Marketing Seminar
| What | Seminar |
|---|---|
| When |
Nov 04, 2009
Nov 04, 2009
Nov 04, 2009 from 02:00 pm to 03:30 pm |
| Where | Pittsburgh 4206 |
| Contact Name | Sharon Kelliher |
| Contact Email | kellis@rpi.edu |
| Contact Phone | 518.276.2337 |
Jane Gu
Assistant Professor of Marketing, State University of New York, Albany
This study develops a game-theoretical model to examine firms’ strategic decisions regarding whether to disclose private information on their products’ horizontal attributes in a competitive market. Our investigation reveals two motives for competitive firms to disclose horizontal information. First, by disclosing horizontal information, a firm creates heterogeneity in consumer preferences for its product. This consumer-heterogeneity-effect allows the firm to exploit increased surplus of consumers who find good fits with the product. Second, in a competitive market, horizontal information disclosure creates horizontal differentiation between products. This horizontal-differentiation-effect softens price competition. A firm benefits from both effects when it discloses horizontal information and only benefits from the horizontal-differentiation-effect when it free-rides on its competitor’s information disclosure. Our analysis generates a set of interesting results. First, we find that the firm selling the premium quality product is more likely to disclose horizontal information than the firm selling the inferior quality product as long as the quality difference between the two competitive products is not too large. Second, we find that in a competitive market, both the premium product firm and the inferior product firm disclose more information than they would as a market monopolist. Third, disclosing horizontal information allows firms to charge higher prices. These theoretical predictions provide useful insights for marketing practitioners seeking to optimally design their horizontal information disclosure strategies. We also obtain empirical support for some of our theoretical predictions using sampling data from the pharmaceutical industry.
RSVP Not Required