IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v64y2022i3d10.1007_s12599-022-00754-y.html
   My bibliography  Save this article

When Self-Humanization Leads to Algorithm Aversion

Author

Listed:
  • Pascal Oliver Heßler

    (University of Giessen)

  • Jella Pfeiffer

    (University of Giessen)

  • Sebastian Hafenbrädl

    (IESE Business School)

Abstract

Decision support systems are increasingly being adopted by various digital platforms. However, prior research has shown that certain contexts can induce algorithm aversion, leading people to reject their decision support. This paper investigates how and why the context in which users are making decisions (for-profit versus prosocial microlending decisions) affects their degree of algorithm aversion and ultimately their preference for more human-like (versus computer-like) decision support systems. The study proposes that contexts vary in their affordances for self-humanization. Specifically, people perceive prosocial decisions as more relevant to self-humanization than for-profit contexts, and, in consequence, they ascribe more importance to empathy and autonomy while making decisions in prosocial contexts. This increased importance of empathy and autonomy leads to a higher degree of algorithm aversion. At the same time, it also leads to a stronger preference for human-like decision support, which could therefore serve as a remedy for an algorithm aversion induced by the need for self-humanization. The results from an online experiment support the theorizing. The paper discusses both theoretical and design implications, especially for the potential of anthropomorphized conversational agents on platforms for prosocial decision-making.

