• Korea Journal of Hospital Management
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• v.10 no.4
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• pp.75-97
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• 2005

The research objective is to empirically investigate the compensation packages maximizing the utilities of internal customers by applying the market segmentation theory. Data was collected from four Korean hospitals in Seoul, Busan and Gyunggi-do. The research is designed to seek the compensation package maximizing the utility of doctors by mixture regression model, which has been applied as latent structure and other type of finite mixture models from various academic fields since early 1980s. The mixture regression model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture regression model is to unmix the sample, to identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. The doctors were segmented into 5 groups by their preference for the compensation package. The results of this study imply that the utility of doctors increases with differentiated compensation package segmented by their preference.

• Journal of Korea Water Resources Association
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• v.49 no.3
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• pp.253-262
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• 2016

A Rating curve is a regression equation of discharge versus stage for a given point on a stream where the stream discharge is measured across the stream channel with a stage and discharge measurement. The curve is generally used to calculate discharge based on the stage. However, the existing approach showed problems in terms of estimating uncertainty associated with regression parameters including the separation parameter for low and high flow. In this regard, this study aimed to develop a new method for the aforementioned problems based on Bayesian approach, which can better estimate the parameter and its uncertainty. In addition, this study used a Bayesian Multi-Segmented (Bayesian M-S) model which is provided a comparison between the existing and proposed scheme. The proposed model showed better results for the parameter estimation than the existing approach, and provided better performance in terms of estimating uncertainty range.

• Health Policy and Management
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• v.1 no.1
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• pp.19-26
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• 1991

Demographic variables have a great deal of impact on the utilization of health services. In this paper, the use of segmented polinomials is shown to be superior to the simple use of dummy variables and simple polinomials in explaining differences in health care utilization with respect to sex and age differences.

• Journal of the Korean Geographical Society
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• v.43 no.6
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• pp.938-950
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• 2008

This study was to investigate if there were any significant relationships between cultural destination selection attributes and travel satisfaction according to segmented groups of cultural destination attributes. Survey questionnaire was developed based on the previous study and data were collected from on site survey, which was one of the famous cultural tourism destination in Korea such as Booyoe and Kongjoo. Six dimensions of cultural destination attributes were identified from factor analysis and three different segmented groups were determined from cluster analysis. Then, Multiple regression analysis conducted with six destination attributes as independent variables and one travel satisfaction as dependent variable, while Fisher's Z score for three segmented groups were considered as moderator's variable. The results showed that cultural destination attribute affected respondents' level of travel satisfaction and there was differences among segmented groups in terms of their affecting factors to the travel satisfaction. These findings suggested that there were different segmented groups of cultural destination selection attributes and each group pursued different cultural travel products and services.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.8
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• pp.1197-1208
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• 2000

The purpose of this study was to find out the effects of the accord between consumers benefit factors and attribute factors of brand image on brand attitude. This study was based on Kellers conceptualizing model of brand image. The subjects were 605 working women in their twenties living in Seoul, Korea. The data were analyzed by Euclidian distance model, ANOVA of repeated measures, regression, F-test by Extra Sum of Squares Principle. The results were as follows. 1. There were significant differences among the brands and among the segmented groups in the accord between benefit factors and attribute factors of brand image and in the brand preference. Moreover there were significant interactions between the brands and the segmented groups in the accord between benefit factors and attribute factors of brand image and in the brand preference. 2. There were significant effects of the accord between benefit factors and attribute factor of brand image on brand attitude. 3. There were significantly different effects of the accord between benefit factors and attribute factors of brand image on brand attitude among the segmented groups.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.1 s.139
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• pp.103-113
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• 2005

This study was intended to examine factor structure of value and clothing behavior and the effects of value on clothing behavior, to investigate clothing behavior and clothing purchasing behavior of the groups segmented by the value factors and the difference of those between male group and female group and to provide useful information for establishment of marketing strategies. The subjects were 575 university students. A total of 575 questionnaires was analyzed with factor analysis, cluster analysis, ANOVA, Duncan's multiple range test, ${\chi}^2-test$, regression analysis, and correlation analysis. The results were as follows: 1. Value was composed of 2 factors: personal orientation value and social orientation value. Clothing behavior were composed of 9 factors: interest, fashion, statue symbol, individuality, psychological dependence, comfort, aesthetic sense, economical efficiency, and social approval. 2. Clothing behavior and clothing purchasing behavior were significantly different among 3 groups segmented by 2 value factors. 3. The effects of value on clothing behavior was significantly different. 4. The effects of value on clothing behavior, clothing behavior and clothing purchasing behavior between male group and female group were different.

• Horticultural Science & Technology
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• v.30 no.3
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• pp.270-277
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• 2012

Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of $CO_2$ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse $CO_2$ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of $CO_2$ level. In this study, a mathematical model was developed to estimate the $CO_2$ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between $CO_2$ concentrations at the soil surface and 5-cm depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of $CO_2$ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict $CO_2$ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for $CO_2$ enrichment in a soil-based greenhouse.

• Korean Journal of Clinical Pharmacy
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• v.20 no.3
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• pp.242-247
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• 2010

Controlling inappropriate antibiotics prescribing for acute upper respiratory infections(URI) is a very important for prudent use of antibiotics and resistance control. Health Insurance Review and Assessment Service (HIRA) introduced Prescribing Evaluation Program and publicly reported antibiotics prescribing rate for URI of each health institution. We performed segmented regression analysis of interrupted time series to estimate the effect of public report on antibiotics prescribing rate using national health insurance claims data. The results indicate that just before the public report period, clinics' monthly antibiotics prescribing rate for URI was 66.7%. Right after the public report, the estimated antibiotics prescribing rate dropped abruptly by 12.3%p. There was no significant changes in month-to-month trend in the prescribing rate before and after the intervention.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.7
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• pp.953-963
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• 2000

This study intended to analyse the factors of brand image and brand image positioning of domestic 20’s female apparel(formal wear) among the consumer groups segmented by benefits sought in apparel and to provide marketing strategy of brand image. The subject of this study were 605 working women in their 20’s living in seoul, and the model sampling was done by convenienced sampling method based on the subjects age and occupation. Survey based on references and former studies was used. and statistical methods such as frequency, percentage, mean, factor analysis, preference regression were applied. The results of this study were as follows. 1. The factor structures of brand image were classified into symbolism/aesthetics, and practicality. 2. Perception, ideal preference vector, and brand preference of brand image were proven to be significantly different among the four segmented consumer groups.

• Asia Marketing Journal
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• v.16 no.3
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• pp.57-75
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• 2014

This paper explores the possibility of segmentation of consumers based on their quality expectations toward the automotive telematics service. Hypotheses on utilizing consumers' expectations toward the automotive telematics service for the market segmentation and linking the segments with optimal product designs are formulated. Samples are segmented based on their perceived service quality to the service attributes from various configurations of automotive telematics service. Then, a regression analysis on the segmented groups of users is performed to check whether they have qualitatively differing evaluation on the service quality. The result indicates that the proposed segmentation is operational and differing product attributes configuration is desirable according to the characteristics of the consumer segment. Hence, according to the characteristics of each consumer segment formed based on their expectation toward the telematics service, a product differentiation strategy of the automotive telematics system can be designed and be proposed to the product line designer.