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Industry 4.0 and energy in manufacturing sectors in China

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  • Kunkel, S.
  • Neuhäusler, P.
  • Matthess, M.
  • Dachrodt, M.F.

Abstract

Digitalisation in manufacturing (or “industry 4.0”) is expected to improve energy efficiency and thus reduce energy intensity in manufacturing, but studies show that it may also increase energy consumption. In this article, we investigate to what extent the degree of industry 4.0 is linked to energy consumption and energy intensity in ten Chinese manufacturing sectors between 2006 and 2019. We approximate the degree of industry 4.0 by combining data on a) patent intensity of industry 4.0-related technologies and b) industrial robot intensity. Our results indicate that there is no significant overall relationship between the degree of industry 4.0 and energy consumption or energy intensity, in contrast to some earlier studies in the Chinese context which find energy intensity reducing effects of digitalisation. We argue that industry 4.0 in China might have fewer energy related benefits than expected by politics and industry. Growth-inducing effects and outsourcing of energy-intensive manufacturing tasks, for instance, may counteract efficiency-related savings. To decarbonise manufacturing in line with China's proclaimed objective of carbon neutrality by 2060, policy makers and industry should identify specific opportunities and take seriously risks of industry 4.0. The focus should be on reducing absolute energy consumption as opposed to energy intensity, which may disguise digital rebound effects; and on integrating renewable energies, particularly in the most energy-intensive sectors (metals, chemicals, non-metallic minerals).

