Understanding Generation Z: Work-Life Balance and Job Embeddedness in Retention Dynamics

Authors

  • Sherly Rosalina Tanoto Management Department, School of Business and Management, Petra Christian University
  • Erin Go Tami Management Department, School of Business and Management, Petra Christian University

DOI:

https://doi.org/10.21512/bbr.v15i3.11277

Keywords:

Generation Z, work-life balance, job embeddedness, retention dynamics

Abstract

The Great Resignation has presented a significant challenge for companies aiming to retain top talent and
emphasize the critical need for effective employee retention strategies. The research investigated the relationship
between work-life balance, employee retention, and turnover intention among Generation Z employees across
various industries in Indonesia. By encompassing multiple sectors such as technology, finance, healthcare, and
hospitality, the research aimed to capture Generation Z employees’ diverse experiences and perceptions. The
research involved 373 Generation Z respondents across various industries, employing a quantitative approach.
Data collection was facilitated through online questionnaires, and analysis was conducted using Structural
Equation Modeling (SEM) with Partial Least Square (PLS) as the analytical tool. The findings reveal significant
relationships between various constructs. Work-life balance influences employee retention, turnover intention,
and job embeddedness. Additionally, job embeddedness exerts an impact on both employee retention and turnover
intention. Furthermore, work-life balance indirectly affects employee retention and turnover intention through
its mediation by job embeddedness. The inclusion of diverse industries ensures that the results are broadly
applicable, offering practical recommendations for fostering a resilient and engaged workforce in different
professional environments. Future research should continue to explore industry-specific nuances to further enrich
the understanding of these critical issues.

Dimensions

Plum Analytics

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Published

2024-10-10
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