• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.3
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• pp.304-315
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• 2016

Purpose: The purpose of this study was to explore the relationships of critical thinking disposition (CT), nursing work environment (NWE), and clinical decision making ability among nurses. Methods: A cross-sectional, descriptive study design was conducted on 192 nurses who had worked for more than six months in five general hospitals. A self-reported questionnaire was used to collect data, which included demographics, CT, NWE, and clinical decision making ability. Results: The mean score of CT was 3.5. The highest score was on the objectivity of CT and the lowest on systematicity. The mean score of NWE was 2.3. The highest score was on the collegial nurse-physician relations of NWE and the lowest on the staffing and resource adequacy. The mean score of clinical decision making ability was 3.3. In hierarchical multiple regression, affecting factors on clinical decision making ability were CT and NWE. Conclusion: The findings showed that clinical decision making ability is associated with CT and NWE. To improve clinical decision making ability, it is important to improve CT. In addition, it should be considered to improve NWE where the nurses can make a decision with their job through critical thinking.

• Fashion & Textile Research Journal
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• v.19 no.1
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• pp.19-29
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• 2017

This study identified the purchase decision-making process of outdoor wear consumers and examined the hypothesis that consumer satisfaction mediates the relationship between purchase decision-making process and repurchase intention. Data were acquired from a survey and analyzed with descriptive, factor analysis, reliability analysis and multiple regression analysis. Respondents were 454 adults who have purchased outdoor wear. The results are as follows. First, the purchase decision-making processes of outdoor wear consumers consisted of a series of steps: need recognition & passive information search, active information search, evaluation of alternatives with practical attributes, evaluation of alternatives with unpractical attributes, purchase decision, and post-purchase evaluation. Second, four purchase decision-making processes (except for need recognition & passive information search and active information search) had significantly positive effects on consumer satisfaction. Third, the need recognition & passive information search, the evaluation of alternatives with unpractical attributes and post-purchase evaluation had significantly positive effects on repurchase intention. Lastly, the partial mediation of consumer satisfaction in the relationship between two purchase decision-making processes (evaluation of alternatives with unpractical attributes and post-purchase evaluation) and repurchase intention were indicated. This academic study will help to understand the purchase decision-making processes of outdoor wear and allow companies to obtain information (from the industrial aspect) about which process to invest in and how to manage the process.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.103-129
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• 1998

Corporate level decision making with multiple decision makers in a consistent way is essential in Decision Support System. However, since the decision makers have different interests and knowledge, the models used by them are also different in their level of abstraction. This makes decision makers waste a lot of efforts for an integrated decision making. The purpose of this paper is to propose an integration mechanism so that collaborative decision making models may be used synthetically in multi-abstraction level. Models are classified as multimedia model, mathematical model, qualitative model, causal ＆ directional model, causal model, directional model and relationship model according to the level of abstraction. The proposed integration mechanism consists of model interpretation phase. model transformation phase, and model integration phase. Specifically, the model transformation Phase is divided into (1) model tightening mode which gather information to make a model transformed into upper level model, and (2) model relaxing mode which makes lower level model. In the model integration phase, models of same level are to be integrated schematically. An illustrative M＆A-decision example is given to show the possibility of the methodology.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.229-238
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• 2019

This study examined the relationships among ego resilience, career decision-making self-efficacy and job-seeking stress of senior nursing students. Data was collected through self-reporting questionnaire to 175 nursing students 3rd and 4th grade. Stepwise multiple regression revealed grade, career decision-making self-efficacy, satisfaction on university life to be significant predictors of job-seeking stress. These variables accounted for 13.5% of job-seeking stress. Therefore, it is necessary to reduce the job-seeking stress of senior nursing students through multidisciplinary intervention which strengthens career decision-making self-efficacy considering grade, satisfaction on university life.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.4
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• pp.371-380
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• 2023

Purpose: The purpose of this study is to determine the relationship between nursing students' biomedical and artificial intelligence (AI) ethical awareness, ethical values, professional self-concept, and ethical decision-making confidence, and to then identify factors that can influence their ethical decision-making confidence. Methods: This study employed a descriptive research method and was conducted from June 8 to 12, 2023, with 204 students from three nursing colleges in Korea. The collected data were analyzed by frequency and percentage, independent t-test, Pearson's correlation coefficient, and multiple regression using IBM SPSS 23.0. Results: The results of the multiple regression analysis showed that the regression model was significant (F=18.88, p<.001) and that professional self-concept (β=.46, p<.001), ethics education (β=.23, p<.001), AI ethical awareness (β=.16, p=.020), and relativistic ethical values (β=.14, p=.035) explained 34.6% of the nursing students' ethical decision-making confidence. Conclusion: It is necessary to include professional self-concept, AI ethical awareness, and ethical values contents when constructing the curriculums of educational programs in order to improve nursing students' ethical decision-making confidence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3128-3149
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• 2018

