• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.864-867
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• 2007

Recent advancement in ICT and IT infrastructure drives the construction industry towards a IT-based industry. Accordingly, the importance of the planning phase of a project is significantly highlighted due to recent large-scale national development projects such as U-city and multifunctional administration city. various development and studies are conducted on the convergence of 3D CAD and GIS in order to support the decision making by simulation of each phase of construction prior to the actual construction of a building. However there has been limits to the implementation of the IT technology in the planning phase due to its characteristics such as high reliability on the experts knowledge and the compliance of the administration work. In this study, a trendy issue of the convergence of the GIS technology with the 3D CAD design data is suggested to improve the efficiency of a decision support in the planning phase.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.

• Information Systems Review
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• v.9 no.3
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• pp.45-65
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• 2007

As digital economy era and knowledge society advent, division of the industry has been indistinctive and complex. This change of business environment has leaded todifficulty in operations of firms consisted of continuous decision making. To develop effective SDSS needs systematic strategic decision making process, efficient problem solving techniques, information of good quality, efficiently information system, and analysis ability of problem solver. This research develop SDSS framework combined strategic decision making process with various problem solving techniques for designing SDSS. Finally, this paper developed the technique recommendation system by selected the criterions of technique assortment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.43-51
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• 2000

Many organizations are currently adjusting the statistical forecasts with qualitative factors. However, so for a few forecasting system with adjustment process have been developed. They have difficulties in managing knowledge and estimating the quantity of adjustment. In this study, the forecasting support system adopting the frame based knowledge representation and containing the decision making scheme for adjustment is proposed to overcome these difficulties. According to the experiments, the proposed system improves the forecasting performance on gasoline case.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.1-1
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• 2017

• Architectural research
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• v.7 no.1
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• pp.11-18
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• 2005

In today's building industry the emphasis has been geared more towards construction, thus building maintenance and life cycle have been neglected until now. A direct result of this neglect is the rapid aging of building, which leads to more cost-effective decision making methods for the prolongation of building life span. The following study is conducted in the area of Daegu and Seoul in order to develop the estimation analysis method of the annual operation cost of the Korean high-rise condominiums for the cost-effective decision making support through mathematical and statistical analyses including the present value and standardized measurement corrections. Based on the assumption that the life expectancy of the high rise condominium is 50 years, initial cost is ￦421,212/$m^2$, and a total sum of yearly operation cost during life expectancy is ￦2,154,499//$m^2$), yearly accumulated operation cost is shown as below: $AOC=0.7097t^4-38.803t^3+806.95t^2+11045t-496.52$ ($R^2=0.98$) (Here, AOC = Accumulated Operation Cost, t = given years)

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.72-83
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• 2005

Recall aims to remove the products hazardous to consumers or users from the commerce. However, a recall with a poor decision making procedure could results in disaster to corporations. Therefore, recall managers should establish a proper recall plan in advance to minimize the damage to business. The purpose of the study is to propose a computerized recall management system(RMSys) to handle recall process systematically and timely manners. RMSys, a recall decision-making procedures software, consists of two different modules such as recall decision-making module and recall procedure module. RMSys on the basis of the world wide web is designed to be compatible to ERP(Enterprise Resources Panning). RMSys could play a role as a management support system to help the corporations recall the hazardous products with minimum efforts.

• The Journal of Information Systems
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• v.15 no.1
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• pp.121-144
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• 2006

For constructing the purchasing decision-making model to maximize customer value on the electronic commerce, Means-Ends Network model was used for identifying means and fundamental objectives and their relationships were analyzed by the structural equation. A questionnaire survey of 481 customers in their internet shopping experiences was conducted to extract valid means and fundamental objectives' factors. As a result, 6 means objectives shopping travel, shipping errors, vendor trust, online payment, product choice, and recommender systems and 3 fundamental objectives-shopping convenience, internet ecology, and customer support were founded. Using these 9 factors, structural equation was analyzed 4 times to ensure statistical validities and to establish new interrelationships among them. The results showed that fundamental objectives are affected by the strong relationships within means objectives. This interrelationship with mens and fundamental objectives is interpreted as the purchasing decision-making model to maximize customer value on the electronic commerce in this paper.

• The Journal of Information Systems
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• v.21 no.4
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• pp.109-132
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• 2012

Social Network Analysis is an increasingly important part of a broader 'toolbox' of evaluation methods available to R&D policymakers to support decision-making. The aim of this research is to be an accessible, 'beginner's guide' to social network theory and application in the area of mobile telecommunication research and development (R&D) decision-making. This research suggests the methodology of investigation into new technology, and the methodology suggested by this research is believed to be a meaningful first step toward the establishment of the information analysis structure, which is in desperate need.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.414-422
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• 2022

Presented in this paper is a methodology for combining a Bayesian statistical approach with Data Quality Objectives (a structured decision-making method) to provide increased levels of confidence in analytical data when approaching a waste boundary. Development of sampling and analysis plans for the characterisation of radioactive waste often use a simple, one pass statistical approach as underpinning for the sampling schedule. Using a Bayesian statistical approach introduces the concept of Prior information giving an adaptive sample strategy based on previous knowledge. This aligns more closely with the iterative approach demanded of the most commonly used structured decision-making tool in this area (Data Quality Objectives) and the potential to provide a more fully underpinned justification than the more traditional statistical approach. The approach described has been developed in a UK regulatory context but is translated to a waste stream from the Fukushima Daiichi Nuclear Power Station to demonstrate how the methodology can be applied in this context to support decision making regarding the ultimate disposal option for radioactive waste in a more global context.