Modern consumers increasingly embrace the personalization of services. Whether to disclose private information to companies for the sake of receiving personalized service is largely contingent to relative valuations and the utility of private information. Unfortunately, there is a lack of balanced research that analyzes and reconciles the contradiction between privacy and personalization service. In this study, based on the multi-attribute utility theory (MAUT), we introduce a utility model of privacy in personalization. Our simulation results validate our white-box utility model by demonstrating significant distinctions of calculating benefits and costs among three groups of consumers.
- privacy calculus
- personalization service
- multi-attribute utility theory (MAUT)
- consumer preferences
- fuzzy logic