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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.

Green consumption is a very common phrase in our daily lives, yet product characteristics that mainly contribute to the diffusion of green products are largely unknown. Based on microeconomic theory, we conduct a conjoint survey of consumer preferences for a ubiquitous green product—laundry detergent. We analyze the correlation between consumers' demographic variables and attributes of laundry detergents through a hierarchical Bayesian mixed logit model. We find that consumer preferences for attributes display significant heterogeneity. Age and income significantly influence the marginal preferences for attributes. An examination of consumer willingness to pay and of the relative importance of each attribute reveals that price and base material are the most important attributes. Green attributes, such as skin irritation potential and biodegradability, tend to be less important. This study also examines preference heterogeneity based on previous purchase experience. To promote green consumption, we emphasize the need for policies that reduce the value‐action gap.

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-South Korea is recently under serious situation in supplying electricity with enough power reserve. A single fault of power plant at a peak-load time may lead to a total blackout for whole area connected by a single electric grid and isolated from other grids. Despite of the seriousness of blackout, however, there are scarce studies with ex-ante analysis of the economic costs from blackout. In order to evocate the seriousness, we calculate the economic costs for both industrial and household sectors with using some survey data and statistical methodologies. As a result, total economic costs are 39.23 trillion KRW (35.83 trillion KRW for industrial sector, 3.40 trillion KRW for household sector).