Suggested Citation

  • Kunkel, S. & Neuhäusler, P. & Matthess, M. & Dachrodt, M.F., 2023. "Industry 4.0 and energy in manufacturing sectors in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:rensus:v:188:y:2023:i:c:s1364032123005695
    DOI: 10.1016/j.rser.2023.113712
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    as
    1. Jurkat Anne & Klump Rainer & Schneider Florian, 2022. "Tracking the Rise of Robots: The IFR Database," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 242(5-6), pages 669-689, December.
    2. Lin, Boqiang & Xu, Mengmeng, 2019. "Quantitative assessment of factors affecting energy intensity from sector, region and time perspectives using decomposition method: A case of China’s metallurgical industry," Energy, Elsevier, vol. 189(C).
    3. Victor Ajayi and David Reiner, 2020. "European Industrial Energy Intensity: Innovation, Environmental Regulation, and Price Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 105-128.
    4. Wang, Jianda & Dong, Xiucheng & Dong, Kangyin, 2022. "How digital industries affect China's carbon emissions? Analysis of the direct and indirect structural effects," Technology in Society, Elsevier, vol. 68(C).
    5. Jiang Kejun & He Chenmin & Jiang Weiyi & Chen Sha & Dai Chunyan & Liu Jia & Xiang Pianpian, 2021. "Transition of the Chinese Economy in the Face of Deep Greenhouse Gas Emissions Cuts in the Future," Asian Economic Policy Review, Japan Center for Economic Research, vol. 16(1), pages 142-162, January.
    6. Jan C. T. Bieser & Lorenz M. Hilty, 2018. "Assessing Indirect Environmental Effects of Information and Communication Technology (ICT): A Systematic Literature Review," Sustainability, MDPI, vol. 10(8), pages 1-19, July.
    7. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-355, December.
    8. Arianna Martinelli & Andrea Mina & Massimo Moggi, 2021. "The enabling technologies of industry 4.0: examining the seeds of the fourth industrial revolution [Mapping innovation dynamics in the Internet of Things domain: evidence from patent analysis]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(1), pages 161-188.
    9. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    10. Zhang, Wei & You, Jianmin & Lin, Weiwen, 2021. "Internet plus and China industrial system's low-carbon development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    11. 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).
    12. 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).
    13. Culot, Giovanna & Nassimbeni, Guido & Orzes, Guido & Sartor, Marco, 2020. "Behind the definition of Industry 4.0: Analysis and open questions," International Journal of Production Economics, Elsevier, vol. 226(C).
    14. Xiekui Zhang & Peiyao Liu & Hongfei Zhu, 2022. "The Impact of Industrial Intelligence on Energy Intensity: Evidence from China," Sustainability, MDPI, vol. 14(12), pages 1-16, June.
    15. Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
    16. Min Zhao & Rong Liu & Debao Dai, 2021. "Synergistic Effect between China’s Digital Transformation and Economic Development: A Study Based on Sustainable Development," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    17. Ardito, Lorenzo & D'Adda, Diego & Messeni Petruzzelli, Antonio, 2018. "Mapping innovation dynamics in the Internet of Things domain: Evidence from patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 317-330.
    18. Shahbaz, Muhammad & Wang, Jianda & Dong, Kangyin & Zhao, Jun, 2022. "The impact of digital economy on energy transition across the globe: The mediating role of government governance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    19. Jinqi Su & Ke Su & Shubin Wang, 2021. "Does the Digital Economy Promote Industrial Structural Upgrading?—A Test of Mediating Effects Based on Heterogeneous Technological Innovation," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
    20. Paul E. Brockway & Harry Saunders & Matthew K. Heun & Timothy J. Foxon & Julia K. Steinberger & John R. Barrett & Steve Sorrell, 2017. "Energy Rebound as a Potential Threat to a Low-Carbon Future: Findings from a New Exergy-Based National-Level Rebound Approach," Energies, MDPI, vol. 10(1), pages 1-24, January.
    21. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    22. Hardt, Lukas & Barrett, John & Taylor, Peter G. & Foxon, Timothy J., 2021. "What structural change is needed for a post-growth economy: A framework of analysis and empirical evidence," Ecological Economics, Elsevier, vol. 179(C).
    23. Tetsuya Tsurumi & Shunsuke Managi, 2010. "Decomposition of the environmental Kuznets curve: scale, technique, and composition effects," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 11(1), pages 19-36, February.
    24. Flavio Calvino & Chiara Criscuolo & Luca Marcolin & Mariagrazia Squicciarini, 2018. "A taxonomy of digital intensive sectors," OECD Science, Technology and Industry Working Papers 2018/14, OECD Publishing.
    25. Pappas, Dimitrios & Chalvatzis, Konstantinos J. & Guan, Dabo & Ioannidis, Alexis, 2018. "Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia," Applied Energy, Elsevier, vol. 225(C), pages 183-194.
    26. Ramos, Minerva E. & Garza-Rodríguez, Jorge & Gibaja-Romero, Damian E., 2022. "Automation of employment in the presence of industry 4.0: The case of Mexico," Technology in Society, Elsevier, vol. 68(C).
    27. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei, 2018. "How does information and communication technology affect China's energy intensity? A three-tier structural decomposition analysis," Energy, Elsevier, vol. 151(C), pages 748-759.
    28. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    29. Haldar, Anasuya & Sethi, Narayan, 2022. "Environmental effects of Information and Communication Technology - Exploring the roles of renewable energy, innovation, trade and financial development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    30. Hao, Yu & Li, Ying & Guo, Yunxia & Chai, Jingxia & Yang, Chuxiao & Wu, Haitao, 2022. "Digitalization and electricity consumption: Does internet development contribute to the reduction in electricity intensity in China?," Energy Policy, Elsevier, vol. 164(C).
    31. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    32. Botang Han & Dong Wang & Weina Ding & Lei Han, 2016. "Effect of information and communication technology on energy consumption in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 297-315, November.
    33. 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).
    34. Matthess, Marcel & Kunkel, Stefanie, 2020. "Structural change and digitalization in developing countries: Conceptually linking the two transformations," Technology in Society, Elsevier, vol. 63(C).
    35. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei & Su, Bin, 2019. "How information and communication technology drives carbon emissions: A sector-level analysis for China," Energy Economics, Elsevier, vol. 81(C), pages 380-392.
    36. Hardt, Lukas & Owen, Anne & Brockway, Paul & Heun, Matthew K. & Barrett, John & Taylor, Peter G. & Foxon, Timothy J., 2018. "Untangling the drivers of energy reduction in the UK productive sectors: Efficiency or offshoring?," Applied Energy, Elsevier, vol. 223(C), pages 124-133.
    37. Butollo, Florian, 2021. "Digitalization and the geographies of production: Towards reshoring or global fragmentation?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 25(2), pages 259-278.
    38. Yang, Shenglang & Shi, Xunpeng, 2018. "Intangible capital and sectoral energy intensity: Evidence from 40 economies between 1995 and 2007," Energy Policy, Elsevier, vol. 122(C), pages 118-128.
    39. Xue, Yan & Tang, Chang & Wu, Haitao & Liu, Jianmin & Hao, Yu, 2022. "The emerging driving force of energy consumption in China: Does digital economy development matter?," Energy Policy, Elsevier, vol. 165(C).
    40. 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.
    41. Patrick Schulte & Heinz Welsch & Sascha Rexhäuser, 2016. "ICT and the Demand for Energy: Evidence from OECD Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(1), pages 119-146, January.
    42. 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).
    43. Lange, Steffen & Pohl, Johanna & Santarius, Tilman, 2020. "Digitalization and energy consumption. Does ICT reduce energy demand?," Ecological Economics, Elsevier, vol. 176(C).
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