• Journal of Distribution Science
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• v.22 no.2
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• pp.71-82
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• 2024

Purpose: Despite significant research on decision-making, researchers struggle to comprehend the decision-making process. This paper aims to not only examine the relationship between problem-solving skills, cognitive competency, and decision-making but also develop measurement instruments for cognitive competency and problem-solving skills to better model decision-making. Research Design, Methodology and Approach: A cross-sectional study was conducted by surveying 292 university students in HCM City, Vietnam, via email sent randomly by Google Forms. This study identifies the conceptual framework and tests the hypotheses using a deductive approach. The SPSS program was used to evaluate the scales' reliability, and the SmartPLS program was used to assess the measurement and structural models. Results: The results show that the research model better modelled the relationship between problem-solving skills, cognitive competency, and decision-making. Although thinking ability has no direct impact on decision-making, both creativity and problem-solving skills have a positive impact on decision-making. The mediating role of problem-solving skills is also determined by the positive relationship between cognitive competency and decision-making. Conclusions: This study highlights decision-making efficiency through the cognitive process from low to high levels and provides for policymakers and managers to explain the decision-making process in a variety of sectors, such as distribution chains, marketing, and human resource distribution.

• Journal of Engineering Education Research
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• v.21 no.2
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• pp.28-38
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• 2018

This study examined the effects of entrepreneurship education on the career decision of students in the College of Engineering. The purpose of this study was to examine the perceived desirability, perceived feasibility and the career decision - making effects of career decision - making self - efficacy as subjects of entrepreneurship education. This study was carried out by using PLS 3.0 for engineering students in an university. The results of this study are summarized as follows. First, it shows that entrepreneurship education has a positive impact on perceived desirability, perceived feasibility. Second, perceived desirability and perceived feasibility have different effects on career decision making and entrepreneurship intention. Third, career decision self - efficacy affects entrepreneurship intention and career intention in career decision making. The results of this study suggest the importance of entrepreneurship education for career decision making and provide meaningful implications for educators and policy developers.

• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.2
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• pp.210-219
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• 2016

Purpose: The purpose of this study was to contribute to career counseling and career guidance for nursing students by examining students' career decision-making styles and career decision levels and the relationship between self-efficacy and career decision-making styles and career decision levels. Methods: A descriptive survey design was used and data were collected using questionnaires from a sample of 469 nursing students. The data were analyzed using frequencies means, Kruskal-Wallis test, Pearson correlation coefficient, and multiple regression analysis with SPSS 21.0. Results: Career decision level had a significant correlation with self-efficacy and decision-making styles. Self-efficacy (${\beta}=.143$, p<.001), type of decision-making styles rational type (${\beta}=.180$, p<.001), intuitive type (${\beta}=.137$, p<.001), dependent type (${\beta}=-.236$, p<.001) and sex (${\beta}=-.086$, p=.023), school grades (${\beta}=.086$, p=.033), and satisfaction of nursing major (${\beta}=.209$, p<.001) were significant predictors of career decision level. Conclusion: It is necessary to develop effective career support programs according to type of decision-making styles, sex, school grades, motivation to improve nursing students' self-efficacy and satisfaction in the nursing major.

• Asia pacific journal of information systems
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• v.14 no.2
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• pp.37-59
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• 2004

Team decision making is a collective behavior that needs to be understood by considering properties belonging to team and individual member domains together. This paper introduces a conceptual model called "Dual-Level(DL)" model that describes a team decision-making process in terms of team level, member level, and the relationship between them. The team-level view explains the decision-making process by considering the team as a wholeand divides the process into three stages: Problem Conceptualization, Alternative Generation, and Selection. The member-level view describes what happens to individual members when they go through the group process and splits it into the five phases: Individual Cognitive Mapping, Problem Decomposition, Subproblem Session, Subproblem Integration, and Team Decision. The DL model works as a theoretical framework to explore team decision making by using a set of computational models of team design and team members. In practice, the conceptual framework is used to build a computational model of decision making team, called "Team-Soar."

