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Study on Urban Efficiency Measurement and Spatiotemporal Evolution of Cities in Northwest China Based on the DEA–Malmquist Model

Author

Listed:
  • Jun Yin

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Qingmei Tan

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

Abstract

Urban efficiency can effectively measure the management and allocation level of urban factor inputs. Based on the data of 30 prefecture-level cities in Northwest China from 2006 to 2015, urban efficiency is measured by data envelopment analysis (DEA). Then the spatiotemporal evolution rule is identified by Malmquist model. The results illustrate that the overall average urban efficiency of cities in Northwest China each year from 2006 to 2015 was at the low level. Only Jiayuguan, Yulin, Yan’an, and Karamay reached the high average urban efficiency, while Dingxi, Pingliang, Guyuan, Shangluo, Tianshui, Longnan, and Baiyin were at the inefficient level. Most cities in Northwest China were still in the “growing” stage of increasing returns to scale. The scale of urban investment was relatively insufficient, and economies of scale had not yet formed. Cities with decreasing returns to scale were mainly distributed in the capital cities and the central and sub-central cities of Guanzhong-Tianshui Economic Zone with relatively abundant urban resources and capital. Cities with constant returns to scale were mainly distributed in four cities including Yan’an, Yulin, Jiayuguan, and Karamay with high efficiency. The overall comprehensive efficiency, technical efficiency, and scale efficiency of cities in Northwest China were not only low, but also showing a downward trend. The overall progress of urban technology had failed to make up for the shortfall caused by low efficiency, resulting in total factor productivity (TFP) decreasing by 0.5%. Therefore, the cities in Northwest China should continuously improve their technical efficiency and scale efficiency, and ultimately enhance the comprehensive efficiency.

Suggested Citation

  • Jun Yin & Qingmei Tan, 2019. "Study on Urban Efficiency Measurement and Spatiotemporal Evolution of Cities in Northwest China Based on the DEA–Malmquist Model," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:2:p:434-:d:197985
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    References listed on IDEAS

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    Cited by:

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    2. Benito, Bernardino & Martínez-Córdoba, Pedro-José & Guillamón, María-Dolores, 2021. "Measurement and determinants of efficiency in the municipal police service," Evaluation and Program Planning, Elsevier, vol. 85(C).
    3. Pedro-José Martínez-Córdoba & Nicola Raimo & Filippo Vitolla & Bernardino Benito, 2020. "Achieving Sustainable Development Goals. Efficiency in the Spanish Clean Water and Sanitation Sector," Sustainability, MDPI, vol. 12(7), pages 1-13, April.
    4. Heng Zhang & Qian Chang & Sui Li & Jiandong Huang, 2022. "Determining the Efficiency of the Sponge City Construction Pilots in China Based on the DEA-Malmquist Model," IJERPH, MDPI, vol. 19(18), pages 1-17, September.
    5. Shanwei Li & Jingjie Li & Junli Ding & Mochen Sun & Chenying Cui, 2023. "A Game Strategy Study on Innovation Efficiency of China’s Listed Charging Pile Companies: Based on Generalized Fuzzy DEA Method," Sustainability, MDPI, vol. 15(3), pages 1-23, January.
    6. Zhen Su & Joshua R. Aaron & Yang Guan & Hongchen Wang, 2019. "Sustainable Livelihood Capital and Strategy in Rural Tourism Households: A Seasonality Perspective," Sustainability, MDPI, vol. 11(18), pages 1-14, September.

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