The holistic model of labour retention: The impact of workplace wellbeing factors on employee retention

Artikel

This paper explores the holistic context of workforce retention. The global labour shortages in developed countries have made employers realise that in a world of scarce resources, employee wellbeing and retention are key factors in competitiveness. The aim of the research is to create a model to identify the key determinants of employee well-being and workforce retention. A quantitative research methodology was applied, using a questionnaire with 58 validated statements, completed online by the research participants (n = 406). The PLS-SEM method was used for data analysis and inner and outer modelling. The measurement model was tested for internal consistency reliability and convergent and discriminant validity. Cronbach's » and CR values were above the 0.7 threshold for all constructions, indicating high internal consistency of measurements. In our model, there are a total of 36 significant relationships between latent variables. Based on the research results, the effect of organizational commitment on the intention to quit was determined. If the organizational commitment within an organization changes, the intention to resign changes. Thus, critical variables affecting workforce retention (benefits, promotion, communication, nature of work, coworkers, and normative commitment) have been identified, the changing of which will affect organizational commitment. The results support that if employees perceive these factors negatively, their commitment will drastically decrease.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Administrative Sciences ; ISSN: 2076-3387 ; Volume: 13 ; Year: 2023 ; Issue: 5 ; Pages: 1-25

Classification and Topics

• Classification: Öffentliche Verwaltung
• Subject: commitment ; employee wellbeing ; intention to quit ; psychological wellbeing ; quality job

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gelencsér, Martin ; Szabó-Szentgróti, Gábor ; Kőmüves, Zsolt Sándor ; Hollósy-Vadász, Gábor
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2023

Further information

• DOI: doi:10.3390/admsci13050121
• Handle: http://hdl.handle.net/10419/275586
• Last update: 10.03.2025, 11:42 AM CET