• Journal of the Korea Safety Management & Science
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• v.3 no.2
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• pp.133-144
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• 2001

This article deals with the multiple alternative proposal of Strategy. when Decision makers meet a very complex and important problems to take a good choice. It might not be easy that we make a decision and accept the decision as an exact result of analysis at a complication and uncertain situation. Although the decision under unpredictable state is many existence and each field is classified to support it. he can not provide exact estimations and be able to specify a result and forecasting. This is the reason why the original research use Statistical Survey method and Visual Decision Making Process(VDMP) to improve decision analysis method. Therefore, Our research suggests that the VDMP utilized in the strategic decision making situation as a group decision adding tool, can be applied in the development of a process vision and implementation plan. as a result, researcher describe step by step the process of VDMP.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.615-627
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• 2009

In micro marketing promotion, it is important to know the behavior of customers. In this study we are interested in the forecasting of repurchase of customers from customers' behavior. By analyzing the cosmetic transaction data we derive some variables which play an important role in the knowledge of the customers' behavior and in the modeling of repurchase. As modeling tools we use the decision tree, logistic regression and neural network model. Finally we decide to use the decision tree as a final model since it yields the smallest RASE (root average squared error) and the greatest correct classification rate.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1191-1199
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• 2010

Knowing what factors into a player's ability to affect the outcome of a sports game is crucial. This knowledge helps determine the relative degree of contribution by each team member as well as sets appropriate annual salaries. This study uses statistical analysis to investigate how much the outcome of a professional baseball game is influenced by the records of individual players. We used the Lotte Giants' data on 252 games played between 2007 and 2008 that included environmental data(home or away games and opponents) as well as pitchers' and batters' data. Using a SAS Enterprise Miner, we performed a logistic regression analysis and decision tree analysis on the data. The results obtained through the two analytic methods are compared and discussed.

• 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.

• The Research Journal of the Costume Culture
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• v.22 no.5
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• pp.743-759
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• 2014

The purpose of this study is to identify the antecedents of consumers' decision postponement on purchasing fast fashion brands. Ongoing search behavior, overchoice confusion, and similarity confusion were considered as antecedents. It was hypothesized that ongoing search behavior influences decision postponement both directly and indirectly through overchoice confusion and similarity confusion. Data were gathered by surveying university students in Seoul, using convenience sampling. Three hundred five questionnaires were used in the statistical analysis, which were exploratory factor analysis using SPSS and confirmatory factor analysis and path analysis using AMOS. Factor analysis proved that ongoing search behavior, overchoice confusion, similarity confusion, and decision postponement were uni-dimensions. Tests of the hypothesized path proved that ongoing search behavior influences decision postponement indirectly through overchoice confusion. In addition, similarity confusion influences decision postponement. The results suggest some confusion reduction strategies for marketers of fast fashion brands. Suggestions for future study are also discussed.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.141-156
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• 2002

This article deals with the multiple alternative proposal of Venture Business policy. when Decision makers meet a very complex and important business to take a good choice. It might not be easy that we make a decision and accept the decision as an exact result of analysis at a complication and uncertain situation. This is the reason why the original research use Statistical Survey method and Visual Decision Making Process(VDMP) to improve decision analysis method. Therefore, Our research suggests that the VDMP utilized in the strategic decision making situation as a group decision adding tool, can be applied in the development of a process vision and implementation plan. as a result, researcher describe step by step the process of VDMP

• Journal of the Korean Statistical Society
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• v.20 no.1
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• pp.67-76
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• 1991

The empirical Bayes version involves ″independent″ repetitions(a sequence) of the component decision problem. With the varying sample size possible, these are not identical components. However, we impose the usual assumption that the parameters sequence $\theta$=($\theta$$_1$, $\theta$$_2$, …) consists of independent G-distributed parameters where G is unknown. We assume that G $\in$ g, a known family of distributions. The sample size $N_i$ and the decisin rule $d_i$ for component i of the sequence are determined in an evolutionary way. The sample size $N_1$ and the decision rule $d_1$$\in$ $D_{N1}$ used in the first component are fixed and chosen in advance. The sample size $N_2$and the decision rule $d_2$ are functions of *see full text($\underline{X}^1$equation omitted), the observations in the first component. In general, $N_i$ is an integer-valued function of *see full text(equation omitted) and, given $N_i$, $d_i$ is a $D_{Ni}$/-valued function of *see full text(equation omitted). The action chosen in the i-th component is *(equation omitted) which hides the display of dependence on *(equation omitted). We construct an empirical Bayes decision rule for estimating normal mean and show that it is asymptotically optimal.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.67-77
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• 2003

Watermark detection has a crucial role in copyright protection and authentication for multimedia Because be the correlation -based algorithm which has widely been used in the watermark detection doesn't utilize the distributional characteristics of cover image to be marked, its performance is not optimum. So a new detection algorithm is proposed which is optimum for multiplicative watermark embedding. By relying on statistical decision method, the proposed method is derived according to the Bayes decision theory. Neyman Pearson criterion, and distribution of wavelet coefficients, thus Permitting to minimize the missed detection probability subject to a given false detection probability The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation -based method.