• Journal of Fashion Business
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• v.9 no.6
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• pp.71-85
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• 2005

The purpose of this study is to prove that interchange is the a key factor in costume style changes through case analysis in costume culture interchange, and further, to assist in gaining understanding of costume style changes of the present and the future. Study findings show that the pattern of acceptance of costume interchange was mostly integration, though it was influenced by the method of transmission. The integration is a process in which a foreign costume culture is constructively mixed into the existing one, and a factor that changes the existing costume culture.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.61-71
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• 2014

Recently social shopping, combining e-Commerce with Social Network Service, become a brand-new eBusiness model. In this paper, we aim to identify the structural relationship of the factors affecting the intention of using social shopping. Reviewing the previous works of social shopping, internet shopping and TAM (Technology Acceptance Model), we extract factors affecting the intention of using social shopping and build a structural research model among these factors. To analyze the structural relationship among theses factors, we perform an empirical study - gathering data from a survey and analyzing gathered data using EFA (Exploratory Factor Analysis) and SEM (Structural Equation Model) to identify the structural relationship. We also analyze moderating effect of past experience of social shopping and gender. As a result, We also can find that two factors - Perceived usefulness and Expected enjoyment - are the key factors influencing acceptance of social shopping and that more segmented strategies are required to attract customers since factors affecting Intention to use are somewhat different according to past experience and gender of respondents.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.75-95
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• 2020

Smart Factory is the decisive factor of the Fourth Industrial Revolution and is a key field for national competitiveness. Until now, most smart factory research has focused on policy and technology. In order to spread more technology, it is necessary to study what factors influence the adoption of smart factory technology in the enterprise. Nevertheless, little research has been done. In this study, based on the UTAUT (Unified Theory of Acceptance and Use of Technology), which has been proved through many years of research, I have studied the factors that influence the acceptance of smart factory technology. As a result of research, performance expectancy, social influence, and facilitating conditions of UTAUT model had a positive(+) effect on behavior intention. Their relationship of influence was in the order of performance expectancy (β = .459)> facilitating conditions (β = .212)> social influence (β = .210). However, it was found that the effort expectancy did not affect the behavior intention, and the impact of the newly perceived risk on the behavior intention to use was not confirmed. The main reason is that the acceptance of smart factory technology is not a matter of personal interest but a matter of organizational choice. Trust, on the other hand, was found to be partially mediated between performance expectancy, facilitating conditions, social influence and behavior intention. For many years, many researchers have validated the UTAUT, which has been validated through various empirical studies. It is academically meaningful to begin the study of factors affecting the acceptance of smart factory technology in terms of the UTAUT. In practice, it is necessary to provide SME employees with more information related to the introduction of smart factories, to provide advanced services related to the establishment of smart factories, and to establish a standardized model for each industry.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.38-48
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• 2018

The purpose of this study was to identify various factors that could possibly influence special teachers' adoption intention towards robot-based education and to see how well those factors predict special teachers' adoption intention. To do this, questionnaire items were selected and reconstructed based on preceding research relating to Technology Acceptance Model(TAM). The survey participants consisted of 623 special school teachers, representing various types of special students and levels of their schools. Questionnaires with unfaithful responses were excluded, and a total of 590 questionnaires were analyzed. Data analysis was carried out through Exploratory factor analysis and stepwise multi-regression analysis. According to the results of study, factors that influence special teachers' acceptance intention towards robot-based education are perceived ease of use, perceived usefulness, personal innovation, and social influence. Also, the most decisive factors affecting special teacher's acceptance intention were perceived usefulness and perceived ease of use. These factors directly influenced special teachers' acceptance intention.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.545-559
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• 2016

Recently consumers to access various Word-Of-Mouth information on online. And eWOM (eWOM : electronic Word-Of-Mouth) information had an important effect on consumer attitude(purchase intention). The purpose of this study is to investigate what the general characteristics of eWOM and the effects of how these factors will affect credibility, eWOM acceptance and purchase intention. In this study, the model contains information characteristics variables(consensus, newness), community characteristics(tie strength, interaction) on eWOM characteristics. This study makes contributions as follows. First, information consensus had not effect on credibility. Second, information newness and community characteristics(tie strength, interaction) had a significant on credibility. Third, credibility is the important factor on eWOM acceptance. Lastly, eWOM acceptance had a considerable influence on purchase intentions.

