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The Spatial Effect of Industrial Intelligence on High-Quality Green Development of Industry under Environmental Regulations and Low Carbon Intensity

Author

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  • Taqdees Fatima

    (Department of Economics and Management Sciences, Xi’an University of Technology, Xi’an 710048, China)

  • Bingxiang Li

    (Department of Economics and Management Sciences, Xi’an University of Technology, Xi’an 710048, China)

  • Shahab Alam Malik

    (Faculty of Economics and Management Sciences, Minhaj University, Lahore 54770, Pakistan)

  • Dan Zhang

    (Department of Economics and Management Sciences, Xi’an University of Technology, Xi’an 710048, China)

Abstract

In order to thoroughly investigate how industrial intelligence influences green industrial development through direct, indirect, and spatial spillover effects in China and fill in the gaps left by earlier studies, the study combines industrial intelligence and green industrial development into a single analytical framework. The findings show that implementing industrial intelligence can proactively encourage high-quality green industrial development; additionally, a strong spatial correlation is shown between industrial intelligence and high-quality green industrial development. According to spatial spillover analysis, industrial intelligence fosters the development of green industries both inside and between regions. When regional heterogeneity is analyzed, it is revealed that the eastern part of China experiences industrial intelligence effects more strongly than the central region, while the western areas are unaffected. Environmental regulations are a crucial mediating mechanism for the operation of industrial intelligence; in particular, public-participation environmental regulation and market base environmental regulations strengthen the baseline relationship; however, industrial intelligence does not impact high-quality green industrial development through administrative environmental regulation. The partial mediating effect of carbon intensity was also observed. The findings could be used as a guide for decision-making by experts and policymakers in China and other developing nations to use industrial intelligence and support the green development of the sector during economic transformation.

Suggested Citation

  • Taqdees Fatima & Bingxiang Li & Shahab Alam Malik & Dan Zhang, 2023. "The Spatial Effect of Industrial Intelligence on High-Quality Green Development of Industry under Environmental Regulations and Low Carbon Intensity," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:1903-:d:1040781
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    1. Jeyhun I. Mikayilov & Marzio Galeotti & Fakhri J. Hasanov, 2018. "The Impact of Economic Growth on CO2 Emissions in Azerbaijan," IEFE Working Papers 102, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    2. Lai, Xiaodong & Liu, Jixian & Shi, Qian & Georgiev, Georgi & Wu, Guangdong, 2017. "Driving forces for low carbon technology innovation in the building industry: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 299-315.
    3. Zhijun Feng & Wei Chen, 2018. "Environmental Regulation, Green Innovation, and Industrial Green Development: An Empirical Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    4. Dominik M. Wielgos & Christian Homburg & Christina Kuehnl, 2021. "Digital business capability: its impact on firm and customer performance," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 762-789, July.
    5. Dong, Kangyin & Ren, Xiaohang & Zhao, Jun, 2021. "How does low-carbon energy transition alleviate energy poverty in China? A nonparametric panel causality analysis," Energy Economics, Elsevier, vol. 103(C).
    6. Kirsten S. Wiebe & Norihiko Yamano, 2016. "Estimating CO2 Emissions Embodied in Final Demand and Trade Using the OECD ICIO 2015: Methodology and Results," OECD Science, Technology and Industry Working Papers 2016/5, OECD Publishing.
    7. Costanza, Robert, 1989. "What is ecological economics?," Ecological Economics, Elsevier, vol. 1(1), pages 1-7, February.
    8. Alina Sorescu & Martin Schreier, 2021. "Innovation in the digital economy: a broader view of its scope, antecedents, and consequences," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 627-631, July.
    9. Congbo Chen & Azhong Ye, 2021. "Heterogeneous Effects of ICT across Multiple Economic Development in Chinese Cities: A Spatial Quantile Regression Model," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    10. 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.
    11. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    12. Markus Blut & Cheng Wang & Nancy V. Wünderlich & Christian Brock, 2021. "Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 632-658, July.
    13. A. B. Savchenko & T. L. Borodina, 2020. "Green and Digital Economy for Sustainable Development of Urban Areas," Regional Research of Russia, Springer, vol. 10(4), pages 583-592, October.
    14. Wang, Yuyan & Yu, Zhaoqing & Jin, Mingzhou & Mao, Jiafu, 2021. "Decisions and coordination of retailer-led low-carbon supply chain under altruistic preference," European Journal of Operational Research, Elsevier, vol. 293(3), pages 910-925.
    15. Wu, Haitao & Hao, Yu & Ren, Siyu & Yang, Xiaodong & Xie, Guo, 2021. "Does internet development improve green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 153(C).
    16. Ma, Dan & Zhu, Qing, 2022. "Innovation in emerging economies: Research on the digital economy driving high-quality green development," Journal of Business Research, Elsevier, vol. 145(C), pages 801-813.
    17. Ribeiro-Navarrete, Samuel & Botella-Carrubi, Dolores & Palacios-Marqués, Daniel & Orero-Blat, Maria, 2021. "The effect of digitalization on business performance: An applied study of KIBS," Journal of Business Research, Elsevier, vol. 126(C), pages 319-326.
    18. Chen, Jie & Zhou, Qian, 2017. "City size and urban labor productivity in China: New evidence from spatial city-level panel data analysis," Economic Systems, Elsevier, vol. 41(2), pages 165-178.
    19. J. Paul Elhorst, 2014. "Spatial Econometrics," SpringerBriefs in Regional Science, Springer, edition 127, number 978-3-642-40340-8, November.
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