• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.652-666
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• 2021

This study explores diffusion of information on Covid-19 relating to China on You Tube. For this, information on Covid-19 relating to China was divided into factual information and disinformation, with factual information being categorized into positive and negative information. According to network analysis, there are lots of negative information and disinformation. On the contrary positive information is rare. There are lots of videos about rumor on the leak of Wuhan institute among disinformation. Rumor on the manipulation of genes has the highest average value of view count and betweenness centrality. Main stream youtube channel has only role of messenger which delivers messages as it is instead of fact-checking on disinformation. The fact which there are much more negative information or disinformation among videos about Covid-19 relating with China shows that Youtube users skewed toward negative information and disinformation than positive ones. In summary, disinformation on youtube brings spreadable effect by making user watch similar contents.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.1
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• pp.19-36
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• 2021

Real-time two-way communication has become an important factor in the relationship between consumers and broadcasters in the Live Commerce environment. To clarify, the relationship of the factors, and the effect of Live Commerce's on consumer purchase intention were examined. In addition, the role of Wanghong, who broadcasts Live Commerce and Co-experience that occurs between consumer and broadcasters influences consumer purchase intention. An online survey method was conducted for 403 subjects in their 20s that were Live Commerce users in Shanghai, Beijing, and Guangzhou, China. The number of final the data used for the analysis was 274 and anlaysis was conducted using SPSS 26.0 program and a Sobel test was employed. Based on the analysis of the data, it was found that Live Commerce's characteristics consisted of interactivity, security, and Wanghong's characteristics consisted of honesty, originality, and expertise. Also, it revealed that Co-experience was consisted of responsiveness and vividness. Second, for Live Commerce's characteristics, the Wanghong's characteristics, and Co-experience had a positive effect on the consumers' purchase intention. Third, the Wanghong's characteristics and vividness, a factor of Co-experience, had significant mediating effects on the relationship between Live Commerce's characteristics and the consumers' purchase intention. Finally, responsiveness of Co-experience had a noteworthy mediating effect on the relationship between the interactivity of Live Commerce's characteristics and the consumers' purchase intention. This study confirmed the important role of Live Commerce's characteristics, the Wanghong's characteristics and Co-experience in relation to the consumers' purchase intention. In addition, the Wanghong's characteristics and Co-experience were proposed as a significant mediating factors.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.138-154
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• 2021

'Live commerce', a brand new format of online shopping, is actively promoted in China recently. This research focused on 'Taobao-live', China's largest live commerce platform to investigate the relationships among para-social interaction, source characteristics (e.g., trustworthiness, attractiveness, and expertise), perceived ease of use, perceived usefulness, and shopping intention based on Technology Acceptance Model. A total of 536 Taobao live users were recruited through the Chinese research platform. The results showed that para-social interactivity positively affected perceived ease of use and usefulness, whereas the source characteristics had no significant effect on consumers' perceptions. Furthermore, higher perceived ease of use generated higher perceived usefulness, and both perceived ease of use and usefulness positively influenced consumers' intention to shop through Taobao live. This research can provide theoretical background for understanding the potential of live commerce platforms and help brands come up with effective online shopping strategies using live commerce platforms.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.659-665
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• 2021

Short video applications (e.g., TikTok, YouTube shorts) are growing quickly in terms of active users and usage time. Of course, advertising industry is utilizing the app as AD channel. The current study, however, argues that the effectiveness of ADs in short video apps are not articulated well and that precise research for measuring the effect is required. In this context, this study measured the effects of storytelling ad types(reality, parody, creative) and message sensation value(high vs. low level) on story transportation. The notable finding is that when creative storytelling ad type which requires more cognitive resources than other two types meets high level of message sensation value, ad viewers could reach cognitive overload state which induced low effectiveness of ad. As its result, the effectiveness of AD reduced. More specific theoretical discussion and suggestions for advertising producers are described.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.59-68
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• 2022

