IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p13843-d952649.html
   My bibliography  Save this article

Dynamic Estimation of Urban Land Use Efficiency and Sustainability Analysis in China

Author

Listed:
  • Huifang Cheng

    (School of Economics, Zhejiang University of Technology, Hangzhou 310023, China)

  • Ting Yu

    (School of Economics, Zhejiang University of Technology, Hangzhou 310023, China)

  • Hao Zhang

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

  • Kaifeng Duan

    (School of Economics and Management, Fuzhou University, Fuzhou 350108, China)

  • Jianing Zhu

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

Abstract

With rapid urbanization in China, land use efficiency (LUE) and related sustainability should be reasonably evaluated and improved. Studies have rarely investigated urban LUE and lack an analysis from the sustainability perspective. Long-term analysis can help identify the weaknesses in LUE and obtain a more stable evaluation. Hence, in this paper we develop a dynamic data envelopment analysis (DEA) model to assess urban LUE considering the time dimension. Differing from studies on traditional static DEA models, this study connects the observed periods by creating a common objective function. In addition, a method for estimating the sustainability of urban LUE is proposed under the DEA framework. The proposed method was applied to 34 major Chinese cities over a 3-year period, from 2015 to 2017. The results reveal that urban LUE still has potential for improvement in most cities. There was a distinct difference in efficiency among eastern, central, and western cities during the observed period. The average efficiency was higher in eastern cities than in central and western cities. The potential to optimize the land area and GDP should be realized with more efforts by most cities to strengthen LUE. Additionally, most inefficient cities have weak performance regarding the sustainability of LUE. The proposed approach enriches the sustainable measurement of LUE. Some management implications are provided to improve urban LUE. The empirical findings provide important support for sustainable land use in practice, and the proposed model is an important empirical extension of the DEA method in the land management field.

