• 유통과학연구
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• 제18권12호
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• pp.31-43
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• 2020

Purpose: This study examined how many determinant factors (service dimensions, food quality, and price perception) affect revisit intention. This practical concept is service quality (SERVQUAL), customer satisfaction, and repeated/revisit behavioral intention based on the theory of reasoned action (TRA). Research design, data and methodology: This research applied a hybrid mixed-method comprising exploratory and explanatory sequential design by Creswell (2014). The 400 responses were collected in four townships in Myanmar. This study drilled down to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA) prior to test the hypothesized factor structure of all the variables resulted in the form of the goodness of fit. For further data analysis, structural equation modeling (SEM) was applied to test the relationships among the variables of the proposed model. Results: The results showed that perceived service quality, food quality, and price perception have direct effects on customer satisfaction and indirect effect on revisit intention. The perceived service quality has the most significant influence while the food quality has the least influence on customer satisfaction. Conclusions: The results are useful for the restaurant managers to better understand the significant strategic choice factors to improve higher quality service amongst restaurants both domestic and international under the stiff competition.

• 응용통계연구
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• 제27권4호
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• pp.629-643
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• 2014

회귀모형을 이용하여 자료를 분석하는 경우 이상점이나 영향점과 같은 특이값들의 유무를 검정하는 회귀진단기법은 모형의 적합성을 체크하기 위한 필수적인 도구로 잡은 지 오래이다. 이러한 점들이 존재 하는 경우 회귀분석의 결과가 왜곡되어 해석이 된다. Jang과 Anderson-Cook (2013)은 불꽃그림이란 이름을 붙인 그림도구를 발표하였는데 관측값에 부여된 가중치를 1에서 0으로 변화함에 따라 이상점이나 영향점이 회귀계수 및 잔차제곱합(SSE)에 어떠한 영향을 미치는지 3차원 그림에 추적곡선을 그려 보았을 뿐 아니라 쌍으로 대비시켜 봄으로써 분석의 시각적인 효과를 증대시켰다. 본 연구에서는 더 나아가 이러한 시도가 기존 방법과 어떤 차이점이 있는지 2013년에는 반영치 않은 통계량을 포함해서 더 많은 해석이 가능한지 혼합물 실험 계획을 통해 다양한 통계량의 민감도 분석을 실행하였다. 왜냐하면 작은 혼합물실험인 자료인 경우 더욱 세밀한 통계량에 대한 민감도 분석이 필요하기 때문이다.

• 한국빅데이터학회지
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• 제8권1호
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• pp.35-47
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• 2023

It is crucial to develop effective and efficient big data analytics methods for problem-solving in the field of business in order to improve the performance of data analytics and reduce costs and risks in the analysis of customer data. In this study, a big data-driven data analysis system using artificial intelligence techniques is designed to increase the accuracy of big data analytics along with the rapid growth of the field of data science. We present a key direction for big data analysis systems through missing value imputation, outlier detection, feature extraction, utilization of explainable artificial intelligence techniques, and exploratory data analysis. Our objective is not only to develop big data analysis techniques with complex structures of business data but also to bridge the gap between the theoretical ideas in artificial intelligence methods and the analysis of real-world data in the field of business.

• International Journal of Reliability and Applications
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• 제14권2호
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• pp.107-114
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• 2013

Modelling of failures is an important element of reliability modelling. Empirical modelling approach suitable for complex item is explored in this paper. First step of the empirical modelling approach is to plot hazard function, density function, Weibull probability plot as well as cumulative intensity function to see which model fits best for the given data. Next step of the empirical modelling approach is select appropriate model for the data and fit the parametric model accordingly and estimate the parameters.

• 디지털산업정보학회논문지
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• 제20권1호
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• pp.87-98
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• 2024

This study conducted an empirical study on the application of innovative teaching methods in the tourism field in a situation where innovative teaching methods suitable for the AI era are required. It was intended to provide exploratory basic data on the application of a wide range of innovative teaching methods through actual verification of the educational effectiveness before and after the application of the innovative teaching method. To this end, the effectiveness before and after education was empirically verified with 60 students who majored in tourism at Y University in the metropolitan area. Reliability analysis, corresponding sample t-test, and map analysis using graphs were performed on the collected data to increase visibility. As a result of the study, it was found that all the competencies of the innovative teaching method had a statistically significant influence after the application of the innovative teaching method. In addition, by increasing the effect of interaction between instructors and learners acting as facilitators, exploratory results were derived for potential benefits and areas that could be improved.

