Subscription-based platforms offer consumers access to a large selection of content at a fixed subscription fee. Recommender systems (RS) can help consumers by reducing the size of this choice set by predicting consumers' preferences. However, because the prediction is based on limited...

An increasing number of consumption decisions happen on two (or more) sided platforms that carry goods and services from a large number of suppliers. In principle, such easy access to a multiplicity of products should lower consumers' search costs and thereby enhance their decision-making. In...

Recommender systems are prevalent across digital platforms. They use machine learning techniques to help consumers make choices by predicting their preferred items. If RS had perfect information about consumer preferences and item attributes, they could recommend the most suitable item for each...

We develop a theoretical model to study the effects of an ad valorem taxation regime differentiated according to product characteristics (quality) within an imperfectly competitive market. Then to test our theoretical prediction we use yearly data from the Irish automobile market during the...

Apple iOS is a closed platform;Google Android is open. In this paper,we combine data on iOS and Android tablet sales with data on the top 1000 mobile applications from both platforms for five European countries and estimate a structural demand model.We find that the quality of applications...