at the top-level during the sample period. Meanwhile, the disparity of GTFP between cities in PRDUA becomes narrowing in the overall trend. Finally, according to the empirical results of the GTFP of the PRDUA, this paper puts forward targeted policy recommendations to facilitate greener development in the PRDUA.

Suggested Citation

  • Li, Ye & Chen, Yiyan, 2021. "Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    • Handle: RePEc:eee:rensus:v:145:y:2021:i:c:s1364032121004196
    DOI: 10.1016/j.rser.2021.111131
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032121004196
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2021.111131?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Agha Iqbal Ali & Catherine Lerme, 1997. "Comparative advantage and disadvantage in DEA," Annals of Operations Research, Springer, vol. 73(0), pages 215-232, October.
    2. Zachary Baynham-Herd, 2017. "Enlist blockchain to boost conservation," Nature, Nature, vol. 548(7669), pages 523-523, August.
    3. Zhu, Bangzhu & Zhang, Mengfan & Huang, Liqing & Wang, Ping & Su, Bin & Wei, Yi-Ming, 2020. "Exploring the effect of carbon trading mechanism on China's green development efficiency: A novel integrated approach," Energy Economics, Elsevier, vol. 85(C).
    4. Christopher H. Trisos & Cory Merow & Alex L. Pigot, 2020. "The projected timing of abrupt ecological disruption from climate change," Nature, Nature, vol. 580(7804), pages 496-501, April.
    5. Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
    6. 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).
    7. Berg, Sigbjorn Atle & Forsund, Finn R & Jansen, Eilev S, 1992. " Malmquist Indices of Productivity Growth during the Deregulation of Norwegian Banking, 1980-89," Scandinavian Journal of Economics, Wiley Blackwell, vol. 94(0), pages 211-228, Supplemen.
    8. David Zilberman & Ben Gordon & Gal Hochman & Justus Wesseler, 2018. "Economics of Sustainable Development and the Bioeconomy," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 40(1), pages 22-37.
    9. Fuyou Guo & LianJun Tong & Limeng Xu & Xiao Lu & Yanwen Sheng, 2020. "Spatio‐temporal pattern evolution and spatial spillover effect of green development efficiency: Evidence from Shandong Province, China," Growth and Change, Wiley Blackwell, vol. 51(1), pages 382-401, March.
    10. Bo Zhang & Robert M. Hughes, 2017. "China deploys big data to clear smog," Nature, Nature, vol. 542(7639), pages 31-31, February.
    11. 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.
    12. Martin de Jong & Dong Wang & Chang Yu, 2013. "Exploring the Relevance of the Eco-City Concept in China: The Case of Shenzhen Sino-Dutch Low Carbon City," Journal of Urban Technology, Taylor & Francis Journals, vol. 20(1), pages 95-113, January.
    13. Holstenkamp, Lars, 2019. "What do we know about cooperative sustainable electrification in the global South? A synthesis of the literature and refined social-ecological systems framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 307-320.
    14. 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.
    15. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, November.
    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. Xiaoyu He & Bo Li, 2023. "A Study on the Influence of Green Industrial Policy on Urban Green Development: Based on the Empirical Data of Ecological Industrial Park Pilot Construction," Sustainability, MDPI, vol. 15(13), pages 1-29, June.
    2. Jinhua Sun & Decai Tang & Haojia Kong & Valentina Boamah, 2022. "Impact of Industrial Structure Upgrading on Green Total Factor Productivity in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(6), pages 1-15, March.
    3. Susheng Wang & Gang Chen & Xue Han, 2021. "An Analysis of the Impact of the Emissions Trading System on the Green Total Factor Productivity Based on the Spatial Difference-in-Differences Approach: The Case of China," IJERPH, MDPI, vol. 18(17), pages 1-18, August.
    4. Gao(高凯), Kai & Wang(王玲), Ling & Liu(刘婷婷), Tingting & Zhao(赵华擎), Huaqing, 2022. "Management executive power and corporate green innovation——Empirical evidence from China's state-owned manufacturing sector," Technology in Society, Elsevier, vol. 70(C).
    5. Xin Zhang & Felix Nutakor & Michael Kaku Minlah & Jinke Li, 2023. "Can Digital Transformation Drive Green Transformation in Manufacturing Companies?—Based on Socio-Technical Systems Theory Perspective," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    6. Xiangyu Hua & Haiping Lv & Xiangrong Jin, 2021. "Research on High-Quality Development Efficiency and Total Factor Productivity of Regional Economies in China," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    7. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    8. Yuxin Fang & Hongjun Cao & Jihui Sun, 2022. "Impact of Artificial Intelligence on Regional Green Development under China’s Environmental Decentralization System—Based on Spatial Durbin Model and Threshold Effect," IJERPH, MDPI, vol. 19(22), pages 1-27, November.
    9. Haoran Yang & Yaoben Lin & Yang Hu & Xueqing Liu & Qun Wu, 2022. "Influence Mechanism of Industrial Agglomeration and Technological Innovation on Land Granting on Green Total Factor Productivity," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
    10. Lv, Chengchao & Song, Jie & Lee, Chien-Chiang, 2022. "Can digital finance narrow the regional disparities in the quality of economic growth? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 502-521.
    11. Chenyang Liu & Lihang Cui & Cuixia Li, 2022. "Impact of Environmental Regulation on the Green Total Factor Productivity of Dairy Farming: Evidence from China," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    12. Dawei Huang & Gang Chen, 2022. "Can the Carbon Emissions Trading System Improve the Green Total Factor Productivity of the Pilot Cities?—A Spatial Difference-in-Differences Econometric Analysis in China," IJERPH, MDPI, vol. 19(3), pages 1-18, January.
    13. Yin, Linfei & Tao, Min, 2023. "Balanced broad learning prediction model for carbon emissions of integrated energy systems considering distributed ground source heat pump heat storage systems and carbon capture & storage," Applied Energy, Elsevier, vol. 329(C).
    14. Pei Zhao & Junhua Guo & Yang Wang, 2023. "How Does the Digital Economy Affect Green Development?—Evidence from 284 Cities in China," Sustainability, MDPI, vol. 15(15), pages 1-24, July.
    15. Sheng Xu & Wenran Pan & Demei Wen, 2023. "Do Carbon Emission Trading Schemes Promote the Green Transition of Enterprises? Evidence from China," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    16. Dongchu Han & Mianfang Liu, 2022. "How Does the Digital Economy Empower Green Development? From the Perspective of the Division of Labor in New Classical Economics," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    17. Jiekuan Zhang & Yan Zhang, 2023. "Examining the effects of economic growth pressure on green total factor productivity: evidence from China," Economic Change and Restructuring, Springer, vol. 56(6), pages 4309-4337, December.
    18. Zhou, Di & Yin, Xiaoshuo & Xie, Dongchun, 2023. "Local governments’ environmental targets and green total factor productivity in Chinese cities," Economic Modelling, Elsevier, vol. 120(C).
    19. Shuxing Xiao & Zuxin He & Weikun Zhang & Xiaoming Qin, 2022. "The Agricultural Green Production following the Technological Progress: Evidence from China," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
    20. Dongchu Han & Mianfang Liu, 2022. "How Does the Digital Economy Contribute to Regional Green Development in China? Evidence-Based on the Intermediary Effect of Technological Innovation," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    21. Xinfei Li & Baodong Cheng & Qiling Hong & Chang Xu, 2021. "Can a Win–Win Situation of Economy and Environment Be Achieved in Cities by the Government’s Environmental Regulations?," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    22. Can Cheng & Xiuwen Yu & Heng Hu & Zitian Su & Shangfeng Zhang, 2022. "Measurement of China’s Green Total Factor Productivity Introducing Human Capital Composition," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    23. Chunbin Zhang & Rong Zhou & Jundong Hou & Mengtong Feng, 2022. "Spatial-Temporal Evolution and Convergence Characteristics of Agricultural Eco-Efficiency in China from a Low-Carbon Perspective," Sustainability, MDPI, vol. 14(24), pages 1-24, December.
    24. Guang Chen & Akira Hibiki, 2022. "Can the Carbon Emission Trading Scheme Influence Industrial Green Production in China?," Sustainability, MDPI, vol. 14(23), pages 1-22, November.

