Pay for Content or Pay for Referral? An Empirical Study on Content Pricing

Abstract

This paper examines how online content providers monetize their content when the residing platform gives them full pricing autonomy and allows referral program for their audience acquisition. By using unique data from a popular Chinese content provision platform, we use a structural approach to model a content provider’s pricing and referral marketing decisions. The estimation results highlight the trade-off of the referral program: it helps attract more audience but incurs revenue loss from referral payments. The counterfactual analyses show that platform policy change may cause potential homogeneity of content provision and huge demand loss.