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Managing Marginal Employees: The Use of Warnings and Dismissals

Authors: Charles A. O'Reilly; Barton A. Weitz;

Managing Marginal Employees: The Use of Warnings and Dismissals

Abstract

The authors gratefully acknowledge the invaluable assistance of Susan Hoyt in conducting the research and the comments of George Strauss on an earlier version of the manuscript. This study was supported in part by a research grant from the UCLA Academic Senate. This study examines how first-level supervisors identify and manage marginal employees. It was expected that supervisors would differ both in their approaches to marginal employees and in their willingness to use negative sanctions (informal warnings, formal warnings, and dismissals). Results corroborated these expectations and showed a significant positive correlation between supervisors' use of sanctions and ratings of unit performance by higher level managers. An interpretation based on social learning theory rather than operant conditioning is offered; it suggests that appropriate use of sanctions may be perceived by employees as legitimate and may be conducive to the development of productive group norms.

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
77
Top 10%
Top 1%
Top 10%
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