Earticle

On the Internet age, the news is generated and distributed not only by traditional news media, but also by a variety of online news media, news platforms, content websites/content farms, and social media. Since it is an easy task to create and distribute news, some of these news reports may contain fake or false facts. In the end, the cyberspace is full of fake or false messages. People may wonder if these fake news actually influence our decision making. In this paper, we discussed a real case of fake news. In this case, a Taiwanese company used some fake news, advertorial news, and news placement to manipulate or influence its stock price and trade volume. We collected all news for the case company during a period of four years and five months (from January 2013 to May 2017). We analyzed the relationship between published news and stock price. Based on the analysis results, we conclude that we should not ignore the influence of news placement and fake business news on the stock price.

Social media are used as a tool which is suitable for delivering various images emotionally in the area of fashion. How deeply consumers are led by the brands to be engaged in the brands’ SNS, how often they visit SNS and gain information, how much empathy they elicit from visitors with their contents and how continuously brands provide up-to-date information are the important factors to raise consumers’ fashion consciousness and draw out their fashion consumption to express themselves. Therefore, this study aims to explore the effect of social media engagement and contents characteristics on fashion consumption tendency and purchase intention. In order to verify the research question, study makes analysis centering on the 2 × 2 × 2 MANCOVA model to draw out results of the differences among groups. As a result of analysis, this study verifies the difference between the effect of social media engagement on purchase intention and the effect of interaction of three variables on fashion consumption propensity and purchase intention and summarizes the implications.

This study analyzed the factors influencing the technology acceptance of the general public in the drones and ARs, one of the key technologies of the industry 4.0. The theoretical basis was the extended unified theory of acceptance and use of technology model(UTAUT2), which uses performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation as factors common to both services. The price value factor was excluded considering that most ARs were free, and the perceived risk factors, including privacy, which were not in UTAUT2, were included because they are important factors for ICT technology acceptance. The hypothesis was tested by structure equation model. Social influence and hedonic motivation had a positive(+) effect on intention to use technology. On the other hand, in the case of effort expectancy, neither the AR nor the drone had a significant influence on intention to use technology. Furthermore, performance expectancy had a positive(+) effect on intention to use in AR, but no significant influence was found out in drones. On the contrary, in the case of the facilitating conditions, the influence of the drones was positive (+), but the relation of AR was not investigated. The perceived risk was tested for the negative (-) influence of use intention of AR, but no significant relationship was found out for the drones. Among the significant influencing factors, hedonic motivation was the most powerful factor in AR and drones. Theoretical and practical implications are presented based on these results.

The volatility of major crypto currencies was examined and they are diagnosed whether they have a systematic risk or not, by estimating market beta representing systematic risk using GARCH( Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that their prices are very volatile over time because of the existence of ARCH and GARCH effects. Second, in terms of efficiency, asymmetric GJR model was estimated to be the most appropriate model because the standard error of a market beta was less than that of the OLS model and GARCH model. Third, the estimated market beta of Bitcoin using GJR model was less than 1 at 0.8791, showing that there is no systematic risk. However, unlike OLS model, the market beta of Ethereum and Ripple was estimated at 1.0581 and 1.1222, showing that there is systematic risk. This result shows that bitcoin is less dangerous than Ripple and Ethereum, and ripple is the most dangerous of all three crypto currencies. Finally, the major cryptocurrency found that the negative impact caused greater variability than the positive impact, causing bad news to fluctuate more than good news, and therefore good news and bad news had a different effect on the variability.

This study describes the accounting approach of separating the value chain components that occur between the origin and destination of a country's total exports, and applied this analysis to the nation's information and communication industry. As a result of this study, the analysis results of ICT's global value chain for the United States and China, focusing on Korea, are as follows: First of all, the value added standard was relatively lower than the export amount standard for the information and communication industry. In particular, the gap was starkly visible in the information and communication manufacturing sector, where global vertical specialization was developed relatively. As a representative sector, the computer-related equipment sector exported to China became more specialized vertically than other information and communication industries. Next, the method of participating in vertical specialization of Korea`s information and communication sector and its relative position in the global value chain came from domestic products (0.25/35.16) whose total exports, which were double calculated in the case of the U.S. market, returned home. On the other hand, about 32.68 percent returned to the Chinese market. Finally, in the global value chain level, the SW sector occupied a medium vertical culture location for the information and communication equipment sector and the information and communication service sector.

