• 한국경영과학회지
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• 제23권2호
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• pp.103-129
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• 1998

Corporate level decision making with multiple decision makers in a consistent way is essential in Decision Support System. However, since the decision makers have different interests and knowledge, the models used by them are also different in their level of abstraction. This makes decision makers waste a lot of efforts for an integrated decision making. The purpose of this paper is to propose an integration mechanism so that collaborative decision making models may be used synthetically in multi-abstraction level. Models are classified as multimedia model, mathematical model, qualitative model, causal ＆ directional model, causal model, directional model and relationship model according to the level of abstraction. The proposed integration mechanism consists of model interpretation phase. model transformation phase, and model integration phase. Specifically, the model transformation Phase is divided into (1) model tightening mode which gather information to make a model transformed into upper level model, and (2) model relaxing mode which makes lower level model. In the model integration phase, models of same level are to be integrated schematically. An illustrative M＆A-decision example is given to show the possibility of the methodology.

• 한국경영과학회지
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• 제30권1호
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• pp.75-94
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• 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.

• 산업경영시스템학회지
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• 제41권4호
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.101-104
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• 1997

Providing information on corporate level decision making for multiple decision makers in a consistent way is essential in Decision Support Systems. However, since the decision makers have different background and knowledge, the models used by them are also different in representation models. This makes the decision makers require a lot of efforts for model integration in an integrated decision making. The purpose of this paper is to propose an integration mechanism for synthetic use of multi-abstraction level decision making models. The proposed integration mechanism consists of model interpretation phase, model transformation phase and model integration phase. Specifically, the model transformation phase is divided into model tightening mode which gather information to makes a model transformed into upper level model, and model relaxing mode which makes lower level model.

• 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.

• Asia pacific journal of information systems
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• 제14권2호
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• pp.37-59
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• 2004

Team decision making is a collective behavior that needs to be understood by considering properties belonging to team and individual member domains together. This paper introduces a conceptual model called "Dual-Level(DL)" model that describes a team decision-making process in terms of team level, member level, and the relationship between them. The team-level view explains the decision-making process by considering the team as a wholeand divides the process into three stages: Problem Conceptualization, Alternative Generation, and Selection. The member-level view describes what happens to individual members when they go through the group process and splits it into the five phases: Individual Cognitive Mapping, Problem Decomposition, Subproblem Session, Subproblem Integration, and Team Decision. The DL model works as a theoretical framework to explore team decision making by using a set of computational models of team design and team members. In practice, the conceptual framework is used to build a computational model of decision making team, called "Team-Soar."

• 품질경영학회지
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• 제17권2호
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• pp.113-120
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• 1989

The purposes of this paper are to compare expert systems and decision support systems, and illustrate the possible benefits when expert systems are integrated into the model base of a decision support systems for supporting decision-makers. Integrating expert systems capability into decision support systems may enhance the quality and efficiency of both computerized systems. This integration can improve selection of model, analysis, model management, judgement, and modeling. Thus the results are much more powerful decision support systems than are presently available.

• 한국도서관정보학회지
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• 제13권
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• pp.131-166
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• 1986

This study is designed to review the methods of duplicate copies decision making in the academic library. In this thesis, I surveyed queueing & markov model, statistical model, and simulation model. The contents of the study can be summarized as follows: 1) Queueing and markov model is used for one of duplicate copies decision-making methods. This model was suggested by Leimkuler, Morse, and Chen, etc. Leimkuler proposed growth model, storage model, and availability model through using system analysis method. Queueing theory is a n.0, pplied to Leimkuler's availability model. Morse ad Chen a n.0, pplied queueing and markov model to their theory. They used queueing theory for measuring satisfaction level and Markov model for predicting user demand. 2) Another model of duplicate copies decision-making methods is statistical model. This model is suggested by Grant and Sohn, Jung Pyo. Grant suggested a model with a formula to satisfy the user demand more than 95%, Sohn, Jung Pyo suggested a model with two formulars: one for duplicate copies decision-making by using standard deviation and the other for duplicate copies predicting by using coefficient of variation. 3) Simulation model is used for one of duplicate copies decision-making methods. This model is suggested by Buckland and Arms. Buckland considered both loan period and duplicate copies simultaneously in his simulation model. Arms suggested computer-simulation model as one of duplicate copies decision-making methods. These methods can help improve the efficiency of collection development and solve some problems (space, staff, budget, etc, ) of Korean academic libraries today.

• 철학연구
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• 제144권
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• pp.257-283
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• 2017

이 논문의 목적은 집단적 의사형성 및 의사결정의 모델을 검토하고 성숙한 민주주의 사회에 적합한 의사형성 및 의사결정의 모델을 제안하는 것이다. 하버마스는 이런 의사형성 및 의사결정의 모델을 그 정당화 유형에 따라 자유주의적 모델, 공화주의적 모델, 심의정치적 모델로 구분하고, 호네트는 자유주의, 공화주의, 절차주의의 세 가지 모델로 구분하고 있다. 이에 따라 논자는 민주주의 사회에서 가능한 의사결정의 모델을 그 특징에 따라 다시 세 가지, 즉 힘에 의한 모델과 절차에 따른 모델, 공화주의적 모델로 구별하고자 한다. 왜냐하면 이런 구별을 통해 각각의 의사결정이 가진 특징을 뚜렷이 부각시키며 이와 더불어 각각의 장단점을 파악하고자하기 때문이다. 이런 장단점에 대한 분석은 결국 올바른 의사형성 및 의사결정의 방법을 모색하고자 하는 의도를 반영한다. 그러나 올바른 의사결정의 방법을 분석하기 위해서는 오늘날 의사결정의 목표가 무엇인지 또한 밝혀져야 한다. 따라서 집단적 의사형성 및 의사결정의 목표는 사회적 행복에 있음을 해명하며, 이 사회적 행복을 증진시킬 수 있을 때 집단적 의사결정은 정당화될 수 있다. 그러나 이 사회적 행복을 도모하기 위한 정당한 의사결정의 방법은 오늘날 현대 사회의 조건에 대한 분석을 또한 요구한다. 따라서 현대 탈형이상학적 시대와 다원주의 사회에서 정당한 의사형성 및 의사결정이 되기 위한 조건에 대한 분석도 시도될 것이다.

• Journal of Information Technology Applications and Management
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• 제11권1호
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.