• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.87-95
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• 2008

The purpose of this study is to provide a decision support to select an appropriate rapid prototyping(RP) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model for molding, material property, build time and part cost that greatly affect the performance of RP machines. However, the selection of a RP is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate RP machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify RP machines that the users consider. After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of RP machines.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.271-281
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• 2013

In the trend toward globalization, cross-cultural teams in organizations are becoming more and more common. In particular, the influence of China and Western Europe on the global economy is getting increased. With this trend, it is important to understand cross-cultural characteristics for group decision making in managerial environments. This study aims at analyzing cross-cultural differences between China and Western Europe in light of the effect of group discussion in group decision making. An experiment simulating a decision of a car purchase was conducted. A total of 48 subjects (24 Chinese and 24 Western Europeans) assigned in decision groups were asked to judge relative importance ratios of nine factors affecting their purchase decisions using the AHP program developed for the experiment. Three dependent variables (consistency, satisfaction, and consensus) were measured. Chinese were slightly more consistent than Western Europeans in discussion-involved group decision making. In terms of decision satisfaction, Western Europeans were more satisfied with discussion-included decisions than discussion-excluded decisions. Chinese, on the contrary, did not show a significant difference. There was no significant difference between two cultures in decision consensus.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.265-272
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• 2009

Fuzzy number intuitionistic fuzzy sets (FNIFSs), each of which is characterized by a membership function and a non-membership function whose values are trigonometric fuzzy number rather than exact numbers, are a very useful means to describe the decision information in the process of decision making. Wang [10] developed some arithmetic aggregation operators, such as the fuzzy number intuitionistic fuzzy weighted averaging (FIFWA) operator, the fuzzy number intuitionistic fuzzy ordered weighted averaging (FIFOWA) operator and the fuzzy number intuitionistic fuzzy hybrid aggregation (FIFHA) operator. In this paper, based on the FIFHA operator and the FIFWA operator, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as fuzzy number intuitionistic fuzzy decision matrices where each of the elements is characterized by fuzzy number intuitionistic fuzzy numbers, and the information about attribute weights is partially known. An example is used to illustrate the applicability of the proposed approach.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.187-194
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• 2008

Recently, the constructions of widening bridges or new bridges are often undergoing as a part of road widening because traffic volumes are rapidly increasing caused by fast-growing population and urbanization. But in general, there is no rational decision process and specification to justify the validity of the bridge widening. Moreover, there are also numerous events including various uncertainties involved in widening bridges. In this paper, therefore, a decision making model is proposed for widening bridges using decision tree based on quantitative LCC analysis considering a variety of uncertainties for the rational and practical approach to a quantitative decision making for alternatives.

• Journal of the Korean Home Economics Association
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• v.44 no.9
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• pp.51-59
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• 2006

The role of consumer self-confidence is important in consumer's purchase decision. Nevertheless, the use of self-esteem measures might cause misinformation in the specific situation of the marketing-related point of view. In this study, consumer self-confidence was measured by marketing oriented tools to clarify the dimensions of consumer self-confidence while the influence of consumer self-confidence on clothing satisfaction was also investigated. A total of 325 questionnaires were collected by surveying university students in Seoul and the surrounding metropolitan area using convenient sampling. The data were analysed by factor analysis, ANOVA, t-test, and regression by using SPSSWIN program. The findings of the study were as fellows. First, the consumer self-confidence was composed of 6 sub-scales: information acquisition, personal outcomes decision making, social outcomes decision making, consideration-set formation, persuasion knowledge, and marketplace interfaces. Second, female subjects rated higher on consumer self-confidence than male subjects did in social outcomes decision making and consideration-set formation. Third, higher income was correlated with higher social outcomes decision making and consideration-set formation. Finally, clothing satisfaction was influenced by personal outcomes decision making and information acquisition.

• The Korean Journal of Financial Management
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• v.1 no.1
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• pp.1-27
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• 1985

One of the most important research works in modern business enterpise is the relation between the purpose of business enterprise and decision making behavior of manager. It is because the coincidence of the former and the latter is considered an ideal type in evaluating the result of business management. Here I have set up assumptions in order to solve the above statements: (1) What purpose does the modern business enterprise set up and what kind of economic background does it have? (2) What is the theory of maximization of stock value among the purposes of business enterprise? (3) What kind of decision making do we do in the maximization of stock value in busiess administration? (4) How is the behavior of business financial manager's intention and decision made? The result pursued under the above assumptions shows that business manager's behavior of decision making is affected according to the degree that he gets some information, but basically is determined in consideration of his autonomous standpoint, namely the stability of business enterprise and the stability of manager himself while he faithfully performs his duty which is entrusted by stockholders. Therefore we come to the conclusion that there is a little gap between a manager's behavior of decision-making and the purpose of stock value maximization.

• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.367-376
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• 2009

This paper proposes an application methodology of AHP(Analytic Hierarchy Process) based decision making theory for improvement priority by assessment of various risk factors affecting on deterioration of water supply systems, as major social infrastructure. AHP method is organized with three level of hierarchy which is introduced for multi-criteria decision making in this study. In the first level, assessment outputs are calculated by AHP for each affecting factor. In the second level, criteria are estimated by using assessment results with respect to structural and environmental factors. Consequently, ranking decision is performed in the third level. In order to present the effectiveness, a proposed method is compared with FCP(Fuzzy Composite Programming) for decision making. Since the results of the proposed method show better performance with consistent results, it can be applied as an efficient information for the determination for improvement priority of the study infrastructure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.175-183
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• 2012

The purpose of this study is to investigate the relationships between institutional pressures and IT investment decision making of management. To analyze the proposed model, we distribute survey questionnaires to mid-size IT firms and collect data from them. Furthermore, the proposed model was tested by PLS(Partial Least Squares) technique. We found that coercive pressure and normative pressure have an effect on mimetic pressure. However, these two pressures do not influence the IT investment decision making. The mimetic pressure has an effect on the IT investment decision making. The conclusions and implications are discussed.