• Journal of Korean Academy of Nursing
• /
• v.30 no.1
• /
• pp.47-59
• /
• 2000

The purpose of this study was to explore decision making phenomenon of living kidney donation experienced by kidney donors. Data were collected through semi-structured indepth interviews from 12 kidney donors. All interviewes were audiotaped and transcribed verbatim. Constant comparative analysis was used to analyze the data with NUDIST4.0 software program. process have effects on the execution of kidney donation. Based on the degree of "wish to give", three distinct patterns were identified: Voluntary, compromising, and passive. The voluntary decision making was the most frequent one, while the passive the least. The degree of "wish to give" was influenced by intimacy between the donor and the receipient, geographical locations, economical efficiency of kidney transplantation, and religion. Each pattern was explained by describing interfering and facilitating factors as well as other issues occured in the decision making process. The results of this study will help nurses make effective nursing intervention by understanding the characteristics of decision-making patterns and decision-making process to donate a living kidney.

• Asia pacific journal of information systems
• /
• v.13 no.2
• /
• pp.105-117
• /
• 2003

As E-commerce is getting more popular, consumers faces more decision complexity than ever before because they can get greater alternative choices. Futhermore, consumers are sometimes motivated to expand effort in making a good decision in the case of relatively important and non-routine decison, such as buying a house or car. Thus, a buying decision support function is required to help consumers make decisions that have the greatest effects on consumer's lives. We develop a propotype system of a web-based buying decision support system for a cyber shopping mall. A buying decision of a consumer is a multi-attribute decision problem and is supported using analytic hierarchy process model. The system was implemented using HTML, Java, Java applet, JSP.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.931-939
• /
• 2003

This paper is aimed at proposing a new framework to predict decision performance, by Investigating decision maker's cognitive resonance. We assume that every decision maker has two kinds of schema­emotional schema and rational schema. Cognitive resonance is believed to have a close relationship with the two schemata and decision performance. In literature on decision performance there is no study' seeking relationship among the two schemata ana cognitive resonance. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among two schemata, cognitive resonance, and decision Performance, and (2) to empirically prove its validity applying to. Internet shopping Situation. Based on the questionnaires from 13S- respondents, we used a second order confirmatory factor analysis (CFA) to extract valid constructs, and structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. Experimental results supported our research model with some further research issues.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.13 no.22
• /
• pp.51-57
• /
• 1990

A new interactive multiobjective decision making technique, which is called the fuzzy sequential proxy optimization technique, has been proposed. This technique is the revised version the sequential proxy optimization technique that the decision-maker's marginal rates of substitution is interpreted as type of L-R fuzzy numbers. It used to the square of normalized scalar product as the doptimalilry condition. However, this technique ignores the imprecise nature of a decision-maker's judgement of marginal rates of substitution. Also, it have a shortcoming that can be only applied over three objective functions. In this paper, considering the imprecise nature of a decision-maker's judgement, we presents an interactive fuzzy decision-making method on the basis of the decision-maker's MRS presented through the use of five types of membership functions including non-linear functions. FORTRAN programs that run in conversational mode are developed to implement man-machine interactive procedure.

• MALSORI
• /
• no.45
• /
• pp.117-126
• /
• 2003

Decision tree-based state tying has been proposed in recent years as the most popular approach for clustering the states of context-dependent hidden Markov model-based speech recognition. The aims of state tying is to reduce the number of free parameters and predict state probability distributions of unseen models. But, when doing state tying, the size of a decision tree is very important for word independent recognition. In this paper, we try to construct optimized decision tree based on the average of feature vectors in state pool and the number of seen modes. We observed that the proposed optimal decision tree is effective in predicting the state probability distribution of unseen models.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2006.11a
• /
• pp.54-59
• /
• 2006

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for these data.

• The Research Journal of the Costume Culture
• /
• v.22 no.5
• /
• pp.743-759
• /
• 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.

• Journal of Korean Academy of Nursing
• /
• v.34 no.2
• /
• pp.270-277
• /
• 2004

Purpose: The purpose of this study was to investigate the relationship between decision-making factors(theoretical knowledge, expertise, empowerment, intuition) and participation in proportion to nurses's clinical experience. Method: Data was collected by quota sampling from July 10, 2001 to August 22, 2001 from 132 clinical nurses who work for 3 General hospitals. Data was analyzed using SPSSWIN 10.0 with crosstab, ANOVA, and stepwise multiple regression. Result: Expertise(F=34.347, p=.000), empowerment(F=29.316, p=.000), and participation(F=3.276, p=.041) were significantly different among 3 clinical experience groups. Clinical experience correlated with expertise(r=.551, p=.000) and empowerment(r=.492, p=.000), and Decision-making participation also correlated with expertise(r=.351, p=.000) and empowerment(r=.265, p=.002). Decision-making participation is effected by theoretical knowledge(under 3.00yr clinical experience), expertise(3.01-5.00yr), and empowerment(above 5.01yr). Conclusion: These findings indicate that factors(theoretical knowledge, expertise, or empowerment) on decision-making participation varies as nurses's clinical experience differs. Therefore, decision-making needs bilateral agreement between staff nurses and nurse managers rather than the responsibility of one.

• Korean System Dynamics Review
• /
• v.3 no.2
• /
• pp.69-91
• /
• 2002

This paper presents an analysis of the impact of the causal looping method to the Korean middle managers' decision-making processes. The sample included the observations of decisions made by 70 groups with 5 to 7 members each. The results showed that the causal looping method was a strong device to help Korean managers followed value-focused decision processes, as opposite to alternative-focuses ones. The lessons from this study suggest a direction for the development of the education method to improve group decision-making processes.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.30 no.1
• /
• pp.75-94
• /
• 2005

Research in the decision sciences has continued to develop a variety of mathematical models as well as software tools supporting corporate decision-making. Yet. in spite of their potential usefulness, the models are little used in real-world decision making since the model solution processes are too complex for ordinary users to get accustomed. This paper proposes an intelligent and flexible model-solver integration framework that enables the user to solve decision problems using multiple models and solvers without having precise knowledge of the model-solution processes. Specifically, for intuitive model-solution, the framework enables a decision support system to suggest the compatible solvers of a model autonomously without direct user intervention and to solve the model by matching the model and solver parameters intelligently without any serious conflicts. Thus, the framework would improve the productivity of institutional model solving tasks by relieving the user from the burden of leaning model and solver semantics requiring considerable time and efforts.