• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.231-244
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• 2020

With the rapid progress of the 4th industrial revolution, technical human capitals are considered to be the core competing factors of the enterprise. Technical manpower training of the 4th industrial revolution through technical education has become an essential task of venture start-ups. The opening of technical training courses and the education support system of companies are increasing, but the shortage of technical manpower is getting worse. This study was conducted to analyze the factors affecting participation intention of the 4th industrial revolution technology education. The research model was established based on the model of goal-directed behavior. For the analysis, 250 valid questionnaire data were used to test with a structural equation model. The results of the study are as follows. First, attitude had a positive effect on the intention to participate in education. Second, subjective norms had a positive effect on the intention to participate in education. Third, the perceived behavioral control has not been tested for a significant influence on educational participation intention. Fourth, positive and negative anticipated emotions had a significant effect on educational intention. The impact of significant variables were found in the order of positive anticipated emotions, attitudes, negative anticipated emotions, subjective norms. On the other hand, as a result of testing the mediating effect of desires, it was found that desires plays a mediating role between attitude, subjective norm, perceived behavioral control, positive anticipated emotions, negative anticipated emotions, and participation intention. In particular, the causal relationship between perceived behavioral control and intention to participate in education was not significant, but perceived behavioral control had a significant effect(full mediation) on participation intention through desires. Based on the results of this study, the following implication were suggested. First, the model of goal-directed behavior(MGB) was applied to the technical education field. Second, the direct relationship between antecedent variables and behavioral intentions was simultaneously tested. Third, unlike the existing education-related research, the factors affecting participation in education were analyzed. Fourth, the importance of desires for education were suggested.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.171-183
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• 2016

It is often reported that foreign tourists visiting Korea are not satisfied with dining in a Korean restaurant, and the reason is assumed that most of the Korean restaurants are targeting Koreans and operating in a traditional way; thus, this study suggests the need of a new type of Korean restaurant such as quick service restaurant, where foreign tourists could have Korean food in a more familiar way. It is attempted to examine foreign tourists' visit intention toward Korean quick service restaurant (QSR) applying the model of goal-oriented behavior (MGB). The survey was conducted with foreign tourists and total 275 data was gathered. Structural equation modeling was used for analysis. Among MGB variables, attitude, subjective norm, perceived behavioral control had significant effect on desire, while postive and negative anticipated emotions did not had significant effect. Also, involvement showed a significant moderating effect as positive anticipated emotion had much stronger effect on desire in a high involvement group.

• Journal of Information Technology Services
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• v.6 no.1
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• pp.83-99
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• 2007

The purpose of this research is to identify the determinants of loyalty in online games. This study developed a research model to analyze the factors explaining the loyalty level from gamers, employing social identification, flow, and positive anticipated emotion as major research variables, and collected 1308 survey responses from gamers. Within the context of arguing that the exploration of age range issues with respect to online games is important, this research also examines the age differences in path coefficients. To this end, the structural model was tested with the data from entire data sample (i.e., the age of 10s, 20s, and 30s pooled together) and each of the subsamples (i.e., teens taken separately, twenties taken separately, and thirties taken separately). Properties of the causal paths, including standardized path coefficients, the significance of difference, in the hypothesized model, are also presented, so that we can investigate the relative influences of different dominants, demonstrating how teens, twenties, and thirties differ in their decision-making processes regarding the flow, social identification and loyalty from online games.

• Korea Trade Review
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• v.46 no.2
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• pp.193-212
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• 2021

This study investigates the structural relationship among 11 latent factors that potentially influence the intention of Chinese consumers to purchase electrical vehicles (EV) by applying the MGB and TAM models, both based on well-established socio-psychological theories. For this research, we conducted an online survey using a Chinese platform collecting 287 valid responses to our questionnaire. The analysis reveals that 10 out of the 12 hypotheses were adopted while 2 were rejected. Specifically, it was found that EC (environment concern) and PEV (perceived environment value) had a positive effect on the PEU (perceived environmental usefulness) of electric vehicles. In addition, ATT (attitude), PAE (positive anticipated emotion), and PBC (perceived behavior control) were confirmed to have a significant positive relationship with DES (desire) for EV purchase. At the same time, the results of the analysis show a statistically significant relationship between PEU, ATT as well as PI (purchase intention). This study further analyzed and presented the results of the moderating effects of gender, based on the adopted relationship hypotheses. This study is novel in that it is the first attempt in the literature to apply both the MGB model and the TAM simultaneously to predict EV purchasing behavior.