• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.139-148
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• 2024

In the post-pandemic era, the demand for online education platforms has surged, leading to increased consumer reliance on online reviews for decision-making. This study investigates the impact of Chinese online customer reviews on consumer purchase behavior in online education. By examining the role of trust, review sentiment, and the quantity and timeliness of reviews, the research aims to understand how these factors influence consumer decisions. By using regression model, findings reveal that negative reviews, timely feedback, and a higher volume of reviews positively affect consumer purchase decisions, while course pricing demonstrates an inverse relationship. Furthermore, cognitive and affective trust mediate the relationship between reviews and purchase behavior, highlighting a reverse U-shaped effect on consumer decision inclination. These insights provide valuable implications for online education providers, emphasizing the need to manage and leverage online reviews to foster consumer trust and improve sales performance.

• The Journal of Korean Obstetrics and Gynecology
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• v.37 no.1
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• pp.23-39
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• 2024

Objectives: Primary dysmenorrhea (PD) is defined as abdominal pain during menstruation period in the absence of an identifiable pathological lesion. Corydalis tuber (CT) is an herbal medicine that has an excellent effect in relieving pain and convulsions. The purpose of this study is to observe the effect of Corydalis tuber aqueous extracts (CTe) on primary dysmenorrhea. Methods: The rats were injected with estradiol benzoate subcutaneously for 10 days (2.5 mg/kg on the first and 10th days, and 1 mg/kg from the 2~9th day). Oxytocin 1 U/kg was treated by peritoneal injection 1 hour after the last 10th injection of estradiol benzoate. CTe 400, 200 and 100 mg/kg were administered orally, once a day for 10 days at 30 minutes after each estradiol benzoate treatment. The results of CTe were compared to those of IND 5 mg/kg orally treated rats. Results: As results of estradiol benzoate and oxytocin administration, noticeable decreases of body weights and gains, uterus weights were observed with congestion and enlargement of the uterus at gross inspections, and increases of abdominal writhing responses, uterus MDA levels, GSH contents, SOD and CAT activities. However, these oxidative stress mediated PD signs were dose-dependently decreased by 10 consecutive days of oral administration of three different doses of CTe 400, 200 and 100 mg/kg as comparable to those of IND 5 mg/kg in CTe 200 mg/kg. Conclusions: CTe had a significant improvement effect on primary dysmenorrhea in the PD rat model induced by estrogen benzoate and oxytocin.

• Information Systems Review
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• v.19 no.1
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• pp.49-74
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• 2017

The development of smart devices has affected employees' working environments and their lives. However, using smart devices is causing employees to experience technostress. This study aims to investigate the effects of technostress in using smart devices on usage intention in an organization. Moreover, the study investigates the effect of employees' stress-coping methods on the intention to use smart devices. This study posits familiarity, use innovativeness, role ambiguity, system vulnerability, technological limitation, and ubiquity as the antecedents of technostress. Data collected from 317 users who have experience in using smart devices in organizations are empirically tested against a research model using the PLS graph. Analysis results show that role ambiguity, system vulnerability, and technological limitation significantly influence technostress. Moreover, users take up emotion-focused coping behaviors because of technostress. Emotion-focused coping behaviors affect usage intention in organizations. However, technostress and problem-focused coping behaviors do not directly affect usage intention in organizations.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.211-216
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• 2024

The purpose of this study is to examine the functional aspects linked to the productivity innovation of ChatGPT, which emerged as a result of the rapid development of AI technology, and to identify ways to apply it in the jewelry industry. By analyzing the definition of ChatGPT and its features that improve productivity, I identify the scope of its application in the jewelry production process and derive meaningful implications. ChatGPT has the characteristics of 'learning', 'communication', and 'generative'. It enhances productivity by applying it to the jewelry industry. Social issues arise from the paradigm shift in the creation methods of generative AI. The version of ChatGPT is continuously upgraded along with the expansion of parameters. Accordingly, we would like to discuss ways to strengthen the competitiveness of the jewelry industry by conducting continuous research.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.1
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• pp.205-215
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• 2006

In this study 3-D shell FEM model was applied to analyze the behavior of curved steel box girders stiffened by diaphragms. The reliability of the analytical method has been proved by comparing with the existing results. It was also found from this analysis that main factors affecting a distortional stress are length of a girder, curvature of the girder, and spacing of diaphragms. A modelled bridge with 30m of span length and 40m of radius was analyzed to find an optimum spacing of diaphragm, and as a result of applying different spacings, 5m was found to be most appropriate to control the stress ratio regulated by specifications. In the effect of diaphragm shape, the rhamen-typed diaphragm is found to be more effective than the fully filled-up one in the range of opening ratio of 0.4 to 0.6. But, the fully filled-up diaphragm had more efficiency in terms of reducing the distortional stress than X-truss typed diaphragm.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1739-1756
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• 2021