Suggested Citation

  • Huifang Cheng & Ting Yu & Hao Zhang & Kaifeng Duan & Jianing Zhu, 2022. "Dynamic Estimation of Urban Land Use Efficiency and Sustainability Analysis in China," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13843-:d:952649
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/13843/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/13843/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaodong Yang & Yongxiang Wu & Hang Dang, 2017. "Urban Land Use Efficiency and Coordination in China," Sustainability, MDPI, vol. 9(3), pages 1-12, March.
    2. Xie, Hualin & Chen, Qianru & Lu, Fucai & Wu, Qing & Wang, Wei, 2018. "Spatial-temporal disparities, saving potential and influential factors of industrial land use efficiency: A case study in urban agglomeration in the middle reaches of the Yangtze River," Land Use Policy, Elsevier, vol. 75(C), pages 518-529.
    3. Qiaowen Lin & Huiting Ling, 2021. "Study on Green Utilization Efficiency of Urban Land in Yangtze River Delta," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    4. Zhu, Xinhua & Li, Yan & Zhang, Peifeng & Wei, Yigang & Zheng, Xuyang & Xie, Lingling, 2019. "Temporal–spatial characteristics of urban land use efficiency of China’s 35mega cities based on DEA: Decomposing technology and scale efficiency," Land Use Policy, Elsevier, vol. 88(C).
    5. Liu, Shuchang & Xiao, Wu & Li, Linlin & Ye, Yanmei & Song, Xiaoli, 2020. "Urban land use efficiency and improvement potential in China: A stochastic frontier analysis," Land Use Policy, Elsevier, vol. 99(C).
    6. Hualin Xie & Wei Wang, 2015. "Exploring the Spatial-Temporal Disparities of Urban Land Use Economic Efficiency in China and Its Influencing Factors under Environmental Constraints Based on a Sequential Slacks-Based Model," Sustainability, MDPI, vol. 7(8), pages 1-20, July.
    7. Jing Huang & Dongqian Xue, 2019. "Study on Temporal and Spatial Variation Characteristics and Influencing Factors of Land Use Efficiency in Xi’an, China," Sustainability, MDPI, vol. 11(23), pages 1-16, November.
    8. Yue Zhou & Yi Chen & Yi Hu, 2021. "Assessing Efficiency of Urban Land Utilisation under Environmental Constraints in Yangtze River Delta, China," IJERPH, MDPI, vol. 18(23), pages 1-18, November.
    9. Kuang, Bing & Lu, Xinhai & Zhou, Min & Chen, Danling, 2020. "Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    10. Xie, Hualin & Chen, Qianru & Wang, Wei & He, Yafen, 2018. "Analyzing the green efficiency of arable land use in China," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 15-28.
    11. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    12. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    13. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    14. 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.
    15. Jingxin, Gao & Jinbo, Song & Lufang, Wu, 2022. "A new methodology to measure the urban construction land-use efficiency based on the two-stage DEA model," Land Use Policy, Elsevier, vol. 112(C).
    16. Yongrok Choi & Na Wang, 2017. "The Economic Efficiency of Urban Land Use with a Sequential Slack-Based Model in Korea," Sustainability, MDPI, vol. 9(1), pages 1-12, January.
    17. Tan, Shukui & Hu, Bixia & Kuang, Bing & Zhou, Min, 2021. "Regional differences and dynamic evolution of urban land green use efficiency within the Yangtze River Delta, China," Land Use Policy, Elsevier, vol. 106(C).
    18. Yu, Junqing & Zhou, Kaile & Yang, Shanlin, 2019. "Land use efficiency and influencing factors of urban agglomerations in China," Land Use Policy, Elsevier, vol. 88(C).
    19. 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.
    20. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    21. Nemoto, Jiro & Goto, Mika, 1999. "Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies," Economics Letters, Elsevier, vol. 64(1), pages 51-56, July.
    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. Yin Ma & Minrui Zheng & Xinqi Zheng & Yi Huang & Feng Xu & Xiaoli Wang & Jiantao Liu & Yongqiang Lv & Wenchao Liu, 2023. "Land Use Efficiency Assessment under Sustainable Development Goals: A Systematic Review," Land, MDPI, vol. 12(4), pages 1-21, April.
    2. Mengchao Yao & Yihua Zhang, 2021. "Evaluation and Optimization of Urban Land-Use Efficiency: A Case Study in Sichuan Province of China," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    3. Yanxi Lei & Zuoji Dong & Jichang Dong & Zhi Dong, 2023. "Multidimensional Evaluation of Urban Land-Use Efficiency and Innovation Capability Analysis: A Case Study in the Pearl River Delta Region, China," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    4. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    5. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    6. Han Chen & Chunyu Meng & Qilin Cao, 2022. "Measurement and Influencing Factors of Low Carbon Urban Land Use Efficiency—Based on Non-Radial Directional Distance Function," Land, MDPI, vol. 11(7), pages 1-16, July.
    7. Di Zhu & Yinghong Wang & Shangui Peng & Fenglin Zhang, 2022. "Influence Mechanism of Polycentric Spatial Structure on Urban Land Use Efficiency: A Moderated Mediation Model," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    8. Hao Su & Shuo Yang, 2022. "Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China," IJERPH, MDPI, vol. 19(19), pages 1-28, October.
    9. Jahanshahloo, G.R. & Soleimani-damaneh, M. & Ghobadi, S., 2015. "Inverse DEA under inter-temporal dependence using multiple-objective programming," European Journal of Operational Research, Elsevier, vol. 240(2), pages 447-456.
    10. Khalili-Damghani, Kaveh & Tavana, Madjid & Santos-Arteaga, Francisco J. & Mohtasham, Sima, 2015. "A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry," Energy Economics, Elsevier, vol. 51(C), pages 320-328.
    11. Tan, Shukui & Hu, Bixia & Kuang, Bing & Zhou, Min, 2021. "Regional differences and dynamic evolution of urban land green use efficiency within the Yangtze River Delta, China," Land Use Policy, Elsevier, vol. 106(C).
    12. Xufeng Cui & Sheng Yang & Guanghong Zhang & Bin Liang & Fei Li, 2020. "An Exploration of a Synthetic Construction Land Use Quality Evaluation Based on Economic-Social-Ecological Coupling Perspective: A Case Study in Major Chinese Cities," IJERPH, MDPI, vol. 17(10), pages 1-16, May.
    13. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    14. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
    15. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    16. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    17. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    18. Kao, Han-Ying & Wu, Dong-Jyun & Huang, Chia-Hui, 2017. "Evaluation of cloud service industry with dynamic and network DEA models," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 188-202.
    19. Xinhai Lu & Yifeng Tang & Shangan Ke, 2021. "Does the Construction and Operation of High-Speed Rail Improve Urban Land Use Efficiency? Evidence from China," Land, MDPI, vol. 10(3), pages 1-15, March.
    20. Rongtian Zhang & Jianfei Lu, 2022. "Spatial–Temporal Pattern and Convergence Characteristics of Provincial Urban Land Use Efficiency under Environmental Constraints in China," IJERPH, MDPI, vol. 19(17), pages 1-15, August.

    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:14:y:2022:i:21:p:13843-:d:952649. 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.