IDEAS home Printed from https://ideas.repec.org/p/zbw/vfsc23/277692.html
   My bibliography  Save this paper

Measuring Preferences for Algorithms - Are people really algorithm averse after seeing the algorithm perform?

Author

Listed:
  • Ivanova-Stenzel, Radosveta
  • Tolksdorf, Michel

Abstract

No abstract is available for this item.

Suggested Citation

  • Ivanova-Stenzel, Radosveta & Tolksdorf, Michel, 2023. "Measuring Preferences for Algorithms - Are people really algorithm averse after seeing the algorithm perform?," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277692, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc23:277692
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/277692/1/vfs-2023-pid-87307.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ben Greiner, 2015. "Subject pool recruitment procedures: organizing experiments with ORSEE," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 114-125, July.
    2. 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.
    3. 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.
    4. Dargnies, Marie-Pierre & Hakimov, Rustamdjan & Kübler, Dorothea, 2022. "Aversion to hiring algorithms: Transparency, gender profiling, and self-confidence," Discussion Papers, Research Unit: Market Behavior SP II 2022-202, WZB Berlin Social Science Center.
    5. Kocher, Martin G. & Lahno, Amrei Marie & Trautmann, Stefan T., 2018. "Ambiguity aversion is not universal," European Economic Review, Elsevier, vol. 101(C), pages 268-283.
    6. Jussupow, Ekaterina & Benbasat, Izak & Heinzl, Armin, 2020. "Why Are We Averse Towards Algorithms? A Comprehensive Literature Review on Algorithm Aversion," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138565, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Filiz, Ibrahim & Judek, Jan René & Lorenz, Marco & Spiwoks, Markus, 2021. "Reducing algorithm aversion through experience," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    8. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    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. Zulia Gubaydullina & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2022. "Comparing Different Kinds of Influence on an Algorithm in Its Forecasting Process and Their Impact on Algorithm Aversion," Businesses, MDPI, vol. 2(4), pages 1-23, October.
    2. Jan René Judek, 2024. "Willingness to Use Algorithms Varies with Social Information on Weak vs. Strong Adoption: An Experimental Study on Algorithm Aversion," FinTech, MDPI, vol. 3(1), pages 1-11, January.
    3. Alexia GAUDEUL & Caterina GIANNETTI, 2023. "Trade-offs in the design of financial algorithms," Discussion Papers 2023/288, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    4. 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).
    5. Mallory Avery & Andreas Leibbrandt & Joseph Vecci, 2023. "Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech," Monash Economics Working Papers 2023-09, Monash University, Department of Economics.
    6. Xu, Yilong & Xu, Xiaogeng & Tucker, Steven, 2018. "Ambiguity attitudes in the loss domain: Decisions for self versus others," Economics Letters, Elsevier, vol. 170(C), pages 100-103.
    7. Mathieu Chevrier & Brice Corgnet & Eric Guerci & Julie Rosaz, 2024. "Algorithm Credulity: Human and Algorithmic Advice in Prediction Experiments," GREDEG Working Papers 2024-03, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    8. Wendelin Schnedler & Nina Lucia Stephan, 2020. "Revisiting a Remedy Against Chains of Unkindness," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(3), pages 347-364, July.
    9. Kyung Hwan Baik & Subhasish M. Chowdhury & Abhijit Ramalingam, 2021. "Group size and matching protocol in contests," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(4), pages 1716-1736, November.
    10. David J. Cooper & Krista Saral & Marie Claire Villeval, 2021. "Why Join a Team?," Management Science, INFORMS, vol. 67(11), pages 6980-6997, November.
    11. Zakaria Babutsidze & Nobuyuki Hanaki & Adam Zylbersztejn, 2019. "Digital Communication and Swift Trust," Post-Print halshs-02409314, HAL.
    12. Galliera, Arianna, 2018. "Self-selecting random or cumulative pay? A bargaining experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 72(C), pages 106-120.
    13. Gächter, Simon & Starmer, Chris & Tufano, Fabio, 2022. "Measuring "Group Cohesion" to Reveal the Power of Social Relationships in Team Production," IZA Discussion Papers 15512, Institute of Labor Economics (IZA).
    14. Cornaglia, Francesca & Drouvelis, Michalis & Masella, Paolo, 2019. "Competition and the role of group identity," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 136-145.
    15. Gantner, Anita & Horn, Kristian & Kerschbamer, Rudolf, 2016. "Fair and efficient division through unanimity bargaining when claims are subjective," Journal of Economic Psychology, Elsevier, vol. 57(C), pages 56-73.
    16. Buser, Thomas & Ranehill, Eva & van Veldhuizen, Roel, 2021. "Gender differences in willingness to compete: The role of public observability," Journal of Economic Psychology, Elsevier, vol. 83(C).
    17. Martin G. Kocher & Fangfang Tan & Jing Yu, 2018. "Providing Global Public Goods: Electoral Delegation And Cooperation," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 381-397, January.
    18. Kessel, Dany & Mollerstrom, Johanna & van Veldhuizen, Roel, 2021. "Can simple advice eliminate the gender gap in willingness to compete?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 138, pages 1-1.
    19. Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022. "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series 10188, CESifo.
    20. Fischbacher, Urs & Kübler, Dorothea & Stüber, Robert, 2022. "Betting on diversity: Occupational segregation and gender stereotypes," Discussion Papers, Research Unit: Market Behavior SP II 2022-207, WZB Berlin Social Science Center.

    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    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:vfsc23:277692. 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/vfsocea.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.