Atmospheric nitrogen dioxide (NO₂) is mainly caused by anthropogenic emissions. It contributes to the formation of secondary pollutants and ozone through chemical reactions, and adversely affects human health. Although ground stations to monitor NO₂ concentrations in real time are operated in Korea, they have a limitation that it is difficult to analyze the spatial distribution of NO₂ concentrations, especially over the areas with no stations. Therefore, this study conducted a comparative experiment of spatial interpolation of NO₂ concentrations based on two linear-regression methods(i.e., multi linear regression (MLR), and regression kriging (RK)), and two machine learning approaches (i.e., random forest (RF), and support vector regression (SVR)) for the year of 2020. Four approaches were compared using leave-one-out-cross validation (LOOCV). The daily LOOCV results showed that MLR, RK, and SVR produced the average daily index of agreement (IOA) of 0.57, which was higher than that of RF (0.50). The average daily normalized root mean square error of RK was 0.9483%, which was slightly lower than those of the other models. MLR, RK and SVR showed similar seasonal distribution patterns, and the dynamic range of the resultant NO₂ concentrations from these three models was similar while that from RF was relatively small. The multivariate linear regression approaches are expected to be a promising method for spatial interpolation of ground-level NO₂ concentrations and other parameters in urban areas.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.976-983
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• 2023

Purpose: The dynamic behavior of a bridge structure under seismic loading depends on many uncertainties, such as the nature of the seismic waves and the material and geometric properties. However, not all uncertainties have a significant impact on the dynamic behavior of a bridge structure. Since probabilistic seismic performance evaluation considering even low-impact uncertainties is computationally expensive, the uncertainties should be identified by considering their impact on the dynamic behavior of the bridge. Therefore, in this study, a global sensitivity analysis was performed to identify the main parameters affecting the dynamic behavior of bridges with I-curved girders. Method: Considering the uncertainty of the earthquake and the material and geometric uncertainty of the curved bridge, a finite element analysis was performed, and a surrogate model was developed based on the analysis results. The surrogate model was evaluated using performance metrics such as coefficient of determination, and finally, a global sensitivity analysis based on the surrogate model was performed. Result: The uncertainty factors that have the greatest influence on the stress response of the I-curved girder under seismic loading are the peak ground acceleration (PGA), the height of the bridge (h), and the yield stress of the steel (fy). The main effect sensitivity indices of PGA, h, and fy were found to be 0.7096, 0.0839, and 0.0352, respectively, and the total sensitivity indices were found to be 0.9459, 0.1297, and 0.0678, respectively. Conclusion: The stress response of the I-shaped curved girder is dominated by the uncertainty of the input motions and is strongly influenced by the interaction effect between each uncertainty factor. Therefore, additional sensitivity analysis of the uncertainty of the input motions, such as the number of input motions and the intensity measure(IM), and a global sensitivity analysis considering the structural uncertainty, such as the number and curvature of the curved girders, are required.

• Korean Journal of Heritage: History & Science
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• v.57 no.3
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• pp.24-35
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• 2024

Recently, research using deep learning technologies such as artificial intelligence, convolutional neural networks, etc. has been actively conducted in various fields including healthcare, manufacturing, autonomous driving, and security, and is having a significant influence on society. In line with this trend, the present study attempted to apply deep learning to the classification of archaeological artifacts, specifically ancient Korean roof-end tiles. Using 100 images of roof-end tiles from each of the Goguryeo, Baekje, and Silla dynasties, for a total of 300 base images, a dataset was formed and expanded to 1,200 images using data augmentation techniques. After building a model using transfer learning from the pre-trained EfficientNetB0 model and conducting five-fold cross-validation, an average training accuracy of 98.06% and validation accuracy of 97.08% were achieved. Furthermore, when model performance was evaluated with a test dataset of 240 images, it could classify the roof-end tile images from the three dynasties with a minimum accuracy of 91%. In particular, with a learning rate of 0.0001, the model exhibited the highest performance, with accuracy of 92.92%, precision of 92.96%, recall of 92.92%, and F1 score of 92.93%. This optimal result was obtained by preventing overfitting and underfitting issues using various learning rate settings and finding the optimal hyperparameters. The study's findings confirm the potential for applying deep learning technologies to the classification of Korean archaeological materials, which is significant. Additionally, it was confirmed that the existing ImageNet dataset and parameters could be positively applied to the analysis of archaeological data. This approach could lead to the creation of various models for future archaeological database accumulation, the use of artifacts in museums, and classification and organization of artifacts.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.125-137
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• 2018

