IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i11p1272-d683675.html
   My bibliography  Save this article

Analysis of Spatial–Temporal Characteristics of Industrial Land Supply Scale in Relation to Industrial Structure in China

Author

Listed:
  • Peichao Dai

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Ruxu Sheng

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Zhongzhen Miao

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

  • Zanxu Chen

    (School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Yuan Zhou

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

Abstract

Taking China’s industrial land transfer data as the data source, this study quantitatively analyzes the transfer structure and spatial distribution of China’s industrial land from 2010 to 2019. By constructing the information entropy and the equilibrium degree model of industrial land-use structure, this study evaluates the transfer characteristics of industrial land of different functional types in various provinces of China, analyzes the scale advantages of various types of transferred industrial land by using the land transfer scale advantage index, and summarizes the spatial distribution characteristics of different types of industrial land transfer in China through the spatial center of gravity analysis and cold/hot spot regional distribution mapping. The following results were obtained. (1) There are significant differences in the transfer scale of industrial land among provinces in China. The transfer scale of Eastern and Central China is large, whereas that of Western China is small. (2) From the perspective of land-use structure, the transfer scale of industrial land in the central and western regions is more balanced than that in the east. (3) From the gravity center distribution of the standard deviation ellipse, the land transfer direction of the energy industry, and the mining industry, and other types of industries is more significant than that of the culture and sports hygiene industries, modern manufacturing industry, and high-tech industry. (4) From the analysis of cold and hot spots, the mining industry, the energy industry, and other types of industries in the western region with rich mineral resources are the hot spots of industrial land transfer, and the southeast coast is the cold spot; the eastern coastal area is a hot area for land transfer of modern manufacturing, the high-tech industry, and the culture and sports hygiene industries. The results reveal the regional differences and spatial distribution characteristics of industrial transfer in China and provide a reference for authorities to formulate industrial planning and industrial land collection, storage, and transfer plans.

