IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3801-d1073771.html
   My bibliography  Save this article

The Impact of Technology Innovation on Urban Land Intensive Use in China: Evidence from 284 Cities in China

Author

Listed:
  • Yu Wang

    (School of Accounting, Harbin University of Commerce, Harbin 150028, China)

  • Lin Zhang

    (School of Accounting, Harbin University of Commerce, Harbin 150028, China)

Abstract

How to improve the level of urban land intensive use (ULIU) has been of wide concern to academic circles. Technology innovation, as the internal driving force of economic development, has an important impact on ULIU. To clarify the impacts of technology innovation on ULIU, this study measures the ULIU level index of China from 2006 to 2019 from four dimensions: the input-output level of economic efficiency, the carrying capacity of ecological environment, the harmony of the man-land relationship and the rationality of relationships between regions. On this basis, as there are different production technologies and land use technologies between cities, the differences of ULIU in different regions are analysed. Using the spatial econometric model, this study empirically analyzes the impact of technology innovation on ULIU. In addition, considering the differences in geographical distribution, natural resource endowment and technological type, this study analyzes the heterogeneous impact of technology innovation on ULIU. The main conclusions are as follows: (1) The level of ULIU and technology innovation in China is increasing year by year. The level of ULIU and technology innovation in the eastern region is higher than that in the central and western regions. (2) From the spatial perspective, ULIU has a significant positive spatial spillover effect. (3) On the whole, technology innovation significantly improves the level of ULIU. (4) The impact of technology innovation in different regions, different types of cities and different types of technologies on ULIU is heterogeneous. Our results not only enrich the research on the relationship between technology innovation and ULIU, but also provide a reference for the formulation of relevant policies.

