Integrating Sustainable HRM, AI, and Employee Well-Being to Enhance Engagement in Greater Jakarta: An SDG 3 Perspective
This study explores a combination of Sustainable Human Resource Management and Artificial Intelligence on employee well-being with a view to improving employee engagement for workers in Greater Jakarta, Indonesia. We applied Chi-Square and Rasch Model analyses on data collected from a cross-sectiona...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00020.pdf |
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| Summary: | This study explores a combination of Sustainable Human Resource Management and Artificial Intelligence on employee well-being with a view to improving employee engagement for workers in Greater Jakarta, Indonesia. We applied Chi-Square and Rasch Model analyses on data collected from a cross-sectional survey of 366 employees. The results yield significant positive associations between the sustainability of HRM practices and employee engagement along with those of well-being and engagement. However, it also noted that the integration of AI technology enhances employee engagement by reducing workload and enhancing decision-making support. Therefore, these findings emphasize the need to adopt sustainable HRM practices that aim to guarantee employee welfare and well-being, resulting in a more productive and engaged workforce. Contribution to the literature: A multidimensional model of employee engagement that integrates the role of sustainability, well-being, and technology. Practical implications include organizations investing in holistic HRM strategies that are commensurate with their sustainability goals and using AI to leverage value-added responses in employees. Future research directions could also be suggested, such as longitudinal studies and a broader approach to sampling, thereby enhancing generalizability across diverse contexts. |
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| ISSN: | 2267-1242 |