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AI-Driven Metaverse Integration for Sustainable Manufacturing: The Mediating Role of Digital Supply Chain Resilience in Jordan’s Industrial Sector

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  • Ahmad Fathi Alheet

    (Business Administration Department, Al-Ahliyya Amman University, Amman 19111, Jordan)

Abstract

Background : This study examines how AI-driven metaverse integration enhances sustainable manufacturing performance in Jordan’s industrial sector, with particular emphasis on the mediating role of digital supply chain resilience. Grounded in resource orchestration theory (ROT), the research explains how digital twin systems, predictive AI analytics, and virtual collaboration technologies jointly support sustainability through improved supply chain agility, responsiveness, and continuity. Methods : Data were collected from 500 industrial managers, of which 415 valid responses were analyzed using partial least squares structural equation modeling (PLS-SEM). Results : The findings indicate that AI-powered metaverse dimensions have significant and positive effects on sustainable manufacturing performance, both directly and indirectly through digital supply chain resilience. The mediation analysis confirms that resilience serves as a critical mechanism linking metaverse-based technology adoption to sustainability outcomes. Conclusions : The study highlights the strategic importance of integrating advanced digital and virtual technologies into supply chains to address sustainability challenges, particularly in emerging economies such as Jordan. By extending resource orchestration theory to the metaverse context, this research contributes to theory development and offers practical insights for industrial managers seeking to leverage digital transformation as a source of sustainable competitive advantage.

Suggested Citation

  • Ahmad Fathi Alheet, 2026. "AI-Driven Metaverse Integration for Sustainable Manufacturing: The Mediating Role of Digital Supply Chain Resilience in Jordan’s Industrial Sector," Logistics, MDPI, vol. 10(1), pages 1-26, January.
  • Handle: RePEc:gam:jlogis:v:10:y:2026:i:1:p:15-:d:1835509
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