• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.3-12
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• 2021

In the remodeling projects, clients without architectural expertise have limitations in presenting requirements accurately. In some cases, designers and contractors may not recognize their demands exactly, and deliver final products that are different from the clients' intentions. 3D modeling visualizing final products in previous has been regarded as a solution to enhance understanding and communication. However, this approach has the limitation that the final results are presented as a virtual outputs. In the remodeling project, an alternative, mixed-reality, is likely to reinforce the reality as it enables to present remain structure and the parts to be built together. This paper examines the mixed reality as a solution to support decision making of clients and practitioners in remodeling projects. The examinations is conducted in high-rise office remodeling projects by means of action-research. Clients and practitioners, overview product models presented in the format of 2D drawings, BIM and mixed reality asked to evaluate the effectiveness of each methods in 12 standards. The results have shown that mixed reality has improved the sense of reality, making it easier to predict results, but recognizing patterns is difficult in some areas such as the floor, and it caused dizziness.

• Health Policy and Management
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• v.19 no.4
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• pp.98-120
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• 2009

The purpose of this study is to elicit preference for drug listing decision criteria and to estimate the ICER threshold in South Korea using the discrete choice experiment (DCE) method. To collect the data, a DCE survey was administered to a subject sample either educated in the principle concepts of pharmacoeconomics or were decision makers within that field. Subjects chose between alternative drug profiles differing in four attributes: ICER, uncertainty, budget impact and severity of disease. The orthogonal and balanced designs were determined through computer algorithm to take the optimal set of drug profiles. The survey employed 15 hypothetical choice sets. A random effect probit model was used to analyze the relative importance of attributes and the probabilities of a recommendation response. Parameter estimates from the models indicated that three attributes (ICER, Impact, Severity of disease) influenced respondents' choice significantly(p${\pm}$0.001). In addition, each parameter displayed an expected sign. The Lower the ICER, the higher the probability of choosing that alternative. Respondents also preferred low levels of uncertainty and smaller impact on health service budget. They were also more likely to choose drugs for serious diseases rather than mild or moderate ones. Uncertainty however is not statistically significant. The ICER threshold, at which the probability of a recommendation was 0.5, was 29,000,000 KW/QALY in expert group and 46,500,000 KW/QALY in industry group. We also found that those in our sample were willing to accept high ICER to get medication for severe diseases. This study demonstrates that the cost-effectiveness, budget impact and severity of disease are the main reimbursement decision criteria in South Korea, and that DCE can be a useful tool in analyzing the decision making process where a variety of factors are considered and prioritized.

• The Journal of Information Systems
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• v.29 no.2
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• pp.287-306
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• 2020

Purpose Youth unemployment is a social problem that continues to emerge in Korea. In this study, we create a model that predicts the employment of college graduates using decision tree, random forest and artificial neural network among machine learning techniques and compare the performance between each model through prediction results. Design/methodology/approach In this study, the data processing was performed, including the acquisition of the college graduates' vocational path survey data first, then the selection of independent variables and setting up dependent variables. We use R to create decision tree, random forest, and artificial neural network models and predicted whether college graduates were employed through each model. And at the end, the performance of each model was compared and evaluated. Findings The results showed that the random forest model had the highest performance, and the artificial neural network model had a narrow difference in performance than the decision tree model. In the decision-making tree model, key nodes were selected as to whether they receive economic support from their families, major affiliates, the route of obtaining information for jobs at universities, the importance of working income when choosing jobs and the location of graduation universities. Identifying the importance of variables in the random forest model, whether they receive economic support from their families as important variables, majors, the route to obtaining job information, the degree of irritating feelings for a month, and the location of the graduating university were selected.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.101-107
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• 2022

Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.

• Korean Business Review
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• v.4
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• pp.355-383
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• 1991

