IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/739.html

Productivity outcomes in online labor markets and within-task complexity and difficultly

Author

Listed:
  • Mourelatos, Evaggelos
  • Giannakopoulos, Nicholas
  • Tzagarakis, Manolis

Abstract

We analyze the impact of within-task difficulty and complexity on workers' productivity in online labor markets. Using a randomized control quasi-experiment in AMT we are able to define the difficulty and complexity embodied in requested sub-tasks within a problem-solved task. We find that our productivity measures are negatively related to the difficulty and complexity of a specific sub-task. This finding is robust to several sources of workers' heterogeneity and to different pay schemes.

Suggested Citation

  • Mourelatos, Evaggelos & Giannakopoulos, Nicholas & Tzagarakis, Manolis, 2020. "Productivity outcomes in online labor markets and within-task complexity and difficultly," GLO Discussion Paper Series 739, Global Labor Organization (GLO).
    • Handle: RePEc:zbw:glodps:739
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/227563/1/GLO-DP-0739.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arindrajit Dube & Jeff Jacobs & Suresh Naidu & Siddharth Suri, 2020. "Monopsony in Online Labor Markets," American Economic Review: Insights, American Economic Association, vol. 2(1), pages 33-46, March.
    2. Maria Cubel & Ana Nuevo‐Chiquero & Santiago Sanchez‐Pages & Marian Vidal‐Fernandez, 2016. "Do Personality Traits Affect Productivity? Evidence from the Laboratory," Economic Journal, Royal Economic Society, vol. 0(592), pages 654-681, May.
    3. John J. Horton, 2017. "The Effects of Algorithmic Labor Market Recommendations: Evidence from a Field Experiment," Journal of Labor Economics, University of Chicago Press, vol. 35(2), pages 345-385.
    4. Evangelos Mourelatos & Nicholas Giannakopoulos & Manolis Tzagarakis, 2022. "Personality traits and performance in online labour markets," Behaviour and Information Technology, Taylor & Francis Journals, vol. 41(3), pages 468-484, February.
    5. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    6. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Evangelos Mourelatos & Jaakko Simonen & Simo Hosio & Daniil Likhobaba & Dmitry Ustalov, 2024. "How has the COVID-19 pandemic shaped behavior in crowdsourcing? The role of online labor market training," Journal of Business Economics, Springer, vol. 94(9), pages 1201-1244, November.
    2. Mourelatos, Evangelos & Krimpas, George & Giotopoulos, Konstantinos, 2022. "Sexual identity and Gender Gap in Leadership. A political intention experiment," GLO Discussion Paper Series 1187, Global Labor Organization (GLO).

    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. Mourelatos, Evangelos, 2023. "Does Mood affect Sexual and Gender Discrimination in Hiring Choices? Evidence from Online Experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 106(C).
    2. Mourelatos, Evangelos, 2021. "Personality and Ethics on Online Labor Markets: How mood influences ethical perceptions," EconStor Preprints 244735, ZBW - Leibniz Information Centre for Economics.
    3. Gomez-Herrera, Estrella & Mueller-Langer, Frank, 2024. "Does information disclosure affect the gender gap in bidding behavior? Empirical evidence from a natural experiment on a large online labor platform," Labour Economics, Elsevier, vol. 90(C).
    4. Evangelos Mourelatos & Nicholas Giannakopoulos & Manolis Tzagarakis, 2022. "Personality traits and performance in online labour markets," Behaviour and Information Technology, Taylor & Francis Journals, vol. 41(3), pages 468-484, February.
    5. Mourelatos, Evangelos & Zervas, Panagiotis & Lagios, Dimitris & Tzimas, Giannis, 2024. "Can AI Bridge the Gender Gap in Competitiveness?," GLO Discussion Paper Series 1404, Global Labor Organization (GLO).
    6. Mourelatos, Evangelos & Krimpas, George & Giotopoulos, Konstantinos, 2022. "Sexual identity and Gender Gap in Leadership. A political intention experiment," GLO Discussion Paper Series 1187, Global Labor Organization (GLO).
    7. Simon Gächter & Lingbo Huang & Martin Sefton, 2016. "Combining “real effort” with induced effort costs: the ball-catching task," Experimental Economics, Springer;Economic Science Association, vol. 19(4), pages 687-712, December.
    8. Chen, Daniel L. & Schonger, Martin & Wickens, Chris, 2016. "oTree—An open-source platform for laboratory, online, and field experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 88-97.
    9. 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.
    10. Cantarella, Michele & Strozzi, Chiara, 2019. "Workers in the Crowd: The Labour Market Impact of the Online Platform Economy," IZA Discussion Papers 12327, Institute of Labor Economics (IZA).
    11. Panos Constantinides & Ola Henfridsson & Geoffrey G. Parker, 2018. "Introduction—Platforms and Infrastructures in the Digital Age," Information Systems Research, INFORMS, vol. 29(2), pages 381-400, June.
    12. Dato, Simon & Feess, Eberhard & Nieken, Petra, 2019. "Lying and reciprocity," Games and Economic Behavior, Elsevier, vol. 118(C), pages 193-218.
    13. Benjamin Beranek & Robin Cubitt & Simon Gächter, 2015. "Stated and revealed inequality aversion in three subject pools," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 43-58, July.
    14. Tim Straub & Henner Gimpel & Florian Teschner & Christof Weinhardt, 2015. "How (not) to Incent Crowd Workers," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(3), pages 167-179, June.
    15. Aurelie Ouss & Alexander Peysakhovich, 2015. "When Punishment Doesn't Pay: "Cold Glow" and Decisions to Punish," Journal of Law and Economics, University of Chicago Press, vol. 58(3).
    16. Gagnon, Nickolas & Bosmans, Kristof & Riedl, Arno, 2020. "The Effect of Unfair Chances and Gender Discrimination on Labor Supply," Research Memorandum 005, Maastricht University, Graduate School of Business and Economics (GSBE).
    17. Hoffmann, Christin & Hoppe, Julia Amelie & Ziemann, Niklas, 2022. "Faster, harder, greener? Empirical evidence on the role of the individual Pace of Life for productivity and pro-environmental behavior," Ecological Economics, Elsevier, vol. 191(C).
    18. Saara Hämäläinen & Vaiva Petrikaitė, 2024. "Prediction algorithms in matching platforms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(3), pages 979-1020, November.
    19. Antonio A. Arechar & Simon Gächter & Lucas Molleman, 2018. "Conducting interactive experiments online," Experimental Economics, Springer;Economic Science Association, vol. 21(1), pages 99-131, March.
    20. Cason, Timothy N. & Lau, Sau-Him Paul & Mui, Vai-Lam, 2019. "Prior interaction, identity, and cooperation in the Inter-group Prisoner's Dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 613-629.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

    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:zbw:glodps:739. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/glabode.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.