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An information (or informational) cascade occurs when people observe the actions of others and then make the same choice that the others have made, independently of their own private information signals. There is a nearly limitless set of situations in which people are influenced by others: in the opinions they hold, the products they buy, the political positions they support, the activities they participate in, the technologies they use, and many other things[1]. Information cascade is commonly seen in groups under immediate stress from external forces, such as in herd behavior[2]. The effect is to cause group decisions based on few signals and can often be against what the individual believes to be true. Because it is usually sensible to do what other people are doing, the phenomenon is assumed to be the result of rational choice. Nevertheless, information cascades can sometimes lead to arbitrary or even erroneous decisions.[citation needed] The concept of information cascades is based on observational learning theory and was formally introduced in a 1992 article by Sushil Bikhchandani, David Hirshleifer, and Ivo Welch.Cite error: The <ref> tag has too many names (see the help page). A less technical article was released by the authors in 1998.[3][4][5][6]

There are two key conditions in an information cascade model:

  1. Sequential decisions with subsequent actors observing decisions (not information) of previous actors.
  2. A limited action space (e.g. an adopt/reject decision).[7]

Examples and fields of application

Information cascades occur in situations where seeing many people make the same choice provides evidence that outweighs one's own judgment. That is, one thinks: "It's more likely that I'm wrong than that all those other people are wrong. Therefore, I will do as they do."

In what has been termed a "reputational cascade", late responders sometimes go along with the decisions of early responders, not just because the late responders think the early responders are right, but also because they perceive their reputation will be damaged if they dissent from the early responders.[8]

An example of social proof in that people will see the actions of the group and will feel compelled to act with the larger group of people. People in large groups will tend to act with a heard mentality. Large groups of people can be controlled with little information passed down from a small few to a large group.

Market cascades

Information cascades have become one of the topics of behavioral economics, as they are often seen in financial markets where they can feed speculation and create cumulative and excessive price moves, either for the whole market (market bubble...) or a specific asset, for example a stock that becomes overly popular among investors.

Marketers also use the idea of cascades to attempt to get a buying cascade started for a new product. If they can induce an initial set of people to adopt the new product, then those who make purchasing decisions later on may also adopt the product even it is no better than, or perhaps even worse than, competing products. This is most effective if these later consumers are able to observe the adoption decisions, but not how satisfied the early customers actually were with the choice. This is consistent with the idea that cascades arise naturally when people can see what others do but not what they know[9].

Information cascades are usually considered by economists:

  • as products of rational expectations at their start,
  • as irrational herd behavior if they persist for too long, which signals that collective emotions come also into play to feed the cascade.

Historical examples

  • Small protests began in Leipzig, Germany in 1989 with just a handful of activists challenging the German Democratic Republic.[10] For almost a year, protesters met every Monday growing by a few people each time.[10] By the time the government attempted to address it in September 1989, it was too big to quash.[10] In October, the number of protesters reached 100,000 and by the first Monday in November, over 400,000 people marched the streets of Leipzig. Two days later the Berlin Wall was dismantled.[10]
  • The adoption rate of drought-resistant hybrid seed corn during the Great Depression and Dust Bowl was slow despite its significant improvement over the previously available seed corn. Researchers at Iowa State University were interested in understanding the public's hesitation to the adoption of this significantly improved technology. After conducting 259 interviews with farmers[11] it was observed that the slow rate of adoption was due to how the farmers valued the opinion of their friends and neighbors instead of the word of a salesman. See [12] for the original report.

The negative effects of informational cascades sometimes become a legal concern and laws have been enacted to neutralize them. Ward Farnsworth, a law professor, analyzed the legal aspects of informational cascades and gave several examples in his book The Legal Analyst: in many military courts, the officers voting to decide a case vote in reverse rank order (the officer of the lowest rank votes first), and he suggested it may be done so the lower-ranked officers would not be tempted by the cascade to vote with the more senior officers, who are believed to have more accurate judgement; another example is that countries such as Israel and France have laws that prohibit polling days or weeks before elections to prevent the effect of informational cascade that may influence the election results.[13]

See also

References

[14]

  1. ^ http://www.infosci.cornell.edu/courses/info204/2007sp/info-cascade.pdf
  2. ^ http://psychology.wikia.com/wiki/Information_cascade
  3. ^ Bikhchandani, S., Hirshleifer, D., and Welch, I. (1998), "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, Volume 12, Issue 3, pp. 151-170. + button to enlarge.
  4. ^ Bikhchandani, S., Hirshleifer, D., and Welch, I. (2008). "information cascades," The New Palgrave Dictionary of Economics, 2nd Edition.Abstract.
  5. ^ Sushil Bikhchandani, David Hirshleifer, and Ivo Welch (1992). "A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades." Journal of Political Economy, 100(5), pp. 992-1026. + button to enlarge.
  6. ^ Sushil Bikhchandani, David Hirshleifer, and Ivo Welch (1998), "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, 12(3), pp. 151-170. + button to enlarge.
  7. ^ Information Cascades and Rational Herding: An Annotated Bibliography and Resource Reference
  8. ^ Pierre Lemieux (2003), "Following the Herd", Regulation, Cato Institute, 21. [1]. Retrieved 14 July 2010.
  9. ^ http://research.ivo-welch.info/palgrave.pdf
  10. ^ a b c d Shirky, Clay (2008). Here Comes Everybody: The Power of Organizing Without Organizations. New York: Penguin Press. pp. 161–164. ISBN 978-1594201530.
  11. ^ Carboneau, Clark. "Using Diffusion of Innovations and Academic Detailing to Spread Evidence-based Practices". Journal for Healthcare Quality. Retrieved 2008-11-11.
  12. ^ Beal, George M. "The Diffusion Process" (Document). Iowa State University of Science and Technology of Ames, Iowa. {{cite document}}: Unknown parameter |accessdate= ignored (help); Unknown parameter |coauthors= ignored (|author= suggested) (help); Unknown parameter |url= ignored (help)
  13. ^ Farnsworth, Ward (2007). The Legal Analyst: A Toolkit for Thinking about the Law. Chicago: University of Chicago Press. ISBN 0226238350
  14. ^ http://psychology.wikia.com/wiki/Information_cascade



Category:Group processes Category:Behavioral finance