Cited by 46Emotional Labor in ProfessionsEthics in Business and EducationJob Satisfaction and Organizational Behavior

An Ethical Analysis of Emotional Labor

Barry, Bruce, Olekalns, Mara, Rees, Laura·2019·Journal of Business Ethics

Integrity signals

Registry

Crossref · 10.1007/s10551-018-3906-2

Cites

112 of 112 references verified0 citation errors · 0 not checkable

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  • Suppressing negative emotions tends to increase emotional exhaustion and depersonalization and decrease feelings of personal accomplishment.

    “Suppressing negative emotions tends to increase emotional exhaustion and depersonalization and decrease feelings of personal accomplishment (Barry et al., 2019;Goodwin et al., 2011;Pugh et al., 2011).”

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Authors
Barry, B., Olekalns, M., & Rees, L.
Affiliations
  • Vanderbilt University (US)
  • The University of Melbourne (AU)
  • University of Missouri–Kansas City (US)
Corresponding author
Rees, Laura
Venue
Journal of Business Ethics
Published
2018-05-08
Volume
160
Issue
1
Pages
17-34
ISSN
  • 0167-4544 (ISSN-L)
  • 1573-0697
OpenAlex
W2802392119
Cited by
46
References
122
Citations by year
2026: 2 · 2025: 2 · 2024: 11 · 2023: 8 · 2022: 9 · 2021: 7 · 2020: 3 · 2019: 3 · 2018: 1
FWCI
7.97
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Business Ethics (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Emotional Labor in Professions
  • Social Sciences › Decision Sciences › Information Systems and Management › Ethics in Business and Education
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
Keywords
emotional labor, employee rights and obligations, organizational requirements, emotional display, normative analysis, management practices

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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