In a big data environment, there are growing concerns about the violation of consumer rights regarding information privacy. To induce rational regulations for protecting personal information, it is necessary to separately estimate consumers' values related to different types of personal information. In this article, discrete choice experiments using hypothetical information leakage situations given certain compensation amounts and discrete choice models were used to quantitatively analyze the value of personal information. The results indicate that consumers generally place high value on information that could cause immediate and actual damage from the leakage after identification, such as basic personal information and purchase list and payment information. Consumers value location information and personal medical information differently based on their perceived importance of privacy and their prior experience with personal information leakage. We suggest that the level of regulation should differ according to the type of personal information based on the consumers' valuation. This article contributes to a better understanding of a quantitative approach to pricing personal information.