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Industry 4.0 and AI amid economic uncertainty: Implications for sustainable markets

Author

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  • Alshammari, Saad
  • Serret, Vanessa
  • Tiwari, Sunil
  • Si Mohammed, Kamel

Abstract

This research examines the dynamic relationships among three distinct asset categories within the context of economic policy uncertainty (EPU). The first category encompasses Industry 4.0 assets related to artificial intelligence (AI) and ESG circular economies (ESGCE). In contrast, the second category focuses on environmentally sustainable markets, specifically green bonds (SPGB) and carbon trading (ICI). Utilizing daily data from December 20, 2017, to September 06, 2023, our innovative R2 decomposed connectedness and portfolio analysis reveal a notably elevated average Total Connectedness Index (TCI), averaging about 60 %. Upon decomposing this measure into contemporaneous and lagged components, we observe that AI and ESG circular indices are primarily influenced by lagged and contemporary spillover. At the same time, EPU and traditional energy are the primary recipients. These findings suggest that investing in Industry 4.0 assets and eco-friendly options consistently yields the highest profits, serving as a reliable hedge against conventional assets.

Suggested Citation

  • Alshammari, Saad & Serret, Vanessa & Tiwari, Sunil & Si Mohammed, Kamel, 2025. "Industry 4.0 and AI amid economic uncertainty: Implications for sustainable markets," Research in International Business and Finance, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:riibaf:v:75:y:2025:i:c:s0275531925000297
    DOI: 10.1016/j.ribaf.2025.102773
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    Keywords

    ESG; Circular economy; AI; Green finance; Carbon market; R2 decomposed; Portfolio analysis;
    All these keywords.

    JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis

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