• Journal of Distribution Science
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• v.16 no.10
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• pp.39-46
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• 2018

Purpose - this research is to examine the relationship between Franchise's experiential value, lovemarks, respectful recognition, and brand loyalty focusing on the control variables. Control variables such as age, occupation, education, monthly income, and kinds of restaurant are included to measure influence on these as well. Research, design, data, and methodology - 500 questionnaires were distributed from June 10th to July 10th, 2017. 225 respondents were totally included in this analysis using SPSS and AMOS program. In order to test hypothesis, factor analysis and reliability verification firstly were employed, and then covariance structure analysis was used. Results - Empirical results are as followed. First, it can be mentioned that the esthetics of dessert cafe is analyzed to have a positive effect on the perception of love and respectful perception. Second, playfulness has a positive effect on perception of love. Third, respect perception has a positive effect on brand loyalty. When variables such as age, occupation, education, monthly income, and restaurant type were used as control variables, only monthly income had a significant effect on respect recognition. This shows that the control variable has a significant effect on the causal relationship of the variables. Conclusions - In summary, it can be stated that it is necessary for marketers to establish marketing strategies in order to boost customers' experiential value such as esthetics of franchise and also to strengthen lovemarks for respectful recognition and brand loyalty.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.167-178
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• 2016

This research is to understand the causal relationship between class participation motivation, acting expressiveness and psychological happiness through the class of the college students majoring in acting. For this purpose, the simple random sampling method was used and the college students majoring play and acting in the college located in Seoul and Gyeonggi-do as a sample group and total 499 questionnaires were used. For the questions, 73 questions of which the reliability and validity is examined were used. As for a data processing method, it used the statistical package of IBM STATISTICS SPSS 22 and AMOS 22 and analyzed the results by applying the descriptive statistics analysis, confirmatory factor analysis, reliability analysis and structural equation model. The conclusion of this research is as follows. Intrinsic motivation and extrinsic motivation among the class participation motivation of the college students majoring in acting have a significant effect on all sub factors of acting expressiveness and psychological happiness statically, and a motivation has no effect on it. Both personality and expressive impulse of acting expressiveness have an effect on a psychological happiness, and mobility has no effect on it.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.337-353
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• 2013

Purpose: As there are more cases of forged brands, change of awareness is urgently required at the governmental, corporate and consumer levels. Therefore, this study aims to positively analyze the correlation between forged brand quality and purchase intentions perceived by consumers based on types of preference of luxury brands. Methods: In order to achieve the above purpose, this study derived a model of causal relationships among the forged brand quality, preference of typified luxury brands, and purchase intentions. SPSS 20.0 was applied for data processing. Frequency analysis ad descriptive statistical analysis were conducted for basic data and measurement tools were verified through feasibility and reliability analyses. Multiple regression analysis was conducted to verify the hypotheses. Results: Based on the results, only utilitarian quality positively (+) affected non-intrinsic preference while its impact on intrinsic preference was negative (-). On the other hand, hedonic quality was significantly positive (+) but the impact was not significant. Both utilitarian and hedonic qualities had significantly positive (+) impacts on the intentions to purchase forged brands with the impact of hedonic quality relatively higher. Conclusion: These results clarified that the overall consumption of Korean consumers had not entered its maturity, yet. Also, Korean consumers regard forged brands as alternatives to luxury brands mostly because of hedonic quality. As hedonic quality is added, Korean consumers' purchase intentions became higher. Based on these results, this study suggested the measures to be taken for the country to develop into an advanced country in the luxury market which is becoming more global and overcome the barrier of its old trend in imitation at the four levels of manufacturers, distributors, government, and consumers.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.791-797
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• 2017

Today, we are using computer simulations in various engineering disciplines to reduce the time and cost of product development. The scope of simulations is increasingly complex and diverse for different fields such as mechanical, electrical, thermal, and fluid. Thus, it is necessary to use integrated simulations. In order to overcome these problems, a language has been developed to effectively describe and implement simulations is Modelica. To model and simulate a system, physical models can be broadly divided into causal and acausal models. The most important feature of Modelica is acausal programming. In this study, we will introduce simple concepts and explain about the usage of Modelica. Furthermore, we will explain the vibration analysis of a two degree-of-freedom system and the design of appropriate parameters by using Modelica.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.230-241
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• 2017

