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The Sound of Silence: Observational Learning in the U.S. Kidney Market

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Author Info

  • Juanjuan Zhang

    ()
    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02114)

Abstract

Mere observation of others' choices can be informative about product quality. This paper develops an individual-level dynamic model of observational learning and applies it to a novel data set from the U.S. kidney market, where transplant candidates on a waiting list sequentially decide whether to accept a kidney offer. We find strong evidence of observational learning: patients draw negative quality inferences from earlier refusals in the queue, thus becoming more inclined towards refusal themselves. This self-reinforcing chain of inferences leads to poor kidney utilization despite the continual shortage in kidney supply. Counterfactual policy simulations show that patients would have made more efficient use of kidneys had the concerns behind earlier refusals been shared. This study yields a set of marketing implications. In particular, we show that observational learning and information sharing shape consumer choices in markedly different ways. Optimal marketing strategies should take into account how consumers learn from others.

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File URL: http://dx.doi.org/10.1287/mksc.1090.0500
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Bibliographic Info

Article provided by INFORMS in its journal Marketing Science.

Volume (Year): 29 (2010)
Issue (Month): 2 (03-04)
Pages: 315-335

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Handle: RePEc:inm:ormksc:v:29:y:2010:i:2:p:315-335

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Related research

Keywords: observational learning; learning models; informational cascades; herding; quality inference; Bayes' rule; dynamic programming; kidney allocation;

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Cited by:
  1. repec:fee:wpaper:1103 is not listed on IDEAS
  2. Nathan Yang, 2011. "An Empirical Model of Industry Dynamics with Common Uncertainty and Learning from the Actions of Competitors," Working Papers 11-16, NET Institute.
  3. Catherine Tucker & Juanjuan Zhang & Ting Zhu, 2009. "Days on Market and Home Sales," Working Papers 09-16, NET Institute, revised Aug 2009.
  4. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
  5. repec:wyi:journl:002151 is not listed on IDEAS
  6. Shachat, Jason & Swarthout, J. Todd, 2012. "Learning about learning in games through experimental control of strategic interdependence," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 383-402.
  7. John Hauser, 2011. "A marketing science perspective on recognition-based heuristics (and the fast-and-frugal paradigm)," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(5), pages 396-408, July.

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