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The Difference Between Information Cascades and Herd Behavior

In 2003, Bogachan Celen and Shachar Kariv conducted research into information cascades, and identified clear distinctions between information cascades and herd behavior. As they studied two distinct phenomena – informational cascades and herd behavior – they found that individuals were easily influenced by the decisions of others, especially in social and economic situations. Even small, everyday decisions like choosing a restaurant, is often influenced by the decisions of others. Moreover, when information is limited, or even asymmetrical (different people have access to different amounts of information), individuals will tend to imitate their predecessor, even though their own information may be contradictory. The biggest distinction between an information cascade and herd behavior is that in an information cascade, individuals actively ignore their private information to instead follow the decision of those before them, while herd behavior occurs without individuals necessarily ignoring their private information.

Essentially, in an information cascade, there is strong belief in the decision, and that belief is so strong that no signal that the individual has is strong enough to outweigh the belief currently in place. Because of this, social learning is topped since individual behavior is no longer as informative, as is what was described in lecture. The study also found that herd behavior was more easily disrupted, while informational cascades are more stable. The reason information cascades are more stable goes back to idea that information cascades are based on belief; it is very hard for signals to change the pattern of behavior already in place. On the other hand, herd behavior can shift suddenly and dramatically based on a strong signal. These findings reveal the underlying theory of fads and mass behavior.

This study supported and complemented the information that lectures and the textbook provided about information cascades. It is interesting to see how information cascades are so present, even in every day life. For example, while vacationing, I often choose where to eat based on how many other people are eating there; if no one is there, I tend to avoid the establishment, even if it received good reviews on Yelp. Celen and Kariv’s study reveal interesting details about information cascade, and the difference between information cascades and mere herd behavior.


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November 2016