• Asia pacific journal of information systems
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• v.4 no.1
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• pp.74-114
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• 1994

In spite of the importance of group decision making in corporations and recent active research efforts in group decision support systems in the US., few studies have been done in the area of group decision making in Korea. There is an urgent need to understand the behavior and peculiar characteristics of group decision making in Korea before we initiate any research in developing computer systems to help group decision making. This study proposes a model for group decision making based on the literature survey and empirical studies have been conducted using the model Although this study is exploratory in nature, tentative hypotheses are given for future research in group decision making.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2942-2960
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• 2022

The core of cognitive radio is the problem concerning intelligent decision-making for communication parameters, the objective of which is to find the most appropriate parameter configuration to optimize transmission performance. The current algorithms have the disadvantages of high dependence on prior knowledge, large amount of calculation, and high complexity. We propose a new decision-making model by making full use of the interactivity of reinforcement learning (RL) and applying the Q-learning algorithm. By simplifying the decision-making process, we avoid large-scale RL, reduce complexity and improve timeliness. The proposed model is able to find the optimal waveform parameter configuration for the communication system in complex channels without prior knowledge. Moreover, this model is more flexible than previous decision-making models. The simulation results demonstrate the effectiveness of our model. The model not only exhibits better decision-making performance in the AWGN channels than the traditional method, but also make reasonable decisions in the fading channels.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.493-493
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• 2000

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of database. The two values (on-off) decision making method without transition had been proposed by one of the author in a previous work for a purpose of realizing human on-off decision making. The current method is an extension of the previous on-off decision making. By combining the conditional probability and the transitional probability, the closed form of the algorithm for the multi-valued transitional decision making was derived. The proposed multi-valued decision making was successfully applied to the determination of the five levels of the vigilance of a subject during the EEG recording; awake stage, drowsy stage and sleeping stages (stage 1, stage 2/3, REM (rapid eye movement)). The method for determining the vigilance level can be directly usable for the two purposes; selection of awake EEG segments for automatic EEG interpretation, and determination of sleep stages through sleep EEG. The proposed multi-valued decision making with a mathematical background of the probability can be applicable widely, in industries and in medical fields for purposes of the multi-valued decision making.

• Journal of the Korean Home Economics Association
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• v.24 no.4
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• pp.163-177
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• 1986

The purpose of this study is to present basic data of clarifying the differences between employed and unemployed wives' family and comparing low classes with other classes for the more reasonable and successful home administration through investigating and analyzing decision-making patterns of the families of working women in the low income group. The questionnaires were distributed in September 1984 to 300 working women in the city of Seoul and Sung-Nam. Statistical methods such as frequency, percentage and the mean value were used for grasping general characteristics of the families and F-test, Pearson's Correlations were used for investigating the interrelation of the related variables. The results of this study were as follows; 1) Wife's participation indecision-making was increased while joint decision-making was decreased compared with those of unemployed wives' family and other classes. 2) Both of the degree of conjugal participation in decision-making and joint decision-making were influenced by wife's educational level, disparity in educations of couple, husbands' occupation, family income, wife's age. But duration of marriage affected only the degree of joint decision-making. Especially family income and husbands; occupations turned to be important variables in low income families. 3) In case of wife's satisfaction with her occupation, joint decision-making was well achieved or not according to certain decision items. Though wife and husband satisfied with their marriage, joint decision-making was not well performed in working wives' family with low income.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1117-1123
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• 2009

Compared with other industries, the construction Industry has many parties(A/E/C) as well as many types of construction activities. Especially, as for the remodeling project, the owner group the remodeling union consists of various stakeholders union and requiring the additional activities of demolition except for the existing new building construction project. Like this, the remodeling project has its own characteristics different from a new building construction project. As for the remodeling project, the Owner's decision making for a remodeling alternative has to be preceded, and other parties are required to propose a remodeling alternative which satisfies the Owner's requirements. However, because of time constraints, many types of problems occur during the decision-making process. In consideration of this, in this research, the authors would like to suggest a decision-making support system to help the Owner's decision-making in the early stage of a remodeling project. For this paper purpose of a remodeling decision-making framework based on Building Information Modeling(BIM) was suggested to help with the Owner's decision-making for each remodeling item and the decision-making support system was evaluated through Case Study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.109-122
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• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.