Andrew Rhodes Publications

This paper provides a framework in which a multiproduct ecosystem competes with many single-product firms in both price and innovation. The ecosystem is able to use data collected on one product to improve the quality of its other products. We study the impact of data regulation which either restricts the ecosystem's cross-product data usage, or which requires it to share data with small firms. Each policy induces small firms to innovate more and set higher prices; it also dampens data spillovers within the ecosystem, reduces the ecosystem's incentive to collect data and innovate, and potentially increases its prices. As a result, data regulation has an ambiguous impact on consumers, and is more likely to benefit consumers when small firms are relatively more efficient in innovation. A data cooperative among small firms, which helps them to share data with each other, does not necessarily benefit small firms and can even harm consumers.

We study personalized pricing in a general oligopoly model. The impact of personalized pricing relative to uniform pricing hinges on the degree of market coverage. If market conditions are such that coverage is high (e.g., the production cost is low or the number of firms is high), personalized pricing harms firms and benefits consumers, whereas the opposite is true if coverage is low. When only some firms have data to personalize prices, consumers can be worse off compared to when either all or no firms personalize prices.

This paper studies consumers' privacy choices when firms can use their data to make personalized offers. We first introduce a general framework of personalization and privacy choice, and then apply it to personalized recommendations, personalized prices, and personalized product design. We argue that due to firms' reaction in the product market, consumers who share their data often impose a negative externality on other consumers. Due to this privacy-choice externality, too many consumers share their data relative to the consumer optimum; moreover, more competition, or improvements in data security, can lower consumer surplus by encouraging more data sharing.

We study personalized pricing (or first-degree price discrimination) in a general oligopoly model. In the short-run, when the market structure is fixed, the impact of personalized pricing hinges on the degree of market coverage (i.e., how many consumers buy). If coverage is high (e.g., because the production cost is low, or the number of firms is large), personalized pricing intensifies competition and so harms firms but benefits consumers, whereas the opposite is true if coverage is low. However in the long-run, when the market structure is endogenous, personalized pricing always benefits consumers because it induces the socially optimal level of firm entry. We also study the asymmetric case where some firms can use consumer data to price discriminate while others cannot, and show it can be worse for consumers than when either all or no firms can personalize prices.