• 대한안전경영과학회지
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• 제3권2호
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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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• 제20권4호
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• pp.615-627
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• 2009

본 연구의 목적은 효과적인 마케팅전략 수립에 도움이 되는 정보를 제공하는 데 있다. 이를 위하여 화장품구매 자료로부터 고객 구매형태와 재구매 간의 관계를 분석하여 고객충성도 예측모형을 개발하였다. 고객충성도는 재구매 가능성으로 측정하였다. 본 연구에서 사용된 자료는 국내의 한 화장품회사 고객들의 2000년부터 2008년까지 9년간의 구매자료 (432,528명, 2,440,107건)이다. 예측모형의 목표변수는 재구매 유무이고, 설명변수는 구매수량, 구매액, 휴면기간 등의 기본변수와 구매횟수와 거래 일자를 이용한 가공변수들이다. 충성도 예측모형은 데이터마이닝 기법인 로지스틱회귀, 의사결정나무 및 신경망모형을 사용하였다. 예측모형평가의 측도로는 하이드게 점수를 사용하였으며, 최대의 하이드게 점수를 가지는 분계점을 선택하였다. 각예측모형에서 선택된 변수는 유사하며, 모형비교 결과 세 모형의 효율과 평가측도의 차이는 크지 않았다. 정분류율이 다소 높고 해석과 활용이 쉬운 의사결정나무모형을 최종모형으로 선택했다.

• 응용통계연구
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• 제23권6호
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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.

• 산업경영시스템학회지
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• 제38권1호
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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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• 제40권3_4호
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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).

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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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.

• 복식문화연구
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• 제22권5호
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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.

• 대한안전경영과학회지
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• 제4권3호
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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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• 제20권1호
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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.

• 한국멀티미디어학회논문지
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• 제6권1호
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• pp.67-77
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• 2003

멀티미디어에 삽입된 워터마크의 검출은 저작권 보호 및 인증 분야에서 매우 중요한 역할을 한다. 최근 워터마크의 검출에 많이 사용되는 유사도 기반 알고리즘은 대상 영상의 분포 특성을 이용하지 않기 때문에 검출 성능이 떨어지는 단점을 가진다. 따라서 본 논문에서는 웨이블릿 변환 영역에서 효율적인 워터마크 검출 알고리즘을 제안하였다. 제안한 워터마크 검출 알고리즘은 통계적 판정법에 근거하여 Bayes판정 이론, Neyman-Pearson 정리, 및 웨이블릿 계수들의 분포 모델을 이용한다. 따라서 제안한 검출 알고리즘에서는 주어진 오류 검출 확률에 대하여 간과 검출 확률을 최소화할 수 있는 장점이 있다. 제안한 검출 알고리즘의 성능 평가는 견고성 측면에서 수행되었고, 실험 결과로부터 제안한 알고리즘이 유사도 기반 알고리즘에 비하여 우수한 성능을 나타냄을 확인하였다.