With the emerging sensing technologies such as mobile crowdsensing andInternet of Things (IoT), people-centric data can be efficiently collected andused for analytics and optimization purposes. This data is typically requiredto develop and render people-centric services. In this paper, we address theprivacy implication, optimal pricing, and bundling of people-centric services.We first define the inverse correlation between the service quality and privacylevel from data analytics perspectives. We then present the profit maximizationmodels of selling standalone, complementary, and substitute services.Specifically, the closed-form solutions of the optimal privacy level andsubscription fee are derived to maximize the gross profit of service providers.For interrelated people-centric services, we show that cooperation by servicebundling of complementary services is profitable compared to the separate salesbut detrimental for substitutes. We also show that the market value of aservice bundle is correlated with the degree of contingency between theinterrelated services. Finally, we incorporate the profit sharing models fromgame theory for dividing the bundling profit among the cooperative serviceproviders.
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