• Journal of Technology Innovation
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• v.12 no.3
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• pp.97-109
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• 2004

According to "structure-conduct-performance" paradigm in IO, market structure (concentration) determines conduct (R&D investments), and conduct yields market performance (ratio of price to marginal cost). Previous empirical studies on Schumpeter Mark I, II assumed that the explanatory variable (market structure) and the disturbance are uncorrelated in the R&D equation. In this situation, Ordinary Least Squares (OLS) estimates of the structural parameters are inconsistent, because the endogeneous variables (R&D and market structure) can be determined simultaneously. So, in this study, full information (or system methods) estimation is used to test Schumpeter hypothesis since joint estimation can as well bring efficiency gains in the seemingly uncorrelated regressions (SUR) setting.

• The Journal of Korean Academic Society of Nursing Education
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• v.28 no.1
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• pp.48-56
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• 2022

Purpose: The main purpose of this study was to identify factors influencing person-centered care competence in nursing students. Methods: The study was conducted in two universities located in the D and J cities of South Korea. Participants were 130 senior nursing students who had experienced clinical practice for at least 3 months. Data were collected from September 7-10, 2019, using a structured questionnaire and analyzed using a hierarchical multiple regression with SPSS/WIN 23.0. Results: The Factor influencing person-centered care competence was compassion competence (β=.49, p<.001) and the explanatory power of this variable was 30% (F=10.98, p<.001). Conclusion: According to the results of this study, nursing faculties need to develop programs and learning content to enhance learners' compassion competence for promotion of person-centered care competence.

• Journal of Agricultural Extension & Community Development
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• v.30 no.4
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• pp.199-212
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• 2023

Recently, despite the active interest and research on biochar, there is a lack of research on the acceptance intention of farmers, who are technology adopters. Accordingly, the purpose of this study was to conduct a survey of 168 farmers and structurally analyze the factors affecting farmers' intention to accept biochar. The analysis results are as follows. First, promotion conditions and network effects have a positive influence on farmers' intention to accept biochar. Second, the mediating variable, network effect, has a complete mediating effect between performance expectations, social influence, and acceptance intention. This suggests that organizations need to be utilized to spread biochar because network effects increase the explanatory power of acceptance intention.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.533-545
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• 2017

Quantile regression models provide a variety of useful statistical information by estimating the conditional quantile function of the response variable. However, the traditional linear quantile regression model can lead to the distorted and incorrect results when analysing real data having a nonlinear relationship between the explanatory variables and the response variables. Furthermore, as the complexity of the data increases, it is required to analyse multiple response variables simultaneously with more sophisticated interpretations. For such reasons, we propose a multivariate quantile regression tree model. In this paper, a new split variable selection algorithm is suggested for a multivariate regression tree model. This algorithm can select the split variable more accurately than the previous method without significant selection bias. We investigate the performance of our proposed method with both simulation and real data studies.

• Journal of the Korean Society for Railway
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• v.7 no.2
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• pp.155-162
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• 2004

In order to account for a price variation of apartment that places near a newly constructed subway station, a spatial hedonic model was developed to examine spacial characteristics that affect a purchasing price of an apartment using a White Estimator. In particular, the paper aims to examine various effects of subway 7 construction on an apartment price in Seoul Metropolitan Area. As explanatory variables, an apartment size, distance to a closest subway station, distance to the Central Business District (CBD) of Seoul, the number of years after building, and a lagged variable of the apartment purchasing price were used. The lagged variable plays a role of representing a spatial weighted average of previous prices of other apartments that locate within 3 km from the apartment. For a precise study, an entire sample was divided into two sets, southern area and southwestern area of Seoul, and two different spatial hedonic models were estimated. Not only before and after analysis, but also with and without analysis were conducted to compare with different effects of the spatial characteristics of two areas. The results show that before the construction of the subway 7, the prices of the apartments in the southern area were more sensitive to the apartment size, the distance to a closest subway station, the distance to the CBD, and the prices of the other apartments locating within 3km rather than those in the southwestern area. After the construction, on contrast, it is found that the apartment purchasing prices in the southwestern area are more sensitive than those in the southern area due to people's expectation regarding a new development around the subway station. In addition, the prices of the apartments locating closely with a transfer station are more likely to go up by increase in the apartment size, the distance to the station, and the prices of the other apartments within 3 km. Compared with the negative effects of the distance to the station on the prices in the other models, the positive effect of the distance to the transfer station might be caused by the characteristics of commercial area in which people are not likely to live.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.361-368
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• 2013