1. The Purpose of This study research: The focus of marketing until recently has simply been on sales which means the transfer of goods from the producer to the consumer and on profits therefrom. However, the excess supply of goods due to the expansion of the economy and the resulting fierce competition between companies have changed the nature of marketing. Maximizing consumers' satisfaction and establishing marketing mix strategies for market subdivision and penetration into the target market are now significant roles of the marketing manager. In addition, with regard to company management, information within the company which had been collected, managed and processed sporadically indegrated manner. The purpose of this research on marketing information systems in connection with the above will be to seek ways enabling us to create an efficient and integrated information system for an entire company. 2. The Method and Scop of This Stdudy: Marketing information systems, as a part of management information systems, shall be examined based on relevant theoretical literature. The research process shall be generally developed as follows: 1) The basic structure of the marketing information systems, including its fundamental purpose and necessity, shall be examined. 2) The method for a specific plan shall be presented through fundamental marketing strategy concepts and marketing decision-making. 3) A general model shall be presented based on examinations of various mod els used for marketing information systems and on research of the models' relationship with management information systems. 4) The direction of development shall be presented as the basis for gradual development following examination of the scope, pertinent issues, and means of improvement of the marketing information systems. 3. Summary and Conclusion: As the competition among the enterprises has become keen and thus the management of the contemporary enterprises shows the tendencies of uncertainty as well as complexity, all the managers must make the correct and prompt decision of their mind. Otherwise, the danger which will lead to and failure in the failure in the business may befall to the enterprise. Though computer system and information related techniques have the endless potentiality for the improvement of the enterprise, those are granted only to the enterprise which will be able to manage the computer system and information related techniques. In the contemporary industrial society, the need to a managerial information system has been increasing because all the complicated information can be stored, disposed and managed by the efficient method. And the marketing information system is also the integrated system which has been formed and developed through the efficient mixture of all the constituent elements including the definition of marketing research as the definition of the information system has been enlarged due to the reason shown above. The common point of the two systems is the man machine system functioning to help the efficient decision of the mind by introducing the computer system on the basis of user manager centered thought in order to provide informations to be useful in operation and management of the organization and the function of the mind decision. The purpose for the marketing information system lies in making the utmost use of marketing information available in the course of the mind decision. The reason why the contemporary enterprises necessitate the marketing information system are as follows: 1) The stages of the business operation are expanded wide to the world. 2) As the living standards of the consumers have been on the rise, the enter prise has to satisfy the consumer's "wants" than simple "needs".

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.190-204
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• 2008

Recently, it has been strongly required to establish a systematic and sustainable performance investigation and evaluation framework on governmental funding projects for IT small and medium-sized enterprises. In this paper, Data Envelopment Analysis (DEA) models are adopted for performance evaluation on governmental funding projects for IT small and medium-sized enterprises. A new data structure is proposed for the DEA performance evaluation. Generally, in using DEA models, DEA multipliers restriction is critical to achieve the reliability of DEA optimal solutions. Based on the outputs and inputs considered in this study, Acceptance Region (AR) constraints are generated and incorporated into the DEA models so as to improve the reliability of DEA efficiency scores. Associated with AR Type I (AR-I), AR Global Model (ARGM) constraints, DEA/ (AR-I, ARGM) models are designed and then sensitivity analysis follows investigating the robustness of DEA efficiency scores relating to AR constraints adjustment. Finally, a performance evaluation is illustrated regarding governmental direct funding projects from Ministry of Information and Communication (MIC) in Korea where each project unit (i.e. Decision Making Unit (DMU)) is determined whether it is efficient or not. By using DEA/(AR-I, ARGM) models designed in this paper, robustly efficient DMUs are gradually identified according to the successive AR constraints adjustment. Among 25 DMUs, results show that 6 DMUs such as B, E, G, Q, S, Y are determined as robustly efficient against AR constraints intermediate adjustment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.57-65
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• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• Journal of Korean Society of Water and Wastewater
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• v.24 no.2
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• pp.183-193
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• 2010

Well planned rehabilitation order of pipes is essential for efficient maintenance and management of Water Distribution Systems. In this study, not only deterioration rate of pipes but also structural and nonstructural failure which causes abnormal condition of WDS is considered to determine rehabilitation order. Probabilistic Neural Network is used for calculating deterioration rate at present and the importance of pipes is computed under structural and nonstructural failure by using Pipe by Pipe Failure Analysis and Effect Index. Utopian Approach, one of the Multi-Criteria Decision Making methods, is used for assessment of final rehabilitation order based on distance measure between utopian point and alternative one. Developed model in this study shows that it gives more reliable results than existing methods considering hydraulic relative importance does in application to real networks. In this point, the newly developed model, which gives advantages over existing models, can make a credible decision and simple application.

• Asian Journal of Business Environment
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• v.8 no.4
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• pp.5-15
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• 2018

Purpose - The research aimed to reveal real decisional behavioral of management institutes in India for social media marketing usage, and analyses of empirical elements of social media consumption pattern. Research design, data, and methodology - The investigation was based around a research methodology using quantitative analysis with appropriate statistical techniques on random surveys of consumers, detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model and multiple regression employed using R studio edition to validate the reliability of the developed models. Results - A new conceptual framework is proposed - the management institutions decision model, providing a tool for effective and more focused decision-making strategies for developing better utilization techniques for social media. Management institutions have different requirements based upon objectives and resources available. The evidence suggests that the administrators need to be more aware of consumer indicators when targeting and designing social media marketing strategy. Conclusions - The research was based on samples and not the entire population of target consumers, providing limitations. As an inferential statistical method was chosen, the results might be susceptible to inaccuracy. The model developed from different age users, thereby providing rich perspectives into social media usage pattern.