• Journal of The Korean Association of Information Education
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• v.9 no.2
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• pp.167-176
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• 2005

It has been an important agenda to acquire effective decision making procedure for various issues occurred in education area. As an example, when it comes for the ministry of education to make a decision on such an issue that proper investment, to enhance information of education area, in national wide elementary schools, an effective decision making procedure will aid to establish right way of investment. Currently, the questionnaires gathered from school teachers or the related professional consultants are the only resources in order for making such a critical and important decision. Recently, however, educational, medical, and financial industries are looking forward the best decision making method integrated with rapidly upgraded modern IT technologies using the various resources and tools which they already possess. With this subject in mind, in this paper we present a generic decision making model applying ADALINE neural network. The model can be easily adapted to various problems arising in education area. We proved the model through simulations with realistic sample data.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.515-520
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• 2004

Manufacturing Production System (MPS) has been widely accepted in construction area for the productivity improvement. However, the MPS does not always provide cost and time saving. It often caused more delays and increased project cost. Therefore the use of the MPS technique, systematic decision-making process is needed by reviewing various project parameters such as cost and time. This study includes extensive literature reviews and case studies on MPS. As a result, a decision-making model is proposed. The decision-making flowchart and decision-making model are developed in three steps: (1) identification and categorization of decision-making factors; (2) calculations of benefits, cost, and duration in accordance with the location and the production capacity of the factory; (3) comparisons of MPS and on-site assembly by varying the locations and sizes of the factory

• 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 Korea Convergence Society
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• v.10 no.11
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• pp.117-124
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• 2019

Recently, medical IT solutions are being provided on a distributed environment basis. In Korea, the necessity of developing a clinical decision support system that can share medical information in a distributed environment has been recognized and studied. The existing clinical decision support system is being built using only medical information of its own within the hospital. This makes it difficult for existing systems to achieve good results in terms of efficiency and accuracy of decision support. In order to solve these limitations, this paper proposes a design and implementation method of clinical decision support system based on common data model in medical field. To explain the application process of the proposed model, we describe the development scenario of the clinical decision support system for the diagnosis of colorectal cancer. We also propose the essential requirements for the development of successful clinical decision support systems. Through this, it is expected that it will be possible to develop clinical decision support system that can be used in various hospitals and improve the efficiency and accuracy of the system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.109-122
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• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.65-69
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• 2003

As complex mathematical models are increasingly adopted for business decision-making, difficulties arise in reusing solvers (i.e., model solving algorithms) against diverse models and data sets and thus the collaboration among users (model/solver builders and decision makers) in multiple departments becomes very difficult. To facilitate the solver reuse, this paper adopts the Web services technologies as the base technologies for linking the solvers to the models, both of which are created on different modeling paradigms and different system platforms, in unified system architecture. Specifically, this paper focuses on designing an ontology that represents the interfacing semantics of the model-solver interactions in a general and standardized form. By referring to the ontology, a model management system (MMS) can autonomously suggest a set of compatible solvers and apply them to individual models even though the decision makers are not knowledgeable enough about all the details of the models and the solvers. Thus, this Web services based MMS would improve the reusability of the solvers by relieving the decision makers from the risk of erroneous application of a solver to syntactically and semantically incompatible models and the burden of considerable understanding of model and solver semantics.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.5
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• pp.606-617
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• 2002

The purpose of this study is to develop a decision model that helps manufacturers and retailers determine the optimal timing of markdown in order to maximize their profit. An optimal timing decision model was developed based on three steps; conjoint measurement, scenario analysis and simulation. Data were collected from the sample of 149 out of 170 undergraduate and graduate students in Seoul in 1997. From the Jeans market, 8 brands; Levi's, lee, Guess, Calvin Klein, Pintos, Get used, MFG, and Basic, were selected as competitors for this study. In the conjoint measurement, respondents estimated the level of preference, from 1 to 100, for each item in which brand, price, style, and colors were used to explain product characteristics. Then, in order to reflect competitive situation in Jeans market, four types of scenarios were developed. In each scenario, simulations were applied to decide optimal timing of markdowns that leads to maximal profitability and sales volume. The profit was calculated based on the equation; Profit = Jean's market volume x market share of each brand - cost, where market volume was obtained by integral calculus for market utility function, and market share by logit value of part-worth from the conjoint analysis. For the purpose of the parsimony of the research, costs and the level of markdown were fixed to 30% of the regular price. In results, the optimal timing decision model identified 3 different types of brands. The brands that do not need to take markdown were Ievi's, MFG, and Basic Jeans characterized by the highest brand power and the highest price zone. The brands that needed to take early markdowns were Guess, Lee, Calvin Klein, and Get Used with the intermediate level of brand power and price. The brand that need late markdown was Pintos with the weakest brand power among the competitors and the lowest price. The optimal range of markdown remains for further research.