Blockchain is a distributed network in a decentralized P2P infrastructure. In this paper, we propose and implement a blockchain-based pet trade service DApp(Decentralized Application). In the existing trading services, there is no way to know the status of dogs in interpersonal transactions and an additional distribution cost has been incurred. As a solution to this problem, we introduce a blockchain technology for a pet trade service where users can check whether an individual pet is healthy or not by its registered biometric data in order to have an efficient and confident trade service. The registered users can purchase puppies or registering information for their dogs to sell through a pet trade service DApp. It is also possible to make a reliable trade by verifying whether the dog is actually the same one through an inscription information of a dog.

Many researchers have been focused on designing beauty product recommendation system for a long time because of increased need of customers for personalized and customized recommendation in beauty product domain. In addition, as the application of the deep neural network technique becomes active recently, various collaborative filtering techniques based on the deep neural network have been introduced. In this context, this study proposes a deep neural network model suitable for beauty product recommendation by applying Neural Collaborative Filtering and Generalized Matrix Factorization (NCF + GMF) to beauty product recommendation. This study also provides an implementation of web API system to commercialize the proposed recommendation model. The overall performance of the NCF + GMF model was the best when the beauty product recommendation problem was defined as the estimation rating score problem and the binary classification problem. The NCF + GMF model showed also high performance in the top N recommendation.

Demand for high power motors is rapidly increasing as the 4th industry and convergence technology has recently emerged. In order to produce high-strength permanent magnets, the magnets used for magnetization have been increased from DC 300V in the 1970s to DC 2.5kV in the 2010s, Up to DC 10kV in the 2030s, It is expected that higher voltage will be used to magnetize. However, in the case of a magnetizer using an existing electric signal control device, it is necessary to use a control device with a high-voltage insulation function in case a high voltage used for magnetization is leaked to the control device. If a short circuit accident occurs, the controller must be shut down and serious problems such as excessive repair costs arise. In this study, a control system adopting optical communication method instead of electric signal control method is proposed to prevent leakage currents in high-voltage magnetizer. We design a transmitter(Tx) and a receiver(Rx) device for the optical communication control device and implemented a prototype connecting the optical cable. In order to demonstrate the utility of high-voltage magnetizer using the optical communication control device, we analyzed the initial cost and the yearly cost for the years to analyze the net present value. As a result, In the case of the low-voltage magnetizer, the electric signal control method cost less, As the operating voltage of the magnetizer becomes higher. It is confirmed that it takes less cost when the optical communication control device is used.

This work examines whether IT managers adopt of real options such as defer, expand, contract, and abandon in order to cope with ERP risks, which include technological risk, relationship risk with SW vendors, economic risk, and security risk. We collect data of logistics firms in Seoul and its suburbs in 2018 to empirically validate the effect of risks upon the adoption of real options. The results suggest that IT managers adopt all 4 options when facing economic risk and adopt contract and abandon options only when facing security risk. Additionally, we find that IT managers prefers expand option and avoid abandon option when they think ERP compatibility is high.

This study is intended for demonstrating the impacts of different factors on the formation of online consumer engagement behavior of young Chinese moviegoer in Korea. Based on Value-Exchange Model [Itani et al., 2019], we build research model to reveal the relationships among perceived enjoyment, perceived movie information value, multiplex-audience relationship quality, multiplex usage satisfaction, and online consumer engagement through experiments on valid data we collected from 186 participants who had lived in Korea and experienced the multiplex pages of top 3 movie theaters, where Smart PLS 3.0 is the tool used for statistical analysis. The experimental results show that both perceived enjoyment and perceived movie information value positively correlate to multiplex-audience relationship quality, and multiplex audience relationship quality significantly influences multiplex usage satisfaction and online consumer engagement. In addition, it is found that relationship quality plays the role of mediator between perceived enjoyment and satisfaction. The findings from this study offer both academic and managerial implications for movie distributors who are interested in developing potential Chinese consumer market in Korea.