IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v365y2024ics0306261924006287.html
   My bibliography  Save this article

Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities

Author

Listed:
  • Lin, Boqiang
  • Xu, Chongchong

Abstract

Industrial intelligence optimizes resource allocation and enhances productivity, but discussions on its potential to empower green growth are inadequate. Utilizing panel data for 279 Chinese cities from 2008 to 2019, this study investigates the effect of industrial intelligence on urban energy-environmental performance. The findings reveal that industrial intelligence enhances urban energy-environmental performance. Technological innovation, industrial agglomeration and labor upgrading constitute critical conduits for reaping such benefits. Heterogeneity analysis demonstrates that industrial intelligence has more pronounced effects in non-resource-based cities, non-old industrial base cities, big cities and megacities. Our findings impart valuable insights to guide policymaking for expediting China's industrial intelligence advancement and facilitating sustainable urban industrial development.

Suggested Citation

  • Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    • Handle: RePEc:eee:appene:v:365:y:2024:i:c:s0306261924006287
    DOI: 10.1016/j.apenergy.2024.123245
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924006287
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123245?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    2. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    3. Jiang, Zhengyu & Zhang, Xinyi & Zhao, Yingzhi & Li, Chengming & Wang, Zeyu, 2023. "The impact of urban digital transformation on resource sustainability: Evidence from a quasi-natural experiment in China," Resources Policy, Elsevier, vol. 85(PA).
    4. Korinek, Anton & Stiglitz, Joseph, 2021. "Artificial Intelligence, Globalization, and Strategies for Economic Development," CEPR Discussion Papers 15772, C.E.P.R. Discussion Papers.
    5. Joseph S. Shapiro & Reed Walker, 2018. "Why Is Pollution from US Manufacturing Declining? The Roles of Environmental Regulation, Productivity, and Trade," American Economic Review, American Economic Association, vol. 108(12), pages 3814-3854, December.
    6. Du, Zhili & Wang, Yao, 2022. "Does energy-saving and emission reduction policy affects carbon reduction performance? A quasi-experimental evidence in China," Applied Energy, Elsevier, vol. 324(C).
    7. Li, Quan & Chen, Huimin & Chen, Yang & Xiao, Tong & Wang, Li, 2023. "Digital economy, financing constraints, and corporate innovation," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    8. Xie, Rui & Wei, Dihan & Han, Feng & Lu, Yue & Fang, Jiayu & Liu, Yu & Wang, Junfeng, 2019. "The effect of traffic density on smog pollution: Evidence from Chinese cities," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 421-427.
    9. Werner Antweiler & Brian R. Copeland & M. Scott Taylor, 2001. "Is Free Trade Good for the Environment?," American Economic Review, American Economic Association, vol. 91(4), pages 877-908, September.
    10. Daron Acemoglu & Pascual Restrepo, 2018. "Low-Skill and High-Skill Automation," Journal of Human Capital, University of Chicago Press, vol. 12(2), pages 204-232.
    11. Wang, Linhui & Wang, Hui & Cao, Zhanglu & He, Yongda & Dong, Zhiqing & Wang, Shixiang, 2022. "Can industrial intellectualization reduce carbon emissions? — Empirical evidence from the perspective of carbon total factor productivity in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    12. Li, Yaya & Zhang, Yuru & Pan, An & Han, Minchun & Veglianti, Eleonora, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Technology in Society, Elsevier, vol. 70(C).
    13. Rubashkina, Yana & Galeotti, Marzio & Verdolini, Elena, 2015. "Environmental regulation and competitiveness: Empirical evidence on the Porter Hypothesis from European manufacturing sectors," Energy Policy, Elsevier, vol. 83(C), pages 288-300.
    14. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    15. Liu, Jun & Liu, Liang & Qian, Yu & Song, Shunfeng, 2022. "The effect of artificial intelligence on carbon intensity: Evidence from China's industrial sector," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    16. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    17. Li, Wencong & Yang, Xingquan & Yin, Xingqiang, 2024. "Digital transformation and labor upgrading," Pacific-Basin Finance Journal, Elsevier, vol. 83(C).
    18. Guo, Qingbin & Wang, Yong & Dong, Xiaobin, 2022. "Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China," Applied Energy, Elsevier, vol. 313(C).
    19. repec:ags:aaea22:335879 is not listed on IDEAS
