IDEAS home Printed from https://ideas.repec.org/a/eee/jobhdp/v165y2021icp213-227.html
   My bibliography  Save this article

Distribution neglect in performance evaluations

Author

Listed:
  • Awtrey, Eli
  • Thornley, Nico
  • Dannals, Jennifer E.
  • Barnes, Christopher M.
  • Uhlmann, Eric Luis

Abstract

Five empirical studies, including both laboratory experiments and an archival investigation, provide evidence that decision makers often fail to consider variability and skew when making judgments about performance. We term this distribution neglect. Participants’ spontaneous explanations for group differences in elite achievement overwhelmingly invoked mean differences rather than group differences in variability, even when the complete distribution and summary statistics were provided (Study 1). A longitudinal examination indicates that NBA teams overweight average performance and underweight consistency of performance when deciding players’ contracts (Study 2), providing evidence that neglecting variance information leads to suboptimal judgments. In a manufacturing scenario involving monitoring assembly line workers, participants were more accurate at identifying top (high mean) performers than consistent (low variability) performers (Study 3). In a hiring simulation, decision makers were more likely to factor in variance when performance data was presented visually as a histogram (Study 4). Finally, participants’ spontaneous explanations for others’ self-assessments of ability assumed egocentric bias, when a skewed performance distribution was also a plausible contributor (Study 5). Individual differences (need for cognition) and task differences (such as style of information display) were associated with increased distribution-based reasoning in multiple studies, suggesting potential boundary conditions for further investigation. Organizational implications, and additional potential remedies for distribution neglect, are discussed.

