• ETRI Journal
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• v.43 no.1
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• pp.74-81
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• 2021

The mixture model is a very powerful and flexible tool in clustering analysis. Based on the Dirichlet process and parsimonious Gaussian distribution, we propose a new nonparametric mixture framework for solving challenging clustering problems. Meanwhile, the inference of the model depends on the efficient online variational Bayesian approach, which enhances the information exchange between the whole and the part to a certain extent and applies to scalable datasets. The experiments on the scene database indicate that the novel clustering framework, when combined with a convolutional neural network for feature extraction, has meaningful advantages over other models.

• Journal of Distribution Science
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• v.21 no.11
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• pp.103-111
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• 2023

Purpose: This research aims to study the selection attributes influencing the purchasing decisions of the MZ generation in online luxury stores and explores the moderating effects of consumer value. The research aims to validate the impact of reasonable pricing, brand reliability, product variety, comprehensive product information, and user-friendly interfaces on customers' decision to purchase products from online luxury stores. Research design, data and methodology: A survey was conducted with 101 participants, and data analysis included exploratory and confirmatory factor analysis, as well as covariance structure model analysis. Results: The findings reveal that brand trust, product variety, and information sufficiency significantly influence brand affect, which in turn influences purchase intention. Additionally, the study identifies that consumers prioritizing hedonic value are more influenced by brand trust and information, while those prioritizing utilitarian value are more responsive to factors like reasonable price, product variety, and ease of use. Conclusions: The study provides insights into the preferences and behaviors of the MZ generation, highlighting their digital proficiency, mobile-centric lifestyle, desire for product variety, price-consciousness, social media influence, and the availability of personalized shopping experiences as factors contributing to their preference for online luxury stores. These findings contribute to understanding consumer behavior and decision-making processes in the context of online luxury shopping.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.261-270
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• 2019

The study examines the relationship between perceived mental benefits, online trust, and personal information disclosure when shopping online in Vietnam. The e-commerce market has been booming in Vietnam since 2015. The number of online transactions and e-commerce sites has increased steadily in recent years. However, the number of online sales in Vietnam is still not high, and consumers are still limited in buying from websites when they have to provide too much information during and after the shopping process. The mix-method is used to ensure the scientific nature of the study. Qualitative research method (phenomenological research) along with the quantitative research method (survey) are applied to meet the research objectives. The data in the study was collected through the group discussion with eight experts and the survey with 917 respondents. Data processing result via SmartPLS software indicate the positive relationships between the factors in the research. The perceived mental benefits have the most potent influence on the online trust of Vietnamese customers; at the same time, both the perceived mental benefits and online trust affect customers personal information disclosure in electronic commerce. Some managerial implications relating increasing the perceived mental benefits, and customers' online trust are proposed for online businesses.

• Journal of Distribution Science
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• v.19 no.12
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• pp.71-81
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• 2021

Purpose: This study to seek to answer two research questions in distribution science: what photo decoration cues in online grocery stores could be identified? Could photo decoration cues significantly effect on the affective perception and behavioral intention of consumers? Research design, data, and methodology: his study conducted a laboratory experiment with a 2×2×2 factorial design to validate the proposed research model and test our proposed hypotheses. Research design, data and methodology: Two stages experiments were adopted in this study, among 360 voluntaries who have had an experience of online grocery shopping, 331 valid data had been collected and analyzed using MANOVA and PLS-SEM algorism. Results: (1) both reflective surface and complementary goods layout lead to visual appeal and shopping enjoyment; (2) contrast color usage positively impacts on visual appeal while does not significantly affect shopping enjoyment; (3) consumers' affective responses positively impact attitudes toward product and store which in turn lead to purchase intention and store loyalty. Implications for research and practice are discussed. Conclusions: Using the media richness theory, visual rhetoric theory and visual design literature as the theoretical foundation, the study provides a solid foundation to comprehend the impact of photo design artifacts on consumers' affective responses when online consumers shopping online for fresh grocery.

• Journal of Distribution Science
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• v.18 no.3
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• pp.77-85
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• 2020

