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Robert Klemmensen, black and white photo.

Robert Klemmensen

Professor

Robert Klemmensen, black and white photo.

Pruning the forest of turnover research: identifying important antecedents using predictive modelling

Author

  • Jens Lems
  • Robert Klemmensen
  • Signe Pihl-Thingvad

Summary, in English

While extant research has identified numerous antecedents of turnover, our understanding of their relative influence on turnover behaviour remains limited. This article evaluates the predictive power of established turnover antecedents and determines which are most important for predicting turnover. Drawing on administrative and survey data from public employees in a large Danish municipality, we use predictive modelling to demonstrate how demographic characteristics are the strongest predictors. In contrast, antecedents related to the work environment, job characteristics, and work attitudes do not significantly enhance predictive accuracy. We discuss the implications of these findings for both theory and practice.

Department/s

  • Department of Political Science
  • LU Profile Area: Natural and Artificial Cognition

Publishing year

2025-10-11

Language

English

Publication/Series

Public Management Review

Document type

Journal article

Publisher

Taylor & Francis

Topic

  • Political Science (excluding Peace and Conflict Studies)

Status

Epub

ISBN/ISSN/Other

  • ISSN: 1471-9037