Product Policy in Markets with Word-of-Mouth Communication

Product Policy in Markets with Word-of-Mouth Communication

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Article ID: iaor2017333
Volume: 63
Issue: 1
Start Page Number: 267
End Page Number: 278
Publication Date: Jan 2017
Journal: Management Science
Authors:
Keywords: management, retailing, communication, simulation, behaviour, advertising
Abstract:

We investigate the equilibrium relationship between product quality and word‐of‐mouth (WOM) communication. Specifically, we ask whether firms should optimally produce ‘better’ products when consumers are more likely to exchange information. The critical moderating factor in our model is the nature of the communication and what its primary impact is. We first look at WOM that expands awareness of a product. We show that quality may either increase or decrease as WOM expands. The answer depends, in part, on the extent to which the expansion of WOM is one of scale alone or whether it also fundamentally changes the structure of communications. Next, we examine a model in which the primary impact of WOM is to help people to evaluate the utility provided by products with which they are already familiar. Our model suggests that more WOM in this context should always lead to higher‐quality products. We demonstrate that the underlying driver of this result is that the elasticity of demand with respect to quality is increasing in the proportion of consumers who are informed about the product’s quality. Taken together, the two models therefore suggest that the firm’s optimal product‐policy response to the growth in social interactions depends on both the content and the structure of the underlying conversations. Finally, we compare both WOM models to analogous models of advertising and demonstrate that the firm’s optimal response to a decrease in advertising costs is quite different from that to an increase in WOM. The reason for these differences can be traced back to a fundamental distinction between advertising and WOM: although the former is optimized, the latter is far more random. This paper was accepted by J. Miguel Villas‐Boas, marketing.

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