We study optimal cartel prices in a two-sided market. We present a simple model showing that prices above the two-sided monopoly price may prevail on one side of a two-sided market as a means to enhance the sustainability of the cartel. We prove that in such a case a higher benefit from the...

Many scholars argue that content providers, when incentivized by ad revenue, are more likely to tailor their content to attract “eyeballs,” and as a result, popular content may be excessively supplied. We empirically test this prediction by taking advantage of the launch of an...

This paper investigates the price war in the UK quality newspaper industry in the 1990s. We build a model of the newspaper market which encompasses demand for differentiated products on both, the readers and advertisers side of the market, and profit maximization by four competing oligopolistic...

This paper empirically investigates the relation between vertical integration and video game performance in the US video game industry. For this purpose, we use a widely used data set from NPD on video game monthly sales from October 2000 to October 2007. We complement these data with handly...

We present a theory for why it might be rational for a platform to limit the number of applications available on it. Our model is based on the observation that even if users prefer application variety, applications often also exhibit direct network effects. When there are direct network effects,...

Theories of multi-sided markets suggest that a platform’s pricing strategies on different sides of the market are closely linked, and in particular, an increase in competition on one side may lead to an increase in price on other sides. We empirically examine platforms’ pricing strategies by...

The aim of this research is to analyze whether and when ratings are informative signals about the quality of movies. The ratings data of Netflix is used to fit a structural Bayesian learning model. This model links revealed experience utilities of raters, previous consumers, to the product...