• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.23-39
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• 2004

This paper focused on empirically testing the ESM(Electronic-Store Success Model). The model was developed by basing upon the ‘Updated D&M(DeLone and McLean) IS Success Model(2003)’ and reflecting the characteristics of marketing and e-business, and composed of the six dimensions including system quality, information quality, service quality, trust, customer loyalty and financial performance. The research model consisting of five dimensions, excluding financial performance, was proposed and empirically verified by structural equation model with respect to data from 224 customers on 69 Electronic-Stores. The results show that system quality and information quality significantly influence service quality, and that service quality also significantly influence trust and customer loyalty, and that trust has significant influence on customer loyalty.

• Journal of Korean Academy of Nursing
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• v.48 no.5
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• pp.622-635
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• 2018

Purpose: This study aimed to develop and test a structural model for sleep quality in female shift work nurses. The hypothetical model was constructed on the basis of Spielman's 3P model of insomnia and previous research related to the sleep quality of shift nurses. Methods: This cross-sectional study used structural equation modeling and recruited 285 female shift work nurses from four general and university hospitals with over 300 beds located in C and J cities in Gyeongsangnamdo. Data were collected from September 27 to October 20, 2016, and then analyzed using descriptive statistics, Pearson's correlation, and structural equation modeling. The study used SPSS/Win 18.0 and AMOS 18.0 in processing the data. Results: The final model showed good fit to the empirical data: ${\chi}^2/df=2.19$, SRMR=.07, RMSEA=.07, AGFI=.85, TLI=.91, GFI=.93, GFI=.89, NFI=.87. The factors that influenced sleep quality were sleep hygiene (${\beta}=.32$), perceived shift work status (${\beta}=-.16$), stress response (${\beta}=.16$), shift work experience (${\beta}=.15$), perceived health status (${\beta}=-.14)$, and circadian rhythm (${\beta}=-.13$) explaining 36.0% of the variance. Conclusion: The model of sleep quality of the shift work nurses constructed in this study is recommended as a model to understand and predict the sleep quality of shift work nurses. The results suggest that strategies for improving the sleep quality of shift work nurses should focus on sleep hygiene, perceived health status, stress response, circadian rhythm, perceived shift work status, and shift work experience.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.547-557
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• 2017

The health-related quality of life data are commonly skewed and bounded with spike at the perfect health status, and the variance tended to be heteroscedastic. In this study, we have developed a prediction model for EQ-5D using linear regression model, beta regression model, and extended beta regression model with mean and precision submodel, and also compared the predictive accuracy. The extended beta regression model allows to model skewness and differences in dispersion related to covariates. Although the extended beta regression model has higher prediction accuracy than the linear regression model, the overlapped confidence intervals suggested that the extended beta regression model was superior to the linear regression model. However, the expended beta regression model could explain the heteroscedasticity and predict within the bounded range. Therefore, the expended beta regression model are appropriate for fitting the health-related quality of life data such as EQ-5D.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1300-1312
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• 2019

BSTRACT In this paper, PM10 forecast model using DNN(Deep Neural Network) is developed for Seoul region. The previous Julian forecast model has been developed using weather and air quality data of Seoul region only. This model gives excellent results for accuracy and false alarm rates, but poor result for POD(Probability of Detection). To solve this problem, an WA(Wide Area) forecasting model that uses Chinese data is developed. The data is highly correlated with the emergence of high concentrations of PM10 in Korea. As a result, the WA model shows better accuracy, and POD improving of 3%(D+0), 21%(D+1), and 36%(D+2) for each forecast period compared with the Julian model.

• Journal of Distribution Science
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• v.14 no.8
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• pp.45-50
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• 2016

Purpose - This study aimed to develop a new practical and universally applicable service quality model by improving the service quality measurement model proposed by many previous studies. Research design, data, and methodology - An in-depth analysis on what influences such service quality model had on the improvement effect of service quality, and Service Evaluation Model("SEM"), which was revised from the existing service quality measurement model, was developed. The model is divided into the two integrative categories: First, activity, that is the group of service-related activities. Next is item, the group of service-related objects. The level of service is evaluated for each category via survey questionnaire on service level evaluation. Based on the model, SEM has visibility by structuring the whole service industry. Results - For the application of the new service quality model, this study attempted to examine the appropriateness of the newly proposed service quality model by applying it to retail service field. Conclusions - As a result, the proposed service model would be a useful and applicable service quality measurement model required by many organizations. Service company can set up self check service levels. Through these results, they can look for the ways to provide better services to customers. Service users can ensure the objectivity of business plan based upon SEM.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.381-384
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• 2002

The purpose of this study is to construct an Environment Database Management System (EDMS) for the Saemangeum watershed based on the linkage of Water Quality Model, i.e. QUALKO and WASP model, and GIS database to estimate water quality effectively in this area. There are two major river systems on this study area, the Mangyeong and the Dongjin rivers. Input data are automatically generated through the calculation of the pollutant loading and inflow concentration from the point and non-point sources. The developed system is composed of three different phases, such as pre-process, model performance and post-process. The Model performance is supported by the database at pre-process phase and model performance results were shown in the graphs and attribution data at post-process phase. The measured data from the Mangyeong and the Dongjin rivers are used to evaluate the applicability of EDMS. The EDMS shows higher reliability, and it is expected to contribute to the effective management and improvement of water quality modeling in the Saemangeum watershed since the system reduces complications of using a model in DOS operating environment and increases the accuracy of water quality analysis.

