• Quality Improvement in Health Care
• /
• v.7 no.2
• /
• pp.230-242
• /
• 2000

Background : The measuring instruments for customer satisfaction in hospitals are often composed of some dimensions reflecting the conceptive complexity of them. Then, overall satisfaction would be expected to be equal the 'weighted' sum of scores by dimensions because the importance rated by customers may be different across the dimensions. But the issue of how to weight the dimensions with importance is not yet solved. We examined 3 sets of weighting methods as to make effect on predictive power against overall satisfaction. Methods : We conducted a survey included 483 subjects who had visited or admitted to a university hospital, using the short form questionnaire being developed by The Korean Society of Quality Assurance in Health Care for out-patient and in-patient. By using a multiple linear regression model, we compared among changes of explanatory powers against overall satisfaction as dependent variable after weighting 4 dimensions of the survey questionnaire as independent variables with importance scores of dimensions perceived by consumers. And we compared the feasibility of each weighting, methods by checking missing cases. Results : There were no weighting methods increasing the explanatory power after applying them. The method of absolute scoring was found higher explanatory-power than others, but this finding had no statistical significance. Regarding the number of missing value, method of absolutely scoring had the least cases. Conclusion : Our findings suggested that weighting the dimensions with importance might have little significance in the cases of scales having items highly correlated, such as consumers' satisfaction. Though asking with items to be answered absolutely, customers might be rating relatively in some degree and this method produced least missing cases. Considering these points, in the cases when weighting the dimensions with importance would be required, we suggest that weighting method by absolute scoring might be better than others.

• Asia pacific journal of information systems
• /
• v.18 no.3
• /
• pp.91-121
• /
• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Journal of Distribution Science
• /
• v.14 no.2
• /
• pp.93-101
• /
• 2016

Purpose - This study aims to advance our knowledge about factors influencing technical startup performance through analysing technical startup process empirically. This study was conducted to focus on industry structure(industry growth rate, competitive intensity, and enter barriers), technology characteristics(technical excellence and wide range of technical application), and the performance in the technology-based start-ups. Specifically, analyzing moderating effect of technology-marketing strategy, this studied how moderating variables affect technical startup performance under industry structure. Research design, data, and methodology - The subject of this study was technology-based start-ups company that received technology transfer from public organization. The development of the paper model is based on the literature of the preceding research analysis in technology commercialization, performance of technology-based start-ups, and marketing strategy. This study has a construct that was defined in the previous studies, such that technology marketing strategy was defined into the two ways of being broad or narrow in strategic application. From November 3. 2015 to December 22, 220 questionnaires were distributed with targeting to start-up companies in technology-based. 188 responses were collected for empirical analysis except the missing and wrong value responses. This data were used for structural equation modeling and regression analysis. Results - The results of this study are as follows. First, as industry structure variables influencing on performance(technical, financial) of technology-based start-ups, industry growth rate, competitive intensity and enter barriers of variables were verified; high growth rate has more positive effect on performance than low growth rate, competitive low intensity has more positive effect on performance than competitive high intensity, low enter barriers have more positive effect on performance than high enter barriers. Second, as technology characteristics variables influences on the performance(technical, financial) of technology-based start-ups, technical excellence and wide range of technical application of variables were verified ; technical high-excellence has more positive effect on performance than technology low-excellence, wide range of technical application has more positive effect on performance than narrow range of technical application. We also find that technology marketing strategy(broad/narrow) in moderating factors on performance (technical, financial) is as follows. Analyzing the moderating effect depending on technology marketing strategy(broad/narrow), application of technology, and the types of technology strategy(broad/narrow) were revealed that broad marketing strategy had a more significant effect on performance of technology-based start-ups. With AMOS, the relevancy of the study model revealed higher for broad technology-marketing strategy than narrow technology marketing strategy, and the explanatory power revealed to be 6.4% higher in broad marketing strategy than narrow marketing strategy. Conclusions - This study confirmed that industry structure and technology characteristics are important factors influencing the performance of technology-based start-ups. Technology-marketing strategy affects the performance of technology-based start-ups between industry structure and technology characteristics. According to additional analysis, moderating variables and technology-marketing strategy are important factors influencing the performance of technology-based start-ups under industry structure and technology characteristics. Broad type of technology-marketing strategy has more attractive industry structure and excellent technology characteristics than narrow types of technology-marketing.

