Consumers have long relied on ratings measures to help them make choices among goods of heterogeneous quality. With the growth of the New Economy over the last 10 years, it is becoming increasingly possible to aggregate information and create ratings for many industries. My research focuses on the effect of quality ratings on consumer choice, the social benefit of the quality signals, and on how well firms that develop ratings signals can capture a share of the social benefit. I examine these issues using data from Netflix, the on--line DVD rental service with mail delivery, which also provides a rating system that aggregates the preferences of the people who use their service. In the first chapter I use a reduced--form specification to analyze the Netflix ratings database and estimate aggregate demand for movies. The second chapter develops a structural Bayesian learning model and assesses the effect of ratings on DVD rental behavior. The last chapter is dedicated to the analysis of consumer and producer welfare as a function of the information created by the ratings system.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/193977 |
| Date | January 2009 |
| Creators | Maryanchyk, Ivan |
| Contributors | Gowrisankaran, Gautam, Gowrisankaran, Gautam, Gelbach, Jonah, Hirano, Keisuke, Xiao, Mo |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | text, Electronic Dissertation |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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