• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.241-260
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• 2011

This paper qualitatively describes logistics behaviors of 113 companies located in Daegu-Gyeongbuk by considering various characteristics such as business location, trade volume, cargo types and the possession of company's own warehouse. A logit model is developed to investigate how predictor variables affect these companies' inclination of utilizing Third Party Logistics Provider(3PL). The estimation results of 102 effective data points show that among the four predictors the location of company's HQs (HQADD) and trade volume (TRDTEU) significantly increase company's tendency towards utilizing 3PL while the remaining two variables (BULK, WAREHS) imparting statistically insignificant influence. The results indicate that those companies located outside the region tend to implement a strategy of using more 3PL and also that the larger the trade volume of the company the more 3PL the company uses to improve the efficiency in logistics.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.187-195
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• 2015

In this paper, we examined the effect of positive affect and negative affect on the life satisfaction in the workplace. Also, this study focused on an empirical test of the role of work self-efficacy and work meaningfulness in the subjective well-being of office worker. To achieve this purpose, we suggested a research model consisting of factors such as work self-efficacy, work meaningfulness, positive affect, negative affect, life satisfaction. Data was collected using the survey method, and analyzed using structural equation model. According to PLS analysis, first, lower negative affect was associated with higher life satisfaction. Secondly, work meaningfulness was a very important predictor for the subjective well-being of office worker.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1253-1262
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• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.605-614
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• 2016

Many Korean colleges funded by the Korean government have actively implemented LINC (Leaders INdustry-university Cooperation) programs to facilitate practical training since 2012. The LINC programs have two major different categories, a technologically and innovative focused program and a field-centered program. A number of studies have applied the TPB (Theory of Planned Behavior) model proposed by Fishbein and Azjen successfully to predict the behavioral intention in many areas, such as marketing, environmental purchasing, and technology, etc. On the other hand, few studies have applied the TPB within industry-university cooperation settings. The purpose of this study was to empirically test the applicability of the TPB model in predicting the employees' participation in LINC programs. To investigate the study's purpose, a closed-ended questionnaire, composed of a total of 32 questions based on previous studies, was developed, and the data from 115 out of 132 employees in the participating companies of LINC were utilized. Specific analysis of the study showed that the attitudes, subjective norm, and perceived behavioral control were significant predictors of the LINC intention. In addition, the LINC intention was a significant predictor of the participation in LINC.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.467-495
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• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• Safety and Health at Work
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• v.10 no.3
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• pp.370-376
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• 2019

Background: Respirator fit testing is a method to assess if the respirator provides an adequate face seal for the worker. Methods: Workers from four Norwegian smelters were invited to participate in the study, and 701 respirator fit tests were performed on 127 workers. Fourteen respirator models were included: one FFABE1P3 and 11 FFP3 respirator models produced in one size and two silicone half masks with P3 filters available in three sizes. The workers performed a quantitative fit test according to Health and Safety Executive 282/28 with 5-6 different respirator models, and they rated the respirators based on comfort. Predictors of overall fit factors were explored. Results: The pass rate for all fit tests was 62%, 56% for women, and 63% for men. The silicone respirators had the highest percentage of passed tests (92-100%). The pass rate for the FFP3 models varied from 19-89%, whereas the FFABE1P3 respirator had a pass rate of 36%. Five workers did not pass with any respirators, and 14 passed with all the respirators tested. Only 63% passed the test with the respirator they normally used. The mean comfort score on the scale from 1 to 5 was 3.2. The respirator model was the strongest predictor of the overall fit factor. The other predictors (age, sex, and comfort score) did not improve the fit of the model. Conclusion: There were large differences in how well the different respirator models fitted the Norwegian smelter workers. The results can be useful when choosing which respirators to include in respirator fit testing programs in similar populations.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.13-31
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• 2019