• The Journal of Bigdata
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• v.2 no.2
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• pp.47-56
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• 2017

The UTAUT was presented as a comprehensive of eight existing theories to improve the limit of Technology Acceptance Model (TAM), and it has been also utilizing in various fields related to acceptance and diffusion of new technology. In this study, we analyzed factors utilized in UTAUT through meta-analysis, and confirms the consistency of the model. We presented the principal factors and the additional factors. Moreover, we presented differences and suggestions through comparative analysis with previous researches. The meta-analysis showed that satisfaction, hedonic motivation, attitude, perceived enjoyment showed a important factors as additional factors. Based on this result, we presented an extended UTAUT model. In the case of Korea studies, it was found that increasing the degree of behavior intention is the most important factor leading to use behavior. The results of this research will be able to support researchers who research the acceptance and diffusion of new technologies, and companies trying to launch new products.

• Korea Journal of Hospital Management
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• v.15 no.3
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• pp.47-68
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• 2010

One of the important complaint factors by the patients using medical institutions is various kinds of waiting time. This research is about the causal relationships among waiting time(application of waiting time, perceived of waiting time, fairness of waiting, explanation of the delay, acceptance possibility), service values, and customer satisfaction. The subjects for this study were 256 out-patients currently using seven general hospitals in the Busan area. The findings of the empirical analysis are as follows: First, the good application of waiting time or fair waiting time procedure didn't actually affect perceived waiting time. Second, though the application of waiting time didn't affect acceptance possibility, the fair procedure of waiting time had an affirmative effect on acceptance possibility. Third, even when there was enough explanation about the need to wait, it could shorten perceived waiting time but failed to get sufficient sympathy or agreement from the patients. Fourth, the possibility of acceptance following the sufficient sympathy of patients had an effect on shortening perceived waiting time. Fifth, perceived waiting time lowered customer satisfaction, but had no negative effect on service values. Finally, the ranges of acceptance possibility by the patients were found to increase customer satisfaction and maximize service values. In conclusion, every medical institution needs to focus on, first of all, shortening waiting time for more customer satisfaction and improved service values.

• The Journal of Industrial Distribution & Business
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• v.9 no.11
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• pp.25-38
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• 2018

Purpose - This study aimed to identify the sub-dimensions of fashion social media quality (information quality, social quality, service quality, system quality) and investigate how they affect purchase intention through fashion information use behavior (information acceptance, information diffusion). Research design, data, and methodology - Data collection was carried out twice for systematic verification of the research model. In the first data collection, the reliability and validity of research variables were verified through 238 respondents and questionnaires were revised and supplemented based on their responses. In March 2018, the final survey was conducted from 755 respondents the age of 20 to 49. Using SPSS 23.0, descriptive statistics, exploratory factor analysis, correlation analysis were performed. In order to test hypotheses, structural equational modeling technique was employed using AMOS 23.0. Results - First of all, fashion Social media quality consists of four factors including information quality, social quality, service quality and system quality. Second, fashion Social media information quality, social quality, and system quality were shown to have a positive(+) effect on information acceptance behavior, and social quality, service quality and system quality were shown to have a positive(+) effect on information diffusion behavior. It was also determined that the acceptance and diffusion behaviors of fashion information through fashion Social media had positive(+) influence on purchase intention. Conclusions - This study holds academic significance in its identification of the components of fashion Social media quality and for conducting an empirical analysis on the causal relationship between fashion information acceptance and diffusion behaviors, and purchase intention. The results of this study indicate that fashion involvement is the key factors in determining the quality of Social media, the acceptance of information through Social media, and, by extension, the purchase of fashion products. Practitioners in the fashion industry may use the findings of this study in order to build more effective Social media strategy.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.554-571
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• 2021

The purpose of this study is to investigate the mediating effect of trust when a media broadcaster (such as a disc jockey [DJ]) acting as an information source and the content they provide during live commerce streaming affect acceptance intention. Live commerce is increasing rapidly, offering a new fashion distribution channel by supplementing possible shortcomings of existing online shopping. Data was collected for the empirical study from female consumers in their 20s who actively accepted fashion technology. Statistical analysis of the data was conducted using IBM SPSS Macro Process 3.5. First, the reliability and validity of the variables for information source characteristics, content informativeness, trust, and acceptance intention were verified, and each variable was confirmed as a single factor. Bootstrap analysis was performed using Macro Process Model 4 to reveal the effects of information source characteristics and content informativeness on acceptance intention. As a result of analyzing the mediating effect for each path model with trust as a parameter, it was found that both the direct and indirect effects of the mediating path were significant. This result means that the characteristics of information sources and content informativeness are partially mediated by trust. Therefore, to promote consumer behavior in a live commerce shopping environment, it is necessary to enhance trust. This can be achieved by a media broadcaster with fashion expertise to increase the perception of the attractiveness of the information source and to improve the usefulness of the fashion information being delivered.