Network Effect-Based Sequential Dynamic Pricing for Mobile Social Data Market

Mobile data demand is increasing tremendously in wireless social networks, and thus efficient pricing for social-enabled services is urgently needed. In this paper, we study the sequential dynamic pricing scheme of a monopoly mobile service provider in a social data market, where the provider, i.e., the seller, individually offers each user, i.e., the buyer, a certain price in multiple time periods dynamically and repeatedly. The proposed scheme exploits the network effects in the behavior model of mobile users that boost the social data demand. Furthermore, due to limited radio resource, the impact of wireless network congestion is taken into account in the pricing scheme. Through both the mathematical analysis and simulation, we demonstrate that our proposed sequential dynamic pricing can help the service provider to achieve greater revenue and mobile users achieve higher total utilities than those of existing optimal static pricing scheme.