Issue |
E3S Web Conf.
Volume 601, 2025
The 3rd International Conference on Energy and Green Computing (ICEGC’2024)
|
|
---|---|---|
Article Number | 00020 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/e3sconf/202560100020 | |
Published online | 16 January 2025 |
Integrating Sustainable HRM, AI, and Employee Well-Being to Enhance Engagement in Greater Jakarta: An SDG 3 Perspective
1 Management Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta, Indonesia 11480
2 Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480
* Corresponding author: herlina01@binus.edu
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.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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