A nonlinear finite element model (FEM) using ATENA-3D software to simulate the axially compressive behavior of circular steel tube confined concrete (CSTCC) columns infilled with ultra high performance concrete (UHPC) was presented in this paper. Some modifications to the material type "CC3DNonlinCementitious2User" of UHPC without and with the incorporation of steel fibers (UHPFRC) in compression and tension were adopted in FEM. The predictions of utimate strength and axial load versus axial strain curves obtained from FEM were in a good agreement with the test results of eighteen tested columns. Based on the results of FEM, the load distribution on the steel tube and the concrete core was derived for each modeled column. Furthermore, the effect of bonding between the steel tube and the concrete core was clarified by the change of friction coefficient in the material type "CC3DInterface" in FEM. The numerical results revealed that the increase in the friction coefficient leads to a greater contribution from the steel tube, a decrease in the ultimate load and an increase in the magnitude of the loss of load capacity. By comparing the results of FEM with experimental results, the appropriate friction coefficient between the steel tube and the concrete core was defined as 0.3 to 0.6. In addition to the numerical evaluation, eighteen analytical models for confined concrete in the literature were used to predict the peak confined strength to assess their suitability. To cope with CSTCC stub and intermediate columns, the equations for estimating the lateral confining stress and the equations for considering the slenderness in the selected models were proposed. It was found that all selected models except for EC2 (2004) gave a very good prediction. Among them, the model of Bing et al. (2001) was the best predictor.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.255-266
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• 2021

The purpose of this study is to compare the effects of treatment on stage III stomach cancer data obtained from the SEER program of the National Cancer Institute and to identify the significant risk factors for the survival rates of stage III stomach cancer. Since the proportional hazards assumption was violated for treatment, we used the restricted mean survival time as an alternative to the proportional hazards model. The restricted mean survival time was estimated using pseudo-observations, and the effects of treatment were compared using a test statistic based on the estimated restricted mean survival times. We conducted the regression analysis using a generalized linear model to investigate the significant predictors for the restricted mean survival time of patients with stage III stomach cancer. We found that there was a significant difference between the restricted mean survival times of treatment groups. Age at diagnosis, race, substage, grade, tumor size, surgery, and treatment were significant predictors for the restricted mean survival time of patients with stage III stomach cancer. Surgery was the most significant predictor for increasing the restricted mean survival time of patients with stage III stomach cancer.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.147-166
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• 2021

As vehicle sharing service is being widely used in China. The sharing economy appeared to be a way to make people's lives more convenient and to utilize limited resources efficiently. Sharing economy companies have created an app to satisfy users' needs with providing more benefits. Although research on vehicle sharing services has been continuously conducted at the level of the sharing economy, there are not many empirical studies related to the perception of the sharing economy from the consumer's point of view. In this sense, this study considered the perceived relationship benefits (social benefits, economic benefits, psychological benefits, and functional benefits) of Didi chuxing service as the key independent variables influencing users' confirmation and satisfaction, And suggests that users' confirmation and satisfaction are the key determinants of Didi continuance intention . To test the proposed research model, this study conducted structural equation model using 268 data collected on the users who have experience of Didi service. According to the empirical analysis results, This study verifies that: First, social benefits, economic benefits, psychological benefits, and functional benefits are determinants of user's satisfaction. Second, expectation confirmation depends on economic benefits, psychological benefits, functional benefits and social influence, meanwhile, social benefit has no effect on expectation confirmation. Third, expectation confirmation is proved to be a positive predictor of users' satisfaction. Finally, this results indicate that continuous use intention is determined by users' satisfaction.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.193-204
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• 2021

Based on risk-benefit theory, this study examined a structural equation model accounting for the mechanisms through which affective perceptions of AI predicting individuals' support for the government's Ai policies. Four perceived characteristics of AI (i.e., usefulness, entertainment value, privacy concern, threat of human replacement) were investigated in relation to perceived benefits/risks, attitudes toward AI, and AI policy support, based on a nationwide sample of South Korea (N=352). The hypothesized model was well supported by the data: Perceived usefulness was a strong predictor of perceived benefit, which in turn predicted attitude and support. Perceived benefit and attitude played significant roles as mediators. Perceived entertainment value along with perceived usefulness and privacy concern predicted attitude, not perceived benefit. Neither attitude nor support was significantly associated with perceived risk which was predicted by privacy concern. Theoretical and practical implications of the results are discussed.