IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i20p7510-d428572.html
   My bibliography  Save this article

Dynamic Changes, Spatiotemporal Differences and Factors Influencing the Urban Eco-Efficiency in the Lower Reaches of the Yellow River

Author

Listed:
  • Yu Zhang

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China)

  • Wenliang Geng

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China)

  • Pengyan Zhang

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China
    Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng 475001, China)

  • Erling Li

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China
    Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng 475001, China)

  • Tianqi Rong

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China)

  • Ying Liu

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China)

  • Jingwen Shao

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China)

  • Hao Chang

    (Research Center of Regional Development and Planning, College of Environment and Planning, Institute of Agriculture and Rural Sustainable Development, Henan University, Kaifeng 475004, China)

Abstract

The measurement of eco-efficiency is an important tool to evaluate the level of urban sustainable development. Therefore; improving urban eco-efficiency in the lower reaches of the Yellow River ensures the implementation of ecological protection and high-quality development strategies in the Yellow River Basin. In this study; the dynamic changes of urban eco-efficiency and spatiotemporal differences in the lower reaches of the Yellow River were investigated using the Super-SBM (Super-Slack measure model) model with undesirable outputs and standard deviation ellipse. The STIRPAT (Stochastic Impacts by Regression Population; Affluence and Technology) model was introduced to analyze the factors affecting the change in urban eco-efficiency. The results showed that the overall urban eco-efficiency in the lower reaches of the Yellow River has not reached the optimal level. The overall eco-efficiency in the lower reaches of the Yellow River in Shandong Province was higher than that in Henan Province but the gap is narrowing. The spatial differentiation of urban eco-efficiency in the lower reaches of the Yellow River showed the following trends: “blooming in the middle and reverse development at both ends” in the high-value area and gradual decrease in the low-value area. From 2007 to 2018; a direction was notable with respect to the development of urban eco-efficiency in the lower reaches of the Yellow River; with the centripetal force weakening. Although the mean center of urban eco-efficiency located in Shandong Province; it notably shifted to the west during the study period. In terms of driving factors; affluence and technological progress play positive roles in driving eco-efficiency; while investment intensity; industrial structure; and foreign investment intensity hindered the optimization and improvement of urban eco-efficiency in the lower reaches of the Yellow River. The results of this study show that urban eco-efficiency in the lower reaches of the Yellow River is improving; but the regional coordination is poor. The main methods promoting the sustainable development in the study area include changing the mode of extensive investments and the introduction of foreign capital; which improve the energy efficiency and promote faster and better economic development.