Suggested Citation

  • Peichao Dai & Ruxu Sheng & Zhongzhen Miao & Zanxu Chen & Yuan Zhou, 2021. "Analysis of Spatial–Temporal Characteristics of Industrial Land Supply Scale in Relation to Industrial Structure in China," Land, MDPI, vol. 10(11), pages 1-18, November.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:11:p:1272-:d:683675
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/11/1272/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/11/1272/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. L. Rachel Ngai & Christopher A. Pissarides, 2007. "Structural Change in a Multisector Model of Growth," American Economic Review, American Economic Association, vol. 97(1), pages 429-443, March.
    2. Yuan Zhou & Heng Lin & Yufei Liu & Wei Ding, 2019. "A novel method to identify emerging technologies using a semi-supervised topic clustering model: a case of 3D printing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 167-185, July.
    3. López, Fernando & Matilla-García, Mariano & Mur, Jesús & Marín, Manuel Ruiz, 2010. "A non-parametric spatial independence test using symbolic entropy," Regional Science and Urban Economics, Elsevier, vol. 40(2-3), pages 106-115, May.
    4. Lei Luo & Zhenhua Zheng & Jing Luo & Yuqiu Jia & Qi Zhang & Chun Wu & Yifeng Zhang & Jia Sun, 2020. "Spatial Agglomeration of Manufacturing in the Wuhan Metropolitan Area: An Analysis of Sectoral Patterns and Determinants," Sustainability, MDPI, vol. 12(19), pages 1-23, September.
    5. Libang Ma & Xijuan Cui & Yao Yao & Shichun Liu, 2021. "Gradient Difference of Structure of Rural Construction Land in Loess Hilly Region: A Case Study of Yuzhong County, Gansu Province, China," Land, MDPI, vol. 10(4), pages 1-17, March.
    6. Yani Lai & Ke Chen & Jinming Zhang & Feihu Liu, 2020. "Transformation of Industrial Land in Urban Renewal in Shenzhen, China," Land, MDPI, vol. 9(10), pages 1-22, October.
    7. Peters, Michael & Schneider, Malte & Griesshaber, Tobias & Hoffmann, Volker H., 2012. "The impact of technology-push and demand-pull policies on technical change – Does the locus of policies matter?," Research Policy, Elsevier, vol. 41(8), pages 1296-1308.
    8. Baochao Li & Xiaoshu Cao & Jianbin Xu & Wulin Wang & Shishu Ouyang & Dan Liu, 2021. "Spatial–Temporal Pattern and Influence Factors of Land Used for Transportation at the County Level since the Implementation of the Reform and Opening-Up Policy in China," Land, MDPI, vol. 10(8), pages 1-17, August.
    9. Sidong Zhao & Yiran Yan & Jing Han, 2021. "Industrial Land Change in Chinese Silk Road Cities and Its Influence on Environments," Land, MDPI, vol. 10(8), pages 1-30, July.
    10. Mengchao Yao & Yihua Zhang, 2021. "Evaluation and Optimization of Urban Land-Use Efficiency: A Case Study in Sichuan Province of China," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    11. Yuting, Yang & Guanghui, Jiang & Qiuyue, Zheng & Dingyang, Zhou & Yuling, Li, 2019. "Does the land use structure change conform to the evolution law of industrial structure? An empirical study of Anhui Province, China," Land Use Policy, Elsevier, vol. 81(C), pages 657-667.
    12. Wu, Yan & Heerink, Nico, 2016. "Foreign direct investment, fiscal decentralization and land conflicts in China," China Economic Review, Elsevier, vol. 38(C), pages 92-107.
    13. Jan Stentoft & Christopher Rajkumar, 2020. "The relevance of Industry 4.0 and its relationship with moving manufacturing out, back and staying at home," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2953-2973, May.
    14. Chen, Wei & Shen, Yue & Wang, Yanan & Wu, Qun, 2018. "How do industrial land price variations affect industrial diffusion? Evidence from a spatial analysis of China," Land Use Policy, Elsevier, vol. 71(C), pages 384-394.
    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. Jiaxin Guo & Zhenqi Hu & Yusheng Liang, 2022. "Causes and Countermeasures for the Failure of Mining Land Use Policy Reform: Practice Analysis from China," Land, MDPI, vol. 11(9), pages 1-19, August.
    2. 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.
    3. Yating Dai & Jian Cheng & Daolin Zhu, 2022. "Understanding the Impact of Land Supply Structure on Low Consumption: Empirical Evidence from China," Land, MDPI, vol. 11(4), pages 1-18, April.
    4. Longji Zeng & Yuandi Wang & Yajuan Deng, 2022. "How Land Transactions Affect Carbon Emissions: Evidence from China," Land, MDPI, vol. 11(5), pages 1-25, May.
    5. Congguo Zhang & Di Yao & Yanlin Zhen & Weiwei Li & Kerun Li, 2022. "Mismatched Relationship between Urban Industrial Land Consumption and Growth of Manufacturing: Evidence from the Yangtze River Delta," Land, MDPI, vol. 11(9), pages 1-35, August.
    6. Fei Xie & Shuaibing Zhang & Kaixu Zhao & Fengmei Quan, 2022. "Evolution Mode, Influencing Factors, and Socioeconomic Value of Urban Industrial Land Management in China," Land, MDPI, vol. 11(9), pages 1-33, September.