Suggested Citation

  • Awtrey, Eli & Thornley, Nico & Dannals, Jennifer E. & Barnes, Christopher M. & Uhlmann, Eric Luis, 2021. "Distribution neglect in performance evaluations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 165(C), pages 213-227.
  • Handle: RePEc:eee:jobhdp:v:165:y:2021:i:c:p:213-227
    DOI: 10.1016/j.obhdp.2021.04.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0749597821000467
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.obhdp.2021.04.007?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rachel Croson & James Sundali, 2005. "The Gambler’s Fallacy and the Hot Hand: Empirical Data from Casinos," Journal of Risk and Uncertainty, Springer, vol. 30(3), pages 195-209, May.
    2. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    3. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. Maria De Paola & Vincenzo Scoppa, 2012. "The Effects of Managerial Turnover," Journal of Sports Economics, , vol. 13(2), pages 152-168, April.
    6. Jahn K. Hakes & Raymond D. Sauer, 2006. "An Economic Evaluation of the Moneyball Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 20(3), pages 173-186, Summer.
    7. Beasley, Mark S. & Clune, Richard & Hermanson, Dana R., 2005. "Enterprise risk management: An empirical analysis of factors associated with the extent of implementation," Journal of Accounting and Public Policy, Elsevier, vol. 24(6), pages 521-531.
    8. Logg, Jennifer M. & Minson, Julia A. & Moore, Don A., 2019. "Algorithm appreciation: People prefer algorithmic to human judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 90-103.
    9. Greenhaus, Jeffrey H. & Parasuraman, Saroj, 1993. "Job Performance Attributions and Career Advancement Prospects: An Examination of Gender and Race Effects," Organizational Behavior and Human Decision Processes, Elsevier, vol. 55(2), pages 273-297, July.
    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. Bryce McLaughlin & Jann Spiess, 2022. "Algorithmic Assistance with Recommendation-Dependent Preferences," Papers 2208.07626, arXiv.org, revised Jan 2024.
    2. Hemesath, Sebastian & Tepe, Markus, 2023. "Framing the approval to test self-driving cars on public roads. The effect of safety and competitiveness on citizens' agreement," Technology in Society, Elsevier, vol. 72(C).
    3. Markus Jung & Mischa Seiter, 2021. "Towards a better understanding on mitigating algorithm aversion in forecasting: an experimental study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 32(4), pages 495-516, December.
    4. Shige Makino & Christine M. Chan, 2017. "Skew and heavy-tail effects on firm performance," Strategic Management Journal, Wiley Blackwell, vol. 38(8), pages 1721-1740, August.
    5. Hopfensitz, Astrid, 2009. "Previous outcomes and reference dependence: A meta study of repeated investment tasks with and without restricted feedback," MPRA Paper 16096, University Library of Munich, Germany.
    6. Ekaterina Jussupow & Kai Spohrer & Armin Heinzl & Joshua Gawlitza, 2021. "Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence," Information Systems Research, INFORMS, vol. 32(3), pages 713-735, September.
    7. repec:cup:judgdm:v:15:y:2020:i:3:p:449-451 is not listed on IDEAS
    8. Kai Barron, 2021. "Belief updating: does the ‘good-news, bad-news’ asymmetry extend to purely financial domains?," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 31-58, March.
    9. Kim Kaivanto & Eike Kroll, 2014. "Alternation bias and reduction in St. Petersburg gambles," Working Papers 65600286, Lancaster University Management School, Economics Department.
    10. repec:cup:judgdm:v:11:y:2016:i:5:p:424-440 is not listed on IDEAS
    11. Kevin Bauer & Andrej Gill, 2024. "Mirror, Mirror on the Wall: Algorithmic Assessments, Transparency, and Self-Fulfilling Prophecies," Information Systems Research, INFORMS, vol. 35(1), pages 226-248, March.
    12. M.S.M. Lim & G. Jocham & L.T. Hunt & T.E.J. Behrens & R.D. Rogers, 2015. "Impulsivity and predictive control are associated with suboptimal action-selection and action-value learning in regular gamblers," International Gambling Studies, Taylor & Francis Journals, vol. 15(3), pages 489-505, December.
    13. Sheremeta, Roman, 2014. "Behavior in Contests," MPRA Paper 57451, University Library of Munich, Germany.
    14. Mahmud, Hasan & Islam, A.K.M. Najmul & Mitra, Ranjan Kumar, 2023. "What drives managers towards algorithm aversion and how to overcome it? Mitigating the impact of innovation resistance through technology readiness," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    15. David Burner & Michael McKee & Rudy Santore, 2008. "Hand in the Cookie Jar: An Experimental Investigation of Equity‐Based Compensation and Managerial Fraud," Southern Economic Journal, John Wiley & Sons, vol. 75(1), pages 261-278, July.
    16. Jürgen Huber & Michael Kirchler & Thomas Stöckl, 2010. "The hot hand belief and the gambler’s fallacy in investment decisions under risk," Theory and Decision, Springer, vol. 68(4), pages 445-462, April.
    17. SATISH KUMAR & Nisha Goyal, 2019. "Exploring Behavioural Biases among Indian Investors: A Qualitative Inquiry," Proceedings of International Academic Conferences 9010790, International Institute of Social and Economic Sciences.
    18. Bucciol, Alessandro & Hu, Alessio & Zarri, Luca, 2019. "The effects of prior outcomes on managerial risk taking: Evidence from Italian professional soccer," Journal of Economic Psychology, Elsevier, vol. 75(PB).
    19. Neszveda, G., 2019. "Essays on behavioral finance," Other publications TiSEM 05059039-5236-42a3-be1b-3, Tilburg University, School of Economics and Management.
    20. Maximilian Rüdisser & Raphael Flepp & Egon Franck, 2017. "When do reference points update? A field analysis of the effect of prior gains and losses on risk-taking over time," Working Papers 369, University of Zurich, Department of Business Administration (IBW).
    21. Reio Tanji, 2021. "Reference Dependence and Monetary Incentives: Evidence from Major League Baseball," Discussion Papers in Economics and Business 20-23, Osaka University, Graduate School of Economics.
    22. Brian Goff & Stephen L. Locke, 2019. "Revisiting Romer: Digging Deeper Into Influences on NFL Managerial Decisions," Journal of Sports Economics, , vol. 20(5), pages 671-689, June.

    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:eee:jobhdp:v:165:y:2021:i:c:p:213-227. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/obhdp .

    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.