Asymmetric relationship between competitive industrial performance, renewable energy, industrialization, and carbon footprint: Does artificial intelligence matter for environmental sustainability?

Muhammad Qamar Rasheed*, Zhao Yuhuan, Abdul Haseeb, Zahoor Ahmed, Shah Saud

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Developing nations have emerged as integral contributors to the global economy since the beginning of the 21st century. Their swift economic expansion and associated activities lead to a rise in carbon footprint. Keeping this in view, unlike previous studies, this study unfolds the asymmetric repercussions of competitive industrial performance and renewable energy within the context of the industrialization era in seven Asian developing countries from 1990 to 2020. The panel NARDL and asymmetric panel causality methodologies have been applied for the purpose of nonlinear analysis. According to the results, the advantageous influence of competitive industrial performance is considerably more pronounced than that of industrialization. The coefficient magnitude associated with the negative shock demonstrates a significantly substantial value in comparison to the positive shock concerning the influence of competitive industrial performance on carbon footprint. Both positive and negative changes in competitive industrial performance mitigate carbon footprint. Renewable energy generates favorable consequences by promoting environmental quality via a reduction in carbon footprint. Across various emerging economies in Asia, the rapid rise of industrialization is linked to the deterioration of environmental quality. Finally, artificial intelligence and natural resource rents decrease carbon footprints while information and communication technology intensifies environmental concerns. The research emphasizes the critical nature of integrating artificial intelligence, robotics, and technological industrial competitiveness in order to adequately tackle the carbon footprint in Asian developing countries.

Original languageEnglish
Article number123346
JournalApplied Energy
Volume367
DOIs
Publication statusPublished - 1 Aug 2024

Keywords

  • Artificial intelligence
  • Asymmetric analysis
  • Carbon footprint
  • Competitive industrial performance
  • Renewable energy

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