Privacy concern is becoming one of the most important issues for personalized online services like websites, computer software and mobile apps, especially those offered for free. In this paper, we develop a dynamic adoption model that combines new product diffusion theory with online services privacy, and seek to offer marketing strategies to maximize vendors’ profit for online services. We divide the diffusion process into two steps: awareness and adoption, and assume awareness process is mainly influenced by word of mouth effect. The adoption process occurs when benefits adjusted personal information demand level (PIDL) from vendors is lower or close to privacy disclosure tolerance level (PDTL) of consumers. We get numerical solutions for this optimal control problem with two differential equations. Our findings suggest WOM effect, network externalities and the initial state of awareness proportion are effective marketing tools for vendors, and parameters or variables like marginal value for consumer information (MVI), population size and the initial state of adoption amount are less effective. Our study should be considered preliminary with limitations and extensions for future research.
Li, Wenli and Geng, Zhaoxin, "Dynamic Adoption Model of Personalized Online Services with Privacy Concerns and WoM Effect" (2015). PACIS 2015 Proceedings. 16.