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Sequential Choice Under Ambiguity: Intuitive Solutions to the Armed-Bandit Problem

Citations

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Cited by:

  1. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2015. "Meaningful Learning in Weighted Voting Games: An Experiment," Working Papers halshs-01216244, HAL.
  2. Noah Gans & George Knox & Rachel Croson, 2007. "Simple Models of Discrete Choice and Their Performance in Bandit Experiments," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 383-408, December.
  3. Barbara Kahn & Alexander Chernev & Ulf Böckenholt & Kate Bundorf & Michaela Draganska & Ryan Hamilton & Robert Meyer & Klaus Wertenbroch, 2014. "Consumer and managerial goals in assortment choice and design," Marketing Letters, Springer, vol. 25(3), pages 293-303, September.
  4. Hoeffler, Steve & Ariely, Dan & West, Pat, 2006. "Path dependent preferences: The role of early experience and biased search in preference development," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 215-229, November.
  5. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2017. "Meaningful learning in weighted voting games: an experiment," Theory and Decision, Springer, vol. 83(1), pages 131-153, June.
  6. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
  7. Farzad Pourbabaee, 2022. "Robust experimentation in the continuous time bandit problem," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(1), pages 151-181, February.
  8. repec:cup:judgdm:v:12:y:2017:i:2:p:104-117 is not listed on IDEAS
  9. Eric M. Schwartz & Eric T. Bradlow & Peter S. Fader, 2017. "Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments," Marketing Science, INFORMS, vol. 36(4), pages 500-522, July.
  10. Christopher Anderson, 2012. "Ambiguity aversion in multi-armed bandit problems," Theory and Decision, Springer, vol. 72(1), pages 15-33, January.
  11. repec:jdm:journl:v:17:y:2022:i:4:p:691-719 is not listed on IDEAS
  12. Mariano, Stefania & Laker, Benjamin, 2024. "On-the-fly decision making within organizations: A systematic literature review and future research directions," Journal of Business Research, Elsevier, vol. 174(C).
  13. Li, Jian, 2019. "The K-armed bandit problem with multiple priors," Journal of Mathematical Economics, Elsevier, vol. 80(C), pages 22-38.
  14. Florian Ederer & Gustavo Manso, 2013. "Is Pay for Performance Detrimental to Innovation?," Management Science, INFORMS, vol. 59(7), pages 1496-1513, July.
  15. Huang, Yanliu & Hutchinson, J. Wesley, 2013. "The roles of planning, learning, and mental models in repeated dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 122(2), pages 163-176.
  16. Daniella Laureiro‐Martínez & Stefano Brusoni, 2018. "Cognitive flexibility and adaptive decision‐making: Evidence from a laboratory study of expert decision makers," Strategic Management Journal, Wiley Blackwell, vol. 39(4), pages 1031-1058, April.
  17. Ye Hu & Stowe Shoemaker, 2024. "Do More Experienced Gamblers Choose Slot Machines with Better Odds? A Large-Scale Multi-Armed Bandit Problem at a Casino," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 11(1), pages 1-18, December.
  18. Marcoul, Philippe & Weninger, Quinn, 2008. "Search and active learning with correlated information: Empirical evidence from mid-Atlantic clam fishermen," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1921-1948, June.
  19. Andrew M. Davis & Vishal Gaur & Dayoung Kim, 2021. "Consumer Learning from Own Experience and Social Information: An Experimental Study," Management Science, INFORMS, vol. 67(5), pages 2924-2943, May.
  20. Yilmaz Kocer, 2010. "Endogenous Learning with Bounded Memory," Working Papers 1290, Princeton University, Department of Economics, Econometric Research Program..
  21. Hu, Yingyao & Kayaba, Yutaka & Shum, Matthew, 2013. "Nonparametric learning rules from bandit experiments: The eyes have it!," Games and Economic Behavior, Elsevier, vol. 81(C), pages 215-231.
