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Unraveling the SCARF: How dimensions of the SCARF model influence the relationship between workplace exclusion and turnover intentions

Published online by Cambridge University Press:  07 July 2025

Matthew Aplin-Houtz*
Affiliation:
Global Leadership and Management, University of Missouri at St. Louis, St. Louis, MO, USA
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Abstract

Workplace exclusion – often subtle and difficult to detect – significantly contributes to employee disengagement and turnover, costing US organizations over $1 trillion annually. This study examines how exclusionary behaviors (EBs) influence turnover intentions (TOIs) through disruption of psychological needs, using Rock’s SCARF model (Status, Certainty, Autonomy, Relatedness, Fairness) and self-determination theory. A two-wave survey of full-time US employees (N = 277) assessed EB, SCARF-based need satisfaction, and TOI. Partial least squares structural equation modeling revealed that EB significantly undermines all five SCARF domains, but only fairness and status mediated the EB–TOI link. Certainty, autonomy, and relatedness did not have significant effects. These findings suggest turnover risk intensifies when employees feel unfairly treated or socially devalued, rather than merely disempowered or disconnected. The study advances theoretical integration between SCARF and SDT and offers practical guidance for managers seeking to reduce attrition by fostering inclusive, respectful, and psychologically safe workplace environments.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press in association with Australian and New Zealand Academy of Management.
Figure 0

Figure 1. Research model.

Figure 1

Table 1. Demographics

Figure 2

Table 2. Correlation analysis

Figure 3

Table 3. Measurement model metrics

Figure 4

Table 4. Discriminate validity assessment

Figure 5

Figure 2. Significant and nonsignificant paths.

Figure 6

Table 5. Path analysis for models with and without controls