IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i10p1703-d930905.html
   My bibliography  Save this article

Industrial Structure Optimization of Wuhan Urban Agglomeration Based on TFP and Industrial Spatial Linkages

Author

Listed:
  • Yan Yu

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Xinxin Gao

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Wenqing Meng

    (Xiangyang Urban Planning and Design Institute Co., Ltd., Xiangyang 441002, China)

  • Yujia He

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Chenhe Zhang

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China)

Abstract

As a complex symbiosis, a reasonable industrial structure of each symbiotic unit within an urban agglomeration (UA) is crucial to the sustainable development of the regional economy. In an urban agglomeration (UA), a reasonable industrial structure is crucial to the sustainable development of the regional economy. This paper comprehensively considers the industrial total factor productivity (TFP) and the industrial spatial linkages between cities to adjust the industrial structure. Malmquist index (MI) is introduced to assess the industry performance in this paper to judge the development status of the industry. The calculation method for identifying industrial structure similarity is improved by combining it with industrial spatial linkages, to accurately reflect the degree of industrial structure convergence in the UA and to recognize which cities need industrial adjustment. The results from a case study on Wuhan UA showed that the method proposed in this paper can provide objective and specific suggestions for every industrial sector in each member city of the UA on a regional scale, so that the city can give priority to the developing industry with a certain foundation on the premise of avoiding the low resource allocation efficiency.