Suggested Citation

  • Pascal Oliver Heßler & Jella Pfeiffer & Sebastian Hafenbrädl, 2022. "When Self-Humanization Leads to Algorithm Aversion," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 275-292, June.
    • Handle: RePEc:spr:binfse:v:64:y:2022:i:3:d:10.1007_s12599-022-00754-y
    DOI: 10.1007/s12599-022-00754-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12599-022-00754-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12599-022-00754-y?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. Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
    2. James Andreoni & Justin M. Rao & Hannah Trachtman, 2017. "Avoiding the Ask: A Field Experiment on Altruism, Empathy, and Charitable Giving," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 625-653.
    3. Todd W. Moss & Donald O. Neubaum & Moriah Meyskens, 2015. "The Effect of Virtuous and Entrepreneurial Orientations on Microfinance Lending and Repayment: A Signaling Theory Perspective," Entrepreneurship Theory and Practice, , vol. 39(1), pages 27-52, January.
    4. 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.
    5. Jella Pfeiffer & Thies Pfeiffer & Martin Meißner & Elisa Weiß, 2020. "Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments," Information Systems Research, INFORMS, vol. 31(3), pages 675-691, September.
    6. Andreoni, James, 1990. "Impure Altruism and Donations to Public Goods: A Theory of Warm-Glow Giving?," Economic Journal, Royal Economic Society, vol. 100(401), pages 464-477, June.
    7. 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.
    8. Sargeant, Adrian & Ford, John B. & West, Douglas C., 2006. "Perceptual determinants of nonprofit giving behavior," Journal of Business Research, Elsevier, vol. 59(2), pages 155-165, February.
    9. Thomas H. Allison & Blakley C. Davis & Jeremy C. Short & Justin W. Webb, 2015. "Crowdfunding in a Prosocial Microlending Environment: Examining the Role of Intrinsic versus Extrinsic Cues," Entrepreneurship Theory and Practice, , vol. 39(1), pages 53-73, January.
    10. Yogesh K. Dwivedi & David Wastell & Sven Laumer & Helle Zinner Henriksen & Michael D. Myers & Deborah Bunker & Amany Elbanna & M. N. Ravishankar & Shirish C. Srivastava, 2015. "Research on information systems failures and successes: Status update and future directions," Information Systems Frontiers, Springer, vol. 17(1), pages 143-157, February.
    11. Small, Deborah A. & Loewenstein, George & Slovic, Paul, 2007. "Sympathy and callousness: The impact of deliberative thought on donations to identifiable and statistical victims," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(2), pages 143-153, March.
    12. Quentin André & Ziv Carmon & Klaus Wertenbroch & Alia Crum & Douglas Frank & William Goldstein & Joel Huber & Leaf Boven & Bernd Weber & Haiyang Yang, 2018. "Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 28-37, March.
    13. Allison, Thomas H. & McKenny, Aaron F. & Short, Jeremy C., 2013. "The effect of entrepreneurial rhetoric on microlending investment: An examination of the warm-glow effect," Journal of Business Venturing, Elsevier, vol. 28(6), pages 690-707.
    14. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    15. Moon, Youngme, 2000. "Intimate Exchanges: Using Computers to Elicit Self-Disclosure from Consumers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 26(4), pages 323-339, March.
    16. Andrew Prahl & Lyn Van Swol, 2017. "Understanding algorithm aversion: When is advice from automation discounted?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 691-702, September.
    17. Christian Janiesch & Marcus Fischer & Axel Winkelmann & Valentin Nentwich, 2019. "Specifying autonomy in the Internet of Things: the autonomy model and notation," Information Systems and e-Business Management, Springer, vol. 17(1), pages 159-194, March.
    18. Ruttan, Rachel L. & Lucas, Brian J., 2018. "Cogs in the machine: The prioritization of money and self-dehumanization," Organizational Behavior and Human Decision Processes, Elsevier, vol. 149(C), pages 47-58.
    19. Jason Dana & Roberto Weber & Jason Kuang, 2007. "Exploiting moral wiggle room: experiments demonstrating an illusory preference for fairness," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(1), pages 67-80, October.
    20. Bonaccio, Silvia & Dalal, Reeshad S., 2006. "Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 127-151, November.
    21. Klaus Wertenbroch & Rom Y. Schrift & Joseph W. Alba & Alixandra Barasch & Amit Bhattacharjee & Markus Giesler & Joshua Knobe & Donald R. Lehmann & Sandra Matz & Gideon Nave & Jeffrey R. Parker & Stefa, 2020. "Autonomy in consumer choice," Marketing Letters, Springer, vol. 31(4), pages 429-439, December.
    22. Garry D Bruton & Susanna Khavul & Helmuth Chavez, 2011. "Microlending in emerging economies: Building a new line of inquiry from the ground up," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 42(5), pages 718-739, June.
    23. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
    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. Chugunova, Marina & Sele, Daniela, 2022. "We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
    2. Merle, Aurélie & St-Onge, Anik & Sénécal, Sylvain, 2022. "Does it pay to be honest? The effect of retailer-provided negative feedback on consumers’ product choice and shopping experience," Journal of Business Research, Elsevier, vol. 147(C), pages 532-543.
    3. Benedikt Berger & Martin Adam & Alexander Rühr & Alexander Benlian, 2021. "Watch Me Improve—Algorithm Aversion and Demonstrating the Ability to Learn," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(1), pages 55-68, February.
    4. 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.
    5. 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.
    6. Hadar Gafni & Marek Hudon & Anaïs Périlleux, 2021. "Business or Basic Needs? The Impact of Loan Purpose on Social Crowdfunding Platforms," Journal of Business Ethics, Springer, vol. 173(4), pages 777-793, November.
    7. Aaron H. Anglin & Jeremy C. Short & David J. Ketchen Jr. & Thomas H. Allison & Aaron F. McKenny, 2020. "Third-Party Signals in Crowdfunded Microfinance: The Role of Microfinance Institutions," Entrepreneurship Theory and Practice, , vol. 44(4), pages 623-644, July.
    8. Jancenelle, Vivien E. & Javalgi, Rajshekhar (Raj) G. & Cavusgil, Erin, 2018. "The role of economic and normative signals in international prosocial crowdfunding: An illustration using market orientation and psychological capital," International Business Review, Elsevier, vol. 27(1), pages 208-217.
    9. Gregor Dorfleitner & Eva-Maria Oswald & Rongxin Zhang, 2021. "From Credit Risk to Social Impact: On the Funding Determinants in Interest-Free Peer-to-Peer Lending," Journal of Business Ethics, Springer, vol. 170(2), pages 375-400, May.
    10. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    11. Johnson, Michael A. & Stevenson, Regan M. & Letwin, Chaim R., 2018. "A woman's place is in the… startup! Crowdfunder judgments, implicit bias, and the stereotype content model," Journal of Business Venturing, Elsevier, vol. 33(6), pages 813-831.
    12. Lourenço, Carlos J.S. & Dellaert, Benedict G.C. & Donkers, Bas, 2020. "Whose Algorithm Says So: The Relationships Between Type of Firm, Perceptions of Trust and Expertise, and the Acceptance of Financial Robo-Advice," Journal of Interactive Marketing, Elsevier, vol. 49(C), pages 107-124.
    13. Martin Adam & Konstantin Roethke & Alexander Benlian, 2023. "Human vs. Automated Sales Agents: How and Why Customer Responses Shift Across Sales Stages," Information Systems Research, INFORMS, vol. 34(3), pages 1148-1168, September.
    14. Stefania Testa & Paolo Roma & Maria Vasi & Silvano Cincotti, 2020. "Crowdfunding as a tool to support sustainability‐oriented initiatives: Preliminary insights into the role of product/service attributes," Business Strategy and the Environment, Wiley Blackwell, vol. 29(2), pages 530-546, February.
    15. de Bellis, Emanuel & Venkataramani Johar, Gita, 2020. "Autonomous Shopping Systems: Identifying and Overcoming Barriers to Consumer Adoption," Journal of Retailing, Elsevier, vol. 96(1), pages 74-87.
    16. Francesco Cappa & Michele Pinelli & Riccardo Maiolini & Maria Isabella Leone, 2021. "“Pledge” me your ears! The role of narratives and narrator experience in explaining crowdfunding success," Small Business Economics, Springer, vol. 57(2), pages 953-973, August.
    17. Aaron H. Anglin & Hana Milanov & Jeremy C. Short, 2023. "Religious Expression and Crowdfunded Microfinance Success: Insights from Role Congruity Theory," Journal of Business Ethics, Springer, vol. 185(2), pages 397-426, June.
    18. Bauer, Kevin & von Zahn, Moritz & Hinz, Oliver, 2022. "Expl(AI)ned: The impact of explainable Artificial Intelligence on cognitive processes," SAFE Working Paper Series 315, Leibniz Institute for Financial Research SAFE, revised 2022.
    19. Andreoni, James & Serra-Garcia, Marta, 2021. "Time inconsistent charitable giving," Journal of Public Economics, Elsevier, vol. 198(C).
    20. 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).

    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:spr:binfse:v:64:y:2022:i:3:d:10.1007_s12599-022-00754-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.