IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp14502.html
   My bibliography  Save this paper

Why Making Promotion after a Burnout Is like Boiling the Ocean

Author

Listed:
  • Sterkens, Philippe

    (Ghent University)

  • Baert, Stijn

    (Ghent University)

  • Rooman, Claudia

    (Ghent University)

  • Derous, Eva

    (Ghent University)

Abstract

Recent studies have explored hiring discrimination as an obstacle to former burnout patients. Many workers, however, return to the same employer, where they face an even more severe aftermath of burnout syndrome: promotion discrimination. To our knowledge, we are the first to directly address this issue in research. More specifically, we conducted a vignette experiment with 406 genuine managers, testing the potential of the main burnout stigma theoretically described in the literature as potential mediators of promotion discrimination. Estimates reveal that compared to employees without an employment interruption, former burnout patients have no less than a 34.4% lower probability of receiving a promotion. Moreover, these employees are perceived as having low (1) leadership, (2) learning capacity, (3) motivation, (4) autonomy and (5) stress tolerance, as well as being (6) less capable of taking on an exemplary role, (7) having worse current and (8) future health, (9) collaborating with them is regarded more negatively, and (10) managers perceive them as having fewer options to leave the organisation if denied a promotion. Four of these perceptions, namely lower leadership capacities, stress tolerance, abilities to take on an exemplary role and chances of finding another job explain almost half the burnout effect on promotion probabilities.

