IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i11p1911-d955046.html
   My bibliography  Save this article

Assessment and Decomposition of Regional Land Use Efficiency of the Service Sector in China

Author

Listed:
  • Mingzhi Zhang

    (School of Economics, Institute of Population and Economic Development, Shandong University of Finance and Economics, Jinan 250014, China)

  • Hongyu Liu

    (School of Economics, Institute of Population and Economic Development, Shandong University of Finance and Economics, Jinan 250014, China)

  • Yangyue Su

    (School of Management Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Xiangyu Zhou

    (School of Economics, Institute of Population and Economic Development, Shandong University of Finance and Economics, Jinan 250014, China)

  • Zhaocheng Li

    (School of Economics, Institute of Population and Economic Development, Shandong University of Finance and Economics, Jinan 250014, China)

  • Chao Chen

    (School of Economics, Institute of Population and Economic Development, Shandong University of Finance and Economics, Jinan 250014, China)

Abstract

High land use efficiency is the key to improving total factor productivity, and also an important force behind achieving sustained economic growth. Existing studies have mainly focused on the land use efficiency of the industry sector. Yet, the issue of land use efficiency of the service sector (SLUE) has been largely overlooked. This study examines regional differences and efficiency decomposition by using a slack based model (SBM) of undesirable output, and the Malmquist productivity index (MPI) under a data envelopment analysis framework. The results reveal that: (1) In China, the land use efficiency of the service sector is unbalanced, showing an inverted growth law of “low in developed areas and high in backward areas”. (2) The land use efficiency of the service sector can be decomposed into technical progress, pure technical efficiency, and scale efficiency. From the decomposition results, the growth rate of pure technical efficiency presents a trend of “low in the east and high in the west”; the scale efficiency also falls into the situation of weak group growth. Technological progress has maintained steady improvement. (3) The coordinated improvement of land use efficiency of the service sector needs to focus on resolving the “beggar-thy-neighbor” issue caused by existing large regional differences. In this article, the puzzle of land use efficiency differences in the service industry is well solved, and thus provides valuable enlightenment for the benign growth of service industries in countries and regions around the world.

