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With the advancement and emergence of new network services, such as social network, Internet of Things, and crowd-sensing, large volume of diverse data is collected, shared, and leveraged to develop analytics services. The data analytics service has become a key commodity that can be traded among various economic entities. In this paper, we address the optimal pricing mechanisms and data management for data analytics services and further discuss the perishable services in the time varying environment. We first propose a data market model and define the data utility based on the impact of data size on the performance of data analytics, e.g., prediction and verification accuracy. For perishable services, we study the perishability of data that affects the service quality and provide a quality decay function. The data analytics services are considered as digital goods and uniquely characterized by “unlimited supply” compared to conventional goods. Therefore, we apply the Bayesian profit maximization mechanism in selling data analytics services, which is truthful, rational, and computationally efficient. The optimal service price, data amount, and service update interval are obtained to maximize the profit under different customer's valuation distributions. Finally, experimental results on realworld datasets show that our data market model and pricing mechanism effectively solve the profit maximization problem and provide useful strategies for the data analytics service provider.
Jiao et al. (Tue,) studied this question.