• Journal of Distribution Science
• /
• v.10 no.11
• /
• pp.79-88
• /
• 2012

Purpose - The objective of this paper is to suggest that a company's CRM activities have an effect on customer loyalty in the Korean retail industry. Typically, Korean customers use large local marts with convenience in the absence of any other choice. Therefore, this study aims to shed light on the fact that customers do not break away from their preferred retail stores, either owing to their stringent loyalty (the lie loyalty) or difficulty in turning to alternative choices. Research design, data, methodology - By surveying a sample of 200 hyper-markets through a questionnaire, and excluding dubious and missing responses, I obtained 181 samples to be included in the empirical analysis. The survey was conducted for two weeks during October 2011. AMOS and SPSS18 statistical packages were used for conducting statistical analysis for this study. This paper was developed using the concept of customer equity on CRM, which is known to have a positive impact on customer loyalty through the satisfaction and switching-barrier parameters. The hypothesis of this paper is that customer equity is composed of relationship equity, value equity and brand equity, and that the relationship equity variable has positive effects on the value equity and brand equity amongst other types of customer equity. Moreover, customer equity influences customer loyalty through parameters including customer satisfaction and switching costs in the Korean retail industry. Results - According to the results of the analysis, it was confirmed that relationship value had a positive effect (+) on all variables, including the perceived QoS (Quality of Service), store brand images, economic value, and store convenience. It was also confirmed that the assumption that the perceived QoS (Quality of Service), economic value, and store convenience had a positive effect on customer satisfaction was shown to be statistically significant, with a p-value below 0.05. Only the store brand value variable had an effect on the switching-cost variable with respect to the causal sequence of the variables, including the perceived QoS, store brand value, economic value, and store convenience. The remaining variables did not seem to influence the switching-cost variable. On the other hand, another effect showed that customer satisfaction had a statistically significant influence on the switching-costs variable. Moreover, the customer satisfaction and switching-cost variables also had a statistical influence on customer loyalty. Conclusions - The CRM activities had an influence on various variables (including perceived QoS, perceived economic value, store brand value, and store convenience) pertaining to customer values. Customer satisfaction and switching-cost had some effects on customer loyalty as a parameter. This confirms that stringent loyalty exists with respect to customer loyalty in the retail industry. The fact that the variable had such a statistically significant influence on the switching-cost and store brand equity variables means that consumers react to the reputation of a brand, confidence about the store, and quality confidence. The implications of this study in the retail industry should be further extended to devise strategies for customer retention.

• Journal of the Korea Institute of Building Construction
• /
• v.17 no.6
• /
• pp.535-544
• /
• 2017

This paper analyzes the relations between design errors, prevented by building information modeling (BIM)-based design validation, and their impacts in order to identify critical consideration factors for implementing BIM-based design validation in architecture, engineering, and construction (AEC) projects. More than 800 design errors detected by BIM-based design validation in two BIM-based projects in South Korea are categorized according to their causes (illogical error, discrepancy, and missing item) and work types (structure, architecture, and mechanical, electrical, and plumbing (MEP)). The probabilistic relations among the independent variables, including the causes and work types of design errors, and the dependent variables, including the project delays, cost overruns, low quality, and rework generation that can be caused by these errors, are analyzed using logistic regression. The characteristics of each design error are analyzed by means of face-to-face interviews with practitioners. According to the results, the impacts of design error causes in predicting the probability values of project delays, cost overruns, low quality, and rework generation were statistically meaningful.

• The Journal of the Korea Contents Association
• /
• v.20 no.10
• /
• pp.436-448
• /
• 2020

This study aims to determine the effect of e-cigarettes on oral health by investigating the association between the use of different tobacco products and oral health among Korean adults aged 19 years and older. Data from the 2017 Community Health Survey were used for the study. Respondents were divided into four groups: non-smokers, cigarette smokers, e-cigarette smokers, and users of both products. A sample of 228,357 respondents was selected for analysis. Twenty-four questionnaires with missing values (non-response or refusal) were excluded from the sample. A regression analysis was performed with oral as the dependent variable. A multivariate regression analysis showed a significant difference between cigarette smokers and users of both products when compared to the non-smokers. However, e-cigarette users showed a significant when the variables were correlated with age and gender. There was no significant difference in other dependent variables in a multivariate regression analysis. The results of the study indicated no association between e-cigarette use and oral health. More research is needed on factors such as amount and intensity of e-cigarette use.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.21
• /
• pp.9529-9534
• /
• 2014

