• Title/Summary/Keyword: Decision Analysis

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Clinical Decision Making Patterns of Pediatric Nurses (아동간호사의 임상적 의사결정 유형에 관한 연구)

  • Hwang, In-Ju
    • Korean Parent-Child Health Journal
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    • v.15 no.1
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    • pp.20-32
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    • 2012
  • Purpose: The purpose of this study was to identify clinical decision making pattern of pediatric nurses and analyze how it shows the differences in types of decision making pattern by nurses characters. Methods: A self-administered questionnaire was used to pediatric nurses of 4 general hospitals in Seoul from February 2004 to April 2004. The data of 251 nurses was analyzed by varimax rotation factor analysis, t-test, and ANOVA. Results: 6 decision making patterns were identified: Individual Patient-oriented, Pattern-oriented Intuitive, Typical Nursing Knowledge-oriented, Nursing Model-oriented, Medical Knowledge-oriented, and Patient-Family-Nurse Collaborative. Individual Patient-oriented, Pattern-oriented Intuitive, Typical Nursing Knowledge-oriented, and Nursing Model-oriented decision making pattern got meaningful differences in age, marital status, total number of years in nursing practice, and number of years in pediatric nursing practice. Conclusion: We expect the result of this study can be applied for promotion of understanding the decision making of nurses that occurs in pediatric nursing practice and also can be used as foundation data for development and expansion of pediatric nursing practice.

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Effects of Clinical Decision-making on Job Satisfaction among Pediatric Nurses: The Mediating Effect of the Nurse-Parent Partnership (아동병동 간호사의 임상의사결정 능력이 직무만족도에 미치는 효과: 아동병동 간호사-환아 부모 간 파트너십 매개효과를 중심으로)

  • Shin, Kyoung-Suk;Kim, Hye-Young
    • Child Health Nursing Research
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    • v.24 no.1
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    • pp.9-17
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    • 2018
  • Purpose: The purpose of this descriptive survey study was to characterize the relationship between clinical decision-making and job satisfaction among pediatric nurses and to elucidate the mediating effects of the nurse-parent partnership on that relationship. Methods: The subjects of the study were 174 nurses who had worked in a pediatric ward in a university hospital, general hospital, or children's hospital. Data were collected from June 20, 2016 to August 10, 2016 and analysed using descriptive statistics, the t-test, analysis of variance, the Pearson correlation coefficient, and three-step mediated regression analysis in SPSS version 22.0 for Windows. Results: The nurse-parent partnership had significant effects on clinical decision-making and job satisfaction, with an explanatory power of 19% and 26%, respectively. The nurse-parent partnership had a partial mediating effect on the relationship between clinical decision-making and job satisfaction (Sobel test: Z=4.31, p<.001). Conclusion: The nurse-parent partnership had a partial mediating effect on the relationship between clinical decision-making and job satisfaction among pediatric nurses. Therefore, in order to improve the job satisfaction of pediatric nurses, it is necessary to develop effective educational programs and strategies to address their clinical decision-making and their experiences of the nurse-parent partnership.

Research on the major selection and the career decision of college students (Centering on students studying Dental Technology in D-College) (대학생의 전공선택과 진로결정 분석 - D대학 치기공과 재학생을 중심으로 -)

  • Lee, Hwa-Sik;Bae, Bong-Jin;Chang, Ki-Whan
    • Journal of Technologic Dentistry
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    • v.33 no.4
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    • pp.427-440
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    • 2011
  • Purpose: The following research analyzes the causes of major selection and career decision of students studying dental technology. It is to be used as basic data for the management of career improvement program. Methods: The survey has been processed to 490 college students studying Dental Technology in D-college. Questionnaire consists of major selection confidence sheet (14 items) and career decision confidence sheet (18 items) and was scored with 5-points per question. The collected data was analyzed by the statistical program: SAS V8 for Windows. To test for significance on each item, p < 0.05 has been decided as a standard. Results: The analysis of result about the level of confidence on major selection has valid difference by genders, serving military service or not, experience of studying one more year to enter the college or not, making career decision and grade. The analysis of result about career decision has valid difference by gender, serving military service, career decision, day and night course, age and native place. Conclusion: We develop the career advice program and manage it effectively, the confidence on the major selection and pride about its faculty will be high to dental technology students.

