Shopping for Information: Consumer Learning with Optimal Pricing and Product Design
SSRN, ISSN: 1556-5068
2017
- 881Usage
- 3Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
I study a monopolistic pricing problem in which the consumer performs product research to determine whether or not to purchase a good. The consumer receives a signal of quality via a Brownian motion process with a type-dependent drift. I fully characterize the consumer’s optimal strategy; she buys the product when she is sufficiently optimistic about the quality and ceases to pay for the signal when she is sufficiently pessimistic. I examine the implications of this behavior for the seller’s optimal pricing decision. I find that the seller prefers to encourage product research when quality is likely to be high and prefers to discourage research when quality is likely to be low. I show that a decrease in search costs or an increase in the quality of information can either raise or lower equilibrium price. I also extend the model so that the seller chooses both price and the level of quality dispersion and demonstrate that the optimal level of dispersion need not be extremal.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85118055124&origin=inward; http://dx.doi.org/10.2139/ssrn.3000558; https://www.ssrn.com/abstract=3000558; https://dx.doi.org/10.2139/ssrn.3000558; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3000558; https://ssrn.com/abstract=3000558
Elsevier BV
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