Suggested Citation

  • Yu Wang & Lin Zhang, 2023. "The Impact of Technology Innovation on Urban Land Intensive Use in China: Evidence from 284 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3801-:d:1073771
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3801/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3801/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Zhu, Xinhua & Li, Yan & Zhang, Peifeng & Wei, Yigang & Zheng, Xuyang & Xie, Lingling, 2019. "Temporal–spatial characteristics of urban land use efficiency of China’s 35mega cities based on DEA: Decomposing technology and scale efficiency," Land Use Policy, Elsevier, vol. 88(C).
    3. Zhang, Wenxi & Wang, Bo & Wang, Jian & Wu, Qun & Wei, Yehua Dennis, 2022. "How does industrial agglomeration affect urban land use efficiency? A spatial analysis of Chinese cities," Land Use Policy, Elsevier, vol. 119(C).
    4. Qamri, Ghulam Muhammad & Sheng, Bin & Adeel-Farooq, Rana Muhammad & Alam, Gazi Mahabubul, 2022. "The criticality of FDI in Environmental Degradation through financial development and economic growth: Implications for promoting the green sector," Resources Policy, Elsevier, vol. 78(C).
    5. Pan, Xiongfeng & Li, Mengna & Wang, Mengyang & Chu, Junhui & Bo, Hongguang, 2020. "The effects of outward foreign direct investment and reverse technology spillover on China's carbon productivity," Energy Policy, Elsevier, vol. 145(C).
    6. Haiou Yang & Wenbo Chen & Zhaofeng Liang, 2017. "Impact of Land Use on PM 2.5 Pollution in a Representative City of Middle China," IJERPH, MDPI, vol. 14(5), pages 1-14, April.
    7. Kuang, Bing & Lu, Xinhai & Zhou, Min & Chen, Danling, 2020. "Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    8. Chen Zeng & Zhe Zhao & Cheng Wen & Jing Yang & Tianyu Lv, 2020. "Effect of Complex Road Networks on Intensive Land Use in China’s Beijing-Tianjin-Hebei Urban Agglomeration," Land, MDPI, vol. 9(12), pages 1-19, December.
    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. Zhang, Pengyan & Yang, Dan & Qin, Mingzhou & Jing, Wenlong, 2020. "Spatial heterogeneity analysis and driving forces exploring of built-up land development intensity in Chinese prefecture-level cities and implications for future Urban Land intensive use," Land Use Policy, Elsevier, vol. 99(C).
    11. Lin, Boqiang & Ma, Ruiyang, 2022. "Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. Xinhai Lu & Zhenxing Shi & Jia Li & Junhao Dong & Mingjie Song & Jiao Hou, 2022. "Research on the Impact of Factor Flow on Urban Land Use Efficiency from the Perspective of Urbanization," Land, MDPI, vol. 11(3), pages 1-17, March.
    13. Fei, Rilong & Lin, Ziyi & Chunga, Joseph, 2021. "How land transfer affects agricultural land use efficiency: Evidence from China’s agricultural sector," Land Use Policy, Elsevier, vol. 103(C).
    14. Jingyi Wang & Kaisi Sun & Jiupai Ni & Deti Xie, 2020. "Evaluation and Factor Analysis of the Intensive Use of Urban Land Based on Technical Efficiency Measurement—A Case Study of 38 Districts and Counties in Chongqing, China," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
    15. Anderson, Dennis, 1990. "Investment and economic growth," World Development, Elsevier, vol. 18(8), pages 1057-1079, August.
    16. Chengkun Huang & Feiyang Lin & Deping Chu & Lanlan Wang & Jiawei Liao & Junqian Wu, 2021. "Coupling Relationship and Interactive Response between Intensive Land Use and Tourism Industry Development in China’s Major Tourist Cities," Land, MDPI, vol. 10(7), pages 1-17, July.
    17. Wang, Jing & Lin, Yifan & Glendinning, Anthony & Xu, Yueqing, 2018. "Land-use changes and land policies evolution in China’s urbanization processes," Land Use Policy, Elsevier, vol. 75(C), pages 375-387.
    18. Qunxi Gong & Gengxuan Guo & Sipan Li & Xuedong Liang, 2021. "Examining the Coupling Coordinated Relationship between Urban Industrial Co-Agglomeration and Intensive Land Use," Land, MDPI, vol. 10(5), pages 1-12, May.
    19. Wu, Ning & Liu, ZuanKuo, 2021. "Higher education development, technological innovation and industrial structure upgrade," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    20. Liu, Jingming & Hou, Xianhui & Wang, Zhanqi & Shen, Yue, 2021. "Study the effect of industrial structure optimization on urban land-use efficiency in China," Land Use Policy, Elsevier, vol. 105(C).
    21. Basso, Matteo, 2019. "Land-use changes triggered by the expansion of wine-growing areas: A study on the Municipalities in the Prosecco’s production zone (Italy)," Land Use Policy, Elsevier, vol. 83(C), pages 390-402.
    22. Xu, Weiyi & Jin, Xiaobin & Liu, Jing & Zhou, Yinkang, 2021. "Analysis of influencing factors of cultivated land fragmentation based on hierarchical linear model: A case study of Jiangsu Province, China," Land Use Policy, Elsevier, vol. 101(C).
    23. 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).
