Research on the Pricing Decisions of a Video Platform Based on Interaction

Abstract

Video platforms allow users to interact with others. They enhance the user experience by providing interaction functions, such as “like”, “comment”, and “share”. In order to explore the value of the users’ behavior to the video platforms, we constructed a video platform operation model that considered interaction and then identified the logical relationships implied by the parameters. We adopted the mathematical model method and analyzed the entire video platform system using numerical optimization techniques. From the pricing decision, we obtained the equilibrium result for the video platform profits and analyzed the favorable market demands. We complemented this strategy by proposing a model that enables platforms to consider the promotion behavior of advertisers. Finally, we expanded the basic model by analyzing the competitive strategies of two video platforms in the market. Our research shows that interactivity, advertisement nuisance, and advertiser profitability are important factors that influence video platform pricing strategies. When interactivity is weak, the platforms need to adjust their pricing to obtain a share of the users in the market. However, they need to obtain all the users in the market to achieve optimal profit. In addition, it is profitable for platforms to adopt promotion strategies when the users are highly sensitive to promotions.