• Child Health Nursing Research
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• v.7 no.3
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• pp.280-297
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• 2001

The purpose of the study was to develop and test the model for the quality of life in mothers of children with nephrotic syndrome. A hypothetical model was constructed on the basis of previous studies and a review of literature. The conceptual framework was built around ten constructs. Exogenous variables included in this model were mother's health, father's health, marital intimacy, mother's attitude on children, economic state, side effect of steroid, severity of illness and social support. Endogenous variables were mother's burden and quality of life. Empirical data for testing the hypothetical model were collected by using a self-report questionnaire from 152 mothers of children with nephrotic syndrom at the outpatient clinics and in the hospital. The data was collected from May, 1999 to August, 1999.Reliability of the seven instruments was tested with Cronbach's alpha which ranged from 0.71 - 0.92.For the data analysis, SPSS 8.0 WIN program and LISREL 8.20 WIN program were used for descriptive statistics and covariance structural analysis. The results of covariance structural analysis were as follow :1. The hypothetical model showed a good fit with the empirical data. [x2 = .56, df = 3, p = .90(p>.05 ), GFI = .99, AGFI = .99, RMSR = .005.] 2. For the parsimony of model, a modified model was constructed by deleting 1 variable and excluding 2 paths according to the criteria of statistical significance and meaning.3. The modified model also showed a good fit with the data[x2 = 2.83, df = 7, p = .90( p>.05 ), GFI = 1.00, AGFI = .97, RMSR = .011].The result of the testing of the hypothesis were as follows : 1. Mother's health(γ21 = .26, t = 4.16), father's health(γ22 = .19, t = 2.92), marital intimacy(γ23 = .26, t = 4.13) and social support(γ28 = .12, t = 2.03) had a significant direct effect on the quality of life.2. Mother's burden(β21 = -.20, t = -3.10) had a significant negative direct effect on the quality of life.3. Mother's attitude on children(γ14 = -.34, t = .-4.57), mother's health(γ11 = -.22, t = -2.96) and side effect of steroid (γ16 = -.23, t = .-2.69) had a significant direct negative effect on the burden. The result of this study showed that mother's health, marital intimacy, mother's burden, father's health, and social support had a significant direct effect on the quality of life. Mother's attitude on children, mother's health, and side effect of steroid had a significant direct effect on mother's burden. These six variables, mother's health, marital intimacy, father's health, social support, mother's attitude on children and side effect of steroid were identified as relatively important variables. The results of this study suggest, it needed to determine the nursing intervention will alleviate mother's burden and promote a greater quality of life in mothers of children with nephrotic syndrom.

• Journal of Korean Society on Water Environment
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• v.37 no.5
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• pp.335-343
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• 2021

Water quality prediction is essential for the proper management of water supply systems. Increased suspended sediment concentration (SSC) has various effects on water supply systems such as increased treatment cost and consequently, there have been various efforts to develop a model for predicting SSC. However, SSC is affected by both the natural and anthropogenic environment, making it challenging to predict SSC. Recently, advanced machine learning models have increasingly been used for water quality prediction. This study developed an ensemble machine learning model to predict SSC using the XGBoost (XGB) algorithm. The observed discharge (Q) and SSC in two fields monitoring stations were used to develop the model. The input variables were clustered in two groups with low and high ranges of Q using the k-means clustering algorithm. Then each group of data was separately used to optimize XGB (Model 1). The model performance was compared with that of the XGB model using the entire data (Model 2). The models were evaluated by mean squared error-ob servation standard deviation ratio (RSR) and root mean squared error. The RSR were 0.51 and 0.57 in the two monitoring stations for Model 2, respectively, while the model performance improved to RSR 0.46 and 0.55, respectively, for Model 1.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.95-113
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• 1999

This paper is to propose an evaluation model of quality system using the concept from the evaluation method of each stage in QFD(Quality Function Deployment). The data of the performance level and weights for the quality system and the job on quality loop in each enterprise has been obtained from the 8 experts who are in charge of quality system construction. Here, the weights were computed by means of the eigenvector method. In this paper, we can acquire the evaluated score for the present level of the quality system. This method will help to manage and improve the quality system. We show the efficiency of this method by illustrating case studies.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.4
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• pp.580-588
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• 2007

The purpose of this study was to measure the effects of the perceived sacrifice, service quality, value and satisfaction on the intention to revisit restaurants. A total of 273 questionnaires were completed. The equation model was used to measure the causal effects. The results demonstrated that the confirmatory factor analysis model provided an excellent model fit. The modified model yielded a significantly better fit to the data than the service quality model, and accounted for a greater share of the variance in intention to revisit than the service quality model. The effects of value and service quality on intention to revisit were statistically significant in both the service quality model and modified model. The effects of perceived sacrifice and service quality on value were statistically significant in the service quality model and modified model. As expected, service quality had a significant effect on satisfaction in the modified model. Satisfaction had a significant effect on intention to revisit in the modified model. Satisfaction also had a significant effect on service quality in the service quality model. Moreover, service quality had an indirect influence on intention to revisit through value and satisfaction in the modified model. Service quality had an indirect influence on the intention to revisit through value in the service quality model. The overall findings offer strong empirical support for the intuitive notion that improving service quality can increase favorable intention to revisit, and decrease unfavorable intention to revisit.