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Regional efficiency disparities in China’s construction sector: A combination of multiregional input–output and data envelopment analyses

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  • Wen, Quan
  • Hong, Jingke
  • Liu, Guiwen
  • Xu, Pengpeng
  • Tang, Miaohan
  • Li, Zhongfu

Abstract

As a major contributor to the increasing adverse environmental impact worldwide, China’s construction industry faces major challenges in energy conservation. Improving energy utilization efficiency is an effective method for mitigating energy-intensive problems induced by this industry. Accordingly, this study combined a multiregional input–output model with data envelopment analysis to assess the energy efficiency of China’s construction industry at the provincial level. Results show that the majority of the provincial construction sectors in China are energy inefficient and the performance of energy efficiency is highly related to the level of regional economic development. Scale efficiency is comparatively high in the regional construction sectors, but technical aspects are lagging behind. Moreover, cross-regional energy allocation demonstrates higher efficiency than that of the energy structure. The inefficient utilization of unclean and clean energy can be attributed to the lack of required instruments that can facilitate clean production processes in the construction field. To solve these problems, this study presents corresponding governmental measures and market-driven strategies from the institutional, technical and management aspects. The findings of this study can provide a holistic understanding of the current efficiency status of the construction industry and help decision makers stratify regional energy conservation targets at the industrial level.

Suggested Citation

  • Wen, Quan & Hong, Jingke & Liu, Guiwen & Xu, Pengpeng & Tang, Miaohan & Li, Zhongfu, 2020. "Regional efficiency disparities in China’s construction sector: A combination of multiregional input–output and data envelopment analyses," Applied Energy, Elsevier, vol. 257(C).
    • Handle: RePEc:eee:appene:v:257:y:2020:i:c:s0306261919316514
    DOI: 10.1016/j.apenergy.2019.113964
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    as
    1. Feng, Chao & Wang, Miao, 2017. "The economy-wide energy efficiency in China’s regional building industry," Energy, Elsevier, vol. 141(C), pages 1869-1879.
    2. Zhang, Guanglu & Lin, Boqiang, 2018. "Impact of structure on unified efficiency for Chinese service sector—A two-stage analysis," Applied Energy, Elsevier, vol. 231(C), pages 876-886.
    3. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    4. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    5. Liu, Zhu & Geng, Yong & Lindner, Soeren & Zhao, Hongyan & Fujita, Tsuyoshi & Guan, Dabo, 2012. "Embodied energy use in China's industrial sectors," Energy Policy, Elsevier, vol. 49(C), pages 751-758.
    6. 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.
    7. Dixit, Manish K., 2017. "Life cycle embodied energy analysis of residential buildings: A review of literature to investigate embodied energy parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 390-413.
    8. Yuan, Jiahai & Xu, Yan & Zhang, Xingping & Hu, Zheng & Xu, Ming, 2014. "China's 2020 clean energy target: Consistency, pathways and policy implications," Energy Policy, Elsevier, vol. 65(C), pages 692-700.
    9. Yujiao Xian & Kexin Yang & Ke Wang & Yi-Ming Wei & Zhimin Huang, 2019. "Cost-environment efficiency analysis of construction industry in China: A materials balance approach," CEEP-BIT Working Papers 122, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Zhou, D.Q. & Wu, F. & Zhou, X. & Zhou, P., 2016. "Output-specific energy efficiency assessment: A data envelopment analysis approach," Applied Energy, Elsevier, vol. 177(C), pages 117-126.
    11. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    12. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    13. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, vol. 130(C), pages 617-631.
    14. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    15. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    16. Yang, Wen-Chi & Lee, Yuh-Ming & Hu, Jin-Li, 2016. "Urban sustainability assessment of Taiwan based on data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 341-353.
    17. Hong, Jingke & Shen, Qiping & Xue, Fan, 2016. "A multi-regional structural path analysis of the energy supply chain in China's construction industry," Energy Policy, Elsevier, vol. 92(C), pages 56-68.
    18. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.
    19. Hong, Jingke & Shen, Geoffrey Qiping & Guo, Shan & Xue, Fan & Zheng, Wei, 2016. "Energy use embodied in China׳s construction industry: A multi-regional input–output analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1303-1312.
    20. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    21. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2012. "A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs?," Energy Policy, Elsevier, vol. 46(C), pages 574-584.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    2. Quan Wen & Zhongfu Li & Yifeng Peng & Baorong Guo, 2020. "Assessing the Effectiveness of Building Information Modeling in Developing Green Buildings from a Lifecycle Perspective," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    3. Nourelfath, Mustapha & Lababidi, Haitham M.S. & Aldowaisan, Tariq, 2022. "Socio-economic impacts of strategic oil and gas megaprojects: A case study in Kuwait," International Journal of Production Economics, Elsevier, vol. 246(C).
    4. Jingke, Hong & Chenyu, Wang & Chang-Richards, Alice & Jingxiao, Zhang & Qiping, Geoffrey Shen & Bei, Qiao, 2022. "A spatiotemporal analysis of energy use pathways in the construction industry: A study of China," Energy, Elsevier, vol. 239(PC).
    5. Duan, Haiyan & Chen, Siyan & Song, Junnian, 2022. "Characterizing regional building energy consumption under joint climatic and socioeconomic impacts," Energy, Elsevier, vol. 245(C).
    6. Gongli Luo & Xiaotong Wang & Lu Wang & Yanlu Guo, 2021. "The Relationship between Environmental Regulations and Green Economic Efficiency: A Study Based on the Provinces in China," IJERPH, MDPI, vol. 18(3), pages 1-17, January.
    7. Avilés-Sacoto, Estefanía Caridad & Avilés-Sacoto, Sonia Valeria & Güemes-Castorena, David & Cook, Wade D., 2021. "Environmental performance evaluation: A state-level DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    8. Huang, He & Hong, Jingke & Wang, Xianzhu & Chang-Richards, Alice & Zhang, Jingxiao & Qiao, Bei, 2022. "A spatiotemporal analysis of the driving forces behind the energy interactions of the Chinese economy: Evidence from static and dynamic perspectives," Energy, Elsevier, vol. 239(PB).

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