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Research Article

Does my leader care about my subgroup? A multilevel model of team faultlines, LMX quality, and employee absenteeism

ORCID Icon, ORCID Icon & ORCID Icon
Pages 234-244 | Received 07 Sep 2021, Accepted 11 Oct 2022, Published online: 22 Oct 2022
 

ABSTRACT

This article investigates the impact of demographic team faultlines on employee absenteeism by considering the level of leader-member exchange (LMX) that supervisors develop with members from different subgroups in a team. We integrate faultline research with the literature on LMX differentiation to build an integrative multilevel model to explain individual absenteeism behaviour. Drawing from social categorization and social comparison theory, we propose that members of subgroups that receive less favourable LMX treatment than their outgroup are particularly likely to increase their absenteeism behaviour due to faultline-induced social categorization. Our predictions receive empirical support in a study with 164 employees from a German electrical engineering company. We discuss implications for the faultline and LMX literature and executives who lead diverse teams.

Acknowledgement

We would like to acknowledge the helpful comments and suggestions by two anonymous reviewers. We also thank Sophia Zimmermann for her support during data collection.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Ethical approval was not provided for this study on human participants because for field survey studies the researchers’ university does not require an ethical approval. The participants provided their written informed consent to participate in this study.

2. Including multiple combination of the control variables did not change the pattern of results (see Robustness Check Section).

3. Note that when we included all three control variables simultaneously, the model did not converge (for a extensive discussion of convergence problems in Poisson models see, Silva & Tenreyro, Citation2011). To circumvent convergence problems, we estimated a series of models where we entered each of the controls individually. In addition we entered pairs of the three control variables.

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