Credit unions organized and operated by the members of communities, work-places or groups are co-operative entities where customers act as owners not just transaction partners. The foregoing organizational characteristic of credit unions exerts beneficial effects on their customer relationship, and underscores the need for diversifying their relationship marketing strategies. This study sheds light on the structural relationship of credit unions in terms of principal variables of relationship marketing, i.e. relationship benefits, customer satisfaction and long-term relationship orientation. Specifically, we classify the relationship benefits into three sub-dimensions, i.e. confidence benefits, social benefits and special treatment benefits, and structuralize a causal model involving the customer satisfaction and long-term relationship orientation. From December 26, 2017 to January 26, 2018, A total of 360 questionnaires was collected. Of these, 346 were selected as the final samples, excluding 14, which are difficult to use in statistics. The reliability analysis, exploratory factor analysis, and regression analysis was performed by using the 'SPSS 24.0'. And confirmatory factor analysis, structural equation model analysis was performed by using 'AMOS 24.0'. The findings highlight the following. First, confidence benefits directly impact on the long-term relationship orientation, and indirectly influence the latter by the medium of customer satisfaction. Second, social benefits directly influence the long-term relationship orientation, without exerting any indirect effects on the latter via customer satisfaction. Third, special treatment benefits do not directly impact on the long-term relationship orientation but have indirect effects on the latter by the medium of customer satisfaction. Fourth, customer satisfaction has positive effects on the long-term relationship orientation. The findings suggest credit unions should establish a long-term relationship with their customers by providing them with confidence benefits to earn their trust and confidence, with social benefits to build a relationship of affinity and friendship, and with special treatment benefits to meet their needs in the long, not short and temporary, term.

• Journal of Distribution Science
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• v.10 no.2
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• pp.19-28
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• 2012

Rapidly growing sales amount and the number of discount stores caused many side effects and sensitive issues in Korea. Because these severe competition due to more expensive cost just like excessive increase in advertising and location selection, and these caused completely ruined small merchants as well as passed on to the consumer. This Study focused on competitiveness of discount store in Korea to the perspective of college students, as explored the relationships between marketing communication and store loyalty. And, examined for two moderating effect, 1) consumers' value separated by hedonic value and utilitarian value between marketing communication and store loyalty, and 2) consumers' value separated by hedonic value and utilitarian value between marketing communication and consumption emotion. Finally, this study examined for mediating effect of consumption emotion between marketing communication and store loyalty. In order to verify the relationship, moderating and mediating effects, data were collected from 130 college students in Whasung, Gyeonggi Province to test theoretical model and its hypotheses. Findings are as followed : First, analysis showed that factors such as advertisement(β =.221, p<.05), publicity(β =.513, p<.01), sales promotion(β =.234, p<.01), word of mouth(β =.627, p<.01) and physical environment(β =.339, p<.01) for marketing communication in the discount store have statistically significant positive effect on store loyalty. But the result of regression analysis for which factors are more impact in marketing communication between store loyalty showed that word of mouth(β =.53, p<.01) is only statistically significant. Second, publicity(β =-.895, p<.05), the sub-dimension of marketing communication shows only statistically significant negative moderating effect on store loyalty. But, the results of the moderating effect of value between marketing communication and consumption emotion verified that utilitarian value show statistically significant, specifically advertisement(β =.294, p<.01), physical environment(β =.418, p<.01), sales promotion(β =.245, p<.01), word of mouth(β =.414, p<.01) and publicity(β =1.137, p<.05), respectively. And hedonic value show statistically significant, specifically advertisement(β =.286, p<.01), physical environment (β =.418, p<.01), sales promotion(β =.236, p<.01) and word of mouth(β =.420, p<.01), respectively. But publicity(β =.145, p=.119) is not statistically significant. Finally, the results verified mediating effect for consumption emotion between all factors for marketing communication and store loyalty showed that factors such as advertisement, publicity, word of mouth and physical environment for marketing communication except sales promotion were statistically significant fully mediated in advertisement, and partially mediated in publicity, word of mouth and physical environment. This testified that the consumption emotion had the most important factor to enhance store loyalty to the perspective of College students. These results can provide important implications and invaluable tips for planning marketing strategies and gaining access to new potential customers. Implications and future research directions are also discussed.