    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. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    2. Yuanyuan Wu & Zhanhua Jia & Tingting Yu, 2022. "Tourism and Green Development: Analysis of Linear and Non-Linear Effects," IJERPH, MDPI, vol. 19(23), pages 1-22, November.
    3. Junfeng Zhang & Jianxu Liu & Jing Li & Yuyan Gao & Chuansong Zhao, 2021. "Green Development Efficiency and Its Influencing Factors in China’s Iron and Steel Industry," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    4. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    5. Põldaru, Reet & Roots, Jüri, 2014. "A PCA–DEA approach to measure the quality of life in Estonian counties," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 65-73.
    6. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    7. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, February.
    8. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    9. Mohammad Nourani & Qian Long Kweh & Evelyn Shyamala Devadason & V.G.R. Chandran, 2020. "A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 885-901, September.
    10. Senhua Huang & Lingming Chen, 2023. "The Impact of the Digital Economy on the Urban Total-Factor Energy Efficiency: Evidence from 275 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    11. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    12. 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.
    13. Chin‐wei Huang & Hsiao‐Yin Chen, 2023. "Using nonradial metafrontier data envelopment analysis to evaluate the metatechnology and metafactor ratios for the Taiwanese hotel industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 1904-1919, June.
    14. Zhang, Fengtai & Xiao, Yuedong & Gao, Lei & Ma, Dalai & Su, Ruiqi & Yang, Qing, 2022. "How agricultural water use efficiency varies in China—A spatial-temporal analysis considering unexpected outputs," Agricultural Water Management, Elsevier, vol. 260(C).
    15. Frederick, Joshua D. & Fung, Derrick W.H. & Yang, Charles C. & Yeh, Jason J.H., 2022. "Individual health insurance reforms in the U.S.: Expanding interstate markets, Medicare for all, or Medicaid for all?," European Journal of Operational Research, Elsevier, vol. 297(2), pages 753-765.
    16. 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.
    17. Jarmila Horváthová & Martina Mokrišová & Mária Vrábliková, 2021. "Benchmarking—A Way of Finding Risk Factors in Business Performance," JRFM, MDPI, vol. 14(5), pages 1-17, May.
    18. Chang, Tsung-Sheng & Tone, Kaoru & Wu, Chen-Hui, 2016. "DEA models incorporating uncertain future performance," European Journal of Operational Research, Elsevier, vol. 254(2), pages 532-549.
    19. Amineh Ghazi & Farhad Hosseinzadeh Lotfi & Masoud Sanei, 2020. "Hybrid efficiency measurement and target setting based on identifying defining hyperplanes of the PPS with negative data," Operational Research, Springer, vol. 20(2), pages 1055-1092, June.
    20. Rui Zhang & Yong Ma & Jie Ren, 2022. "Green Development Performance Evaluation Based on Dual Perspectives of Level and Efficiency: A Case Study of the Yangtze River Economic Belt, China," IJERPH, MDPI, vol. 19(15), pages 1-24, July.

    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:rensus:v:145:y:2021:i:c:s1364032121004196. 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/wps/find/journaldescription.cws_home/600126/description#description .

    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.