Comparative Analysis of Multiattribute Decision Aids with Ordinal Preferences on Attribute Weights (속성 가중치에 대한 서수 정보가 주어질 때 다요소 의사결정 방법의 비교분석에 관한 연구)

  • Ahn Byeong Seok
    • Journal of the Korean Operations Research and Management Science Society
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    • v.30 no.1
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    • pp.161-176
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    • 2005
  • In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

Migration and Economic Inequality in Indonesia: Longitudinal Data Analysis

  • YULIADI, Imamudin;RAHARJA, Sigit Satria
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.11
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    • pp.541-548
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    • 2020
  • This study aimed to explain the factors that influenced an individual's decision to migrate. The method of analysis in this study was the estimation of the probit regression model with data from the Indonesian Family Life Survey (IFLS-5), which covered 30,000 individuals from 13 provinces in Indonesia. Data from IFLS-5 were longitudinal data, meaning that the study was looking for data consistently to get reliable data from respondents. The research variables to determine the individual's decision to migrate were education level, income level, employment status, marital status, land ownership status, health quality, gender, residence status, and poverty status. Individual decision to migrate as a dependent variable was placed as a dummy variable. The results showed that the level of education, income level, employment status, marital status, land ownership status, health quality, and poverty status significantly influenced an individual's decision to migrate. Meanwhile, gender and residence status did not significantly affect an individual's decision to migrate. This research recommends that it is necessary to pursue a policy of economic equality between regions because economic factors are the main trigger for an individual's decision to migrate. Policies to overcome economic disparities among regions will reduce the individual's decision to migrate.

Decision Tree-Based Feature-Selective Neural Network Model: Case of House Price Estimation (의사결정나무를 활용한 신경망 모형의 입력특성 선택: 주택가격 추정 사례)

  • Yoon Han-Seong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.1
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    • pp.109-118
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    • 2023
  • Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

Model of the Fit between Organizational Decision-Making and Decision Support Systems (조직의사결정과 DSS의 적합성 모형)

  • 김명식;유병우
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.44
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    • pp.217-227
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    • 1997
  • There are six perspectives of fit in strategy research, each implying distinct theoretical meaning and requiring the use of specific analytical schemes. But there is a few literature of the perspective in the discipline of Organizational Decision-Making and DSS. This study is a prior research which objective is to investigate the perspective of fit emprically in the discipline. The data were collected throughout the sampled business firms with premade questionaire and analysis were conducted with correlation analysis, regression, ANOVA and so forth. The research finding is that both predictors, one of which can be the moderator, influence the performance, and that the joint-effect of them influence the performance. Thus,'Fit as Moderation' would be suggested to be a proper model for the research in the discipline of Organizational Decision-Making and Decision Support Systems.

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Evaluating Service System Alternatives via a Computer Simulation-enabled MCDM Framework

  • Deng, Wei-Jaw;Pei, Wen;Tsai, Chih-Hung
    • International Journal of Quality Innovation
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    • v.8 no.2
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    • pp.100-114
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    • 2007
  • Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This study proposes a computer simulation-enabled MCDM framework that integrates computer simulation analysis, Taguchi method, expert opinion and multiple criteria decision making (MCDM) to assist decision makers in coping with decision problems. In this framework, Taguchi method is adopted to reduce the time required for the simulation experiment. Computer simulation analysis is adopted to obtain useful information for rapid decision-making without interrupting actual production. MCDM is used to select the optimal alternative. The illustrative result is extremely promising.

Prospect Theory based NPC Decision Making Model on Dynamic Terrain Analysis (동적 지형분석에서의 전망이론 기반 NPC 의사결정 모델)

  • Lee, Dong Hoon
    • Journal of Korea Game Society
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    • v.14 no.4
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    • pp.37-44
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    • 2014
  • In this paper, we propose a NPC decision making model based on Prospect Theory which tries to model real-life choice, rather than optimal decision. For this purpose, we analyse the problems of reference point setting, diminishing sensitivity and loss aversion which are known as limitations of the utility theory and then apply these characteristics into the decision making in game. Dynamic Terrain Analysis is utilized to evaluate the proposed model and experimental result shows the method have effects on inducing diverse personality and emergent behavior on NPC.

A study of constitution diagnosis using decision tree method (의사결정나무법을 이용한 체질진단에 관한 연구)

  • Lee, Yong-Seop;Park, Seong-Sik;Park, Eun-Kyung
    • Journal of Sasang Constitutional Medicine
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    • v.13 no.2
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    • pp.144-155
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    • 2001
  • By the increasing concern about Sasang Constitution Medicine, its practical use is considered very important in disease prevention and medical treatment. However, the method of constitution classification is depending on the doctor's clinical trials because of the lack of the objective test criteria. This study is trying to improve the objectiveness of diagnosis using a new statistical method, decision tree. Decision tree method-a classification technique in the statistical analysis- was used to analyze the result of QSCCII instead of using discriminant analysis. As a result, 16 among 121 QSCCII questions was selected as important questions and 21 terminal nodes was built to classify the constitution. Using only 16 questions shown in the result of decision tree, we can diagnose and interpret the constitution easily and effectively.

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