Peter W. Hom
Arizona State University
92 Papers
207 Citations
Peter W. Hom is an academic researcher from Arizona State University. The author has contributed to research in topics: Turnover & Job satisfaction. The author has an hindex of 39, co-authored 92 publications. Previous affiliations of Peter W. Hom include Saint Petersburg State University & Kent State University.
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Papers
A Meta-Analysis of Antecedents and Correlates of Employee Turnover: Update, Moderator Tests, and Research Implications for the Next Millennium
TL;DR: This article conducted a comprehensive meta-analysis of antecedent turnover antecedents, extending an earlier one by Hom and Griffeth (1995), and reported the results of this comprehensive meta analysis.
4.3K
One hundred years of employee turnover theory and research.
TL;DR: How theory development and testing began in the mid-20th century and dominated the academic literature until the turn of the century is explained and 21st century interest in the psychology of staying (rather than leaving) and attitudinal trajectories in predicting turnover is tracked.
720
Structural equations modeling test of a turnover theory: Cross-sectional and longitudinal analyses.
Peter W. Hom,Rodger W. Griffeth +1 more
TL;DR: In this paper, Hom, Griffeth, and Sellaro's theoretical alternative to Mobley's turnover model was investigated in two studies and conceptual distinctions among model constructs and operationalizations of those constructs were validated.
715
A meta-analytical structural equations analysis of a model of employee turnover.
TL;DR: This paper combined meta-analysis with structural equations modeling (SEM) to validate Mobley, Horner, and Hollingsworth's turnover theory as well as alternative structural networks proposed by Dalessio, Silverman, and Schuck.
688
Toward a Greater Understanding of How Dissatisfaction Drives Employee Turnover
Peter W. Hom,Angelo J. Kinicki +1 more
TL;DR: This paper generalized a leading portrayal of how job dissatisfaction progresses into turnover and rigorously tested this model using structural equations modeling and applied it to real-world job turnover data and found that the model was accurate.
674