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Communication is central to many settings in marketing and economics. A focal attribute of communication is miscommunication. We model this key characteristic as a noise in the messages communicated, so that the sender of a message is uncertain about its perception by the receiver, and then identify the strategic consequences of miscommunication. We study a model where competing senders (of different types) can invest in improving the precision of the informative but noisy message they send to a receiver, and find that there exists a separating equilibrium where senders’ types are completely revealed. Thus, although communication is noisy it delivers perfect results in equilibrium. This result stems from the fact that a sender’s willingness to invest in improving the precision of their messages can itself serve as a signal. Interestingly, the content of the messages is ignored by the receiver in such a signaling equilibrium, but plays a central role by shaping her beliefs off the equilibrium path (and thus, enables separation between the types). This result also illustrates the uniqueness of the signaling model presented here. Unlike other signaling models, the suggested model does not require that the costs and benefits of the senders will be correlated with their types to achieve separation. The model’s results have implications for various marketing communication tools such as advertising and sales forces.
KeywordsInformation Signaling Communication
JEL ClassificationC72 D82 D83 M31
We are grateful to Adam Brandenburger, Eddie Dekel, Chaim Fershtman, Elon Kohlberg, Sridhar Moorthy, Barry Nalebuff, Ariel Pakes, Ben Polak, Julio Rotemberg, Ariel Rubinstein, Dennis Yao, and seminar participants at Hebrew University, Tel-Aviv University, Washington University, Yale University, and various conferences for helpful comments. Our editor, Rajiv Lal, and reviewers were very helpful with their constructive comments and guidance and we appreciate their effort. Anand gratefully acknowledges financial support from the Division of Research at Harvard Business School.
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