Suggested Citation

  • Yu Zhang & Wenliang Geng & Pengyan Zhang & Erling Li & Tianqi Rong & Ying Liu & Jingwen Shao & Hao Chang, 2020. "Dynamic Changes, Spatiotemporal Differences and Factors Influencing the Urban Eco-Efficiency in the Lower Reaches of the Yellow River," IJERPH, MDPI, vol. 17(20), pages 1-19, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:20:p:7510-:d:428572
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/20/7510/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/20/7510/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Yunqiang & Zhu, Jialing & Li, Eldon Y. & Meng, Zhiyi & Song, Yan, 2020. "Environmental regulation, green technological innovation, and eco-efficiency: The case of Yangtze river economic belt in China," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    2. Shi, Kaifang & Yu, Bailang & Zhou, Yuyu & Chen, Yun & Yang, Chengshu & Chen, Zuoqi & Wu, Jianping, 2019. "Spatiotemporal variations of CO2 emissions and their impact factors in China: A comparative analysis between the provincial and prefectural levels," Applied Energy, Elsevier, vol. 233, pages 170-181.
    3. 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.
    4. Gabisa, Elias W. & Gheewala, Shabbir H., 2020. "Can substitution of imported gasoline by locally produced molasses ethanol in Ethiopia be sustainable? An eco-efficiency assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    5. Xionghe Qin & Yanming Sun, 2019. "Cross-Regional Comparative Study on Environmental–Economic Efficiency and Driving Forces behind Efficiency Improvement in China: A Multistage Perspective," IJERPH, MDPI, vol. 16(7), pages 1-21, March.
    6. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 83-116.
    7. Haoran Yang & Qun Wu, 2019. "Land Use Eco-Efficiency and Its Convergence Characteristics Under the Constraint of Carbon Emissions in China," IJERPH, MDPI, vol. 16(17), pages 1-17, August.
    8. Li, Zhi & Ouyang, Xiaoling & Du, Kerui & Zhao, Yang, 2017. "Does government transparency contribute to improved eco-efficiency performance? An empirical study of 262 cities in China," Energy Policy, Elsevier, vol. 110(C), pages 79-89.
    9. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    10. Lin, Boqiang & Zhu, Junpeng, 2019. "Impact of energy saving and emission reduction policy on urban sustainable development: Empirical evidence from China," Applied Energy, Elsevier, vol. 239(C), pages 12-22.
    11. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    12. Haoran Yang & Hao Zheng & Hongguang Liu & Qun Wu, 2019. "NonLinear Effects of Environmental Regulation on Eco-Efficiency under the Constraint of Land Use Carbon Emissions: Evidence Based on a Bootstrapping Approach and Panel Threshold Model," IJERPH, MDPI, vol. 16(10), pages 1-20, May.
    13. Wei, Taoyuan, 2011. "What STIRPAT tells about effects of population and affluence on the environment?," Ecological Economics, Elsevier, vol. 72(C), pages 70-74.
    14. Tianqi Rong & Pengyan Zhang & Wenlong Jing & Yu Zhang & Yanyan Li & Dan Yang & Jiaxin Yang & Hao Chang & Linna Ge, 2020. "Carbon Dioxide Emissions and Their Driving Forces of Land Use Change Based on Economic Contributive Coefficient (ECC) and Ecological Support Coefficient (ESC) in the Lower Yellow River Region (1995–20," Energies, MDPI, vol. 13(10), pages 1-18, May.
    15. Wang, Shaojian & Wang, Jieyu & Zhou, Yuquan, 2018. "Estimating the effects of socioeconomic structure on CO2 emissions in China using an econometric analysis framework," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 18-27.
    16. Wang, Ying & Chen, Xiangyuan, 2020. "Natural resource endowment and ecological efficiency in China: Revisiting resource curse in the context of ecological efficiency," Resources Policy, Elsevier, vol. 66(C).
    17. Yunfeng Cen & Pengyan Zhang & Yuhang Yan & Wenlong Jing & Yu Zhang & Yanyan Li & Dan Yang & Xin Liu & Wenliang Geng & Tianqi Rong, 2019. "Spatial and Temporal Agglomeration Characteristics and Coupling Relationship of Urban Built-Up Land and Economic Hinterland—A Case Study of the Lower Yellow River, China," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    18. 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.
    19. Wei Zhang & Gabriele Villarini & Gabriel A. Vecchi & James A. Smith, 2018. "Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston," Nature, Nature, vol. 563(7731), pages 384-388, November.
    20. Luping Shi & Zhongyao Cai & Xuhui Ding & Rong Di & Qianqian Xiao, 2020. "What Factors Affect the Level of Green Urbanization in the Yellow River Basin in the Context of New-Type Urbanization?," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    21. 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.
    22. Zhao, Yabo & Wang, Shaojian & Ge, Yuejing & Liu, Qianqian & Liu, Xiaofeng, 2017. "The spatial differentiation of the coupling relationship between urbanization and the eco-environment in countries globally: A comprehensive assessment," Ecological Modelling, Elsevier, vol. 360(C), pages 313-327.
    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. Mingjing Xu & Qiang Feng & Shurong Zhang & Meng Lv & Baoling Duan, 2023. "Ecosystem Services Supply–Demand Matching and Its Driving Factors: A Case Study of the Shanxi Section of the Yellow River Basin, China," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    2. Pei-Pei Jiang & Yuan Wang & Jin Luo & Lin Zhu & Rui Shi & Song Hu & Xiaodong Zhu, 2023. "Measuring static and dynamic industrial eco-efficiency in China based on the MinDS–Malmquist–Luenberger model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 5241-5261, June.
    3. Bing Xia & Suocheng Dong & Yu Li & Zehong Li & Dongqi Sun & Wenbiao Zhang & Wenlong Li, 2021. "Evolution Characters and Influencing Factors of Regional Eco-Efficiency in a Developing Country: Evidence from Mongolia," IJERPH, MDPI, vol. 18(20), pages 1-20, October.
    4. Chong Huang & Kedong Yin & Zhe Liu & Tonggang Cao, 2021. "Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors," IJERPH, MDPI, vol. 18(6), pages 1-18, March.

    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. Yongyi Cheng & Tianyuan Shao & Huilin Lai & Manhong Shen & Yi Li, 2019. "Total-Factor Eco-Efficiency and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration, China," IJERPH, MDPI, vol. 16(20), pages 1-14, October.
    2. Tifang Ye & Xiuli Xiang & Xiangyu Ge & Keling Yang, 2022. "Research on Green Finance and Green Development Based Eco-Efficiency and Spatial Econometric Analysis," Sustainability, MDPI, vol. 14(5), pages 1-29, February.
    3. Linbo Zhang & Wenjing Xiang & Dongsheng Shi & Tian Liang & Xi Xiong & Shuyao Wu & Wentao Zhang & Duogui Yang, 2023. "Impact of Green Development Mechanism Innovation on Total-Factor Environmental Efficiency: A Quasi-Natural Experiment Based on National Pilot Cities," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    4. 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.
    5. 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.
    6. Defeng Zheng & Shuai Hao & Caizhi Sun & Leting Lyu, 2019. "Spatial Correlation and Convergence Analysis of Eco-Efficiency in China," Sustainability, MDPI, vol. 11(9), pages 1-16, April.
    7. Li Yue & Dan Xue & Muhammad Umar Draz & Fayyaz Ahmad & Jiaojiao Li & Farrukh Shahzad & Shahid Ali, 2020. "The Double-Edged Sword of Urbanization and Its Nexus with Eco-Efficiency in China," IJERPH, MDPI, vol. 17(2), pages 1-20, January.
    8. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    9. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    10. Xiao Zhang & Di Wang, 2023. "Beyond the Ecological Boundary: A Quasi-Natural Experiment on the Impact of National Marine Parks on Eco-Efficiency in Coastal Cities," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    11. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    12. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    13. Jo, Ah-Hyun & Chang, Young-Tae, 2023. "The effect of airport efficiency on air traffic, using DEA and multilateral resistance terms gravity models," Journal of Air Transport Management, Elsevier, vol. 108(C).
    14. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    15. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    16. 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.
    17. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    18. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    19. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    20. Chia-Nan Wang & Jen-Der Day & Nguyen Thi Kim Lien & Luu Quoc Chien, 2018. "Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam," Sustainability, MDPI, vol. 10(8), pages 1-17, 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:jijerp:v:17:y:2020:i:20:p:7510-:d:428572. 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.