• The Journal of Information Systems
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• v.29 no.1
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• pp.93-111
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• 2020

Purpose The purpose of this paper is to observe the relative priorities of importances among the modified versions of Block chain system, being based on AHP decision support model which should be also proposed in this paper. Design/methodology/approach Four versions modified from the beginning of Block chain were divided into Public& Permissionless, Private&Permissionless, Public&Permissioned and Private&Permissioned types. Five criteria for evaluating the four versions whether the version were suitable for Medical information system were introduced from five factors of Technologies Accept Model, which were Security, Availability, Variety, Reliability and Economical efficiency. We designed Decision support model based on AHP which would select the best alternative version suitable for introducing the Block chain technology into the medical information systems. We established the objective of the AHP model into finding the best choice among the four modified versions. First low layer of the model contains the five factors which consisted of Security, Availability, Variety, Reliability and Economical efficiency. Second low layer of the model contains the four modified versions which consisted Public&Permissionless, Private&Permissionless, Public&Permissioned and Private& Permissioned types. The structural questionnaire based on the AHP decision support model was designed and used to survey experts of medical areas. The collected data by the question investigation was analyzed by AHP analysis technique. Findings The importance priority of Security was highest among five factors of Technologies Accept Mode in the first layer. The importance priority of Private&Permissioned type was highest among four modified versions of Block chain technologies in second low layer. The second importance priority was Private&Permissionless type. The strong point of Private&Permissioned type is to be able to protect personal information and have faster processing speeds. The advantage of Private& Permissionless type is to be also able to protect personal information as well as from forging and altering transaction data. We recognized that it should be necessary to develop new Block chain technologies that would enable to have faster processing speeds as well as from forging and altering transaction data.

• IE interfaces
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• v.13 no.1
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• pp.17-28
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• 2000

As knowledge has been recognized as a new resource in gaining organizational competitiveness, Knowledge Management (KM) is suggested as a method to manage and apply knowledge for business management. KM research, however, has focused on identifying, storing, and distributing the transaction-related knowledge in an organization. There has been little research on applying the knowledge to decision-making or strategy development that is the main task of business management. The application of knowledge to decision making has higher impact on organizational performance rather than just the knowledge management for process transaction. In this research, we suggest System Dynamics (SD) for the knowledge-based decision-making. Based on the modeling method of SD, we can translate partial and implicit knowledge resident in individual's mental model into organized explicit knowledge. The simulation test of the organized knowledge model enables decision-makers to understand the structure of the target problem and its behavior mechanism, which facilitates effective decision-making. We will compare the proposed method and other KM methods and discuss this research based on the application case to a real telecommunication company.

• The Journal of Fisheries Business Administration
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• v.32 no.1
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• pp.81-97
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• 2001

The main objective of this research is to identify the evaluation criteria of the local governments' projects for the fisheries industry development (LGPFID) and to develop the evaluation software prototype applicable to LGPFID. This research does not try to develop the whole evaluation processes and programs for LGPFID, but just to outline the approach to managing LGPFID. The evaluation processes and programs developed in this study is based on the group decision support systems(GDSS), which is a collaborative, system-oriented, and objective system useful in evaluating LGPFID. Specifically the goals of the programs are to : (1) enhance the quality of evaluation process for LGPFID; (2) provide the local government decision makers' and interest groups' access to comprehensive evaluation information; (3) support private-public collaboration in government's decision making. We used analytic hierarchy process model as a group decision making model and programmed the application software prototype with Visual Basic language.