• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.250-251
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• 2021

A subcontract work order is the basis of the construction process and consists of the root and trunk of the construction industry. The construction process through a subcontract work order is an important element of project success, and it is the basic unit of creating profit in the construction industry. Therefore, correct analysis and forecasting of subcontract work orders allow correct estimation of construction cost and profit which is the foundation of corporate decision making. This study has started to provide predictions of subcontractor's bidding-ratio for decision-making. Since the actual project data has been used in this study, the contribution level of the model is highly expected in actual field. The statistical confidential level of adjusted decision coefficient is concluded low because of limited sample numbers. However, its accuracy and confidence level can be increased through increasing sample numbers, considering more variables, and studying of reducing error.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.83-89
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• 2015

Selection of efficient supplier is a very important process as risk or uncertainty of a supply chain and its environment are increasing. Previous deterministic DEA and probabilistic DEAs are very limited to handle various types of risk and uncertainty. In this paper, I propose an improved probabilistic DEA which consists of two steps; Monte Carlo simulation and statistical decision making. The simulation results show that the proposed method is proper to distinguish supplier's performance and provide statistical decision background.

• Journal of applied mathematics & informatics
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• v.40 no.3_4
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• pp.563-575
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• 2022

Many organizations seek statistical modelling facilitated by data analytics technologies for determining the prediction models associated with M&A (Merger and Acquisition). By combining these data analytics tool alongside with data collection approaches aids organizations towards M&A decision making, followed by achieving profitable insights as well. It promotes for better visibility, overall improvements and effective negotiation strategies for post-M&A integration. This paper explores on the impact of pre and post integration of M&A in a standard organizational setting via devising a suitable statistical model via employing techniques such as Naïve Bayes, K-nearest neighbour (KNN), and Decision Tree & Support Vector Machine (SVM).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.931-939
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• 2003

This paper is aimed at proposing a new framework to predict decision performance, by Investigating decision maker's cognitive resonance. We assume that every decision maker has two kinds of schema­emotional schema and rational schema. Cognitive resonance is believed to have a close relationship with the two schemata and decision performance. In literature on decision performance there is no study' seeking relationship among the two schemata ana cognitive resonance. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among two schemata, cognitive resonance, and decision Performance, and (2) to empirically prove its validity applying to. Internet shopping Situation. Based on the questionnaires from 13S- respondents, we used a second order confirmatory factor analysis (CFA) to extract valid constructs, and structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. Experimental results supported our research model with some further research issues.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.951-970
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• 2015

The purpose of this study is to explore related variables to influence gifted college students' career conviction and to propose a structural model. For the study, 292 college students who have experienced university affiliated gifted education program during their school days. Rational decision making test, intrinsic motivation test, career decision efficacy test, and major conviction test were utilized. SPSS program and AMOS were used for statistical analyses. The results are summarized as follows. The fit of measurement model was found to be TLI=.923, CFI=.951, RMSEA=.077, indicating most of the fit indexes were acceptable. The path to career conviction from rational decision making and intrinsic motivation was found to be insignificant, suggesting a revised model. The fit of final revised measurement model was found to be TLI =.926, CFI=.951, RMSEA=.075, indicating the model was acceptable. Interestingly, the career decision efficacy was found to be the complete mediator among the rational decision making, intrinsic motivation, and career conviction. The results of the study showed that career decision efficacy has a very important role in gifted college students'career choice and decision. Implication of the study related to the career education and counseling has been discussed in depth.

• 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.

• The Journal of Information Systems
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• v.18 no.3
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• pp.135-154
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• 2009

As the knowledge is recognized as a core factor of organization's competitiveness and creation of value added, the importance of knowledge management is also increased. To achieve the successful knowledge management, it is important to establish strategy that consider essential purpose of knowledge management such as creating and sharing of knowledge resource, improving performance, and continuing organizational innovation within the organization and influence factor inside and outside of organization. Until now, however, the research for knowledge management strategy was mostly limited to the statistical analysis based on the unilinear causality model, and systematic access and analysis that consider interaction and feedback structure between factors. In this paper, we developed the novel decision-making framework for successful strategy establishment by applying the analytic network process(ANP). Specifically. we derive clusters and components to decide the interaction and feedback structure between the elements of knowledge management by literature studies. And we produced relative importance and preference of clusters, components and alternatives dealing with feedback structure through the survey of experts in the field or related one of knowledge management. In result of this study, we expect that it will help the knowledge officer to decide establishing knowledge management strategy.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.33 no.12
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• pp.13-18
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• 2017

Recently, the form of traditional families has been disintegrated due to low birthrate, aging, declining marriage, individualism, etc. In particular, the number of single households has increased due to the shift to a low-growth advanced economic structure, women's social participation, diversification of lifestyles, and so on. According to the National Statistical Office, the number of single households living alone by 2015 is estimated to be about 5,060,000 households, which is estimated to account for 34.3% of all households, which has greatly increased compared with about 660,000 (6.9%) in 1985. However, the housing market has not been able to respond to such social changes. Therefore, in this research, we presented a plan to visualize the public data of single household in Seoul city and prediction result of occupancy shape for the purpose of supporting decision making of single household consumers.

• 대한공업교육학회지
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• v.43 no.1
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• pp.20-40
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• 2018

This study examined resilience and career decision-making among specialized technical high school students with the aim of proposing preliminary data to suggest ways to improve self-efficacy in career decision-making through establishing proper resilience. The specific research questions were set as; first, to define the resilience status in relation to the students' personal characteristics among students; second, to describe the status of self-efficacy in career decision-making related to the students' personal characteristics among students; and last, to examine the influence of resilience on self-efficacy in career decision-making among specialized technical high school students. To accomplish such research objectives, the assessment survey was developed after reviewing the theoretical literature on specialized technical high school students' background, ego identity, and self-efficacy in career decision-making. The survey was comprised of 54 items including personal characteristics (3 items), resilience (27 items), and self-efficacy in career decision-making (24 items). A total of 990 students from industrial specialized high schools across the country completed the survey, and the responses from 775 students were used for the final analyses after excluding the surveys with unanswered items or untrustworthy responses. Results were as follows: The group with higher levels of school adaptation and satisfaction showed higher resilience and career decision-making than those with lower levels of school adaptation and satisfaction. Furthermore, for the influence of resilience on self-efficacy in career decision-making, the results showed that resilience had positive associations with self-efficacy in career decision-making, and all correlations and coefficients of determination showed a robust statistical significance. Therefore, to enhance self-efficacy in career decision-making, education that could help students better adapt to school, increase satisfaction with the school, and create positive resilience must precede.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.145-154
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• 1995

Empirical Bayes approach is applied to estimation of the binomial parameter when there is a cost for observations. Both the sample size and the decision rule for estimating the parameter are determined stochastically by the data, making the result more useful in applications. Our empirical Bayes problems with non-iid components are compared to the usual empirical Bayes problems with iid components. The asymptotic optimal procedure with a computer simulation is given.