• 산업융합연구
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• 제18권6호
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• pp.19-25
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• 2020

빅데이터 분석은 오늘날 다양한 산업 및 공공분야에서 필수적으로 활용되고 있다. 이에 본 연구에서는 빅데이터 분석을 활용하여 국내 관광 서비스 개선 방안을 LDA분석 방법을 통해 모색하고자 한다. 특히 외국인 방문객이 가장 많은 서울을 중심으로 관광객의 만족도를 높이고 이를 통해 재방문을 향상시킬 수 있고 서비스를 개선할 수 있는 탐색적 접근을 시도하였다. 본 연구에서는 서울시와 한국관광공사의 통계 자료 및 SNS 등의 인터넷 정보들을 R을 통해 수집 및 분석을 진행하였다. 그리고 LDA를 포함한 텍스트 마이닝 기법을 활용하였다. 분석 결과 외국인들의 한국을 방문하는 목적 중 하나는 식도락 관광이었다. 이에 식도락 관광을 중심으로 서비스의 질을 높이기 위한 방안을 도출하고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.514-517
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• 2017

태양광 발전 시스템에서 전력 생산은 기상 상태에 따라 크게 영향을 받으므로 안정적인 부하 운용을 위해 태양광 에너지에 대한 예측이 필수적이다. 따라서 태양광 에너지 예측을 위한 기계학습 알고리즘의 입력으로 기상 상태에 대한 데이터가 필요하다. 본 논문에서는 알고리즘에 대한 입력 데이터로 표면의 3시간 동안 누적된 강수량, 상 하향 장파 복사선 평균, 상 하향 단파 복사선 평균, 지상 2m에서의 3시간 동안 온도, 표면에서의 온도 등 15가지 종류의 기상 데이터를 사용한다. 기상 데이터의 통계적 특성을 파악하고 상관관계를 분석하여 태양광 에너지와 70% 이상의 높은 상관성을 갖는 하향 단파 복사선 평균과 상향 단파 복사선 평균을 특징벡터의 주요 원소로 추출하였다.

• Journal of Information Science Theory and Practice
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• 제10권1호
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• pp.73-88
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• 2022

This exploratory study aims to understand the potential of log data analysis and expand its utilization in user research methods. Transaction log data are records of electronic interactions that have occurred between users and web services, reflecting information-seeking behavior in the context of digital libraries where users interact with the service system during the search for information. Two ways were used to analyze South Korea's National Digital Science Library (NDSL) log data for three days, including 150,000 data: a log pattern analysis, and log context analysis using statistics. First, a pattern-based analysis examined the general paths of usage by logged and unlogged users. The correlation between paths was analyzed through a χ² analysis. The subsequent log context analysis assessed 30 identified users' data using basic statistics and visualized the individual user information-seeking behavior while accessing NDSL. The visualization shows included 30 diverse paths for 30 cases. Log analysis provided insight into general and individual user information-seeking behavior. The results of log analysis can enhance the understanding of user actions. Therefore, it can be utilized as the basic data to improve the design of services and systems in the digital library to meet users' needs.

• 아동학회지
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• 제36권5호
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• pp.95-113
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• 2015

This study aimed to develop and validate a scale which could be used to evaluate mathematical interactions of parents with their young children. The subjects comprised 408 mothers of 4-6-year-old children. Means, standard deviation, $x^2$, Cramer's V, exploratory factor analysis, confirmatory factor analysis, Pearson correlations, and Cronbach's ${\alpha}$ were calculated. First, 49 items were developed through a review of relevant research, parent interviews, confirmation of item adequacy and content validity. These items were then edited down to a final list of 24 items representing 4 factors identified by exploratory factor analysis. Second, this 24-item. 4-factor scale was shown to have adequate construct validity, norm validity, and reliability by confirmatory factor analysis, Pearson correlation analysis, Cronbach's ${\alpha}$. In conclusion, the final mathematical interaction scale for young children's parents was composed of 24 items with 4 factors: "interaction regarding numbers and operations, measurements, and patterns", "interaction regarding data collection and result presentation", "interaction with picture books", and "interaction regarding shapes and figures"

• 한국임상보건과학회지
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• 제6권2호
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• pp.1126-1135
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• 2018

Purpose. The purpose of this study is to investigate the success model related to the hospital information system accomplishment. It is important to examine the success model of the hospital information system and to analyze the factors affecting the job satisfaction accomplishment. Methods. The method of this study is to 150 copies of the entire survey data were distributed and 135 copies were collected, showing a collection rate of 90%. In order to ensure the reliability of the questionnaire items, Cronbach's Alpha was used to test reliability, and exploratory factor analysis was conducted to determine the convergence of various items. In order to grasp the convergence of various items, exploratory factor analysis was performed. The results of exploratory factor analysis were used to analyze the correlations between variables that were proven to have a single dimensionality before calculating factor loadings and regression analysis by Orthogonal Rotation by Varimax method Results. The results of this study, first, the system quality of the hospital information system has a statistically significant effect on user satisfaction. Second, the information quality of hospital information system is statistically significant for user satisfaction, indicating that information quality improves user satisfaction. Third, service quality of hospital information system was statistically significant in user satisfaction. Finally, the higher the satisfaction of the users who use the hospital information system, the higher the accomplishment of the organization Conclusions. This study is based on the successful model of D & M information system. In addition, the hospital information system, the user satisfaction, and the organizational accomplishment in connection with it can be found significant.