  22. Johannes Hoelzemann & Nicolas Klein, 2021. "Bandits in the lab," Quantitative Economics, Econometric Society, vol. 12(3), pages 1021-1051, July.
  23. Gars, Jared & Ward, Patrick S., 2019. "Can differences in individual learning explain patterns of technology adoption? Evidence on heterogeneous learning patterns and hybrid rice adoption in Bihar, India," World Development, Elsevier, vol. 115(C), pages 178-189.
  24. Paul M. Krueger & Robert C. Wilson & Jonathan D. Cohen, 2017. "Strategies for exploration in the domain of losses," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 12(2), pages 104-117, March.
  25. Bruno B Averbeck, 2015. "Theory of Choice in Bandit, Information Sampling and Foraging Tasks," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-28, March.
  26. Daniella Laureiro-Martínez & Stefano Brusoni & Nicola Canessa & Maurizio Zollo, 2015. "Understanding the exploration–exploitation dilemma: An fMRI study of attention control and decision-making performance," Strategic Management Journal, Wiley Blackwell, vol. 36(3), pages 319-338, March.
  27. Jean Paul Rabanal & Aleksei Chernulich & John Horowitz & Olga A. Rud & Manizha Sharifova, 2019. "Market timing under public and private information," Working Papers 151, Peruvian Economic Association.
  28. Tülin Erdem & Kannan Srinivasan & Wilfred Amaldoss & Patrick Bajari & Hai Che & Teck Ho & Wes Hutchinson & Michael Katz & Michael Keane & Robert Meyer & Peter Reiss, 2005. "Theory-Driven Choice Models," Marketing Letters, Springer, vol. 16(3), pages 225-237, December.
  29. Naoki Watanabe, 2022. "Reconsidering Meaningful Learning in a Bandit Experiment on Weighted Voting: Subjects’ Search Behavior," The Review of Socionetwork Strategies, Springer, vol. 16(1), pages 81-107, April.
  30. Stanton Hudja & Daniel Woods, 2024. "Exploration versus exploitation: A laboratory test of the single‐agent exponential bandit model," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 267-286, January.
  31. Daniel E Acuña & Paul Schrater, 2010. "Structure Learning in Human Sequential Decision-Making," PLOS Computational Biology, Public Library of Science, vol. 6(12), pages 1-12, December.
  32. Alina Ferecatu & Arnaud De Bruyn, 2022. "Understanding Managers’ Trade-Offs Between Exploration and Exploitation," Marketing Science, INFORMS, vol. 41(1), pages 139-165, January.
  33. repec:cup:judgdm:v:17:y:2022:i:4:p:691-719 is not listed on IDEAS
  34. Hudja, Stanton, 2021. "Is Experimentation Invariant to Group Size? A Laboratory Analysis of Innovation Contests," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 91(C).
  35. Noah Gans, 2002. "Customer Loyalty and Supplier Quality Competition," Management Science, INFORMS, vol. 48(2), pages 207-221, February.
  36. Farzad Pourbabaee, 2021. "Robust Experimentation in the Continuous Time Bandit Problem," Papers 2104.00102, arXiv.org.
  37. Dinesh Kumar, U. & Saranga, Haritha, 2010. "Optimal selection of obsolescence mitigation strategies using a restless bandit model," European Journal of Operational Research, Elsevier, vol. 200(1), pages 170-180, January.
  38. Koen H. Heimeriks & Christopher B. Bingham & Tomi Laamanen, 2015. "Unveiling the temporally contingent role of codification in alliance success," Strategic Management Journal, Wiley Blackwell, vol. 36(3), pages 462-473, March.
  39. Gars, Jared & Ward, Patrick S., 2016. "The role of learning in technology adoption: Evidence on hybrid rice adoption in Bihar, India," IFPRI discussion papers 1591, International Food Policy Research Institute (IFPRI).
  40. Seow, Hsin-Vonn & Thomas, Lyn C., 2006. "Using adaptive learning in credit scoring to estimate take-up probability distribution," European Journal of Operational Research, Elsevier, vol. 173(3), pages 880-892, September.
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