Purpose: This study examined marketing value as online word-of-mouth media in the foodservice industry, and it did research on online word-of-mouth (e-WOM) communication marketing schemes using mass communication in the industry. The study is also intended to investigate the impact of electronic word-of-mouth (e-WOM) information and communication on product awareness risks, benefits, and word-of-mouth (WOM) impacts on restaurant consumers. Research design, data, and methodology: The analysis was conducted on a valid questionnaire of 425 menu product consumers. The survey was conducted for two months in March 2019. The collected data was analyzed using SPSS and hierarchical regression analysis was applied. Results: It did empirical research on the reciprocal casual relations to online and the existing word-of-mouth communication that have to be preceded to understand characteristics of online word-of-mouth communication for the purpose of this study. The result is summarized as follows. First, the online word-of-mouth (e-WOM) effect on product recognition risk shows the statistically significant effect of information sender characteristics, information recipient characteristics, and online word-of-mouth (e-WOM) communication on product recognition risk. Second, the influence of online word-of-mouth (e-WOM) on product risk benefits shows that the information sender characteristics, the information receiver characteristics, and online communications have a statistically significant effect on product risk benefits. Third, online word of mouth risk recognition had a statistically significant effect on word of mouth acceptance. Fourth, online risk benefit had a statistically significant positive effect on word of mouth (WOM) effect. Conclusions: The communication between online word of mouth (e-WOM) sender and recipient had a positive influence on the product evaluation and attitude change in the foodservice industry, and the word-of-mouth (WOM) effect affected financial and non-financial performance. The results mentioned above indicated that the communication between the sender of the information and the receiver of the information had a positive effect on the product evaluation and attitude change of the menu consumer, and the word-of-mouth (WOM) result affected the financial. Therefore, the online word-of-mouth (e-WOM) effect has a positive effect on the word-of-mouth (WOM) effect of menu products when performed simultaneously and positively between the information sender and the information receiver.

• Fashion & Textile Research Journal
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• v.21 no.2
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• pp.141-150
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• 2019

Online recommendation services help people search for an appropriate product among a huge assortment in stores that also minimize consumers' choice overload. People with a need for uniqueness are likely to prefer this online recommendation service based on individual needs and tastes. This study verifies the effect of consumers' choice overload and similarity avoidance in consumers' evaluation towards an online recommendation service with a focus on innovativeness and use comparability. Two-hundred consumers participated in this study and data were collected through an online survey firm. A mock retailer's webpage was created and showed six types of sneakers, which was presented as a result of product recommendation based on consumers' personal information. Data was analyzed using confirmatory factor analysis (CFA), analysis of variance (ANOVA), and regression analysis. The results show that people with a high similarity avoidance perceive an online recommendation service as an innovative and compatible service. They also perceive a high level of use compatibility for an online recommendation service, especially when it is difficult to choose a product under choice overload. Innovativeness and use compatibility of an online recommendation service increase behavioral intention. The results of this study can contribute to strategies to start online recommendation services from online retailers' websites that identify circumstances in which consumers can adopt innovative services in a positive manner.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.382-386
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• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

• Journal of Distribution Science
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• v.15 no.9
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• pp.27-36
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• 2017

Purpose - In this study, the author investigates which shopping motivations affect regulatory focus differently. This study also determines the effect of shopping motivation on regulatory focus when consumers use different shopping channels. Additionally, the author tries to investigate how information quality affects regulatory focus. Similarly, this study also examines the effect of the shopping channel on the relationship between information quality and regulatory focus. Research design, data, and methodology - With 635 surveyed questionnaires, this study was conducted by SPSS and AMOS 22.0 version. SEM was used to verity hypotheses and model. Results - According to this research, hedonic shopping motivation affects promotion focus positively and prevention focus negatively. Furthermore, when consumers use a mobile channel rather than an online one, hedonic shopping motivation affects prevention focus more negatively. However, depending on the shopping channel, there are no significant differences in the case of the relationship between hedonic motivation and promotion focus. The author also examines how information quality affects regulatory focus. In particular, when consumers use a mobile channel rather than an online one, information quality affects promotion and prevention focus more positively. Conclusions - Through this study, the author suggests that shopping motivation and information quality could influence consumers' regulatory focus, shopping attitude, and intention.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.267-274
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• 2020

The focus of this study is to investigate the mediating role of online market orientation on information capital readiness-business performance relationship. The construct of information capital readiness is rarely researched. The readiness here refers to the availability of information capital needed to support strategy execution. As quantitative research, this study employs the partial least squares structural equation modeling (PLS-SEM) to test the hypotheses. Data was collected using questionnaires from the owners/managers of the micro, small, and medium-sized enterprises (MSMEs) in the East Java Province, Indonesia. As many as 433 respondents had participated. The result indicates that information capital readiness directly and positively affects business performance. Further analysis reveals that online market orientation partially mediates information capital readiness-business performance relationship. In conclusion, this study suggests that the owners/managers of the MSMEs should improve their information capital readiness to support online market orientation strategy so that it can improve their business performance. This is the first study that brings together the issues of information capital readiness and online market orientation as the antecedents of business performance in the Indonesian MSMEs research setting. The mediating role of online market orientation is rarely explored in previous studies.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.123-126
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two important aspects of online reviews are first, the topics consumers choose to address and second, the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre-and post-pandemic periods. After performing topic modeling on Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. Also, the order and magnitude of topics' impact on review sentiment change between pre-and post-pandemic periods for both countries. This study can help businesses to understand how topics and sentiments associated with their products and services changed after pandemic, and also help them identify areas of improvement.