    20. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    21. Hong Cheng & Ruixue Jia & Dandan Li & Hongbin Li, 2019. "The Rise of Robots in China," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 71-88, Spring.
    22. Fang, Jiayu & Tang, Xue & Xie, Rui & Han, Feng, 2020. "The effect of manufacturing agglomerations on smog pollution," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 92-101.
    23. Huang, Hongyun & Mbanyele, William & Fan, Shuangshuang & Zhao, Xin, 2022. "Digital financial inclusion and energy-environment performance: What can learn from China," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 342-366.
    24. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    25. Huang, Geng & He, Ling-Yun & Lin, Xi, 2022. "Robot adoption and energy performance: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 107(C).
    26. Wang, Ting & Zhang, Yi & Liu, Chun, 2024. "Robot adoption and employment adjustment: Firm-level evidence from China," China Economic Review, Elsevier, vol. 84(C).
    27. Cheng, Lu & Mi, Zhifu & Sudmant, Andrew & Coffman, D'Maris, 2022. "Bigger cities better climate? Results from an analysis of urban areas in China," Energy Economics, Elsevier, vol. 107(C).
    28. Bai, Ling & Guo, Tianran & Xu, Wei & Liu, Yaobin & Kuang, Ming & Jiang, Lei, 2023. "Effects of digital economy on carbon emission intensity in Chinese cities: A life-cycle theory and the application of non-linear spatial panel smooth transition threshold model," Energy Policy, Elsevier, vol. 183(C).
    29. Yaya Li & Yuru Zhang & An Pan & Minchun Han & Eleonora Veglianti, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Post-Print hal-04522085, HAL.
    30. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    31. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    32. Huzhou Zhu & Bin Sang & Chunyuan Zhang & Lin Guo, 2023. "Have Industrial Robots Improved Pollution Reduction? A Theoretical Approach and Empirical Analysis," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(4), pages 153-172, July.
    33. Ouyang, Xiaoling & Li, Qiong & Du, Kerui, 2020. "How does environmental regulation promote technological innovations in the industrial sector? Evidence from Chinese provincial panel data," Energy Policy, Elsevier, vol. 139(C).
    34. Haochang Yang & Faming Zhang & Yixin He, 2021. "Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16119-16144, November.
    35. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    36. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    37. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    38. Du, Mengfan & Zhang, Yue-Jun, 2023. "The impact of producer services agglomeration on green economic development: Evidence from 278 Chinese cities," Energy Economics, Elsevier, vol. 124(C).
    39. Wang, Mei & Xu, Mi & Ma, Shaojun, 2021. "The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 427-441.
    40. 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).
    41. Gan, Jiawu & Liu, Lihua & Qiao, Gang & Zhang, Qin, 2023. "The role of robot adoption in green innovation: Evidence from China," Economic Modelling, Elsevier, vol. 119(C).
    42. Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
    43. Ariel J. Binder & John Bound, 2019. "The Declining Labor Market Prospects of Less-Educated Men," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 163-190, Spring.
    44. Ma, Ruiyang & Lin, Boqiang, 2023. "Digitalization and energy-saving and emission reduction in Chinese cities: Synergy between industrialization and digitalization," Applied Energy, Elsevier, vol. 345(C).
    45. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
    46. 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).
    47. Haitao Wu & Ruohan Zhong & Zhen Wang & Yuanfeng Qu & Xiaodong Yang & Yu Hao, 2024. "How Does Industrial Intellectualization Affect Energy Intensity? Evidence from China," The Energy Journal, , vol. 45(2), pages 49-70, March.
    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. Teng Wang & Yani Wang & Weiwei Xiong, 2024. "Does Environmental Information Disclosure Reduce PM2.5 Emissions? Evidence from Chinese Prefecture-Level Cities," Sustainability, MDPI, vol. 16(22), pages 1-20, November.
    2. Jiayu Ou & Zhiqiang Zheng & Xiaojing Ou & Naili Zhang, 2024. "Smart City Construction, Artificial Intelligence Development, and the Quality of Export Products: A Study Based on Micro-Level Data of Chinese Enterprises," Sustainability, MDPI, vol. 16(19), pages 1-25, October.
    3. Hanqing Xu & Zhengxu Cao & Dongqing Han, 2025. "Towards Sustainable Development: Can Industrial Intelligence Promote Carbon Emission Reduction," Sustainability, MDPI, vol. 17(1), pages 1-19, January.

