An information cascade or informational cascade is a phenomenon described in behavioral economics and network theory in which a number of people make the same decision in a sequential fashion. It is similar to, but distinct from herd behavior.[1][2][3]
An information cascade is generally accepted as a two-step process. For a cascade to begin an individual must encounter a scenario with a decision, typically a binary one. Second, outside factors can influence this decision, such as the individual observing others' choices and the apparent outcomes.
The two-step process of an informational cascade can be broken down into five basic components:
There is a decision to be made – for example; whether to adopt a new technology, wear a new style of clothing, eat in a new restaurant, or support a particular political position
A limited action space exists (e.g. an adopt/reject decision)
People make the decision sequentially, and each person can observe the choices made by those who acted earlier
Each person has some information aside from their own that helps guide their decision
A person can't directly observe the outside information that other people know, but he or she can make inferences about this information from what they do
Social perspectives of cascades, which suggest that agents may act irrationally (e.g., against what they think is optimal) when social pressures are great, exist as complements to the concept of information cascades.[4] More often the problem is that the concept of an information cascade is confused with ideas that do not match the two key conditions of the process, such as social proof, information diffusion,[5] and social influence. Indeed, the term information cascade has even been used to refer to such processes.[6]
^Duan, Wenjing; Gu, Bin; Whinston, Andrew B. (March 2009). "Informational Cascades and Software Adoption on the Internet: An Empirical Investigation". MIS Quarterly. 33 (1). Rochester, NY: 23–48. doi:10.2307/20650277. hdl:2144/42029. JSTOR20650277. S2CID909115. SSRN1103165.
^Sadikov, Eldar; Medina, Montserrat; Leskovec, Jure; Garcia-Molina, Hector (2011). "Correcting for missing data in information cascades". Proceedings of the fourth ACM international conference on Web search and data mining. pp. 55–64. doi:10.1145/1935826.1935844. ISBN978-1-4503-0493-1. S2CID6978077.