Suggested Citation

  • Mingzhi Zhang & Hongyu Liu & Yangyue Su & Xiangyu Zhou & Zhaocheng Li & Chao Chen, 2022. "Assessment and Decomposition of Regional Land Use Efficiency of the Service Sector in China," Land, MDPI, vol. 11(11), pages 1-19, October.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:11:p:1911-:d:955046
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/11/1911/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/11/11/1911/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kemeny, Tom & Osman, Taner, 2018. "The wider impacts of high-technology employment: Evidence from U.S. cities," Research Policy, Elsevier, vol. 47(9), pages 1729-1740.
    2. Shorrocks, A F, 1980. "The Class of Additively Decomposable Inequality Measures," Econometrica, Econometric Society, vol. 48(3), pages 613-625, April.
    3. Bourguignon, Francois, 1979. "Decomposable Income Inequality Measures," Econometrica, Econometric Society, vol. 47(4), pages 901-920, July.
    4. Yang Bai & Wei Zhou & Yanjun Guan & Xue Li & Baohua Huang & Fengchun Lei & Hong Yang & Wenmin Huo, 2020. "Evolution of Policy Concerning the Readjustment of Inefficient Urban Land Use in China Based on a Content Analysis Method," Sustainability, MDPI, vol. 12(3), pages 1-21, January.
    5. Frank A. Cowell, 1980. "On the Structure of Additive Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(3), pages 521-531.
    6. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    7. Yingkai Tang & Kun Wang & Xuanming Ji & He Xu & Yangqing Xiao, 2021. "Assessment and Spatial-Temporal Evolution Analysis of Urban Land Use Efficiency under Green Development Orientation: Case of the Yangtze River Delta Urban Agglomerations," Land, MDPI, vol. 10(7), pages 1-19, July.
    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. Lin, Shoufu & Lin, Ruoyun & Sun, Ji & Wang, Fei & Wu, Weixiang, 2021. "Dynamically evaluating technological innovation efficiency of high-tech industry in China: Provincial, regional and industrial perspective," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    10. Koroso, Nesru H. & Zevenbergen, Jaap A. & Lengoiboni, Monica, 2020. "Urban land use efficiency in Ethiopia: An assessment of urban land use sustainability in Addis Ababa," Land Use Policy, Elsevier, vol. 99(C).
    11. Yayuan Pang & Xinjun Wang, 2020. "Land-Use Efficiency in Shandong (China): Empirical Analysis Based on a Super-SBM Model," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    12. Hengji Li & Jiansheng Qu & Dai Wang & Peng Meng & Chenyu Lu & Jingjing Zeng, 2021. "Spatial-Temporal Integrated Measurement of the Efficiency of Urban Land Use in Yellow River Basin," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    13. Zehui Chen & Qianxi Zhang & Fei Li & Jinli Shi, 2021. "Comprehensive Evaluation of Land Use Benefit in the Yellow River Basin from 1995 to 2018," Land, MDPI, vol. 10(6), pages 1-22, June.
    14. Lili Yang & Jian Wang & Yuhao Feng & Qun Wu, 2022. "The Impact of the Regional Differentiation of Land Supply on Total Factor Productivity in China: From the Perspective of Total Factor Productivity Decomposition," Land, MDPI, vol. 11(10), pages 1-17, October.
    15. Gao, Xin & Zhang, Anlu & Sun, Zhanli, 2020. "How regional economic integration influence on urban land use efficiency? A case study of Wuhan metropolitan area, China," Land Use Policy, Elsevier, vol. 90(C).
    16. Aiping Wang & Weifen Lin & Bei Liu & Hui Wang & Hong Xu, 2021. "Does Smart City Construction Improve the Green Utilization Efficiency of Urban Land?," Land, MDPI, vol. 10(6), pages 1-18, June.
    17. Fare, Rolf & Grosskopf, Shawna, 1992. "Malmquist Productivity Indexes and Fisher Ideal Indexes," Economic Journal, Royal Economic Society, vol. 102(410), pages 158-160, January.
    18. Liu Yang & Bingyang Han & Zhili Ma & Ting Wang & Yingchao Lin, 2022. "Analysis of the Urban Land Use Efficiency in the New-Type Urbanization Process of China’s Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(13), pages 1-22, July.
    19. Muhammad, Sulaman & Pan, Yanchun & Agha, Mujtaba Hassan & Umar, Muhammad & Chen, Siyuan, 2022. "Industrial structure, energy intensity and environmental efficiency across developed and developing economies: The intermediary role of primary, secondary and tertiary industry," Energy, Elsevier, vol. 247(C).
    20. 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.
    21. Zheng, Xiao-Ping, 2001. "Determinants of agglomeration economies and diseconomies: : empirical evidence from Tokyo," Socio-Economic Planning Sciences, Elsevier, vol. 35(2), pages 131-144.
    22. Kun Ge & Shan Zou & Danling Chen & Xinhai Lu & Shangan Ke, 2021. "Research on the Spatial Differences and Convergence Mechanism of Urban Land Use Efficiency under the Background of Regional Integration: A Case Study of the Yangtze River Economic Zone, China," Land, MDPI, vol. 10(10), pages 1-20, October.
    23. Mei Gai & Xiuqi Wang & Changli Qi, 2020. "Spatiotemporal Evolution and Influencing Factors of Ecological Civilization Construction in China," Complexity, Hindawi, vol. 2020, pages 1-14, October.
    24. 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.
    25. 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).
    26. Shangui Peng & Jian Wang & Hao Sun & Zhengning Guo, 2022. "How Does the Spatial Misallocation of Land Resources Affect Urban Industrial Transformation and Upgrading? Evidence from China," Land, MDPI, vol. 11(10), pages 1-22, September.
    27. Zhou, Di & Huang, Qing & Chong, Zhaohui, 2022. "Analysis on the effect and mechanism of land misallocation on carbon emissions efficiency: Evidence from China," Land Use Policy, Elsevier, vol. 121(C).
    28. Kottas, Angelos T. & Bozoudis, Michail N. & Madas, Michael A., 2020. "Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA," Omega, Elsevier, vol. 92(C).
    29. Guanglong Dong & Yibing Ge & Haiwei Jia & Chuanzhun Sun & Senyuan Pan, 2021. "Land Use Multi-Suitability, Land Resource Scarcity and Diversity of Human Needs: A New Framework for Land Use Conflict Identification," Land, MDPI, vol. 10(10), pages 1-14, September.
    30. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    31. Xu, Weiyi & Jin, Xiaobin & Liu, Jing & Zhou, Yinkang, 2021. "Analysis of influencing factors of cultivated land fragmentation based on hierarchical linear model: A case study of Jiangsu Province, China," Land Use Policy, Elsevier, vol. 101(C).
    32. Xue, Dan & Yue, Li & Ahmad, Fayyaz & Draz, Muhammad Umar & Chandio, Abbas Ali & Ahmad, Munir & Amin, Waqas, 2022. "Empirical investigation of urban land use efficiency and influencing factors of the Yellow River basin Chinese cities," Land Use Policy, Elsevier, vol. 117(C).
    33. Rao, P.M. & Balasubrahmanya, M.H., 2017. "The rise of IT services clusters in India: A case of growth by replication," Telecommunications Policy, Elsevier, vol. 41(2), pages 90-105.
    34. Xin Janet Ge & Xiaoxia Liu, 2021. "Urban Land Use Efficiency under Resource-Based Economic Transformation—A Case Study of Shanxi Province," Land, MDPI, vol. 10(8), pages 1-20, August.
    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. Chui-Yu Chiu & William Tang, 2022. "Measuring the Operational Efficiency and the Water Resources Management Efficiency for Industrial Parks: Empirical Study of Industrial Parks in Taiwan," Sustainability, MDPI, vol. 14(21), pages 1-22, October.

