Advertisements on Knowledge Payment Platforms: A Game Theoretic Analysis of Pricing Strategies

Most knowledge payment platforms are keen to adopt a business model based on transaction revenue and advertising revenue. However, challenge with platforms has been to balance the interests of advertisers as well as their consumers. Increasing of advertising revenue, by having more advertisers may lead to higher consumers’ aversion. To address these queries, we develop a three-sided model to study the optimal pricing strategy of the knowledge payment platform. Specifically, we discuss the impact of the proportion of transaction fees charged by the platform on platform’s strategy under which the platform charges transaction fees from consumers and advertising fees from advertisers. We find that when the proportion of transaction fees charged by the platform is at a low level, the platform’s profit reaches the maximum. Once the proportion of transaction fees charged by the platform is high, which will have a negative impact on the platform’s profit although the platform adopts a strategy of increasing advertising price for advertisers. Besides, we analyze the changes of pricing strategy of knowledge payment platform under different level of network externalities. We find that with the increase of proportion of transaction fees charged by the platform and network externalities, both of the advertising price and platform’s profit are more sensitive to the proportion of transaction fees charged by the platform. On the contrary, as the degree of consumers’ aversion to advertisements increases, the platform’s profit is less sensitive to the proportion of transaction fees charged by the platform.