IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2022i1p76-d1015723.html
   My bibliography  Save this article

Spatial-Temporal Evolution and Its Influencing Factors on Urban Land Use Efficiency in China’s Yangtze River Economic Belt

Author

Listed:
  • Liguo Zhang

    (School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China)

  • Luchen Huang

    (School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China
    Department of Mathematics and Statistics, Chonnam National University, Gwangju 61186, Republic of Korea)

  • Jinglin Xia

    (School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China)

  • Kaifeng Duan

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

Abstract

Improving urban land use efficiency is a feasible way to realize sustainable development and alleviate urban land pressure on the city. The main purpose of this article is to measure the urban land use efficiency of the Yangtze River Economic Belt, and explore its evolutionary trends and influencing factors, so as to provide references for policy formulation to promote efficient land use and sustainable development. Therefore, we calculated the value of urban land use efficiency in the Yangtze River economic belt from 2004 to 2019, based on the super efficiency SBM model, including unexpected output. Further, we analyzed the spatial-temporal evolution, and spatial correlation and its influencing factors. The main results are as follows: Firstly, urban land use efficiency in the Yangtze River economic belt continues to improve as a whole, but it is higher in the east and lower in the west. In the kernel density evolution map, the development trend is steep at first and then slows, and the gap tends to decrease. Secondly, the spatial correlation of urban land use efficiency in the Yangtze River economic belt increases year by year, showing a positive correlation overall. The high-high agglomeration shifts to the east, low-low agglomeration shifts to the west, and low-high and high-low agglomeration show scattered distribution. The hot and cold spots are distributed regionally and have a diffusion trend. Thirdly, the results of the spatial Dubbin model show that the urbanization level, government expenditure and industrial instruction transformation can promote the improvement of urban land use efficiency, and people density and land use scale can inhibit its improvement. Additionally, there is remarkable heterogeneity in the effect of these influencing factors. On the whole, the effect of non-resource-based cities is better, and it is more so in the cities of the eastern region.

Suggested Citation

  • Liguo Zhang & Luchen Huang & Jinglin Xia & Kaifeng Duan, 2022. "Spatial-Temporal Evolution and Its Influencing Factors on Urban Land Use Efficiency in China’s Yangtze River Economic Belt," Land, MDPI, vol. 12(1), pages 1-19, December.
    • Handle: RePEc:gam:jlands:v:12:y:2022:i:1:p:76-:d:1015723
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/1/76/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/1/76/
    Download Restriction: no
    ---><---

    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. Yangyang Wang & Yanjun Liu & Guolei Zhou & Zuopeng Ma & Hongri Sun & Hui Fu, 2022. "Coordinated Relationship between Compactness and Land-Use Efficiency in Shrinking Cities: A Case Study of Northeast China," Land, MDPI, vol. 11(3), pages 1-19, March.
    3. Sidong Zhao & Kaixu Zhao & Yiran Yan & Kai Zhu & Chiming Guan, 2021. "Spatio-Temporal Evolution Characteristics and Influencing Factors of Urban Service-Industry Land in China," Land, MDPI, vol. 11(1), pages 1-32, December.
    4. 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).
    5. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    6. Richard V. Burkhauser & Ludmila Rovba, 2006. "Income Inequality in the 1990s: Comparing the United States, Great Britain and Germany," Discussion Papers of DIW Berlin 576, DIW Berlin, German Institute for Economic Research.
    7. Song, Yang & Yeung, Godfrey & Zhu, Daolin & Xu, Yang & Zhang, Lixin, 2022. "Efficiency of urban land use in China’s resource-based cities, 2000–2018," Land Use Policy, Elsevier, vol. 115(C).
    8. 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.
    9. Liejia Huang & Peng Yang & Boqing Zhang & Weiyan Hu, 2021. "Spatio-Temporal Coupling Characteristics and the Driving Mechanism of Population-Land-Industry Urbanization in the Yangtze River Economic Belt," Land, MDPI, vol. 10(4), pages 1-17, April.
    10. Shengqiang Jing & Yueguan Yan & Fangqu Niu & Wenhui Song, 2022. "Urban Expansion in China: Spatiotemporal Dynamics and Determinants," Land, MDPI, vol. 11(3), pages 1-16, February.
    11. Yan, Siqi & Peng, Jianchao & Wu, Qun, 2020. "Exploring the non-linear effects of city size on urban industrial land use efficiency: A spatial econometric analysis of cities in eastern China," Land Use Policy, Elsevier, vol. 99(C).
    12. 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.
    13. Du, Juan & Liang, Liang & Zhu, Joe, 2010. "A slacks-based measure of super-efficiency in data envelopment analysis: A comment," European Journal of Operational Research, Elsevier, vol. 204(3), pages 694-697, August.
    14. 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).
    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. Tone, Kaoru & Toloo, Mehdi & Izadikhah, Mohammad, 2020. "A modified slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 287(2), pages 560-571.
    2. Javad Gerami & Mohammad Reza Mozaffari & P. F. Wanke & Henrique Correa, 2022. "A novel slacks-based model for efficiency and super-efficiency in DEA-R," Operational Research, Springer, vol. 22(4), pages 3373-3410, September.
    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. 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.
    5. 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.
    6. 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.
    7. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.
    8. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    9. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    10. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," 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. 31(2), pages 363-391, June.
    11. 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.
    12. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.
    13. Guo, I-Lung & Lee, Hsuan-Shih & Lee, Dan, 2017. "An integrated model for slack-based measure of super-efficiency in additive DEA," Omega, Elsevier, vol. 67(C), pages 160-167.
    14. Chen, Po-Chi & Yu, Ming-Miin & Chang, Ching-Cheng & Hsu, Shih-Hsun & Managi, Shunsuke, 2015. "The enhanced Russell-based directional distance measure with undesirable outputs: Numerical example considering CO2 emissions," Omega, Elsevier, vol. 53(C), pages 30-40.
    15. Behrouz Arabi & Susila Munisamy Doraisamy & Ali Emrouznejad & Alireza Khoshroo, 2017. "Eco-efficiency measurement and material balance principle: an application in power plants Malmquist Luenberger Index," Annals of Operations Research, Springer, vol. 255(1), pages 221-239, August.
    16. ZHAO Xin & XUE Yue-mei & KANG Wang-lin & DING Li-li & ZHU Lin, 2018. "Measuring Efficiency of Ocean Economy in China Based on a Novel Luenberger Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-21, June.
    17. 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.
    18. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    19. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    20. Yangyang Wang & Yanjun Liu & Guolei Zhou & Zuopeng Ma & Hongri Sun & Hui Fu, 2022. "Coordinated Relationship between Compactness and Land-Use Efficiency in Shrinking Cities: A Case Study of Northeast China," Land, MDPI, vol. 11(3), pages 1-19, 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:12:y:2022:i:1:p:76-:d:1015723. 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.