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Pricing music using personal data: mutually advantageous first-degree price discrimination
- Source :
- Electronic Markets. 25(2):139-154
- Publisher :
- Springer Nature
-
Abstract
- In addition to customized products and services, personal data also enables personalized pricing. However, consumers are often unwilling to accept being price discriminated for fear that they would end up paying more for the same product or service. This article demonstrates that by rewarding consumers for disclosing personal information it is possible to achieve a situation where first-degree price discrimination is mutually advantageous and both buyers and sellers gain by adopting such a pricing model. The conditions required for this to happen are investigated and the impact on social welfare is discussed. Finally, the article considers the robustness of this model when consumers adopt an opportunistic behavior which consists in manipulating personal data in order to masquerade as a consumer with a lower willingness to pay.
- Subjects :
- Economics and Econometrics
Personal data
CUSTOMER RECOGNITION
INFORMATION
Social Sciences
Price discrimination
MARKETS
Willingness to pay
Order (exchange)
Business & Economics
Management of Technology and Innovation
Pricing models
Economics
Business
Marketing
Business and International Management
Robustness (economics)
FIELD EXPERIMENT
WELFARE
Service (business)
WANT
First-degree price discrimination
CHOICE
Management
NETWORKS
Computer Science Applications
Product (business)
CONSUMER PRIVACY
OUTPUT
Privacy
Consumer privacy
Personally identifiable information
Digital economy
Subjects
Details
- Language :
- English
- ISSN :
- 10196781
- Volume :
- 25
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Electronic Markets
- Accession number :
- edsair.doi.dedup.....e19ad6e93a9507df565ddc22ed1f9d4e
- Full Text :
- https://doi.org/10.1007/s12525-014-0165-7