    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. 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.
    2. 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.
    3. Liu Yang & Bingyang Han & Zhili Ma & Ting Wang & Yingchao Lin, 2022. "Analysis of the Urban Land Use Efficiency in the New-Type Urbanization Process of China’s Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(13), pages 1-22, July.
    4. Liangen Zeng, 2022. "The Driving Mechanism of Urban Land Green Use Efficiency in China Based on the EBM Model with Undesirable Outputs and the Spatial Dubin Model," IJERPH, MDPI, vol. 19(17), pages 1-20, August.
    5. 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.
    6. Chengzhen Song & Qingfang Liu & Jinping Song & Zhengyun Jiang & Zhilin Lu & Yueying Chen, 2022. "Land Use Efficiency in the Yellow River Basin in the Background of China’s Economic Transformation: Spatial-Temporal Characteristics and Influencing Factors," Land, MDPI, vol. 11(12), pages 1-22, December.
    7. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.
    8. 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.
    9. Zhong, Meirui & Huang, Gangli & He, Ruifang, 2022. "The technological innovation efficiency of China's lithium-ion battery listed enterprises: Evidence from a three-stage DEA model and micro-data," Energy, Elsevier, vol. 246(C).
    10. Xinhai Lu & Zhenxing Shi & Jia Li & Junhao Dong & Mingjie Song & Jiao Hou, 2022. "Research on the Impact of Factor Flow on Urban Land Use Efficiency from the Perspective of Urbanization," Land, MDPI, vol. 11(3), pages 1-17, March.
    11. Guoqing Cui & Wenlong Zheng & Siliang Chen & Yue Dong & Tingyu Huang, 2022. "Study on the Spatial Pattern Characteristics and Influencing Factors of Inefficient Urban Land Use in the Yellow River Basin," Land, MDPI, vol. 11(9), pages 1-24, September.
    12. Jingbo Liu & Haoyuan Feng & Kun Wang, 2022. "The Low-Carbon City Pilot Policy and Urban Land Use Efficiency: A Policy Assessment from China," Land, MDPI, vol. 11(5), pages 1-18, April.
    13. Wang, Zhaohua & Feng, Chao, 2015. "Sources of production inefficiency and productivity growth in China: A global data envelopment analysis," Energy Economics, Elsevier, vol. 49(C), pages 380-389.
    14. Justas Streimikis & Zhuang Miao & Tomas Balezentis, 2021. "Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 576-589, January.
    15. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    16. Jie Zhang & Yajing Wang & Jiangfeng Li, 2023. "Maximize Eco-Economic Benefits with Minimum Land Resources Input: Evaluation and Evolution of Land Use Eco-Efficiency of Agglomerations in Middle Reaches of Yangtze River, China," IJERPH, MDPI, vol. 20(3), pages 1-19, January.
    17. Xufeng Cui & Sisi Huang & Cuicui Liu & Tingting Zhou & Ling Shan & Fengyuan Zhang & Min Chen & Fei Li & Walter T. de Vries, 2021. "Applying SBM-GPA Model to Explore Urban Land Use Efficiency Considering Ecological Development in China," Land, MDPI, vol. 10(9), pages 1-15, August.
    18. Mohsen Afsharian & Mohammadreza Alirezaee & Peter Reichling, 2012. "The master Malmquist index measurement using DEA-based weighted average efficiency," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 4(1), pages 21-42.
    19. Grifell-Tatjé, E. & Lovell, C.A.K., 2021. "Dual productivity analysis: A Konüs/Shephard approach," European Journal of Operational Research, Elsevier, vol. 289(1), pages 328-337.
    20. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, March.

    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:jlands:v:11:y:2022:i:11:p:1911-:d:955046. 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.