Employee Experience as a Driver of Engagement and Retention: Insights from the IT Sector
- DOI
- 10.2991/978-94-6463-898-1_21How to use a DOI?
- Keywords
- Employee experience; employee engagement; turnover intentions
- Abstract
HR ecosystem is witnessing a shift to employee experience. This paper is aimed to augment the comprehension of employee experience as a novel discipline in the human resource management landscape, and to investigate its impact on organizational engagement level and the employee turnover intentions. The study also investigates the mediating role played by employee engagement on the relationship between employee experience (EX) and turnover intentions (TI). The descriptive study employs quantitative analysis to assess the interrelations between the variables. Data of 370 IT-ITES employees was used for analysis. The SEM model using PLS-SEM quantified the measurement, the structure, and the hypothesis. The study reported that employee experience had a significant and positive impact on employee engagement. The relationship between EX and TI is unsupported in this study. However, the study revealed negative significant connection between EE and TI of the employees. This study represents the total mediation exhibited by employee engagement (EE) between the interaction of employee experience (EX) and TI.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Sonal Khandelwal AU - Aanyaa Chaudhary PY - 2025 DA - 2025/11/18 TI - Employee Experience as a Driver of Engagement and Retention: Insights from the IT Sector BT - Proceedings of the International Conference on Artificial Intelligence in Management for Business and Industrial Growth (AIMBIG 2025) PB - Atlantis Press SP - 287 EP - 302 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-898-1_21 DO - 10.2991/978-94-6463-898-1_21 ID - Khandelwal2025 ER -