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

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  • Ivanova-Stenzel, Radosveta
  • Tolksdorf, Michel

Abstract

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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
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    File URL: https://www.econstor.eu/bitstream/10419/277692/1/vfs-2023-pid-87307.pdf
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    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).
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    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

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