• Asia Marketing Journal
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• v.17 no.4
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• pp.21-42
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• 2016

Purpose: Social influence has a decisive role in shaping a person's cognition and behavior. Chinese face consciousness, including moral component, is an important part of Chinese traditional culture, which influences people to implement moral behavior. With both eye-tracking technology and traditional questionnaire, this research aims to explore people's moral psychology and the psychological processing mechanisms of Chinese face consciousness, as well as the impact of Chinese face consciousness on the preference for the ecological product. Method and Data: 75 college and MBA students' eye movement data were collected when they read different kinds of moral materials, as well as data from the subsequent questionnaires. To test the hypothesis, ANOVA analysis and Heat Map analysis were performed. Besides, the PROCESS of bootstrap was used to test mediation effect. Findings: The results reveal that: 1. Compared to the moral-situation reading, when subjects read immoral situations, they need more processing time due to the moral dissonance and cognitive load. 2. Compared to the control condition, when threatened moral self is primed, subjects prefer to choose ecological product. 3. Protective face orientation is the mediator between threatened moral self and preference to ecological product. Key Contributions: First, this study broadens the use of eye-tracking technology in marketing and demonstrates a better understanding of the relationship between morality and consumer behavior in a more scientific way. Second, this study not only distinguishes the meanings between "protective face orientation" and "acquisitive face orientation", but also innovatively validates that when moral self is threatened, consumers tend to choose ecological product as moral compensation in order to protect their face. It can shed light on the promotion of ecological product in practical applications.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.79-91
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• 2022

In this study, the effects of self-efficacy, perceived usefulness, perceived ease of use, and depression on college students' academic persistence in the COVID-19 epidemic and the resulting non-face-to-face education situation were identified as mediating effects on learning satisfaction. In the second semester of 2020, a survey was conducted on students enrolled in a four-year university in Daegu and the data were statistically analyzed. The path coefficient was estimated by the Smart PLS bootstrap method and the significance of the path coefficient was verified. The Sobel Test was conducted to verify the mediating effect of academic continuity intention as a parameter. The research results can be summarized as follows. First, it was found that self-efficacy and perceived usefulness had a significant influence in the relationship with learning satisfaction. Second, the relationship between learning satisfaction and academic continuity intention was found to have a significant influence. Third, depression and ease of use did not show any significant influence in the relationship between learning satisfaction. Finally, a Sobel Test was conducted to verify the mediating effect of academic continuity intention with self-efficacy, usefulness, ease of use, and depression as independent variables and learning satisfaction as parameters. As a result of both regression analyses, it was found that β values decreased, and learning satisfaction had a mediating effect. As a result of this study, it is suggested that research to increase learner satisfaction and develop various contents to increase the effectiveness of education that can increase self-efficacy and perceived usefulness should be conducted in parallel. I think this study can be used as basic data in establishing measures to continue studying for college students in natural disaster situations or psychological crisis situations called COVID-19.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Analytical Science and Technology
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• v.28 no.3
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• pp.187-195
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• 2015

The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.686-701
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• 2020

The purpose of this study is to find out how employee's gratitude disposition affects Organizational Citizenship Behavior(OCB) and empirically validating multiple mediation effect of perceived organizational support(POS) and job satisfaction. For this study, an online survey has been conducted on office workers to analyze 380 sets of answers, reviewed reliability and validity through CFA and used SPSS 25.0, AMOS 25.0, Macro Process 3.0, a bootstrap method to test hypothesis. As a result, it is verified that an employee's gratitude disposition positively affects OCB, POS and job satisfaction and that there exists a multiple mediation effect of POS and job satisfaction. In this study, it is validated that an employee's gratitude disposition has a positive influence on OCB and an employee's gratitude disposition, an individual trait, is a related antecedent variable of POS. The result of this study is meaningful that it suggests boosting gratitude disposition, a positive psychological factor, in an organization can positively affect employees' job attitude and organization effectiveness.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.592-599
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• 2018

The purpose of this study is to examine whether the participation of lifelong learning activities of the elderly is a part of the self - The questionnaire consisted of 12 items of general characteristics, 5 items of lifelong education, 6 items of volunteer activity, 15 items of life satisfaction, and 10 items of self - integration. The subjects of this study were 300 elderly people aged 60 or older living in Seoul, Gyeonggi - do, and Incheon, and participated in lifelong educational institutions such as the elderly welfare center, elderly university, and ward. As a method of analysis, the structural equation model of AMOS 22.0 was applied. The results obtained by applying the structural equation analysis are as follows. First, general characteristics were tested and the reliability of the items was tested. The reliability of the items, predictability, accuracy, and validity were analyzed by principal component analysis. Second, the research hypothesis was verified by verifying the fit of measurement variables through participation factor of lifelong education, self - integration, life satisfaction, and voluntary service. Statistical analysis was performed using the SPSS WIN 22.0 and Amos 22.0 programs.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.150-160
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• 2020

The purpose of this study was to test the effect of socially-perfectionism on depression by mediating ambivalence over emotional expressiveness and experiential avoidance. For this purpose, 201 participants across the country conducted the survey, a measure of MPS, AEQ-K, AAQ-II, CES-D. The descriptive statistics, Pearson correlation, path coefficient were conducted using SPSS 23.0. The indirect effect was examined using bootstrap in PROCESS Macro. The results of the study are as follows. First, all the variables had meaningful positive correlations. Secondly, When socially-perfectionism affects depression, ambivalence over emotional expressiveness, and experiential avoidance were mediated. As a result, the implications and limitations of the study were discussed.

