IDEAS home Printed from https://ideas.repec.org/r/wly/jforec/v36y2017i6p691-702.html
   My bibliography  Save this item

Understanding algorithm aversion: When is advice from automation discounted?

Citations

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


Cited by:

  1. Natalie Leesakul & Anne-Marie Oostveen & Iveta Eimontaite & Max L. Wilson & Richard Hyde, 2022. "Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
  2. 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.
  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. 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.
  5. 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).
  6. 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.
  7. Arikan, Esra & Altinigne, Nesenur & Kuzgun, Ebru & Okan, Mehmet, 2023. "May robots be held responsible for service failure and recovery? The role of robot service provider agents’ human-likeness," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
  8. Florian Pethig & Julia Kroenung, 2023. "Biased Humans, (Un)Biased Algorithms?," Journal of Business Ethics, Springer, vol. 183(3), pages 637-652, March.
  9. 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).
  10. 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).
  11. 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.
  12. Cedric A. Lehmann & Christiane B. Haubitz & Andreas Fügener & Ulrich W. Thonemann, 2022. "The risk of algorithm transparency: How algorithm complexity drives the effects on the use of advice," Production and Operations Management, Production and Operations Management Society, vol. 31(9), pages 3419-3434, September.
  13. 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.
  14. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.
  15. Christoph Keding, 2021. "Understanding the interplay of artificial intelligence and strategic management: four decades of research in review," Management Review Quarterly, Springer, vol. 71(1), pages 91-134, February.
  16. Shiri Melumad & Rhonda Hadi & Christian Hildebrand & Adrian F. Ward, 2020. "Technology-Augmented Choice: How Digital Innovations Are Transforming Consumer Decision Processes," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 90-101, October.
  17. Markus Jung & Mischa Seiter, 2021. "Towards a better understanding on mitigating algorithm aversion in forecasting: an experimental study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 32(4), pages 495-516, December.
  18. Notz, Pascal M. & Pibernik, Richard, 2024. "Explainable subgradient tree boosting for prescriptive analytics in operations management," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1119-1133.
  19. 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).
  20. Ibrahim Filiz & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2022. "Algorithm Aversion as an Obstacle in the Establishment of Robo Advisors," JRFM, MDPI, vol. 15(8), pages 1-25, August.
  21. Kohei Kawaguchi, 2021. "When Will Workers Follow an Algorithm? A Field Experiment with a Retail Business," Management Science, INFORMS, vol. 67(3), pages 1670-1695, March.
  22. Sarah Spiekermann & Hanna Krasnova & Oliver Hinz & Annika Baumann & Alexander Benlian & Henner Gimpel & Irina Heimbach & Antonia Köster & Alexander Maedche & Björn Niehaves & Marten Risius & Manuel Tr, 2022. "Values and Ethics in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 247-264, April.
  23. Kolassa, Stephan, 2022. "Commentary on the M5 forecasting competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1562-1568.
  24. Greiner, Ben & Grünwald, Philipp & Lindner, Thomas & Lintner, Georg & Wiernsperger, Martin, 2024. "Incentives, Framing, and Reliance on Algorithmic Advice: An Experimental Study," Department for Strategy and Innovation Working Paper Series 01/2024, WU Vienna University of Economics and Business.
  25. 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.
  26. 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.
  27. 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.
  28. Achiel Fenneman & Joern Sickmann & Thomas Pitz & Alan G Sanfey, 2021. "Two distinct and separable processes underlie individual differences in algorithm adherence: Differences in predictions and differences in trust thresholds," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-20, February.
  29. 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.
  30. Shiri Melumad & Rhonda Hadi & Christian Hildebrand & Adrian F. Ward, 2021. "Technology-Augmented Choice: How Digital Innovations Are Transforming Consumer Decision Processes," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 90-101, October.
  31. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.