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As recommendation algorithms have been increasingly applied to content personalization services, scholars are voicing concern about the negative impacts of these algorithms, for instance filter bubbles and ideological polarization. This research attempts to analyze the various factors influencing users' continuance intention of recommendation algorithms through structural equation modeling. Based on the Expectation-Confirmation Model, this study proposes an extended framework to empirically examine the impact of confirmation, perceived usefulness, perceived enjoyment, perceived ease of use, perceived risk, and subjective norm on satisfaction and continuance intention. Results indicate that confirmation positively impacts satisfaction, perceived usefulness, and perceived enjoyment. Furthermore, all constructs had a significant effect on satisfaction as well as continuance intention. A group comparison analysis of consumers primarily using news recommendation algorithms and multimedia recommendation algorithms uncovered differences between the two groups. Managerial implications on how to retain recommendation algorithm users are suggested based on the results.

The long-standing signification of car is expected to accompany a big change, which results in the concept of smart car that can not only improve traffic safety by driving and controlling themselves like robots, but also entertain passengers and support their productive activities through connection to the Internet. Many related companies are seeking to enter the smart car market to take a leadership in the growing smart car market. While there are some researches regarding advanced technologies regarding smart car, there are relatively few efforts that focus on the standpoint of market demand. This study thus aims to understand customer value on upcoming smart car through evaluating the relative importance of idiosyncratic key services of smart car based on analytic hierarchy process analysis. In addition, this paper also evaluates firms and industries that are expected to perform well the preferred services through expert survey. The results show that the most important service is driving assistance, followed by infotainment, and IoT hub. Furthermore, Samsung Electronics ranked the highest, followed by Hyundai Motor, Naver, and SKT. In terms of industries, the rank is in the order of IT equipment manufacturers, platform providers, automobile manufacturers, and network providers. This analysis could help companies diagnose their capabilities and recognize their strengths and weaknesses.

Recently, the consumer virtual reality(VR) industry has been established with the introduction of VR head-mount displays(HMDs) and many have expected VR to become the next generation platform. Despite the circumstances, the adoption of VR HMDs is slower than expected. To comprehend this matter, this study explored consumers' preference on the attributes of VR HMDs by implementing the conjoint analysis methodology and deriving the marginal willingness-to-pay(MWTP) of the attributes. Based on past literature and analysis of the product, six attributes were derived: Visualization, Accessories, Weight, Ergonomic Design, Number of Contents, and Price. The results indicate that the wearable aspect of the device is the most important. Implications for future developmental directions for VR HMDs are suggested based on the results.

Smart speakers have become next big thing in IoT industry. However, there is not enough discussion about which application would be killer content in smart speaker market. To boost market participation and the growth of the market, there should be a research predicting killer service in the smart speaker. This study uses an AHP model and framework to assess the priority for applications in smart speakers. This study compares three types of applications – Music, News, E-commerce – to investigate the priority.

Personal information is essential in an information-oriented society for societal development and as a valuable business resource. However, because of poor management and a lack of proper protection, leakage of personal information can take place over time, and the standard for compensation is not well established. In order to establish appropriate policies for its protection, we need to know the economic value of personal information. Using conjoint analysis, we analyze the potential value of personal information by calculating the marginal willingness to pay of Korean consumers for each attribute of personal information, which we estimate to be 7501.70 South Korean won (about 6.81 US dollars) per month. After indirectly estimating the economic value of personal information, we provide some political implications regarding the potential market size of any personal information protection service.