The 36th research workshop on industrial organization and competition policy,, Oct 14, 2023, Institute of Social and Economic Research, Osaka University Invited
Motivated by the GDPR as opt-in regime for privacy this paper;examines how privacy disclosure affects consumers through value-enhancing data analytics. Artificial Intelligence (AI) can help firms to provide products or services to consumers with personalization. This paper considers product personalization when consumers provide their personal data to the AI-enabled firm for improving the value of matching taste under the Hotelling type duopoly.
While firms are interested in exploit consumer surplus through personalized pricing, consumers may disclose their personal information to improve quality of matching taste.
Chen et al.,(2022) focus on the situation where a post-merger firm available a personalized offer can identify consumers' location between two firms based on personal information collected through the acquired firm. For this reason, they analyze in a model that the target of personalized offering starts from consumers with higher preferences in order. However, they treated data analytics quality is exogenous.
We therefore develop their idea in terms of making the quality of data analysis endogenous. Specifically, consumers choose the amount of personal data to improve data analytics quality with considering privacy cost. Model setting and its result are as follows.
The two firms (firm 1 and firm 2) are each located at the endpoints of the hoteling line, where unit mass consumers have the same evaluation of the stand-alone product. Assume that firm 1, which is capable of personalization, already know the consumer’s location. Given that, we consider the situation where consumers targeted for personalization are price discriminated according to their location position, but on the other hand, they can also expect to improve their matching taste.
We then consider a situation in which the target consumer may disclose personal information to update the quality of matching. Disclosing privacy may not be costless for the sake of security protection or psychologically. Since consumers incur privacy cost to disclose their personal data, the targeted consumers do not provide so much personal data that improves the quality of matching.
However, as also considered in Lefouili et al. (2023), consumers increase their incentive to provide more data when investments in AI technology are made. They study monopolist who provides the free online service at the exchange of personal data which is monetized to third party. Contrary to them, this paper assume competition. Provision of personal information affects the maximus scale of personalization non-monotonically depending on the degree of privacy cost. When the targeted consumer is large, the AI investment is not implemented.