IDEAS home Printed from https://ideas.repec.org/a/bla/socsci/v102y2021i4p2006-2019.html
   My bibliography  Save this article

Are people better employees than machines? Dehumanizing language and employee performance appraisals

Author

Listed:
  • Luke Fowler
  • Stephen Utych

Abstract

Objective Although performance appraisals are based on objective procedures, cognitive biases from appraisers may create avenues for errors in judgment of employee performance. Dehumanizing language, or metaphors that characterize humans in nonhuman terms (e.g., cogs in a machine), is one important way cognitive biases can occur Method We conduct a survey experiment to determine if dehumanizing language affects perceptions of employee value or competency within the context of performance appraisals. Result Findings show that when employees are referred to in mechanistic terms, respondents perceive that employee to be deserve hire compensation, and be more competent, as compared to referring to employees in human or animalistic terms. Conclusion Conclusions suggest dehumanizing language is an important type of cognitive bias that affects individuals in administrative environments, and the managerial and ethical implications of its use require further examination.

Suggested Citation

  • Luke Fowler & Stephen Utych, 2021. "Are people better employees than machines? Dehumanizing language and employee performance appraisals," Social Science Quarterly, Southwestern Social Science Association, vol. 102(4), pages 2006-2019, July.
    • Handle: RePEc:bla:socsci:v:102:y:2021:i:4:p:2006-2019
    DOI: 10.1111/ssqu.13057
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ssqu.13057
    Download Restriction: no
    File URL: https://libkey.io/10.1111/ssqu.13057?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. David Johnson & John Barry Ryan, 2020. "Amazon Mechanical Turk workers can provide consistent and economically meaningful data," Southern Economic Journal, John Wiley & Sons, vol. 87(1), pages 369-385, July.
    2. T.K. Das & Bing‐Sheng Teng, 1999. "Cognitive Biases and Strategic Decision Processes: An Integrative Perspective," Journal of Management Studies, Wiley Blackwell, vol. 36(6), pages 757-778, November.
    3. Kevin Arceneaux, 2012. "Cognitive Biases and the Strength of Political Arguments," American Journal of Political Science, John Wiley & Sons, vol. 56(2), pages 271-285, April.
    4. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    5. Mutz, Diana C. & Pemantle, Robin, 2015. "Standards for Experimental Research: Encouraging a Better Understanding of Experimental Methods," Journal of Experimental Political Science, Cambridge University Press, vol. 2(2), pages 192-215, January.
    6. Tuure Väyrynen & Sari Laari-Salmela, 2018. "Men, Mammals, or Machines? Dehumanization Embedded in Organizational Practices," Journal of Business Ethics, Springer, vol. 147(1), pages 95-113, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abel Brodeur, Nikolai M. Cook, Anthony Heyes, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell Us about Publication Bias and p-Hacking in Online Experiments," LCERPA Working Papers am0133, Laurier Centre for Economic Research and Policy Analysis.
    2. Haas, Nicholas & Hassan, Mazen & Mansour, Sarah & Morton, Rebecca B., 2021. "Polarizing information and support for reform," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 883-901.
    3. Danny Hayes & Jennifer L. Lawless & Gail Baitinger, 2014. "Who Cares What They Wear? Media, Gender, and the Influence of Candidate Appearance," Social Science Quarterly, Southwestern Social Science Association, vol. 95(5), pages 1194-1212, December.
    4. Kaitlynn Sandstrom‐Mistry & Frank Lupi & Hyunjung Kim & Joseph A. Herriges, 2023. "Comparing water quality valuation across probability and non‐probability samples," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(2), pages 744-761, June.
    5. Kevin E. Levay & Jeremy Freese & James N. Druckman, 2016. "The Demographic and Political Composition of Mechanical Turk Samples," SAGE Open, , vol. 6(1), pages 21582440166, March.
    6. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell us about p-Hacking and Publication Bias in Online Experiments," GLO Discussion Paper Series 1157, Global Labor Organization (GLO).
    7. repec:osf:metaar:a9vhr_v1 is not listed on IDEAS
    8. Johannes G. Jaspersen & Marc A. Ragin & Justin R. Sydnor, 2022. "Insurance demand experiments: Comparing crowdworking to the lab," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(4), pages 1077-1107, December.
    9. Adam S. Chilton, 2015. "The Laws of War and Public Opinion: An Experimental Study," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 171(1), pages 181-201, March.
    10. David Chavanne & Zak Danz & Jitu Dribssa & Rachel Powell & Matthew Sambor, 2022. "Context and the Perceived Fairness of Price Increases Coming out of COVID‐19," Social Science Quarterly, Southwestern Social Science Association, vol. 103(1), pages 55-68, January.
    11. Scott Simon Boddery & Damon Cann & Laura Moyer & Jeff Yates, 2023. "The role of cable news hosts in public support for Supreme Court decisions," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 20(4), pages 1045-1069, December.
    12. Pan, Jing Yu & Liu, Dahai, 2022. "Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behavior model," Transport Policy, Elsevier, vol. 119(C), pages 32-44.
    13. repec:plo:pone00:0085508 is not listed on IDEAS
    14. Lala Muradova & Ross James Gildea, 2021. "Oil wealth and US public support for war," Conflict Management and Peace Science, Peace Science Society (International), vol. 38(1), pages 3-19, January.
    15. Michele Cantarella & Chiara Strozzi, 2021. "Workers in the crowd: the labor market impact of the online platform economy [An evaluation of instrumental variable strategies for estimating the effects of catholic schooling]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(6), pages 1429-1458.
    16. Robbett, Andrea & Matthews, Peter Hans, 2018. "Partisan bias and expressive voting," Journal of Public Economics, Elsevier, vol. 157(C), pages 107-120.
    17. Brañas-Garza, Pablo & Capraro, Valerio & Rascón-Ramírez, Ericka, 2018. "Gender differences in altruism on Mechanical Turk: Expectations and actual behaviour," Economics Letters, Elsevier, vol. 170(C), pages 19-23.
    18. Logan S. Casey & Jesse Chandler & Adam Seth Levine & Andrew Proctor & Dara Z. Strolovitch, 2017. "Intertemporal Differences Among MTurk Workers: Time-Based Sample Variations and Implications for Online Data Collection," SAGE Open, , vol. 7(2), pages 21582440177, June.
    19. Winter, Scott R. & Rice, Stephen & Rains, Taylor & Milner, Mattie & Mehta, Rian, 2017. "A longitudinal study on the alteration of consumer perceptions and the use of pilot medication," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 100-106.
    20. Damian Clarke & Sonia Oreffice & Climent Quintana‐Domeque, 2021. "On the Value of Birth Weight," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1130-1159, October.
    21. Wladislaw Mill & Jonathan Stäbler, 2023. "Spite in Litigation," CESifo Working Paper Series 10290, CESifo.
    22. Aigul Mavletova & James Witte, 2017. "Is the willingness to take risks contagious? A comparison of immigrants and native-born in the United States," Journal of Risk Research, Taylor & Francis Journals, vol. 20(7), pages 827-845, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:socsci:v:102:y:2021:i:4:p:2006-2019. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0038-4941 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.