The main purpose of this study was to empirically investigate the effects of participation behavior and performance improvement on motivation factors of Korean university students which participated in LINC by utilizing Vroom's Expectancy Theory. Three motivation factors of valence, instrumentality, and expectancy were examined in this study. In addition, two different models (valence and force model) analyzed the causal relationships regarding participation behavior and performance improvement. 236 data were collected and findings of this study were as follows: First, comparative analysis between demographic characteristics including university, major, and residence had no significant differences in mean value. However, females had higher levels of recognition related to valence (attractiveness) relative to males. Second, valence and the force model were significant predictors of LINC participation behavior and performance improvement. Furthermore, the coefficient of determination and beta coefficient of the force model were higher compared with the valence model. Third, the level of mediation effects including direct, indirect, and total effect of the force model was higher than the valence model. LINC participation behavior had a partial mediating effect between the three motivation factors and performance improvement variable.

• Journal of The Korean Association For Science Education
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• v.35 no.5
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• pp.919-929
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• 2015

This study aims to develop a modeling-based learning program about geologic structures and to reveal the relationship between the argumentation patterns and levels of students' mental models. Participants included 126 second grade high school students in four sessions of modeling-based learning regarding continental drift, oceanic ridges, transform faults, and characteristics of faults. A modeling-based learning program was implemented in two classes of the experimental group, and teacher-centered traditional classes were carried out for the other students in the comparison group. Science achievement scores and the distribution of students' mental models in experimental and comparison groups were quantitatively compared. The video-taped transcripts of five teams' argumentation were qualitatively analyzed based on the analytic framework developed in the study. The analytic framework for coding students' argumentation in the modeling-based learning was composed of five components of TAP and the corresponding components containing alternative concepts. The results suggest that the frequencies of causal two-dimensional model and cubic model were high in the experimental group, while the frequencies of simple two-dimensional model and simple cross sectional model were high in the comparison group. The higher the frequency of claims, an argumentation pattern was proven successful, and the level of mental model was higher. After the rebuttal was suggested, students observed the model again and claimed again according to new data. Therefore, the model could be confirmed as having a positive impact on students' argumentation process.

• Korean Journal of Social Welfare
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• v.62 no.2
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• pp.161-185
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• 2010

The purpose of this study is to verify the causal relationship between depression and aggressiveness among adolescents. The 4-year longitudinal data collected from 2,670 4th grade elementary school students by the Korean Youth Panel study was used in this study. From the analysis result using the Autoregressive Cross-Lagged Model, the depression and aggressiveness in adolescents were continued from elementary school 4th grade to middle school 7th grade in significant stability. In addition, the previous aggressiveness turned out to have significant positive effect on the later period depression. Similarly, the previous depression had significant effect on the later aggressiveness, but the direction was negative. This means that the adolescents's depression increases as their aggressiveness increases, but as the depression increases, the later aggressiveness of the adolescents decreases. There were no differences between girls and boys within the relationship of these two variables. Finally, the implication derived from the results, the limitation of this study, and suggestion for following studies were presented.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.1
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• pp.87-96
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• 2014

E-shopping is traditional method to purchase products in a modern society. Fashion products are one of the most popular product categories sold and impulsively bought online. This study examined the causal relationship of shopping value, positive emotion, urge to buy impulsively, and e-impulse buying in the context of shopping for apparel products. A self-administered questionnaire developed from the literature was administered in class to 501 female college students in Busan. AMOS 21.0 estimated the structural equation model of e-impulse buying using a correlation matrix with a maximum likelihood. The analysis of the data supported most of the predictions. The results suggested that consumer shopping values (hedonic shopping value and utilitarian shopping value) had a positive effect on positive emotion; in addition, positive emotion urge to buy impulsively directly affected the e-impulse buying of apparel products. In the structural model, e-impulse buying of consumers can be predicted by the attitudinal component (e.g., shopping values), emotional factors (e.g., enthusiastic or proud), and the urge to buy impulsively felt by young consumers. There are implications that both positive emotion and impulsive buying are important predictors for the e-impulse buying of apparel products by consumers. Moreover, the urge to buy impulsively was an important mediator to determine the e-impulse buying of apparel products. This study provides insight to retailers and researchers to understand the structural relationship of consumer characteristics and the e-impulse buying of apparel products.