• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.13-26
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• 1999

When we try to design a production planning system for a manufacturing company, it is a time consuming task to analyze various planning activities and identify inter-relationship among a lot of decisions made for the production planning. Most of the research efforts have been concentrated to well-organized independent decision-making problems that may usually be identified only after analyzing the characteristics of the decision-making process as a whole. In this paper, a methodology is suggested to characterize the whole process of the production planning for a manufacturing company and reduce the complexity of decision-making problems. The methodology is based on an experience of developing a production planning software for an automobile component manufacturer in korea. First, it is explained how to identify and represent the dependency among various decision-making variables. And a methodology is proposed to analyze the identified dependency among decision variables and identify decision-making process. Lastly, a practical example is provided to illustrate the analysis procedure in this paper.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.141-152
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• 2006

This paper presents the development of a decision model to examine the optimal repair action for a deteriorating system. In order to make a reasonable decision, it is necessary to perform an analysis of the uncertainties embedded in deterioration and to evaluate the repair actions based on the expected future cost. Focusing on the power law failure model, the uncertainties related to deterioration are analyzed based on the Bayesian approach. In addition, we develop a decision model for the optimal repair action by applying a repair cost function. A case study is given to illustrate a decision-making process by analyzing the loss incurred due to deterioration.

• Journal of the military operations research society of Korea
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• v.24 no.1
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• pp.18-40
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• 1998

This paper is aimed to design an intelligent military decision aiding system in a network computing environment, especially focusing on designing an intelligent analytic system that has data mining tools and inference engine. Through this study, we concluded that the intelligent analytic system can aid military decision making processes. Highlights of the proposed system are as follows : 1) Decision making time can be reduced by the On-line and Real-time analysis ; 2) Intelligent analysis on military decision problems in network computing environments in enabled; 3) The WWW-based implementation models, which provide a standard user interface with seamless information sharing and integration capability and knowledge repository.

• Asia-Pacific Journal of Business
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• v.4 no.2
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• pp.11-20
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• 2013

This study extends the extant scope of understanding investment decision, beyond the dominant 'technical' emphasis on the application of discounted cash flow techniques. The research methodology draws the positivist and interpretive research paradigms. It uses a deductive approach, survey strategy and principal component analysis for the analysis. Three key sets of factors emerged as important in the investment decision process in the hydropower sector. They are: group consensus (framing), influences on own judgment (heuristics), and application of knowledge & experience (intuition). The use of purposive and convenient sampling might have some unintended impact on the findings. Consequently, any generalizations of the findings to a wider population of organizations and managers need to be made with care. It is hoped that this paper will encourage other researchers to go beyond the analytic techniques of investment appraisal that have dominated investment decision research and seek to balance the emphasis by focusing on human involvement and behavioral aspects of investment decision.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.549-556
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• 2006

In this paper, we consider interval-valued Choquet integrals and fuzzy measures. Using these properties, we discuss some applications of them in multicriteria decision aid. In particular, we show how these interval-valued Choquet integrals can model behavioral analysis of aggregation in ulticriteria decision aid.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.605-618
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• 2012

In this study, the possibility of decision error is investigated to identify and improve the reliability of participants in the process of conducting the sound quality analysis for laser printers. So far, there is not a way to identify and express the possibility of individual participant quantitatively. Thus, the decision error model is proposed which is based on the expectation value between the perceived sounds. Through the experimental verification on the laser printers, it was found that the possibility of decision error is affected according to the normalized difference. The possibility of decision error has inversely proportional to the normalized difference between the perceived sounds. When the normalized difference becomes small value, the uncertainly between decisions is inversely increase, and then it is difficult to obtain the proper result in the process of the jury evaluation for laser printers. For this reason, in this study, the proposed decision error model is added in the previous step of the correlation verification. Comparing to the conventional process only using the correlation based method, after the reliability of each participant is verified, the correlation with the mean response of participants is verified. It was found that the participants who were recognized as having unusual preferences are actually identified as having the reliability problem. Based on the results of this study, the proposed decision error model will be helpful to identify and improve the reliability of participants in the following study for the sound quality analysis.

• Journal of the Korean Home Economics Association
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• v.50 no.7
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• pp.59-66
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• 2012

The purpose of this study was to identify a causal relationship in the career preparation behavior, parental social support, career decision making self-efficacy and the career maturity of the pre-service elementary school teachers. A total of 374 questionnaires were used for data analysis, excluding the 23 copies deemed insincere in response. To ensure the reliability and validity of the questions, technical statistics of the frequency, ratio, average, standard deviation, skewness, and kurtosis via PASW 18.0, item-total correlation, the totality, and the reliability analysis. The structural analysis via AMOS 7.0 in the bootstrapping method was undertaken to perform the path analysis among the variables and to assess the suitability of the model. The findings of the study led to the following conclusions: First, the causal model for the career preparation behavior, parental social support, career decision making self-efficacy, and the career maturity of the pre-service elementary school teachers is suitable to empirical analysis on research variables. Second, the career decision making self-efficacy of pre-service elementary teachers has direct effect on career preparation behavior positively. Third, parental social support of the pre-service elementary teachers has indirect effects on the career preparation behavior positively.

• Journal of Engineering Education Research
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• v.13 no.4
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• pp.51-59
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• 2010

In order to manage the lectures efficiently in the university and improve the educational outcome, the process is needed that make diagnosis of the present educational outcome of each classes on a lecture and find factors of educational outcome. In most studies for finding the factors of the efficient lecture, statistical methods such as association analysis, regression analysis are used usually, and recently decision tree analysis is employed, too. The decision tree analysis have the merits that is easy to understand a result model, and to be easy to apply for the decision making, but have the weaknesses that is not strong for characteristic of input data such as multicollinearity. This paper indicates the weaknesses of decision tree analysis, and suggests the experimental solution using multiple decision tree algorithm to supplement these problems. The experimental result shows that the suggested method is more effective in finding the reliable factors of the educational outcome.

• IE interfaces
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• v.24 no.4
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• pp.408-419
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• 2011

R&D is a foundation for new business chance and productivity improvement leading to enormous expense and a long-term multi-step process. During the R&D process, decision-makers are confused due to the various future uncertainties that influence economic and technical success of the R&D projects. For these reasons, several decision-making models for R&D project investment have been suggested; they are based on traditional methods such as Discounted Cash Flow (DCF), Decision Tree Analysis (DTA) and Real Option Analysis (ROA) or some fusion forms of the traditional methods. However, almost of the models have constraints in practical use owing to limits on application, procedural complexity and incomplete reflection of the uncertainties. In this study, to make the constraints minimized, we propose a new model named Real Option Decision Tree Model which is a conceptual combination form of ROA and DTA. With this model, it is possible for the decision-makers to simulate the project value applying the uncertainties onto the decision making nodes.

• Journal of the Korea Convergence Society
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• v.3 no.2
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• pp.27-32
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• 2012

The purpose of this study was to find out the effect of self-efficacy, career decision-making styles, and career decision-making level of the college the department of Dental Hygiene 1,2,3 students. The subjects of this study were 106 university students of the department of Dental Hygiene in K university. The instrument employed were the Career Decision Making Self Efficacy Scale, career decision level, career preparation behavior.The data collected were analyzed using Frequency analysis, t-test, Regression analysis and the pearson correlation of the spss 19.0 version.