Optimal recommendation and long-tail provision strategies for content monetization

This paper examines the optimal strategies for pricing, contents variety supply and recommendation system investment by digital contents providers. With the fast development of digitalization technology and social participation in recent years, the ways to create and access information contents become diverse with greater convenience and much lower cost. How to attract more customers of different segments and raise sales revenue becomes the most essential issue for content providers as the long tail phenomenon becomes significant. From the supply side, increasing and maintaining a wide variety of content can attract more users. From the demand side, adapting suitable recommender systems is considered as an effective implementation for content sale promotion. However, they both require the providers to make more efforts on information acquisition and balancing the budget allocated on various types of recommender systems, which leads to differentiated changes of sales patterns. In this paper, we propose an economic model to capture the technological and market factors affecting the categorization of sales pattern and develop the proper business strategies of content provision and content recommendation for supporting the operations of digital content providers.