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Correlation Effects, Driving Forces and Evolutionary Paths of Cross-Industry Transfer of Energy Consumption in China: A New Analytical Framework

Author

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  • Yufan Liang

    (School of Business, Macau University of Science and Technology, Macau 999078, China)

  • Yu Song

    (School of Business, Macau University of Science and Technology, Macau 999078, China
    Institute of Development Economics, Macau University of Science and Technology, Macau 999078, China)

  • Zuxu Chen

    (The Institute for Sustainable Development, Macau University of Science and Technology, Macau 999078, China)

Abstract

This paper constructs a modified hypothesis extraction method (MHEM)–structural decomposition analysis (SDA)–structural path decomposition (SPD) analytical framework and employs the 2018–2022 Chinese input–output tables to discuss sectoral consumption correlations, driving forces of consumption, and the transmission paths of carbon energy (CE), oil and gas energy (OGE) and electric energy (EE). The results of the study indicate that energy-exporting sectors are primarily energy production or conversion industries, while energy-importing sectors are mainly in the construction sector. China’s energy consumption has shown consistent year-on-year growth, with the primary driving force being the intensity of energy consumption and the secondary factor being per capita demand. The consumption of all three types of energy is primarily directed toward domestic consumption and capital formation. Regarding energy consumption transmission paths, the first-order path with the largest overall impact on CE is “electricity, gas, and water supply sector → domestic consumption”, while higher-order paths are primarily subpaths of “electricity, gas, and water supply sector → capital formation”. For OGE, the main supply and transfer path is “coke, refined petroleum, and nuclear fuel sector → domestic consumption”, along with its subpaths. In contrast, EE transmission is more balanced, with a high demand for electricity across all sectors.

Suggested Citation

  • Yufan Liang & Yu Song & Zuxu Chen, 2025. "Correlation Effects, Driving Forces and Evolutionary Paths of Cross-Industry Transfer of Energy Consumption in China: A New Analytical Framework," Energies, MDPI, vol. 18(12), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:12:p:3128-:d:1678824
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    as
    1. Shen, Jinlong & Zhang, Yu & Chen, Xiaonan, 2024. "Environmental regulation and energy consumption transition of rural residents: A case of China," Energy, Elsevier, vol. 310(C).
    2. Gui, Shusen & Mu, Hailin & Li, Nan, 2014. "Analysis of impact factors on China's CO2 emissions from the view of supply chain paths," Energy, Elsevier, vol. 74(C), pages 405-416.
    3. Zhang, Dongyang & Zhao, Mengjiao & Wang, Yizhi & Vigne, Samuel A. & Benkraiem, Ramzi, 2024. "Technological innovation and its influence on energy risk management: Unpacking China’s energy consumption structure optimisation amidst climate change," Energy Economics, Elsevier, vol. 131(C).
    4. Huang, Weiping & Das, Ghansham & Dilanchiev, Azer & Giyasova, Zeynab & Gu, Mangi, 2024. "Role of multiple energy sources under carbon neturality goals, income and energy consumption in transition economies: A joint case study between China and Uzbekistan," Energy, Elsevier, vol. 309(C).
    5. D. Zhang & M. Zhao & Y. Wang & S. Vigne & R. Benkraiem, 2024. "Technological innovation and its influence on energy risk management: Unpacking China’s energy consumption structure optimisation amidst climate change," Post-Print hal-04864387, HAL.
    6. Zeng, Sheng & Su, Bin & Zhang, Minglong & Gao, Yuan & Liu, Jun & Luo, Song & Tao, Qingmei, 2021. "Analysis and forecast of China's energy consumption structure," Energy Policy, Elsevier, vol. 159(C).
    7. Zheng, Jiajia & Dang, Yongjie & Assad, Ullah, 2024. "Household energy consumption, energy efficiency, and household income–Evidence from China," Applied Energy, Elsevier, vol. 353(PA).
    8. Wang, Yong & Sun, Lang & Yang, Rui & He, Wenao & Tang, Yanbing & Zhang, Zejia & Wang, Yunhui & Sapnken, Flavian Emmanuel, 2023. "A novel structure adaptive fractional derivative grey model and its application in energy consumption prediction," Energy, Elsevier, vol. 282(C).
    9. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    10. Lan, Jun & Malik, Arunima & Lenzen, Manfred & McBain, Darian & Kanemoto, Keiichiro, 2016. "A structural decomposition analysis of global energy footprints," Applied Energy, Elsevier, vol. 163(C), pages 436-451.
    11. Muhammad Azam & Liu Liu & Najid Ahmad, 2021. "Impact of institutional quality on environment and energy consumption: evidence from developing world," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(2), pages 1646-1667, February.
    12. Guo, Shan & Zheng, Shupeng & Hu, Yunhao & Hong, Jingke & Wu, Xiaofang & Tang, Miaohan, 2019. "Embodied energy use in the global construction industry," Applied Energy, Elsevier, vol. 256(C).
    13. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    14. Shinwari, Riazullah & Wang, Yangjie & Gozgor, Giray & Mousavi, Mahdi, 2024. "Does FDI affect energy consumption in the belt and road initiative economies? The role of green technologies," Energy Economics, Elsevier, vol. 132(C).
    15. Anne Owen & Richard Wood & John Barrett & Andrew Evans, 2016. "Explaining value chain differences in MRIO databases through structural path decomposition," Economic Systems Research, Taylor & Francis Journals, vol. 28(2), pages 243-272, June.
    16. Wu, Liangpeng & Xu, Chengzhen & Zhu, Qingyuan & Zhou, Dequn, 2024. "Multiple energy price distortions and improvement of potential energy consumption structure in the energy transition," Applied Energy, Elsevier, vol. 362(C).
    17. Fu, Rao & Jin, Gui & Chen, Jinyue & Ye, Yuyao, 2021. "The effects of poverty alleviation investment on carbon emissions in China based on the multiregional input–output model," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
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