From Organizational Justice Perceptions to Turnover Intentions: The Mediating Effects of Burnout and Job Satisfaction
Juan Diego Vaamonde, Alicia Omar, Solana Salessi
Europe's Journal of Psychology · 2018
doi:10.5964/ejop.v14i3.1490 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
Turnover intentions (TI) stand as an insidious problem that impacts on the functioning of organizations and the well-being of their members. Currently, there is a growing interest in identifying the explanatory mechanisms of TI, in order to strengthen and retain valued employees for organizations. In line with this trend, the aim of the present study was to test an integrative serial multiple mediation model that examined the possible mediating role of burnout and job satisfaction in the relationships between organizational justice and TI. To achieve this objective, a cross-sectional empirical study was carried out on a multi-occupational sample of 408 Argentine employees (219 women and 189 men). Participants completed a self-report questionnaire comprising previously validated measures for the target population. Structural equation modeling showed that perceptions of distributive, procedural, and interpersonal justice have negative indirect effects on TI through burnout and job satisfaction, while perceptions of informational justice exert such effects on TI only through job satisfaction. These results indicate that distributive, procedural, and interpersonal justice perceptions relate to lower levels of burnout, which in turn promote greater job satisfaction and lower TI among employees. In addition, informational justice perceptions are positively related to job satisfaction, leading to a decrease in employees’ TI. Findings are discussed in light of their theoretical and practical implications. Managers and human resource professionals could consider the research results in their attempts to design and implement talent retention strategies within organizations.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.