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Cited by 1,085

The DOI matches its Crossref record; 181 of the 181 references it cites were found in a registry or an index.

The Too-Much-of-a-Good-Thing Effect in Management

Open access
Pierce, Jason R., Aguinis, Herman·2013·Journal of Management
DOI 10.1177/0149206311410060
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Abstract

A growing body of empirical evidence in the management literature suggests that antecedent variables widely accepted as leading to desirable consequences actually lead to negative outcomes. These increasingly pervasive and often countertheoretical findings permeate levels of analysis (i.e., from micro to macro) and management subfields (e.g., organizational behavior, strategic management). Although seemingly unrelated, the authors contend that this body of empirical research can be accounted for by a meta-theoretical principle they call the too-much-of-a-good-thing effect (TMGT effect). The authors posit that, due to the TMGT effect, all seemingly monotonic positive relations reach context-specific inflection points after which the relations turn asymptotic and often negative, resulting in an overall pattern of curvilinearity. They illustrate how the TMGT effect provides a meta-theoretical explanation for a host of seemingly puzzling results in key areas of organizational behavior (e.g., leadership, personality), human resource management (e.g., job design, personnel selection), entrepreneurship (e.g., new venture planning, firm growth rate), and strategic management (e.g., diversification, organizational slack). Finally, the authors discuss implications of the TMGT effect for theory development, theory testing, and management practice.

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Metadata

Authors
Pierce, J. R., & Aguinis, H.
Venue
Journal of Management
Publisher
SAGE Publications
Published
2011-06-10
Volume
39
Issue
2
Pages
313-338
ISSN
  • 0149-2063 (ISSN-L)
  • 1557-1211
DOI
10.1177/0149206311410060
OpenAlex
W2144783312
Cited by
1,085
References
181
FWCI
45.87
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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