• 복식문화연구
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• 제6권4호
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• pp.120-135
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• 1998

The purpose of this study were to develop the taxonomy of apparel buying decision approaches and to identify the relationships between the apparel buying decision approaches and the situational characteristics. Data were collected via a questionnaire developed on the previous studies and the focus interview from 425 female college students living at Pusan, and analyzed by Factor Analysis, Cluster Analysis, Analysis of Variance, and Discriminant Analysis. Results indicated that apparel buying decision approaches consisted of eight dimensions and situational characteristics of affecting a particular apparel buying decision approaches were composed of three or five factors. The four types of apparel buying decision approaches were derived by Cluster Analysis and ANOVA: Recreational Shoppers, Brand Conscious Shoppers, Quality Conscious Shoppers, and Apathetic Shoppers. The findings revealed some patterns that were similar to previous studies and was useful to marketing managers who can view their customer segments in terms of the types in the taxonomy. Further, it provided a tool by which sales representatives can develop adaptive selling approaches based on a small set of buying situation and corresponding apparel buying decision approaches.

• 복식문화연구
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• 제22권5호
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• pp.743-759
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• 2014

The purpose of this study is to identify the antecedents of consumers' decision postponement on purchasing fast fashion brands. Ongoing search behavior, overchoice confusion, and similarity confusion were considered as antecedents. It was hypothesized that ongoing search behavior influences decision postponement both directly and indirectly through overchoice confusion and similarity confusion. Data were gathered by surveying university students in Seoul, using convenience sampling. Three hundred five questionnaires were used in the statistical analysis, which were exploratory factor analysis using SPSS and confirmatory factor analysis and path analysis using AMOS. Factor analysis proved that ongoing search behavior, overchoice confusion, similarity confusion, and decision postponement were uni-dimensions. Tests of the hypothesized path proved that ongoing search behavior influences decision postponement indirectly through overchoice confusion. In addition, similarity confusion influences decision postponement. The results suggest some confusion reduction strategies for marketers of fast fashion brands. Suggestions for future study are also discussed.

• International journal of advanced smart convergence
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• 제11권4호
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Spatial Information Research
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• 제9권1호
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• pp.91-105
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• 2001

이 연구에서는 도시공원의 입지결정에 관련된 행정 업무의 효율성과 의사결정의 질향상을 위하여, GIS와 의사결정 분석기법이 통합된 의사결정 지원시스템을 구축하고자 하였다. 이 시스템은 현황분석, 대안생성, 대안평가에 이르는 일련의 과정을 일관성있는 시스템환경 하에 통합하여 효율적인 관리과정을 제공하고 있다. 도시공원 입지결정을 위하여 형평성, 효율성, 수혜인구, 동별공원비율, 지가, 지장물, 녹지연계성 등의 기준이 적용되었고, 단계별 특성에 따라 MAUT, AHP, ELECTRE 등의 다양한 의사결정 분석기법들이 접목되었으며, GIS를 이용한 다양한 공간분석 기능과 의사결정 과정을 시각적으로 확인할 수 있는 기능들이 개발되었다. 이 시스템은 향후 도시공원 관리기능을 포함하여 종합적인 도시공원 관리시스템으로 발전될 수 있으며, 연구과정에서 개발된 방법론들은 도시공원뿐 아니라 기타 도시시설의 입지결정에도 활용될 수 있을 것이다.

• Asia pacific journal of information systems
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• 제21권2호
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• pp.19-42
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• 2011

This paper proposes a new framework to predict decision performance by investigating the cognitive fit of decision makers. We assume that every decision maker has two kinds of schema: emotional and rational. Cognitive fit is believed to have a close relationship with the two schemata and decision performance. In the literature on decision performance there is few studies investigating the relationship between the two schemata and cognitive fit. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among the two schemata, cognitive fit. and decision performance, and (2) to empirically prove its validity in the application to an Internet shopping environment. Based on the questionnaires from 104 respondents, we used a second order, confirmatory factor analysis (CFA) model to extract valid constructs, and a structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. The experimental results supported our research model.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.985-994
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• 2007

We note that the time of adolescents is very important time for obtaining informations about their jobs, exploring and making appropriate their career decision. In order to understand the career decision level of adolescents, we needed a study on effects of personal variables and family variables affecting the career decision level. For this, we provide direct, indirect and total effects of family variables and personal variables on the career decision level using the path analysis. Therefore, in this study, we give the real usefulness for making a different diagnosis and strategy solving some problems of career decision level.