    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. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    2. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    3. Zhang, Zhenhua & Zhang, Yunpeng & Wu, Huangbin & Song, Shunfeng & Pan, Yuxi & Feng, Yanchao, 2024. "Dual effects of automation on economy and environment: Evidence from A-share listed enterprises in China," China Economic Review, Elsevier, vol. 88(C).
    4. Lee, Chien-Chiang & Xuan, Chengnan & Wang, Fuhao, 2024. "Natural resources and green economic growth: The role of artificial intelligence," Resources Policy, Elsevier, vol. 98(C).
    5. Wang, Jianlong & Wang, Weilong & Liu, Yong & Wu, Haitao, 2023. "Can industrial robots reduce carbon emissions? Based on the perspective of energy rebound effect and labor factor flow in China," Technology in Society, Elsevier, vol. 72(C).
    6. FU, Yunyun & SHEN, Yongchang & SONG, Malin & WANG, Weiyu, 2024. "Does artificial intelligence reduce corporate energy consumption? New evidence from China," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 548-561.
    7. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    8. Wang, Hua & Liao, Lingtao & Wu, Ji (George), 2023. "Robot adoption and firm's capacity utilization: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    9. Peng Liang & Xinhui Sun & Luzhuang Qi, 2024. "Does artificial intelligence technology enhance green transformation of enterprises: based on green innovation perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 21651-21687, August.
    10. Han, Wang-Zhe & Zhang, Yi-Ming, 2024. "Carbon reduction effect of industrial robots: Breaking the impasse for carbon emissions and development," Innovation and Green Development, Elsevier, vol. 3(3).
    11. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).
    12. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    13. Liu, Yunxin & Cao, Yuqiang & Lu, Meiting & Shan, Yaowen & Xu, Jiangang, 2024. "Automating efficiency: The impact of industrial robots on labor investment in China," Economic Modelling, Elsevier, vol. 140(C).
    14. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).
    15. Ding, Tao & Li, Hao & Liu, Li & Feng, Kui, 2024. "An inquiry into the nexus between artificial intelligence and energy poverty in the light of global evidence," Energy Economics, Elsevier, vol. 136(C).
    16. Shurong Zi & Ziyuan Pan & Yanjie Chen & Xinheng Liu & Qi Ban, 2025. "Intelligent Manufacturing and Pollution Emissions from Chinese Manufacturing Firms: Theories and Mechanisms," Sustainability, MDPI, vol. 17(2), pages 1-21, January.
    17. Tao, Weiliang & Weng, Shimei & Chen, Xueli & ALHussan, Fawaz Baddar & Song, Malin, 2024. "Artificial intelligence-driven transformations in low-carbon energy structure: Evidence from China," Energy Economics, Elsevier, vol. 136(C).
    18. Fu, Tong & Qiu, Zhaoxuan & Yang, Xiangyang & Li, Zijun, 2024. "The impact of artificial intelligence on green technology cycles in China," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    19. Schneider, Florian, 2024. "Do robots boost productivity? A quantitative meta-study," MPRA Paper 123392, University Library of Munich, Germany.
    20. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).

    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:eee:appene:v:365:y:2024:i:c:s0306261924006287. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.