    24. Yang, Haochang & Li, Lianshui & Liu, Yaobin, 2022. "The effect of manufacturing intelligence on green innovation performance in China," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    25. Du, Kerui & Li, Pengzhen & Yan, Zheming, 2019. "Do green technology innovations contribute to carbon dioxide emission reduction? Empirical evidence from patent data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 297-303.
    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. 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.
    2. Sijia Li & Meichen Fu & Yi Tian & Yuqing Xiong & Cankun Wei, 2022. "Relationship between Urban Land Use Efficiency and Economic Development Level in the Beijing–Tianjin–Hebei Region," Land, MDPI, vol. 11(7), pages 1-18, June.
    3. Zhang, Han & Zheng, Jinhui & Hunjra, Ahmed Imran & Zhao, Shikuan & Bouri, Elie, 2024. "How does urban land use efficiency improve resource and environment carrying capacity?," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    4. Haiyang Qiu & Xin Li & Long Zhang, 2023. "Influential Effect and Mechanism of Digital Finance on Urban Land Use Efficiency in China," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    5. Hangang Hu & Lisha Pan & Xin Jing & Guan Li & Yuefei Zhuo & Zhongguo Xu & Yang Chen & Xueqi Wang, 2022. "The Spatiotemporal Non-Stationary Effect of Industrial Agglomeration on Urban Land Use Efficiency: A Case Study of Yangtze River Delta, China," Land, MDPI, vol. 11(5), pages 1-27, May.
    6. Liu Yang & Bingyang Han & Zhili Ma & Ting Wang & Yingchao Lin, 2022. "Analysis of the Urban Land Use Efficiency in the New-Type Urbanization Process of China’s Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(13), pages 1-22, July.
    7. Kun Ge & Shan Zou & Xinhai Lu & Shangan Ke & Danling Chen & Zhangsheng Liu, 2022. "Dynamic Evolution and the Mechanism behind the Coupling Coordination Relationship between Industrial Integration and Urban Land-Use Efficiency: A Case Study of the Yangtze River Economic Zone in China," Land, MDPI, vol. 11(2), pages 1-22, February.
    8. Yi, Zhang & Zhou, Wenwu & Razzaq, Asif & Yang, Yao, 2023. "Land resource management and sustainable development: Evidence from China's regional data," Resources Policy, Elsevier, vol. 84(C).
    9. Ning Xu & Desen Zhao & Wenjie Zhang & He Zhang & Wanxu Chen & Min Ji & Ming Liu, 2022. "Innovation-Driven Development and Urban Land Low-Carbon Use Efficiency: A Policy Assessment from China," Land, MDPI, vol. 11(10), pages 1-21, September.
    10. Di Zhu & Yinghong Wang & Shangui Peng & Fenglin Zhang, 2022. "Influence Mechanism of Polycentric Spatial Structure on Urban Land Use Efficiency: A Moderated Mediation Model," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    11. Xinping Li & Qiongxia Qin & Yongliang Yang, 2023. "The Impact of Green Innovation on Carbon Emissions: Evidence from the Construction Sector in China," Energies, MDPI, vol. 16(11), pages 1-23, June.
    12. Chengkun Huang & Feiyang Lin & Deping Chu & Lanlan Wang & Jiawei Liao & Junqian Wu, 2021. "Coupling Relationship and Interactive Response between Intensive Land Use and Tourism Industry Development in China’s Major Tourist Cities," Land, MDPI, vol. 10(7), pages 1-17, July.
    13. Lili Guo & Yuting Song & Mengqian Tang & Jinyang Tang & Bright Senyo Dogbe & Mengying Su & Houjian Li, 2022. "Assessing the Relationship among Land Transfer, Fertilizer Usage, and PM 2.5 Pollution: Evidence from Rural China," IJERPH, MDPI, vol. 19(14), pages 1-18, July.
    14. Shang, Hua & Jiang, Li & Pan, Xianyou & Pan, Xiongfeng, 2022. "Green technology innovation spillover effect and urban eco-efficiency convergence: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 114(C).
    15. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    16. Lin, Boqiang & Ullah, Sami, 2023. "Towards the goal of going green: Do green growth and innovation matter for environmental sustainability in Pakistan," Energy, Elsevier, vol. 285(C).
    17. Shuting Liu & Junsong Jia & Hanzhi Huang & Dilan Chen & Yexi Zhong & Yangming Zhou, 2023. "China’s CO 2 Emissions: A Thorough Analysis of Spatiotemporal Characteristics and Sustainable Policy from the Agricultural Land-Use Perspective during 1995–2020," Land, MDPI, vol. 12(6), pages 1-20, June.
    18. Cai, Chunlin & Li, Ning, 2023. "The threshold effect of export sophistication on natural resources-trade diversification nexus," Resources Policy, Elsevier, vol. 86(PA).
    19. Lu, Zhou & Mahalik, Mantu Kumar & Mahalik, Hrushikesh & Zhao, Rui, 2022. "The moderating effects of democracy and technology adoption on the relationship between trade liberalisation and carbon emissions," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    20. Chris Belmert Milindi & Roula Inglesi-Lotz, 2023. "Impact of technological progress on carbon emissions in different country income groups," Energy & Environment, , vol. 34(5), pages 1348-1382, 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:jsusta:v:15:y:2023:i:4:p:3801-:d:1073771. 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.