• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.297-308
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• 1994

In the information system, there are many fields that used by decision making support system. Nowadays, the reasons that the need of the decision making system in audit is increased, are as follows. \circled1 The increased of competitiveness in audit environment \circled2 The rapid replenishment of computer hardware and computer system in corporations. The purposes of this study are as follows. \circled1 The connection of Internal management assess results and practical examination. \circled2 In the making of audit opinion, the establish of non-measure and evaluate logic. \circled3 The suggestion of knowledge base structure about the audit task. \circled4 The development of prototype system for the accounting audit expert system. The expected usefulness of accounting audit expert system development are as follows. \circled1 Audit time may be saved \circled2 The consistence of opinion will be increased \circled3 The elevation of audit technique \circled4 The decreased of audit risk \circled5 In the decision making rationlization of accounting information users, it will be proved as usefulness.

• Korean Management Science Review
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• v.9 no.1
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• pp.53-65
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• 1992

Decision Support System(DSS) is an advanced information system concept prevailing since 1980s. It supports managers' decision making activities by providing not only information but decision alternatives. It essentially consists of the components of database, modelbase and dialogue systems. With the development of its databases, POSCO needs a number of modelbases in establishing DSSs in various areas such as production planning and investment. This research particularly focuses on establishment of a mid-and long-range investment DSS and investigates the necessity and the problems of an investment DSS and the decision criteria for investment priority. We (1) propose a modelbase which uses the concepts of Analytic Hierarchy Process(AHP) and Zero-Base Budgeting(ZBB), along with an appropriate scoring method, database and dialogue system to support the investment manager in evaluating investment proposals ; (2) implement the system using relational database management system ; and (3) discuss the results of implementing the investment DSS.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.97-106
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• 2012

In the past, executive managers made a decision based on personal experience and knowledge due to lack of the appropriate and timely information. With the development of information systems and technologies, efficiency and productivity of business operation has been enhanced. In this study, we propose a system design and architecture blue-print related to strategic decision making support system. The proposed system consists of 3 key parts; individual business feasibility test, business portfolio feasibility test, business portfolio management. The three key parts are comprised of 11 components to generate information and knowledge based on various data input from inside and outside of firm. This system is expected to provide objective and reliable output to users. In addition, the proposed strategic decision support system would help respond to a rapidly changing business environment.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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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.

• Asia pacific journal of information systems
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• v.11 no.3
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• pp.127-147
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• 2001

This paper presents an analysis of Korean middle managers' decision-making processes. The sample included the observations of decisions made by 17 groups with 5 to 7 members each. The 5 hour-long, in average, decision processes were analysed by a modified system of Fisher's(1970) Interaction Process Analysis. The results showed that Korean managers followed alternative-focused decision processes, as opposite to value-focused ones. That is, the decision-making groups showed a strong trend to elaborate on alternative generation and evaluation right after the situation analysis. They tended to discuss the objectives of decision and relevant criteria only to resolve conflicts arisen during the evaluation process of alternatives. The analysis also showed that a decision proposition was more frequently followed by negative responses than positive ones and by interpretative evaluations than substantiative ones. The lessons from this study suggest a direction for the development of group decision support systems tailored for Korean cultural characteristics. This study is also meaningful as the first observation and empirical analysis of Korean middle managers' decision-making processes.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.3
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• pp.101-113
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• 2011

The purpose of this study are to develop a SDSS (Spatial Decision Support System) that can incorporate diverse opinions of stakeholders related the designation of protected areas (PA), and to employ the model for the readjustment of the boundary line of the Jirisan National Park of Korea. The SDSS would lead to more rational and less controversial decision-making during the expansion or removal of PA in Korea. Research methods are as follows. Firstly, to select evaluation criteria for SDSS for PA designation by using expert interview and literature survey. Secondly, to measure their preferences on the designation of additional PA or the removal of a part of PA based on the opinions of various stakeholders such as local residents, environmental groups, or public officials. Thirdly, to produce conservation priority maps based on a multi-criteria decision making technique. The SDSS would be used to rational decision making for the expansion of PA or the release of a certain part of PA by reflecting diverse preferences on biodiversity conservation and economic interest of residents. The visualization of conservation priority maps would also increase the efficiency of such decision making processes. The evaluation criteria for the expansion of PA for biodiversity conservation includes vegetation conservation value, wildlife conservation value, and the habitats of key species. The evaluation criteria for the removal of PA includes the proximity to roads and the boundary of PA, land use types, and conservation zoning of the PA. Preference weights are based on data collected from the Jirisan National Park. Both the conservation priority and removal priority maps are based on land parcels so that property rights of all parcels would be correctly represented.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.435-440
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• 2004

Most of our GIS implementation activities have been focussed on the management of urban information in local municipalities. Management of urban facilities has been the major issue of concern and has little role in providing the decision maker with alternatives from which one can analyse and choose the optimum solution. For this reason, the spatial decision support system is in need. Business analysis software is effectively used for site analysis of new stores, customer prospecting and other issues of decision making for business purposes, The same geoprocessing module of business analysis software would be useful if put to use for the management of disaster management especially for storm surge management. Application of the business analysis model for disaster management has been reviewed. Specially in case of storm surge, where quick response is crucial, the spatial decision support system will be most effective.

• Asia pacific journal of information systems
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• v.11 no.2
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• pp.181-203
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• 2001

As the Internet is used extensively, multimedia information becomes more prevailing and accessible. However, legacy decision support systems rarely mention how to put such multimedia contents into practical use for decision making and support. In particular, no proposals have yet been made on how to integrate the decision technologies and multimedia databases in model management systems. Hence, the aim of this paper is to propose a new model management method to integrating decision technologies and an image database management system to create a multimedia decision support. For this purpose, extended ARG and structured modeling techniques are adopted, to represent image contents and mathematical models respectively. A web-based prototype system is presented to illustrate the feasibility and usability of the methodology.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.679-682
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• 1996

The level of informaiton provided by most current EIS systems is not above presentation and reporting. To maximize the effect of EIS, we must increase executives' use-rate. To do so, it is important to provide information really required by the user. In a addition, the decision support funcitons should be provided for strategic decision making. In this paper we propose the methodology for adding the analysis and prediciton functions to the EIS that is, for supporting the decision making with the system. Finally, we present a pilot system based on the proposed methodology.

• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.