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Cited by 615

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Firm reputation and applicant pool characteristics

Turban, Daniel B., Cable, Daniel M.·2003·Journal of Organizational Behavior

Abstract

Scholars have suggested that a firm's reputation can provide it with a competitive advantage by attracting more, and possibly higher‐caliber, applicants. No research has actually investigated this relationship, however, in large part because researchers have not assessed applicant pool characteristics but instead have measured applicants' intentions. Therefore, we conducted two studies to investigate whether organizational reputation influenced the number and the quality of applicants actually seeking positions with firms. Company reputation was operationalized using two different published reputation measures, and applicant quality data were obtained from career services offices at business schools at two universities. Results from both studies supported the previously untested belief that firms with better reputations attract more applicants. Furthermore, some evidence suggested that firms with better reputations could select higher‐quality applicants. Copyright © 2003 John Wiley & Sons, Ltd.

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Metadata

Authors
Turban, D. B., & Cable, D. M.
Venue
Journal of Organizational Behavior
Publisher
Wiley
Published
2003-08-12
Volume
24
Issue
6
Pages
733-751
ISSN
  • 0894-3796 (ISSN-L)
  • 1099-1379
OpenAlex
W2086142012
Cited by
615
References
54
FWCI
9.12
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Firm reputation and applicant pool characteristics. https://app.cochat.ai/papers/10.1002/job.215
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Turban, D. B., & Cable, D. M. (2003). Firm reputation and applicant pool characteristics. Journal of Organizational Behavior. https://doi.org/10.1002/job.215

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

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.