• 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.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.

• 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.

• Health Policy and Management
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• v.23 no.1
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• pp.19-34
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• 2013

Background: The study describes the changes resulted from imposition on tertiary hospital outpatient coinsurance rate rise policy and in tertiary or general hospital drug coverage rise policy on healthcare service utilization. Methods: Accordingly, the hypothesis about outpatient healthcare utilization after rise policy in outpatient coinsurance rate and drug coverage was established, using interrupted time-series analysis and segmented regression analysis to test the hypothesis. 5-year analysis period (2007. 3-2012. 3) from the outset year was designated, the data about most common 10 high-ranking of the main diseases targeting visiting patient from age of 6 to 64 were collected. Results: The summary on the major research is followed. First, the medical expense and duration of treatment tends to be increased in case of imposition about rise policy in outpatient coinsurance rate in the tertiary hospital under the interrupted time-series analysis. It showed temporary increase and slow down on account of influenza A even after the policy enforcement. In segmented regression analysis, duration of visit and medical expense in the tertiary hospital increased temporally right after the policy implementation and the decreased rapidly depends on period. Both rise and fall is statistically significant. The second, In case of tertiary or general hospital outpatient drug coverage rise policy, all of the tertiary hospital healthcare service utilization variables by the interrupted time-series analysis, drug coverage policy in the general hospital deeply declined according to decreasing trend before policy implementation. The third, in case of segmented regression analysis, the visit duration and medical expense statistically declined right after the policy implementation in both the tertiary and general hospital. Meanwhile, administration day was statistically meaningful only for the decrease right after the policy implementation. Otherwise, general hospital changes are not statistically meaningful. And the medicine cost was statistically, meaningfully decreased after the increase in drug coverage. Conclusion: Finally, the result demonstrated according to the analysis is only 1 hypothesis is denied, the other 2 are partially supported. Then, tertiary hospital outpatient coinsurance rate increase policy comparatively makes decrease effect on long-term healthcare utilization, and tertiary or general hospital outpatient drug coverage policy showed partially short-term effect is assured.

• 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.

• Journal of the Korean Home Economics Association
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• v.43 no.11 s.213
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• pp.185-196
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• 2005

The purpose of this research was to determine the relation between clothing evaluative criteria and segmented groups based on the perception of somatotype. The data for this research were collected from questionnaires of 192 females in Busan. Data were analyzed by frequency, factor analysis, cluster analysis, discriminant analysis, and regression analysis. Cluster analysis was used to identify groups of respondents based on the perception of somatotype difference factors. Based on the findings, three distinct groups were clustered: thin, moderate, fat. There were significant differences among the three groups in terms of clothing evaluative criteria. The result of regression analysis revealed that the perception of somatotype is a major determinant to influence the clothing evaluative criteria. The thin group preferred practical clothes while the fat group liked symbol clothes.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.11
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

• 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.