An analytic approach to measure information aggregation and evaluate the stability of informational cascades under incomplete information settings
Refereed conference paper presented and published in conference proceedings

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AbstractInformational cascades describe a situation in which people observe the actions of others and then make the same choice, regardless of their own information. Behavioral conformity prevents information aggregation (Bikhchandani et al., 1992). However, under incomplete information settings, individual's information is a sample of the whole information pool as we are facing information more than we can handle in daily business routine. As we can rule out the possibility that predecessors get enough information to shatter a cascade if cascade continues, it is reasonable to consider there is information injected into cascade even when decision-maker follows predecessor's behavior. Taking this belief into consideration, we analyze the threshold point of convergence/deviation, and propose a model to measure Information aggregation and evaluate the stability of informational cascades under incomplete information settings. This model helps to optimize sequential decision-making process by utilizing the statistical aspects of informational cascades.
All Author(s) ListHu H., Jia Y.
Name of Conference19th European Conference on Information Systems - ICT and Sustainable Service Development, ECIS 2011
Start Date of Conference09/06/2011
End Date of Conference11/06/2011
Place of ConferenceHelsinki
Country/Region of ConferenceFinland
Detailed descriptionorganized by Association for Information Systems,
Year2011
Month12
Day1
LanguagesEnglish-United Kingdom
KeywordsHerd, Information aggregation, Informational cascades, Stability

Last updated on 2020-03-09 at 03:50