• Research in Community and Public Health Nursing
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• v.29 no.3
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• pp.371-381
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• 2018

Purpose: The purpose of this study is to identify the mediating effects of self-esteem between social comparison orientation and social network service (SNS) addiction in university students. Methods: Descriptive cross-sectional survey design was employed. The data were statistically analyzed by using the descriptive and inferential statistics. Sobel test and Bootstrap method, and Kappa squared mediation effect size measure were used to identify the mediator's significance. A convenience sample of 195 subjects was recruited from two universities in Korea. Results: The mean age of the subjects was $22.58{\pm}1.81$. The subjects showed relatively high levels of SNS addiction with a mean score of $14.33{\pm}4.80$. The overall model significantly explained 37.0% of variances in the subjects' SNS addiction after controlling gender, age, grade, major, period of SNS using, time spent on SNS per day, and times accessed SNS per day. Of the predictors, time spent on SNS per day, social comparison orientation, and self-esteem were significantly associated with SNS addiction. Self-esteem was the mediator between social comparison orientation and SNS addiction. Conclusion: When developing strategies for preventing SNS addiction, interventions for reducing time spent on SNS per day, not having upward social comparison orientation, and improving the self-esteem should be considered. These findings might provide a theoretical basis for developing effective strategies for preventing SNS addiction in university students.

• The Journal of Fisheries Business Administration
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• v.43 no.2
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• pp.79-94
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• 2012

The purpose of this study is to investigate the production efficiencies of the Korean aquaculture fishery with respect to species and methods using a Data Envelopment Analysis. The study extracted the 8 fishes in each of the sea cage culture, aquarium basin, and enclosed aquaculture for the analytical purposes. First, the study estimated the technical, pure technical, and scale efficiencies of the total of 24 aquaculture fishes based on the traditional DEA under the assumptions of both CRS and VRS. 2 fishes were identified as the efficient DMUs under the CCR-model, and 6 fishes under the BCC-model. Second, we tested to see if there was any difference in production efficiencies regarding those three different methods of aquaculture. we could not find any evidence of the differences in efficiency using a rank sum test based on the traditional DEA. However, we could do find that the pure technical efficiency in the sea cage culture was lower than others at 1% level of significance and the pure technical efficiency in enclosed aquaculture was also lower than others at 5% level of significance using Bilateral-DEA, which could explicitly consider the heterogeneity in the 3 production methods of aquaculture. Finally, the study obtained the 95% confidence intervals of the efficiency scores for the 24 fishes under our study using the smoothed bootstraping method in the process of the re-sampling in cooperation with both a kernel density estimation and a reflection method. At the same time, we could estimate the bias-corrected efficiency scores while the traditionally estimated efficiency scores suffered from the biases in the process of solving a linear programming with the deterministic nature of a production frontier. And hence, we could distinguish the differences in production efficiencies of the 8 fishes with respect to those 3 methods of aquaculture.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.43 no.5
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• pp.482-488
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• 2010

Three specimens of Cynoglossidae larvae were collected from the southern Korean Sea in May and August of 2009, and were identified using morphological and molecular analysis. Specimens were divided into two groups based on the number of elongated dorsal fin rays on the top of the head: Cynoglossidae sp. A was defined as having two elongated dorsal fin rays, while Cynoglossidae sp. B possessed a single elongated dorsal fin ray. One specimen of Cynoglossidae sp. A, a post-larva with a notochord length (NL) of 5.8 mm was thought to be a Cynoglossus joyneri larva based on the presence of 115 dorsal pterogiophores, 85 anal pterogiophores, and 50 myomeres. Two specimens of Cynoglossidae sp. B, a 4.1 mm NL larva and a 11.3 mm NL juvenile, were thought to be Cynoglossus abbreviatus based on the presence of yolk in the former and 133 dorsal fin rays, 105 anal fin rays, and 63 myomeres in the latter. To test this morphology-based identification, molecular analysis was conducted using 419-422 bp of mitochondrial DNA 16S rRNA. Cynoglossidae sp. A was clearly matched to a Cynoglossus joyneri adult (d=0.000) and Cynoglossidae sp. B clustered closely with Cynoglossus abbreviatus adults (d=0.002). A neighbor-joining tree supported this robust relationship (bootstrap value=100%). Therefore, these molecular data validate the morphological identification of the two Cynoglossidae larval species.