An empirical test of conceptual arguments to retire the three-component model of work commitment: Implications for commitment research

Mark Somers, Dee Birnbaum, Jose Casal

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: The purpose of this paper is to empirically assess conceptually based arguments that the three-component model (TCM) is not a model of commitment but rather of employee turnover, and that the mindsets that comprise the TCM do not form a unified construct. Design/methodology/approach: A survey design was used that was comprised of 223 staff nurses located in a large, urban hospital in the USA. Data were analyzed using dominance analysis, a variant of multiple linear regression that provides more accurate estimates of the strength of relationships between predictor and criterion variables when multicolinearity among predictors is present. Findings: Results from OLS regression and dominance analysis provided no support for concerns about the viability of the TCM. First, there was no evidence that the continuance and normative mindsets were associated only with employee turnover, and there was strong support that this was not the case. Second, our overall patterns of results indicated that the mindsets that comprise the TCM operated as a unified construct that is consistent with the theory and research underpinning the TCM. Practical implications: This study indicates that work commitment is multidimensional and must be managed accordingly so that it is important to be mindful of the development and implications of different constellations of work commitment. Originality/value: Conceptually grounded criticisms of the TCM have not been tested empirically leading to uncertainty about the nature of work commitment. This study adds an empirical perspective that is augmented by an advanced application of multiple regression analysis.

Original languageEnglish (US)
Pages (from-to)887-902
Number of pages16
JournalPersonnel Review
Volume49
Issue number3
DOIs
StatePublished - Mar 23 2020

All Science Journal Classification (ASJC) codes

  • Applied Psychology
  • Organizational Behavior and Human Resource Management

Keywords

  • Advanced statistical
  • Commitment
  • Hierarchical regression
  • Quantitative
  • Turnover

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