Information Cascade Experiment: General Knowledge Quiz

  • Shintaro Mori
  • Masato Hisakado
Part of the Agent-Based Social Systems book series (ABSS, volume 14)


Information cascade experiment has long history. In the canonical setting of the experiment, urn choice quiz is used where a correct urn is chosen at random from two types of urns and subjects answer which urn is the correct one with private signal and the observation of previous subjects’ choices. In this chapter, we use general knowledge two-choice quiz in the experiment. The subjects answer sequentially after observing the summary statistics of the number of subjects who have chosen each option. We estimate the response function f(z) of the subjects that describe the probability of the correct choice under the influence of the ratio of correct answers of the previous subjects. As the difficulty of the question changes, f(z) changes, which results in the change in the number of equilibrium of the nonlinear Pólya urn. When the question is easy and there is one equilibrium, the domino effect disappears, and the majority choice always converges to the correct answer. When the question is difficult, there appear two equilibria, and the domino effect continues forever. If the first subject chooses a wrong option, it continues to affect the later subjects. The probability that the majority choice converges to a wrong option increases by the first subject’s choice.


  1. Anderson LR, Holt CA (1997) Information cascades in the laboratory. Am Econ Rev 87:847–862Google Scholar
  2. Bikhchandani S, Hirshleifer D, Welch I (1992) A theory of fads, fashion, custom, and cultural changes as informational cascades. J Polit Econ 100:992–1026CrossRefGoogle Scholar
  3. Devenow A, Welch I (1996) Rational herding in financial economics. Euro Econ Rev 40:603–615CrossRefGoogle Scholar
  4. Hill B, Lane D, Sudderth W (1980) A strong law for some generalized urn processes. Ann Prob 8:214–226CrossRefGoogle Scholar
  5. Hisakado M, Mori S (2011) Digital herders and phase transition in a voting model. J Phys A Math Theor 44:275204–275220CrossRefGoogle Scholar
  6. Mori S, Hisakado M (2015a) Finite-size scaling analysis of binary stochastic processes and universality classes of information cascade phase transition. J Phys Soc Jpn 84:054001–054013CrossRefGoogle Scholar
  7. Mori S, Hisakado M (2015b) Correlation function for generalized Pólya urns: finite-size scaling analysis. Phys Rev E92:052112–052121Google Scholar
  8. Mori S, Hisakado M, Takahashi T (2012) Phase transition to two-peaks phase in an information cascade voting experiment. Phys Rev E86:026109–026118Google Scholar
  9. Mori S, Hisakado M, Takahashi T (2013) Collective adoption of max-min strategy in an information cascade voting experiment. J Phys Soc Jpn 82:0840004–0840013Google Scholar
  10. Pemantle R (2007) A survey of random processes with reinforcement. Pobab Surv 4:1–79CrossRefGoogle Scholar
  11. Pólya G (1931) Sur quelques points de la théorie des probabilités. Ann Inst Henri Poincar 1:117–161Google Scholar

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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Shintaro Mori
    • 1
  • Masato Hisakado
    • 2
  1. 1.Faculty of Science and Technology, Department of Mathematics and PhysicsHirosaki UniversityHirosakiJapan
  2. 2.Nomura Holdings, Inc.Chiyoda-kuJapan

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