Too Good to Hire? Capability and Inferences about Commitment in Labor Markets
We examine how signals of a candidate’s capability affect perceptions of that person’s commitment to an employer. In four experimental studies that use hiring managers as subjects, we test and show that managers perceive highly capable candidates to have lower commitment to the organization than les...
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Published in | Administrative science quarterly Vol. 65; no. 2; pp. 275 - 313 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Los Angeles, CA
Sage Publications, Inc
01.06.2020
SAGE Publications SAGE PUBLICATIONS, INC |
Subjects | |
Online Access | Get full text |
ISSN | 0001-8392 1930-3815 |
DOI | 10.1177/0001839219840022 |
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Abstract | We examine how signals of a candidate’s capability affect perceptions of that person’s commitment to an employer. In four experimental studies that use hiring managers as subjects, we test and show that managers perceive highly capable candidates to have lower commitment to the organization than less capable but adequate candidates and, as a result, penalize high-capability candidates in the hiring process. Our results show that managers have concerns about a high-capability candidate’s future commitment to the organization because they view highly capable candidates as having lower levels of organizational interest—meaning they care less about the mission and values of the organization and exert a lower level of effort toward those ends—and because they assume highly capable candidates have more outside job options, increasing their flight risk. Our findings highlight that capability signals do not necessarily afford candidates an advantage in selection, suggesting an upper limit on credentials and other signals of capability in helping candidates get jobs. Our study contributes to research on labor markets, human capital, and credentialing by offering a theory for why and when capability signals can negatively influence job candidate selection decisions. |
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AbstractList | We examine how signals of a candidate’s capability affect perceptions of that person’s commitment to an employer. In four experimental studies that use hiring managers as subjects, we test and show that managers perceive highly capable candidates to have lower commitment to the organization than less capable but adequate candidates and, as a result, penalize high-capability candidates in the hiring process. Our results show that managers have concerns about a high-capability candidate’s future commitment to the organization because they view highly capable candidates as having lower levels of organizational interest—meaning they care less about the mission and values of the organization and exert a lower level of effort toward those ends—and because they assume highly capable candidates have more outside job options, increasing their flight risk. Our findings highlight that capability signals do not necessarily afford candidates an advantage in selection, suggesting an upper limit on credentials and other signals of capability in helping candidates get jobs. Our study contributes to research on labor markets, human capital, and credentialing by offering a theory for why and when capability signals can negatively influence job candidate selection decisions. |
Author | Hahl, Oliver Galperin, Roman V. Guo, Jerry Sterling, Adina D. |
Author_xml | – sequence: 1 givenname: Roman V. surname: Galperin fullname: Galperin, Roman V. – sequence: 2 givenname: Oliver surname: Hahl fullname: Hahl, Oliver – sequence: 3 givenname: Adina D. surname: Sterling fullname: Sterling, Adina D. – sequence: 4 givenname: Jerry surname: Guo fullname: Guo, Jerry |
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Snippet | We examine how signals of a candidate’s capability affect perceptions of that person’s commitment to an employer. In four experimental studies that use hiring... |
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SubjectTerms | Candidates Certification Commitment Credentials Employers Hiring Human capital Labor market Managers Meaning Values |
Title | Too Good to Hire? Capability and Inferences about Commitment in Labor Markets |
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