As real-time live streaming broadcasting and non-face-to-face classes are spreading in the Corona era, it is time to take academic interest in online streaming classes. In particular, it is important to clarify why users use online streaming classes. Therefore, this study proposes social presence, interest, convenience of use, and interactivity as characteristics of online streaming classes, and aims to verify how these characteristics affect learning satisfaction and furthermore, recommendation intention. As a result of conducting a survey on 338 Chinese collegestudents, it was found that interactivity, social presence, and interest had a positive effect on learning satisfaction, but the effect of ease did not appear. On the other hand, it was confirmed that learning satisfaction had a positive effect on the online streaming class recommendation intention.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1238-1247
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• 2022

The e-commerce market is growing faster as demand for non-face-to-face shopping increases due to COVID-19. These changes lead to the expansion of various opportunities for consumers, but companies are required to understand consumer characteristics and reflect them in their sales strategies so that they can be competitive in the market. This study examined how the perceived ease and utility of consumers affect the intention to use the platform according to the technology acceptance model (TAM). As a result, it was confirmed that the price competitiveness, awareness, and ease of use of the platform had a significant effect on the utility. In addition, it was confirmed that there was no moderating effect of user characteristics on the effect of ease of use on the platform intention. These results present important implications for a company's sales strategy, and in future studies, it is necessary to expand the study in consideration of more diverse variables.

• Information Systems Review
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• v.23 no.3
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• pp.77-96
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• 2021

This research investigates the pivotal role of AI-enabled technologies in vitalizing the local economy. Collaborating with a leading search engine company, we examine the direct and indirect of an AI-based location search service on the success of sampled 7,035 local restaurants in Gangnam area in Seoul. We find that increased use of AI-enabled search and recommendation services significantly improved the selections of previously less-discovered or less-popular restaurants by users, and it also enhanced the stores' overall conversion rates. The main research findings have contributions to extant literature in theorizing the value of AI applications in local economy and have managerial implications for search businesses and local stores by recommending strategic use of AI applications in their businesses that are effective in highly competitive markets.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.1-16
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• 2024

As the COVID-19 pandemic confirmed the culture of non-face-to-face consumption. In retail commerce, the 'live commerce' market, where sales are made by communicating with customers in the form of live streaming broadcasts, has grown rapidly. Although previous studies have consistently confirmed the phenomenon of "influencers" in society and culture, there is a lack of research on the "sales expertise" of live commerce broadcasters such as Wang Hong in China. In China, "Wang Hong" is short for "Wang Luo Hong Ren", a combination of "Wang Luo", which means the Internet, and "Hong Ren", which means star, and refers to a person who is popular through social platforms and is gaining popularity from many fans. Therefore, this study focuses on Wang Hong's developing "selling expertise" and examines it from the perspective of a shopping curator. In particular, we applied Harold Jarche(2011)'s "Seek-Sense-Share" model to influencers to verify their influence on trust and purchase intention in live commerce. Furthermore, we analyzed the differences between Korea and China.A survey was conducted among live commerce users in Korea and China, and a total of 228 questionnaires were used in the final analysis. Basic statistical analysis was conducted using SPSS and hypotheses were tested using PLS 3.0. The results of the hypothesis testing showed that influencers' curatorial competence "Seek-Sense-Share" had a significant effect on trust, and trust had a positive effect on purchase intention. In addition, there is a significant difference between Korean and Chinese consumers in this relationship.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Management & Information Systems Review
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• v.33 no.2
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• pp.63-79
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• 2014

This study is based on the previous studies on m-commerce features, found factors that affects reliability and user's intention. After that, it examined how these factors influence the relationship between reliability and user's intention. In addition, this study showed that some factors have different influence on Korean and Chinese users in terms of reliability and user's intention. The main results of this study are as follows: (1) Personal innovation attributed to reliability in both Korea and China. Personal innovation also attributed to user's intention in Korea. (2) Localization, reach ability, security, and convenience had different influence on use and reliability in the two countries. (3) And the influences between reliability and user's intention are all positive both in Korea and China. Based on the result of this empirical study, this study reveal some implications for the firms that running with mobile business in both Korea and China.