Consumer preference structure of online privacy concerns in an IoT environment

Abstract

Due to the development of the Internet of Things (IoT) and IoT environments, various concerns have been raised regarding personal information infringement and leakage. To establish a policy for addressing this issue, it is essential to estimate the damage caused by personal information infringement and leakage and decide upon an appropriate policy direction that reflects consumer’s value of their personal information. Therefore, we first estimated how much consumers value each type of personal information using contingent valuation method and assigning a monetary value to each information type. Second, we analyzed consumers’ preference for conditions in which they will provide personal information. A conjoint analysis was used to discover consumer preference concerning the various attributes of the conditions and a mixed logit model was used for the empirical analysis. The results of the analysis show that consumers valued personal information related to private life the most, at approximately USD 110 on average. We also found that demographic variables such as gender and income level affect personal information values. The results of the attributes required to provide personal information analysis found that opt-in was preferred to opt-out and that consumers preferred having optimal authority to control their personal information, rather than whole authority. These results show that consumers are willing to provide their personal information when an adequate reward is given. Therefore, formulating policy direction to establish a confidential market for trading personal information rather than unconditional personal information protection is required.