This research aims to offer the information required for demand increase on marketing strategy level by investigating Mudeungsan visitors' demographic characteristics and social economical variables. To accomplish this study, the proper analyzing model needs to be applied because a grave error of parameters will be led if regression model appropriate for analyzing the data of a continuous probability variable is applied, in case that dependent variable is a discrete random variable which have a discrete probability distribution. Therefore data analysis was performed with Poisson model. However, as the data was showing an overdispersion, parameter was estimated with the Binomial Poisson model able to cover the problem. As a result, some explanatory variables turned out to be significant such as visitor's age, occupation, preferred season to visit, type of company, five days working, and preferring type of tourism. Author could offer to the national park the information about characteristics of core market revealed and marketing strategy for it, based on those influential variables.

• Asia-Pacific Journal of Business
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• v.14 no.3
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• pp.167-186
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• 2023

Purpose - The purpose of this study is to empirically investigate whether the auditor accreditation system for IPO firms improves the efficiency of the KOSDAQ IPO market. To verify the effectiveness of the auditor designation system, we time series compare four measures of IPO firms (earnings management, long-term stock performance, change in operating performance, and possibility of delisting). Design/methodology/approach - We test the hypothesis through event research method and regression analysis. Specifically, the dependent variables of the regression model are discretionary accruals in the year of IPO, 36-month holding period excess return after IPO, change in operating performance for 3 years after IPO, and dummy variable for delisting. And the explanatory variable is a dummy variable that separates the period before and after the implementation of the auditor designation system. Findings - We find that earnings management and delisting risks decreased more in the period after the implementation of the auditor accreditation system than in the previous period. In addition, we find that long-term stock performance and operating performance after IPO increase further after the implementation of the auditor accreditation system. Research implications or Originality - Overall, the results of this study suggest that the implementation of the auditor accreditation system for IPO firms contributes to improving market efficiency in the KOSDAQ market, where information asymmetry is high. Our study differs from previous studies in that it demonstrates the effectiveness of the auditor designation system using various measures.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.

• Journal of Korean Academy of Nursing Administration
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• v.6 no.1
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• pp.109-122
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• 2000

The present study examined the causal relationships among nurses' perceived autonomy, job satisfaction, work environment (work overload, role conflict, situational support, head nurses' leadership), personal aspects(experiences, need for achievement, professional knowledge and skill) by constructing and testing a theoretical framework. Based on literature review nurses' perceived autonomy and job satisfaction were conceived of as outcomes of the interplay among work environment and personal characteristics. Work environment factors involved work overload, role conflict, situational support, and head nurses' leadership (task oriented leadership, relation oriented leadership). Personal charateristics included experiences, need for achievement, and professional knowledge and skill. Three large general hospital in Chonbuk were selected to participate. The total sample of 516 registered nurses represents a response rate of 92 percent. Data for this study was collected from July to September in 1998 by Questionnaire. Path analyses with LISREL 7.16 program were used to test the fit of the proposed conceptual model to the data and to examine the causal relationship among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however, that path analisis can not count measurement errors; measurement error can attenuate estimates of coefficient and explanatory power. Nevertheless the model revealed relatively high explanatory power. 42 percent of nurses' perceived autonomy was explained by predicted variables; 32 percent of nurses' job satisfaction was explained by by predicted variables. Tn predicting nurses' perceived autonomy the findings of this study clearly demonstrated the work overload might be the most important variable of all the antecedent variables. Head nurses' relation oriented leadership, situational supports, need for achievement, and role conflict were also found to be important determinants for nurses' perceived autonomy. As for the job satisfaction, role conflict, situational supports, need for the achievement, and head nurses' relation oriented leadership were in turn important predictors. Unexpectedly the result showed perceived autonomy have few influence on job satisfaction. The results were discussed, including directions for the future research and practical implication drawn from the research were suggested.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.407-419
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• 2006

In this paper, we analyze household overdue loans in Korea which has been causing serious social and economical problems. We consider customers of Bank A in Korea and focus on overdue cash services which have been snowballing in the past few years. From analysis of overdue loans, one can predict possible delays for current customers as well as build a credit evaluation and risk management system for future customers. As a statistical analytical tool, we propose a two-stage Generalized Linear regression Model (GLM) which assumes a logistic model for presence/non-presence of overdue and a gamma model for the amount of overdue in the case of overdue. We perform goodness of fit test for the two-stage model and select significant explanatory variables in each stage of the model. It turns out that age, the amount of credit loans from other financial companies, the amount of cash service from other companies, debit balance, the average amount of cash service, and net profit are important explanatory variables relevant to overdue credit card cash service in Korea.