    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. Congguo Zhang & Di Yao & Yanlin Zhen & Weiwei Li & Kerun Li, 2022. "Mismatched Relationship between Urban Industrial Land Consumption and Growth of Manufacturing: Evidence from the Yangtze River Delta," Land, MDPI, vol. 11(9), pages 1-35, August.
    2. Jihong Li & Kaiming Li & Rongxu Qiu, 2022. "The Suburbanization and Revitalization of Industrial Land in Shanghai, China," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
    3. Qian Wang & Yanan Wang & Wei Chen & Xue Zhou & Minjuan Zhao, 2021. "Factors affecting industrial land use efficiency in China: analysis from government and land market," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10973-10993, July.
    4. Fei Xie & Shuaibing Zhang & Kaixu Zhao & Fengmei Quan, 2022. "Evolution Mode, Influencing Factors, and Socioeconomic Value of Urban Industrial Land Management in China," Land, MDPI, vol. 11(9), pages 1-33, September.
    5. Fei Bao & Zhenzhi Zhao, 2022. "“Takeover” and “Activation” Effects of National Strategies for Industrial Relocation—Based on the Perspective of Marketisation of Land Elements," Sustainability, MDPI, vol. 14(20), pages 1-23, October.
    6. Ngai, L. Rachel & Pissarides, Christopher A., 2009. "Welfare policy and the distribution of hours of work," LSE Research Online Documents on Economics 28698, London School of Economics and Political Science, LSE Library.
    7. Burda, Michael C. & Zessner-Spitzenberg, Leopold, 2024. "Greenhouse Gas Mitigation and Price-Driven Growth in a Solow-Swan Economy with an Environmental Limit," IZA Discussion Papers 16771, Institute of Labor Economics (IZA).
    8. Libo Zhang & Qian Du & Dequn Zhou, 2021. "Grid Parity Analysis of China’s Centralized Photovoltaic Generation under Multiple Uncertainties," Energies, MDPI, vol. 14(7), pages 1-19, March.
    9. Zilu Ma & Yaping Huang, 2024. "The Spatial Pattern and Influencing Factors of Urban Knowledge-Intensive Business Services: A Case Study of Wuhan Metropolitan Area, China," Sustainability, MDPI, vol. 16(3), pages 1-16, January.
    10. Dennis C. Hutschenreiter & Tommaso Santini & Eugenia Vella, 2022. "Automation and sectoral reallocation," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 335-362, May.
    11. Yi Li, 2020. "Internet Development and Structural Transformation: Evidence from China," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-8.
    12. Hille, Erik & Althammer, Wilhelm & Diederich, Henning, 2020. "Environmental regulation and innovation in renewable energy technologies: Does the policy instrument matter?," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    13. Andrew Foerster & Andreas Hornstein & Pierre-Daniel G. Sarte & Mark W. Watson, 2019. "Aggregate Implications of Changing Sectoral Trends," Working Paper 19-11, Federal Reserve Bank of Richmond.
    14. Storesletten, Kjetil & Zhao, Bo & Zilibotti, Fabrizio, 2020. "Business Cycle during Structural Change: Arthur Lewis’ Theory from a Neoclassical Perspective," CEPR Discussion Papers 14964, C.E.P.R. Discussion Papers.
    15. Ying Zhang & Yingli Huang, 2023. "Killing Two Birds with One Stone or Missing One of Them? The Synergistic Governance Effect of China’s Carbon Emissions Trading Scheme on Pollution Control and Carbon Emission Reduction," Sustainability, MDPI, vol. 15(13), pages 1-25, June.
    16. Herrendorf, Berthold & Rogerson, Richard & Valentinyi, Ákos, 2014. "Growth and Structural Transformation," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 6, pages 855-941, Elsevier.
    17. repec:zbw:rwirep:0005 is not listed on IDEAS
    18. Dalila Nicet-Chenaf & Eric Rougier, 2009. "Human capital and structural change: how do they interact with each others in growth," Post-Print hal-00798441, HAL.
    19. Simon Alder & Timo Boppart & Andreas Müller, 2022. "A Theory of Structural Change That Can Fit the Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(2), pages 160-206, April.
    20. Alonso-Carrera, Jaime & Raurich, Xavier, 2015. "Demand-based structural change and balanced economic growth," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 359-374.
    21. Paula Bustos & Juan Manuel Castro Vincenzi & Joan Monras & Jacopo Ponticelli, 2019. "Structural Transformation, Industrial Specialization, and Endogenous Growth," Working Papers wp2019_1906, CEMFI.

    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:10:y:2021:i:11:p:1272-:d:683675. 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.