Suggested Citation

  • Sterkens, Philippe & Baert, Stijn & Rooman, Claudia & Derous, Eva, 2021. "Why Making Promotion after a Burnout Is like Boiling the Ocean," IZA Discussion Papers 14502, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp14502
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp14502.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Piopiunik, Marc & Schwerdt, Guido & Simon, Lisa & Woessmann, Ludger, 2020. "Skills, signals, and employability: An experimental investigation," European Economic Review, Elsevier, vol. 123(C).
    2. Jed DeVaro & Antti Kauhanen & Nelli Valmari, 2019. "Internal and External Hiring," ILR Review, Cornell University, ILR School, vol. 72(4), pages 981-1008, August.
    3. Paul Milgrom & Sharon Oster, 1987. "Job Discrimination, Market Forces, and the Invisibility Hypothesis," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(3), pages 453-476.
    4. Stijn Baert & Ann-Sophie De Pauw & Nick Deschacht, 2016. "Do Employer Preferences Contribute to Sticky Floors?," ILR Review, Cornell University, ILR School, vol. 69(3), pages 714-736, May.
    5. Van Borm, Hannah & Burn, Ian & Baert, Stijn, 2021. "What Does a Job Candidate's Age Signal to Employers?," Labour Economics, Elsevier, vol. 71(C).
    6. Kübler, Dorothea & Schmid, Julia & Stüber, Robert, 2018. "Gender discrimination in hiring across occupations: a nationally-representative vignette study," Labour Economics, Elsevier, vol. 55(C), pages 215-229.
    7. Baert, Stijn & De Pauw, Ann-Sophie, 2014. "Is ethnic discrimination due to distaste or statistics?," Economics Letters, Elsevier, vol. 125(2), pages 270-273.
    8. Sterkens, Philippe & Baert, Stijn & Rooman, Claudia & Derous, Eva, 2021. "As if it weren’t hard enough already: Breaking down hiring discrimination following burnout," Economics & Human Biology, Elsevier, vol. 43(C).
    9. Sato, Kaori & Hashimoto, Yuki & Owan, Hideo, 2019. "Gender differences in Career," Journal of the Japanese and International Economies, Elsevier, vol. 53(C), pages 1-1.
    10. Albrecht, Konstanze & von Essen, Emma & Parys, Juliane & Szech, Nora, 2013. "Updating, self-confidence, and discrimination," European Economic Review, Elsevier, vol. 60(C), pages 144-169.
    11. James Johnston, 2002. "Tenure, promotion and executive remuneration," Applied Economics, Taylor & Francis Journals, vol. 34(8), pages 993-997.
    12. Baert, Stijn & Norga, Jennifer & Thuy, Yannick & Van Hecke, Marieke, 2016. "Getting grey hairs in the labour market. An alternative experiment on age discrimination," Journal of Economic Psychology, Elsevier, vol. 57(C), pages 86-101.
    13. Ann-Sophie De Pauw, 2016. "Do employer preferences contribute to sticky floors ?," Post-Print hal-01772258, HAL.
    14. David Neumark, 2018. "Experimental Research on Labor Market Discrimination," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 799-866, September.
    15. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    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. Van Borm, Hannah & Baert, Stijn, 2022. "Diving in the minds of recruiters: What triggers gender stereotypes in hiring?," GLO Discussion Paper Series 1083, Global Labor Organization (GLO).
    2. Carlsson, Magnus & Eriksson, Stefan, 2019. "Age discrimination in hiring decisions: Evidence from a field experiment in the labor market," Labour Economics, Elsevier, vol. 59(C), pages 173-183.
    3. Sterkens, Philippe & Baert, Stijn & Rooman, Claudia & Derous, Eva, 2021. "As if it weren’t hard enough already: Breaking down hiring discrimination following burnout," Economics & Human Biology, Elsevier, vol. 43(C).
    4. Becker, Sascha O. & Fernandes, Ana & Weichselbaumer, Doris, 2019. "Discrimination in hiring based on potential and realized fertility: Evidence from a large-scale field experiment," Labour Economics, Elsevier, vol. 59(C), pages 139-152.
    5. Hannah Van Borm & Louis Lippens & Stijn Baert, 2022. "An Arab, an Asian, and a Black guy walk into a job interview: ethnic stigma in hiring after controlling for social class," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 22/1054, Ghent University, Faculty of Economics and Business Administration.
    6. Philippe Sterkens & Stijn Baert & Claudia Rooman & Eva Derous, 2020. "As if it weren’t hard enough already: Breaking down hiring discrimination following burnout A causal machine learning evaluation of training in Belgium," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/1000, Ghent University, Faculty of Economics and Business Administration.
    7. Daniel Martin & Philip Marx, 2022. "A Robust Test of Prejudice for Discrimination Experiments," Management Science, INFORMS, vol. 68(6), pages 4527-4536, June.
    8. Mohanty, Smrutirekha, 2021. "A distributional analysis of the gender wage gap among technical degree and diploma holders in urban India," International Journal of Educational Development, Elsevier, vol. 80(C).
    9. Piopiunik, Marc & Schwerdt, Guido & Simon, Lisa & Woessmann, Ludger, 2020. "Skills, signals, and employability: An experimental investigation," European Economic Review, Elsevier, vol. 123(C).
    10. Axana Dalle & Philippe Sterkens & Stijn Baert, 2023. "A poisoned gift? The hireability signals of an income-support program for the senior unemployed," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1066, Ghent University, Faculty of Economics and Business Administration.
    11. Valfort, Marie-Anne, 2020. "Anti-Muslim discrimination in France: Evidence from a field experiment," World Development, Elsevier, vol. 135(C).
    12. Igor Asanov & Maria Mavlikeeva, 2023. "Can group identity explain the gender gap in the recruitment process?," Industrial Relations Journal, Wiley Blackwell, vol. 54(1), pages 95-113, January.
    13. Gaddis, S. Michael, 2018. "An Introduction to Audit Studies in the Social Sciences," SocArXiv e5hfc, Center for Open Science.
    14. Mladen Adamovic & Andreas Leibbrandt, 2023. "A large‐scale field experiment on occupational gender segregation and hiring discrimination," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 62(1), pages 34-59, January.
    15. Ali M. Ahmed & Elisabeth Lång, 2017. "The employability of ex-offenders: a field experiment in the Swedish labor market," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 6(1), pages 1-23, December.
    16. Élisabeth Tovar & Matthieu Bunel, 2019. "Profit vs morality: how unfair is labor market discrimination? Results from a survey experiment," EconomiX Working Papers 2019-25, University of Paris Nanterre, EconomiX.
    17. Van Borm, Hannah & Burn, Ian & Baert, Stijn, 2021. "What Does a Job Candidate's Age Signal to Employers?," Labour Economics, Elsevier, vol. 71(C).
    18. Giovanni Busetta & Fabio Fiorillo & Giulio Palomba, 2021. "The impact of attractiveness on job opportunities in Italy: a gender field experiment," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(1), pages 171-201, April.
    19. Brecht Neyt & Stijn Baert & Jana Vynckier, 2022. "Job Prestige and Mobile Dating Success: A Field Experiment," De Economist, Springer, vol. 170(4), pages 435-458, November.
    20. Lennart Struth & Max Thon, 2022. "Discrimination, Quotas, and Stereotypes," ECONtribute Discussion Papers Series 188, University of Bonn and University of Cologne, Germany.

    More about this item

    Keywords

    burnout; statistical discrimination; invisibility hypothesis; taste-based discrimination; promotion;
    All these keywords.

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:iza:izadps:dp14502. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    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.