A number of effective methods for multiple-attribute group decision making (MAGDM) with interval-valued intuitionistic fuzzy numbers (IVIFNs) have been proposed in recent years. However, the different methods frequently yield different, even sometimes contradictory, results for the same problem. In this paper a novel criterion to determine the advantages and disadvantages of different methods is proposed. First, the decision-making process is divided into three parts: translation of experts' preferences, aggregation of experts' opinions, and comparison of the alternatives. Experts' preferences aggregation is considered the core step, and the quality of the collective matrix is considered the most important evaluation index for the aggregation methods. Then, methods to calculate the similarity measure, correlation, correlation coefficient, and energy of the intuitionistic fuzzy matrices are proposed, which are employed to evaluate the collective matrix. Thus, the optimal method can be selected by comparing the collective matrices when all the methods yield different results. Finally, a novel approach for aggregating experts' preferences with IVIFN is presented. In this approach, experts' preferences are mapped as points into two-dimensional planes, with the plant growth simulation algorithm (PGSA) being employed to calculate the optimal rally points, which are inversely mapped to IVIFNs to establish the collective matrix. In the study, four different methods are used to address one example problem to illustrate the feasibility and effectiveness of the proposed approach.

• Journal of Korean Academy of Nursing
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• v.37 no.6
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• pp.863-871
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• 2007

Purpose: The purpose of this study was to investigate the factors influencing nurses' clinical decision making focusing on critical thinking disposition. Methods: The subjects of this study consisted of 505 nurses working at one of the general hospitals located in Seoul. Data was collected by a self-administered questionnaire between December 2006 and January 2007. Data was analyzed by one way ANOVA, Pearson correlation coefficients, and stepwise multiple regression using SPSS Win 14.0. Results: The mean scores of critical thinking disposition and clinical decision making were 99.10 and 134.32 respectively. Clinical decision making scores were significantly higher in groups under continuing education, with a master or higher degree, with clinical experience more than 5 years, or with experts. Critical thinking disposition and its subscales have a significant correlation with clinical decision making. Intellectual eagerness/curiosity, prudence, clinical experience, intellectual honesty, self-confidence, and healthy skepticism were important factors influencing clinical decision making(adjusted $R^2=33%$). Conclusion: Results of this study suggest that various strategies such as retaining experienced nurses, encouraging them to continue with education and enhancing critical thinking disposition are warranted for development of clinical decision making.

• Journal of Korean society of Dental Hygiene
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• v.22 no.1
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• pp.73-79
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• 2022

Objectives: This study aimed to analyze the correlation among dental hygiene students' life stress, grit, and career decisionmaking self-efficacy, and to identify the factors influencing career decision-making self-efficacy. Methods: Data were collected through a survey from October 19 to November 7, 2020, targeting 196 students enrolled in dental hygiene departments in Daejeon and Daegu. Life stress, grit, and career decision-making self-efficacy were measured. For data analysis, the descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple regression analysis were performed using SPSS/WIN 24.0. Results: Life stress was 2.12 points, grit was 3.07 points, and career decision-making self-efficacy was 3.43 points. Career decision-making self-efficacy was influenced by satisfaction with the course department, as well as life stress and grit; the most influential factor was found to be grit. These variables could explain career decision-making self-efficacy by 23.8%. Conclusions: For students to advance successfully into society as dental hygienists, a career decision-making self-efficacy promotion program that can help students achieve self-confidence and establish career goals should be developed. additionally, a program that can enhance grit should be included in this development.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.139-144
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• 2008

Generally, real system that is the object of decision-making is very variable and sometimes it lies situations with uncertainty. To solve these problem, it has used statistical methods as significance level, certainty factor, sensitivity analysis and so on. In this paper, we propose a method for fuzzy decision-making based on MFAC(Multiple Fuzzy Alpha Cut) to improve the definiteness of classification results with similarity evaluation. In the proposed method, MFAC is used for extracting multiple a ${\alpha}$-level with proximity degree at proximity relation between relative Hamming distance and max-min method and for minimizing the number of data which are associated with the partition intervals extracted by MFAC. To determine final alternative of decision-making, we compute the weighted value between extracted data by MFAC From the experimental results, we can see the fact that the proposed method is simpler and more definite than classification performance of the conventional methods and determines an alternative efficiently for decision-maker by testing significance of sample data through statistical method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.249-254
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• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.