IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i17p10729-d900437.html
   My bibliography  Save this article

Research on High-Quality Development Evaluation, Space–Time Characteristics and Driving Factors of China’s Construction Industry under Carbon Emission Constraints

Author

Listed:
  • Yan Wang

    (College of Architecture and Urban Planning, Guizhou University, Guiyang 550025, China)

  • Xi Wu

    (Shaanxi Provincial Department of Housing and Urban Rural Development, Xi’an 710004, China)

Abstract

Research on the regional difference characteristics and driving mechanisms of high-quality developmental evaluations of the construction industry under the constraint of carbon emissions has important practical significance for guiding the efficient development of the construction industry, alleviating the contradiction between economic and social development and resource conservation, low-carbon requirements in the process of rapid urbanization, and realizing regional coordinated development. Taking carbon emissions as unexpected output into the evaluation system of high-quality development of construction industry, this paper studies the spatial–temporal differentiation characteristics, dynamic trend evolution and its driving factors of high-quality development of China’s construction industry from 2006 to 2021 by using the SE-SBM model of unexpected output, GML index analysis and grey correlation model. The research results show that: (1) from 2006 to 2021, the high-quality development of the construction industry generally fluctuated in a sinusoidal function pattern, and the high-quality development level of the construction industry in China was improved as a whole. It is manifested in the coexistence of regional imbalance and spatial correlation. High-efficiency provinces are concentrated in the eastern coastal areas, forming an obvious cluster effect; however, the radiation-driving effect is weak. (2) The regional difference in technological scale change is the largest, which is the main reason for the difference in regional total factor production growth rate; the contribution of technological progress to the difference in total factor growth rate is also relatively large. Generally speaking, technological factors are the key to reducing the difference of total factor growth rate between regions. (3) Urbanization level, carbon emission constraints, government regulation, scientific and technological R & D investment and industrial structure upgrading are the main driving factors that affect the spatiotemporal differentiation and evolution of high-quality development of the construction industry.

Suggested Citation

  • Yan Wang & Xi Wu, 2022. "Research on High-Quality Development Evaluation, Space–Time Characteristics and Driving Factors of China’s Construction Industry under Carbon Emission Constraints," Sustainability, MDPI, vol. 14(17), pages 1-19, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10729-:d:900437
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/17/10729/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/17/10729/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Na Lu & Shuyi Feng & Ziming Liu & Weidong Wang & Hualiang Lu & Miao Wang, 2020. "The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    2. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    3. Yue Zheng & Jinpei Ou & Guangzhao Chen & Xinxin Wu & Xiaoping Liu, 2022. "Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England," IJERPH, MDPI, vol. 19(10), pages 1-22, May.
    4. Roni Rinne & Hüseyin Emre Ilgın & Markku Karjalainen, 2022. "Comparative Study on Life-Cycle Assessment and Carbon Footprint of Hybrid, Concrete and Timber Apartment Buildings in Finland," IJERPH, MDPI, vol. 19(2), pages 1-24, January.
    5. Qingye Han & Junjie Chang & Guiwen Liu & Heng Zhang, 2022. "The Carbon Emission Assessment of a Building with Different Prefabrication Rates in the Construction Stage," IJERPH, MDPI, vol. 19(4), pages 1-17, February.
    6. E. Grifell-Tatjé & C. Lovell, 1999. "A generalized Malmquist productivity index," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 7(1), pages 81-101, June.
    7. Li Zhang & Laura Balangé & Kathrin Braun & Roberta Di Bari & Rafael Horn & Deniz Hos & Cordula Kropp & Philip Leistner & Volker Schwieger, 2020. "Quality as Driver for Sustainable Construction—Holistic Quality Model and Assessment," Sustainability, MDPI, vol. 12(19), pages 1-23, September.
    8. 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.
    9. Yi Gao & Gaosheng Yang & Qiuhao Xie, 2020. "Spatial-Temporal Evolution and Driving Factors of Green Building Development in China," Sustainability, MDPI, vol. 12(7), pages 1-21, April.
    10. 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.
    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. Sun, Yu & Yang, Feng & Wang, Dawei & Ang, Sheng, 2023. "Efficiency evaluation for higher education institutions in China considering unbalanced regional development: A meta-frontier Super-SBM model," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    2. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    3. Yongyi Cheng & Liheng Lu & Tianyuan Shao & Manhong Shen & Laiqun Jin, 2018. "Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach," IJERPH, MDPI, vol. 15(12), pages 1-23, December.
    4. 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.
    5. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    6. Shuai Wang & Cunyi Yang & Zhenghui Li, 2021. "Spatio-Temporal Evolution Characteristics and Spatial Interaction Spillover Effects of New-Urbanization and Green Land Utilization Efficiency," Land, MDPI, vol. 10(10), pages 1-26, October.
    7. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.
    8. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    9. Feng Dong & Chang Qin & Xiaoyun Zhang & Xu Zhao & Yuling Pan & Yujin Gao & Jiao Zhu & Yangfan Li, 2021. "Towards Carbon Neutrality: The Impact of Renewable Energy Development on Carbon Emission Efficiency," IJERPH, MDPI, vol. 18(24), pages 1-23, December.
    10. Sheng Xu & Wenran Pan & Demei Wen, 2023. "Do Carbon Emission Trading Schemes Promote the Green Transition of Enterprises? Evidence from China," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    11. Dan Xue & Xianzong Li & Fayyaz Ahmad & Nabila Abid & Zulqarnain Mushtaq, 2022. "Exploring Tourism Efficiency and Its Drivers to Understand the Backwardness of the Tourism Industry in Gansu, China," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    12. Zeng, Juying & Škare, Marinko & Lafont, Juan, 2021. "The co-integration identification of green innovation efficiency in Yangtze River Delta region," Journal of Business Research, Elsevier, vol. 134(C), pages 252-262.
    13. Meng, Conghui & Du, Xiaoyun & Zhu, Mengcheng & Ren, Yitian & Fang, Kai, 2023. "The static and dynamic carbon emission efficiency of transport industry in China," Energy, Elsevier, vol. 274(C).
    14. Hepei Zhang & Zhangbao Zhong, 2022. "How Does Environmental Regulation Affect the Green Growth of China’s Citrus Industry? The Mediating Role of Technological Innovation," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    15. Huijun Li & Jianhua Zhang & Edward Osei & Mark Yu, 2018. "Sustainable Development of China’s Industrial Economy: An Empirical Study of the Period 2001–2011," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    16. 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.
    17. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    18. 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).
    19. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    20. 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.

    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:14:y:2022:i:17:p:10729-:d:900437. 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.