Abstract
We model the sequential decisions made by receivers in response to multiple signals. In the first part, we model this in a special setting where the signals in the system are generated by either truth-telling or lying. We classify the signals as binary high or low, and study the information herding behavior. Then we study the decision-making in response to signals that cannot be simply classified as binary high or low. Last, we apply the Polya urn process to model the dynamics of public announcements made by the receivers in a more general setting, and discuss how senders can design their strategies to take advantage of public announcements and further increase their benefits. This research quantitatively examines people’s reactions to signals, and can be generalized and adapted to cases like the design of game shows, advertising, biding, and customer review management.
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