• The Journal of Information Systems
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• v.10 no.1
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• pp.5-25
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• 2001

The main purpose of this paper is to develop a Delphi Decision Support System based on the web, which can improve the conventional Delphi method. Among major drawbacks of the conventional Delphi methods are cost and efforts to distribute and collect the questionnaire by the regular mail and the tardiness in collecting, categorizing, analyzing, and reporting the result of the questionnaire. With the proposed Delphi Decision Support System, the moderator sends the e-mail to invite the member of panels so that they may visit the homepage of the Delphi Decision Support System. When the panelists input their opinions about the issues, the Delphi Decision Support System analyzes the inputs and reports the result without delay. To implement the Delphi Decision Support System, we integrated Microsoft SQL Server 6.5, jdbcKona/MS SQLServer 4 JDBC driver, and Java Development Kit 1.2

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• Asia pacific journal of information systems
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• v.10 no.1
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• pp.1-18
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• 2000

One stream of the GDSS(Group Decision Support System) research is to investigate how GDSS affects decision performances of small groups according to task types, support features, meeting facilitation modes and meeting environments. But little study has investigated the effects of group member characteristics on group decision processes and outcomes depending upon whether GDSS is provided or not. To date, most GDSS studies have not controlled group member characteristics(e,g. personality, sex, decision style) in laboratory experiments. However, this study included the decision styles of group members as an independent variable. Therefore, this study investigated how differently members of two different decision styles perceive the use of GDSS in small group meetings through lab experiments. The two decision styles are feeling(F) style and thinking(T) style. We found that the effect of GDSS is a function of individual's decision style only in the communication thoroughness variable. The decision style is a statistically significant factor that can mediate the effects of the group support technology on the perceived communication thoroughness. Specifically, the GDSS is positively related to participants' perception about satisfaction on decision process, goal achievement, communication thoroughness, degree of influence-outward and effort for achieving meeting goals.

• Journal of Ecology and Environment
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• v.35 no.4
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• pp.251-258
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• 2012

Many aquatic ecosystems suffer from anthropogenic disturbances, including the introduction of damaging levels of toxic substances. The effects of disturbances include complex relations with various components involved in the systems, and can include physical, chemical, and hydrological disruption depending of the contaminant. Decision Support Systems (DSSs) are developed to help decision makers to deal with complex management crises, through the systematic structuring and evaluation of decisions, and through providing easy-to-use and integrated tools for information elaboration and display. We reviewed various DSSs developed for toxic substances in aquatic ecosystems, and suggested a conceptual framework which is best suited to the management of such issues within Korea. It may assist stakeholders with their decision making process, and in the achievement of a consensus on water management solutions.

• Management Science and Financial Engineering
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• v.10 no.1
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• pp.1-23
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• 2004

The changing structure of organization and the increasing diversity of business have forced organizations to have abilities to coordinate dispersed business activities. They have required cooperation and coordination among the functional units in the organization which should involve group decision-making processes. Although many group decision-making support tools and methods have been introduced to enable the collaborative process of group decision-making, they often lack the features supporting the dynamic complexity issue frequently occurring at group decision-making processes. This results in cognitive unfit between the group decision-making tasks and their supporting tools, bringing about mixed results in their effects on group decision-making. This study proposes system dynamics modeling as a group decision-making support tool to deal with the group decision -making tasks having properties of dynamic complexity in terms of cognitive fit theory.

• Korean Management Science Review
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• v.8 no.1
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• pp.51-70
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• 1991

This paper discusses planning and scheduling problems for efficient utilization of an FMS and presents an integrated decision support system for FMS production planning and scheduling problems. The decision support system, FMSDS(Flexible Manufacturing Systems Decision Support System), includes of data of handling module, part selection module, loading module, load adjusting module, scheduling module and simulation module etc. This paper includes the solution methodology of each subproblem. And an integrated interface scheme between the subproblems is presented. The interface scheme considers the relationships between the subproblems and generates solution using hierarchical and looping approaches. FMSDS is made up of six alternative models considering 3 loading objectives and 2 production order processing strategies. Performance comparisons among 6 alternatives and other decision support systems are shown using the non-terminating simulation techniques.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.202-209
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• 2005

In this paper, benchmark tests of Rapid Prototyping(RP) are presented to evaluate characteristics of various RP Systems and Processes, and several decision-support systems are developed to select RP Machine/Process suitable to user's requirements. Results of the RP benchmark tests are applied to the recently developed RP machines for the purpose of analyzing attributes such as dimensional accuracy, surface roughness, build cost, build time, and etc. Decision-making support systems are also developed, which contain not only new LCE (Linear Confidence Equation) algorithm but also modified PRES and MDS algorithm. Those algorithms are proved to be effective in that reasonably acceptable results are obtained on several cases of different inputs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.19-22
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• 2000

In this paper, we present forecasting ozone concentration with decision support system. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.817-824
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• 2003

We employed a hierarchical document classification method to classify a massive collection of electronic medical records(EMR) written in both Korean and English. Our experimental system has been learned from 5,000 records of EMR text data and predicted a newly given set of EMR text data over 68% correctly. We expect the accuracy rate can be improved greatly provided a dictionary of medical terms or a suitable medical thesaurus. The classification system might play a key role in some clinical decision support systems and various interpretation systems for clinical data.

• Asia pacific journal of information systems
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• v.14 no.1
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• pp.125-142
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• 2004

Knowledge management has been increasingly recognized as important in business management context. Although knowledge management has been proposed as an enabler to reach competitive advantage, little research has considered applying knowledge to business decision-making activities, which may be the main task of enterprise management. The application of knowledge to decision-making has a more significant impact on organizational performance than mere knowledge management for operational level processing. For this purpose, the present study proposes a decision support loop based on the integration of knowledge by adopting a cognitive modeling approach. The proposed model is then discussed, in the real context of an application case.