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Exploring the Impact of Artificial Intelligence (AI-Driven) Job Crafting on Employee Performance: A Bibliometric Analysis and Research Agenda

In: Vietnamese Business and Sustainable Development in a Globalized and Digitalized Era

Author

Listed:
  • Tri Minh Nguyen

    (Tan Tao University, School of Economics and Business Administration (SBE))

  • Nhat Tan Pham

    (International University, Vietnam National University, School of Business Administration)

  • Nguyen Le Khanh Trang

    (Vietcombank)

Abstract

This study uses bibliometric analysis to explore the knowledge structure and research trends on job crafting and employee performance. A dataset of 183 documents retrieved from the Scopus database to explore existing research on this topic, using a methodology that included bibliometric analysis, network analysis, and content analysis (CA) and analyzing by VOSViewer. The results show that although there have been many studies on the relationship between job crafting and employee performance, there is still a research gap on the impact of AI-driven job crafting on employee performance. By synthesizing theory and previous studies, an integrated model is proposed, which considers mediating factors such as digital resilience, employee psychological well-being, employee engagement with AI, and moderating factors such as sustainable leadership and employee AI-driven change readiness. The model results will provide theoretical and practical foundation, guiding businesses in applying AI to change and design work to improve employee performance.

Suggested Citation

  • Tri Minh Nguyen & Nhat Tan Pham & Nguyen Le Khanh Trang, 2026. "Exploring the Impact of Artificial Intelligence (AI-Driven) Job Crafting on Employee Performance: A Bibliometric Analysis and Research Agenda," Springer Proceedings in Business and Economics, in: Zafar U. Ahmed & Nhat Tan Pham (ed.), Vietnamese Business and Sustainable Development in a Globalized and Digitalized Era, pages 290-311, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-24745-2_16
    DOI: 10.1007/978-3-032-24745-2_16
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