Purpose: This study aims to investigate the antecedents of mobile Internet users’ perception of information sensitivity (PIS) and willingness to provide personal information (WTP). It provides insights about how these antecedents influence users’ perceived information sensitivity and willingness to provide.Design/methodology/approach: An online survey of mobile Internet users was conducted in China, generating a total of 1,000 qualified responses for analysis.Findings: Results reveal the differential effects of some major antecedents of mobile Internet users’ perceived information sensitivity and willingness to provide (individual disposition to value privacy, age, gender, app type and privacy concerns) and such impact vary across low-, medium- and high-privacy segments.Originality/value: This study provides insights into the antecedents of mobile Internet users’ attitudes towards personal information privacy. It also extends the understanding of users’ perceived information sensitivity and willingness to provide such information comparatively among four countries.

Containers are used by an increasing number of Internet service providers to deploy their applications in multi-access edge computing (MEC) systems. Although container-based virtualization technologies significantly increase application availability, they may suffer expensive communication overhead and resource use imbalances. However, so far there has been a scarcity of studies to conquer these difficulties. In this paper, we design a workflow-based mathematical model for applications built upon interdependent multitasking composition, formulate a multi-objective combinatorial optimization problem composed of two subproblems—graph partitioning and multi-choice vector bin packing, and propose several joint task-containerization-and -container-placement methods to reduce communication overhead and balance multi-type computing resource utilization. The performance superiority of the proposed algorithms is demonstrated by comparison with the state-of-the-art task and container scheduling schemes.

Data services are growing explosively, and the potential scale of the online data service industry is huge. However, the price system of data services is chaotic and the pricing is not standardized, which hinders the healthy development of the online data service industry. Aiming at the pricing problem in the data service market, this paper proposes a data service pricing scheme based on basic cost and premium. According to the analysis of the factors affecting the price of online data services, a data service price index system is constructed, and the data service price composition is divided into two parts: basic cost and premium. Tiered data service pricing mechanism.