Authors :
Nguyen Vu Hieu Thao; Dr. Luu Thi Thanh Mai
Volume/Issue :
Volume 10 - 2025, Issue 10 - October
Google Scholar :
https://tinyurl.com/3hym7cnv
Scribd :
https://tinyurl.com/uavfmst2
DOI :
https://doi.org/10.38124/ijisrt/25oct658
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
In the context of Industry 4.0, artificial intelligence (AI) is transforming not only business operations but also the
way employees perceive work, motivation, and value creation. While AI-driven technologies have enabled automation,
efficiency, and data-driven decision-making, they also raise concerns about job insecurity, digital stress, and the erosion of
intrinsic motivation. This study explores how employee motivation can be optimized within AI-augmented work
environments through a qualitative case study at MH Raroma – a digital creative enterprise specializing in manga and
webtoon production in Vietnam.
Using in-depth interviews and focus group discussions with 20 participants (artists, editors, and managers), the
research identifies five major determinants of motivation in the AI era: (1) AI integration and work redesign, (2) leadership
and organizational culture, (3) compensation and recognition systems, (4) digital skills and professional growth, and (5)
psychological well-being under technological stress. The findings reveal that AI adoption simultaneously enhances and
threatens motivation — it increases productivity and autonomy but also generates anxiety and burnout when not managed
properly.
The study contributes to the literature by conceptualizing the notion of “Work Motivation Optimization” as a dynamic
balance between human needs and technological transformation. Practical implications are proposed for managers to foster
a human-centered digital culture, align AI implementation with intrinsic motivators, and design sustainable motivation
frameworks for creative and knowledge-intensive industries.
Keywords :
Employee Motivation, Artificial Intelligence (AI), Digital Transformation, Human Resource Management, Creative Industry, Vietnam, Work Engagement.
References :
- Bakker, A. B., & Demerouti, E. (2008). Towards a model of work engagement. Career Development International, 13(3), 209–223. https://doi.org/10.1108/13620430810870476
- Bakker, A. B., & Demerouti, E. (2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273–285. https://doi.org/10.1037/ocp0000056
- Bass, B. M. (1990). From transactional to transformational leadership: Learning to share the vision. Organizational Dynamics, 18(3), 19–31.
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
- Brennen, S. (2020). Creativity and artificial intelligence: The paradox of automation. Journal of Media Innovation, 7(1), 32–45.
- Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton & Company.
- Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum Press.
- Gagné, M., & Deci, E. L. (2005). Self-determination theory and work motivation. Journal of Organizational Behavior, 26(4), 331–362. https://doi.org/10.1002/job.322
- Gagné, M., Forest, J., Vansteenkiste, M., Crevier-Braud, L., Van den Broeck, A., Aspeli, A. K., … & Westbye, C. (2015). The multidimensional work motivation scale: Validation evidence in seven languages and nine countries. European Journal of Work and Organizational Psychology, 24(2), 178–196.
- Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250–279.
- Herzberg, F. (1959). The motivation to work. John Wiley & Sons.
- Huang, M. H., Rust, R. T., & Maksimovic, V. (2021). The feeling economy: Managing in the next generation of artificial intelligence (AI). California Management Review, 63(3), 5–25.
- Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2015). Strategy, not technology, drives digital transformation. MIT Sloan Management Review and Deloitte University Press.
- Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Occupational Behavior, 2(2), 99–113.
- Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396.
- McClelland, D. C. (1985). Human motivation. Cambridge University Press.
- Parker, S. K., & Grote, G. (2020). Automation, algorithms, and beyond: Why work design matters more than ever in a digital world. Applied Psychology, 69(4), 956–1022. https://doi.org/10.1111/apps.12241
- Pinder, C. C. (2008). Work motivation in organizational behavior (2nd ed.). Psychology Press.
- Ryan, R. M., & Deci, E. L. (2020). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.
- Tarafdar, M., Maier, C., & Laumer, S. (2019). Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior. Information Systems Journal, 29(2), 408–435.
- Tran, K. D. (2015). Human resource management in the digital economy: Evidence from Vietnam. Vietnam Journal of Economics and Development, 207(9), 57–68.
- Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
- Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into business transformation. Harvard Business Review Press.
- Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
In the context of Industry 4.0, artificial intelligence (AI) is transforming not only business operations but also the
way employees perceive work, motivation, and value creation. While AI-driven technologies have enabled automation,
efficiency, and data-driven decision-making, they also raise concerns about job insecurity, digital stress, and the erosion of
intrinsic motivation. This study explores how employee motivation can be optimized within AI-augmented work
environments through a qualitative case study at MH Raroma – a digital creative enterprise specializing in manga and
webtoon production in Vietnam.
Using in-depth interviews and focus group discussions with 20 participants (artists, editors, and managers), the
research identifies five major determinants of motivation in the AI era: (1) AI integration and work redesign, (2) leadership
and organizational culture, (3) compensation and recognition systems, (4) digital skills and professional growth, and (5)
psychological well-being under technological stress. The findings reveal that AI adoption simultaneously enhances and
threatens motivation — it increases productivity and autonomy but also generates anxiety and burnout when not managed
properly.
The study contributes to the literature by conceptualizing the notion of “Work Motivation Optimization” as a dynamic
balance between human needs and technological transformation. Practical implications are proposed for managers to foster
a human-centered digital culture, align AI implementation with intrinsic motivators, and design sustainable motivation
frameworks for creative and knowledge-intensive industries.
Keywords :
Employee Motivation, Artificial Intelligence (AI), Digital Transformation, Human Resource Management, Creative Industry, Vietnam, Work Engagement.