Band 16, Heft 3 - Special Issue: Economics of Digitization / Guest Editors: Paul Belleflamme, Alexandre de Cornière, Oliver Falck and Axel Gautier

Knowledge spillovers in Open Source Software (OSS) can occur via two channels: In the first channel, programmers take knowledge and experience gained from one OSS project they work on and employ it in another OSS project they work on. In the second channel, programmers reuse software code by taking code from an OSS project and employing it in another. We develop a methodology to measure software reuse in a large OSS network at the micro level and show that projects that reuse code from other projects have higher success. We also demonstrate knowledge spillovers from projects connected via common programmers.

In this paper we propose a model where consumer personal data have multidimensional characteristics, and are used by platforms to offer ad slots with better targeting possibilities to a market of differentiated advertisers through real-time auctions. A platform controls the amount of information about consumers that it discloses to advertisers, thereby affecting the dispersion of advertisers’ valuations for the slot. We first show by way of simulations that the amount of consumer-specific information that is optimally revealed to advertisers increases with the degree of competition on the advertising market and decreases with the cost of information disclosure for a monopolistic platform, competing platforms or a welfare-maximizing platform, provided the advertising market is not highly concentrated. Second, we exhibit different properties between the welfare-maximizing situation and the imperfectly competitive market situations with respect to how the incremental value of information varies: there are decreasing social returns to consumers’ data, while private returns may be increasing or decreasing locally.

This paper studies how product customization and consumer privacy affect a monopolist’s incentives to engage in perfect price discrimination. We consider a monopolist that faces an ex ante choice to commit to price discrimination or to a uniform price. We introduce a simple model in which a monopolist can use analytics to access consumer data to both price-discriminate and offer customized products. In turn, consumers can protect their privacy to avoid price discrimination at a cost. By committing not to price-discriminate, the firm induces consumers to not protect their data, which allows it to customize the product. It can then extract the extra value through an increased uniform price. This strategy is profitable when the value added through customization is sufficiently high. An intermediate quality of analytics gives the monopolist more incentives to set a uniform price.

When a consumer pays by card, the merchant’s bank pays to the consumer’s bank an interchange fee. In this article, we construct a general model of a card platform that unifies the literature on interchange fees. We enrich the existing frameworks by analyzing the choice of the interchange fee when consumer demand is elastic to retail prices. We show that the difference between the privately set structure of payment card fees and the socially optimal one depends both on banks’ and merchants’ pass-through of their costs to consumers. We argue that the maturity of the payment card market impacts the redistributive effects of interchange fees (i.e. between consumers and merchants, card and cash users) and therefore, their optimal regulation.