• 대한치과보철학회지
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• 제46권6호
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• pp.610-619
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• 2008

STATEMENT OF PROBLEM: Factors affecting patients' decision-making for dental prosthetic treatment should be examined in terms of understanding improving patients' oral health. PURPOSE: The main purpose of this dissertation was to investigate patients' dental prosthetic treatment and factors affecting patients' decision-making for dental prosthesis treatment in Deagu and Gyungbook areas. MATERIAL AND METHODS: This study was based on the preliminary survey of dental patients conducted from July 1 to August 31 in 2006. A total of 700 questionnaires had been distributed and 640 were collected. 629 questionnaires were used for the statistical analysis. Descriptive and inferential statistics, such as frequencies, cross tabulation analysis, correlation analysis, logistic regression analysis, and multiple regression analysis were introduced. In the multiple regression analysis and logistic regression analysis, twenty-two independent variables were employed to explore the factors which have impacts on decision-making and satisfaction. RESULTS: The results of this dissertation are as follows: Logistic regression analysis turned out that monthly income, age, degree of expectation, marital status, and employer-insured policy of national insurance statistically increased the odds of decision-making of dental prosthesis treatment. But educational attainment decreased the odds ratio of the decision-making of dental prosthesis treatment. However, the rest independent variables do not have statistically significant impacts on the decision-making of dental prosthesis treatment CONCLUSION: Among independent variables, marital status had the most significant influence on the decision making of dental prosthesis treatment. Finally, suggestions for the future study and policy implications to improve satisfaction of the patients' dental prosthetic treatment were discussed.

• Physical Therapy Rehabilitation Science
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• 제12권2호
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• pp.80-91
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• 2023

Objective: The purpose of this study is to identify factors that affect the incidence of hypertension using logistic regression and decision tree analysis, and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 9,859 subjects from the Korean health panel annual 2019 data provided by the Korea Institute for Health and Social Affairs and National Health Insurance Service. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In logistic regression analysis, those who were 60 years of age or older (Odds ratio, OR=68.801, p<0.001), those who were divorced/widowhood/separated (OR=1.377, p<0.001), those who graduated from middle school or younger (OR=1, reference), those who did not walk at all (OR=1, reference), those who were obese (OR=5.109, p<0.001), and those who had poor subjective health status (OR=2.163, p<0.001) were more likely to develop hypertension. In the decision tree, those over 60 years of age, overweight or obese, and those who graduated from middle school or younger had the highest probability of developing hypertension at 83.3%. Logistic regression analysis showed a specificity of 85.3% and sensitivity of 47.9%; while decision tree analysis showed a specificity of 81.9% and sensitivity of 52.9%. In classification accuracy, logistic regression and decision tree analysis showed 73.6% and 72.6% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. It is thought that both analysis methods can be used as useful data for constructing a predictive model for hypertension.

• 한국국방경영분석학회지
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• 제24권1호
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• pp.68-87
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• 1998

Techniques from decision analysis and expert system have both been extensively used in the development of computerized decision aids, although each discipline uses different approaches in knowledge (information or input) acquisition, representation, and problem solving methodology. From the perspective of many types of practical decision aiding applications, both normative decision aids and expert system technology have significant limitations. Many research efforts have been exerted toward complementing the one's deficiency with the other's possible techniques or vice versa. In this paper, among many possible complementary techniques for better decision aiding between decision analysis and expert system, we focus on the using prescriptive methodology of decision analysis which incorporates user's preference knowledge for conflict resolution in rule based expert system.

• 한국태양에너지학회 논문집
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• 제24권4호
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• pp.55-63
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• 2004

The purpose of this study is to development of life cycle cost analysis methodology of HVAC system for decision maker. The results of this study are as follows; maintenance/management, equipment construction, planning/design, and demolition/sell phases (1) To develop the cost breakdown structure for LCC in HVAC system, this study apply the method of additional pertinent level, title, CBS number, block number and variable index. (2) LCC analysis order of HVAC system compose four phase. (3) Life cycle costing influence diagram can bring us to make the most efficient decision through a visual graphical diagram that is shown relationship among variables and that decision maker traces easily from life cycle cost analysis situation.