Background: Cancer staging enables planning for the best treatments, evaluation of prognosis, and predictions for survival. The Collaborative Stage (CS) system makes it possible to significantly reduce the proportion of patients labeled at an "unknown" stage as well as discrepancies among different staging systems. This study aims to analyze the factors that influence the accuracy and validity of CS data. Materials and Methods: Data were randomly selected (233 cases) from stomach cancer cases enrolled for CS survey at the Korea Central Cancer Registry. Two questionnaires were used to assess CS values for each case and to review the cancer registration environment for each hospital. Data were analyzed in terms of the relationships between the time spent for acquisition and registration of CS information, environments relating to cancer registration in the hospitals, and document sources of CS information for each item. Results: The time for extracting and registering data was found to be shorter when the hospitals had prior experience gained from participating in a CS pilot study and when they were equipped with full-time cancer registrars. Evaluation of the CS information according to medical record sources found that the percentage of items missing for Site Specific Factor (SSF) was 30% higher than for other CS variables. Errors in CS coding were found in variables such as "CS Extension," "CS Lymph Nodes," "CS Metastasis at Diagnosis," and "SSF25 Involvement of Cardia and Distance from Esophagogastric Junction (EGJ)." Conclusions: To build CS system data that are reliable for cancer registration and clinical research, the following components are required: 1) training programs for medical records administrators; 2) supporting materials to promote active participation; and 3) format development to improve registration validity.

• The Journal of Korean Society for School & Community Health Education
• /
• v.21 no.3
• /
• pp.35-47
• /
• 2020

Objectives: This study is a descriptive research study conducted to grasp the Prediction factors of the sexual violence experience of college students. Methods: A convenience sampling was performed for 500 students from one college located in Gyeongsangbuk-do, who agreed to the purpose of this study. Data collection was conducted from October 5, 2015, to October 23, 2015, by filling out the self-report questionnaire. Among the 450 subjects excluding those with missing values, a questionnaire of dating violence experience was applied to 317 college students who answered that they had a friend of the opposite sex, and variables and prediction factors related to dating violence experiences were identified. The statistical methods used were descriptive statistics, x²-test, t-test, Pearson's correlation coefficient and binary logistic regression analysis. Results: As a result of the study, the experience of sexual behavior before entering college (𝑥²=6.52, p=.011), experience of sexual violence damage before entering college(p=.045), the experience of sexual assault before entering college (p=.007) and experience of school violence damage(p=.002) were variables related to the sexual violence experience of college students. School violence victimization (OR=4.831, p=.007) and controlling dating partners (OR=1.349, p<.001) were predictors of dating sexual violence. Dating sexual violence experience group were compared to dating sexual violence non-experience group, the relative degree of controlling dating partners was high (t=4.25, p<.001) and had a traditional gender role attitude (t=2.94, p=.004). and there was a positive correlation (r=.358, p<.001) between controlling dating partners and gender role attitude. Conclusions: In order to prevent sexual violence on dating among college students, it is expected that more effective health education results will emerge if the contents of the school-age school violence victimization experience and the control of dating partners, which are predicted factors of sexual violence on dating, are included in the sexual violence prevention program.

• Environmental and Resource Economics Review
• /
• v.26 no.4
• /
• pp.473-498
• /
• 2017

This study examines the effect of environmental regulation considering the endogeneity on the productivity of Korean manufacturing industry based on the Porter hypothesis using data from the Mining and Manufacturing Survey, Survey of Research and Development in Korea, and Environmental Statistics Portal from 2003 to 2013 with fixed effect model. In order to eliminate the bias of the missing variables that may occur in the existing studies, we analyze factors affecting productivity such as market competition, R&D investment as explanatory variables. And, in order to eliminate measurement error and inverse causality, we use instrumental variable approach. The main results are as follows. First, our findings that the environmental regulation improve the productivity of Korean manufacturing in the long-run support the Porter hypothesis. Second, our findings suggest that measurement error and reverse causality are main sources of the endogeneity, while omitted variable is not. Finally, environmental technology R&D has reduced productivity in the short-run.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.4
• /
• pp.12-22
• /
• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.