Suggested Citation

  • Yan Yu & Xinxin Gao & Wenqing Meng & Yujia He & Chenhe Zhang, 2022. "Industrial Structure Optimization of Wuhan Urban Agglomeration Based on TFP and Industrial Spatial Linkages," Land, MDPI, vol. 11(10), pages 1-13, September.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1703-:d:930905
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/10/1703/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/10/1703/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dan Zheng & Tatsuaki Kuroda, 2013. "The impact of economic policy on industrial specialization and regional concentration of China’s high-tech industries," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(3), pages 771-790, June.
    2. Joshua Drucker, 2011. "Regional Industrial Structure Concentration in the United States: Trends and Implications," Economic Geography, Taylor & Francis Journals, vol. 87(4), pages 421-452, October.
    3. Fracasso, Andrea, 2014. "A gravity model of virtual water trade," Ecological Economics, Elsevier, vol. 108(C), pages 215-228.
    4. Song, Malin & Zheng, Wanping & Wang, Shuhong, 2017. "Measuring green technology progress in large-scale thermoelectric enterprises based on Malmquist–Luenberger life cycle assessment," Resources, Conservation & Recycling, Elsevier, vol. 122(C), pages 261-269.
    5. Yan Yu & Qianwen Han & Wenwu Tang & Yanbin Yuan & Yan Tong, 2018. "Exploration of the Industrial Spatial Linkages in Urban Agglomerations: A Case of Urban Agglomeration in the Middle Reaches of the Yangtze River, China," Sustainability, MDPI, vol. 10(5), pages 1-18, May.
    6. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
    7. Peneder, Michael, 2003. "Industrial structure and aggregate growth," Structural Change and Economic Dynamics, Elsevier, vol. 14(4), pages 427-448, December.
    8. Joshua Drucker, 2011. "Regional Industrial Structure Concentration in the United States: Trends and Implications," Economic Geography, Clark University, vol. 87(4), pages 421-452, October.
    9. Cheng, Zhonghua & Li, Lianshui & Liu, Jun, 2018. "Industrial structure, technical progress and carbon intensity in China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2935-2946.
    10. Zhang, Chunhong & Liu, Haiying & Bressers, Hans Th.A. & Buchanan, Karen S., 2011. "Productivity growth and environmental regulations - accounting for undesirable outputs: Analysis of China's thirty provincial regions using the Malmquist–Luenberger index," Ecological Economics, Elsevier, vol. 70(12), pages 2369-2379.
    11. Meng Wang & Yaoqiu Kuang & Ningsheng Huang, 2015. "Sustainable Urban External Service Function Development for Building the International Megalopolis in the Pearl River Delta, China," Sustainability, MDPI, vol. 7(10), pages 1-26, September.
    12. HE Canfei & ZHU Shengjun, 2007. "Economic Transition and Industrial Restructuring in China: Structural Convergence or Divergence?," Post-Communist Economies, Taylor & Francis Journals, vol. 19(3), pages 317-342.
    13. Qipeng Sun & Sijie Wang & Kaiqi Zhang & Fei Ma & Xiaozhuang Guo & Tingzhen Li, 2019. "Spatial Pattern of Urban System Based on Gravity Model and Whole Network Analysis in Eight Urban Agglomerations of China," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-17, August.
    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. Hanchu Liu & Jie Fan & Kan Zhou, 2018. "An Empirical Study on Spatial–Temporal Dynamics and Influencing Factors of Tea Production in China," Sustainability, MDPI, vol. 10(9), pages 1-15, August.
    2. Li, Li & Hong, Xuefei & Peng, Ke, 2019. "A spatial panel analysis of carbon emissions, economic growth and high-technology industry in China," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 83-92.
    3. Lei Nie & Yuanyuan Wang & Yanrui Wu, 2024. "Service Sector Agglomeration and Industrial Structure Optimization: Evidence from China’s Resource-Based Cities," Economics Discussion / Working Papers 24-04, The University of Western Australia, Department of Economics.
    4. Saheum Hong & Yu Xiao, 2016. "The Influence of Multiple Specializations on Economic Performance in U.S. Metropolitan Areas," Sustainability, MDPI, vol. 8(9), pages 1-16, September.
    5. Wolfgang Dauth & Michaela Fuchs & Anne Otto, 2018. "Long‐run processes of geographical concentration and dispersion: Evidence from Germany," Papers in Regional Science, Wiley Blackwell, vol. 97(3), pages 569-593, August.
    6. Lu, Lan & Yin, Shuiying & Wen, Fuying & Xu, Qingqing, 2023. "The spatial structure of labour force employment in China’s industries: Measurement and extraction," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 472-486.
    7. Lu, Xin-hai & Jiang, Xu & Gong, Meng-qi, 2020. "How land transfer marketization influence on green total factor productivity from the approach of industrial structure? Evidence from China," Land Use Policy, Elsevier, vol. 95(C).
    8. Gefu Liang & Dajia Yu & Lifei Ke, 2021. "An Empirical Study on Dynamic Evolution of Industrial Structure and Green Economic Growth—Based on Data from China’s Underdeveloped Areas," Sustainability, MDPI, vol. 13(15), pages 1-16, July.
    9. You, Jiansheng & Hu, Jin & Jiang, Bing, 2024. "The correlation evolution and formation mechanism of energy ecological efficiency in China: A spatial network approach," Energy, Elsevier, vol. 313(C).
    10. Maier, Gunther & Trippl, Michaela, 2012. "The Pitfalls and Booby Traps of Cluster Policy," SRE-Discussion Papers 2012/01, WU Vienna University of Economics and Business.
    11. Elizabeth Mack & Yifan Zhang & Sergio Rey & Ross Maciejewski, 2014. "Spatio-temporal analysis of industrial composition with IVIID: an interactive visual analytics interface for industrial diversity," Journal of Geographical Systems, Springer, vol. 16(2), pages 183-209, April.
    12. Adiwan F. Aritenang, 2021. "The Importance of Agglomeration Economies and Technological Level on Local Economic Growth: the Case of Indonesia," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 544-563, June.
    13. Hervas Oliver,Jose Luis & Gonzalez,Gregorio & Caja,Pedro, 2014. "Clusters and industrial districts: where is the literature going? Identifying emerging sub-fields of research," INGENIO (CSIC-UPV) Working Paper Series 201409, INGENIO (CSIC-UPV).
    14. Zhao, Jun & Shahbaz, Muhammad & Dong, Kangyin, 2022. "How does energy poverty eradication promote green growth in China? The role of technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    15. Lin, Boqiang & Zhou, Yicheng, 2021. "How does vertical fiscal imbalance affect the upgrading of industrial structure? Empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    16. Zhou, Xiaoxiao & Pan, Zixuan & Shahbaz, Muhammad & Song, Malin, 2020. "Directed technological progress driven by diversified industrial structural change," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 112-129.
    17. Yang Liu & Yanlin Yang & Huihui Li & Kaiyang Zhong, 2022. "Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China’s Cities," IJERPH, MDPI, vol. 19(4), pages 1-23, February.
    18. Salvador Vivas-López & Francisco Puig & Victor Oltra & Miguel González-Loureiro, 2016. "Globalized Markets and Startup Dynamics in Mature Manufacturing Industries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 7(4), pages 947-962, December.
    19. Richard V. Adkisson & Comfort F. Ricketts, 2016. "Exploring the Redistribution of Manufacturing Employment Among the American States in the Face of Overall Declines in Employment," Economic Development Quarterly, , vol. 30(3), pages 215-231, August.
    20. Li, Kai & Qi, Shouzhou & Shi, Xunpeng, 2023. "Environmental policies and low-carbon industrial upgrading: Heterogenous effects among policies, sectors, and technologies in China," Technological Forecasting and Social Change, Elsevier, vol. 191(C).

    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:10:p:1703-:d:930905. 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.