• Journal of Home Health Care Nursing
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• v.30 no.2
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• pp.163-173
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• 2023

Purpose: The aim of this descriptive research study was to identify the factors affecting the ethical decision-making of nursing students. Methods: A convenience sample of 193 nursing students from three nursing colleges in D city who were engaged in clinical practice completed an online Google Forms questionnaire from September 9 to September 20, 2021. Using SPSS 23.0, data were analyzed with descriptive statistics, an independent t-test, a one-way ANOVA, Scheffé's test, Pearson's correlation coefficient, and a multiple regression analysis. Results: The influencing factors of ideal ethical decision-making were guilt (β=.38, p<.001), awareness of the nurses' Code of Ethics (β=.18, p=.023) and motivation for entering school, among general characteristics (β=-.18, p=.033). The explanatory power of the model was 22.2%. Further, the influencing factors of realistic ethical decision-making were ideal ethical decision-making (β=.26, p=.001) and grade (among general characteristics) (β=.15, p=.029); the explanatory power of the model was 17.9%. Conclusion: Various educational tools and programs pertaining to making ideal and ethical decisions must be enhanced to promote ethical choices in clinical areas and realistic ethical decision-making ability to actually make such choices. This focus may enable nurses to improve their nursing professionalism in the future.

• Informatization Policy
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• v.26 no.3
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• pp.3-35
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• 2019

In the fourth industrial revolution age, because of advance in the intelligence information technologies, the various roles of AI have attracted public attention. Starting with Google's Alphago, AI is now no longer a fantasized technology but a real one that can bring ripple effect in entire society. Already, AI has performed well in the medical service, legal service, and the private sector's business decision making. This study conducted an exploratory analysis on the possibilities and issues of AI-driven policy decision making in the public sector. The three research purposes are i) could AI make a policy decision in public sector?; ii) how different is AI-driven policy decision making compared to the existing methods of decision making?; and iii) what issues would be revealed by AI's policy decision making? AI-driven policy decision making is differentiated from the traditional ways of decision making in that the former is represented by rationality based on sufficient amount of information and alternatives, increased transparency and trust, more objective views for policy issues, and faster decision making process. However, there are several controversial issues regarding superiority of AI, ethics, accountability, changes in democracy, substitution of human labor in the public sector, and data usage problems for AI. Since the adoption of AI for policy decision making will be soon realized, it is necessary to take an integrative approach, considering both the positive and adverse effects, to minimize social impact.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.169-176
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• 2013

PURPOSES : Lots of criticism such as over/duplication investment, inconsistency of the policies among local governments and national plans etc. has been aroused due to the policy of supply-driven construction for transportation facilities. Recently, according to the environmental-friendly transportation policy, the investment of railroad has been expanded gradually, however the duplication with existing road facility makes it difficult to construct railroad. Thus it is necessary to evaluate the interrelationship between new project and existing facilities in the planning stage. However the method and the criteria for analyzing the duplication and over-investment of projects are not established in the manual, thus the feasibility of these projects are carried out from the economic point of view. METHODS: First, It reviewed about interrelationship criteria(domestic, overseas) and proposed implications and this study directions. Next, It developed the methods of evaluating independency, competitiveness and complementarity. RESULTS : In this study, the methods of evaluating independency, competitiveness and complementarity etc. are suggested to analyze the interrelationship between transportation facilities. The case study was carried out to examine the applicability of the methods. CONCLUSIONS: The methods raise rationality of decision-making compared to existing one. In the future, these methods are introduced into the manual of pre-feasibility study and feasibility study, more efficient decision-making and investment are expected.

• Journal of Korean Society of Forest Science
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• v.85 no.2
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• pp.149-157
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• 1996

The applications of multiple criteria decision making(MCDM) methods were investigated to determine the priority order in forest road construction for timber harvesting and silvicultrual activities in 22 regions. In this paper, MCDM methods have five methods from two kinds of models. The one is non-compensatory preference model including maximin and maximax method; the other is compensatory preference model including simple additive weighting method(SAW), hierarchical additive weighting method(HAW) and technique for order preference by similarity to ideal solution(TOPSIS), SAW and TOPSIS methods turned out to be the most adequate for forest road construction priority order among the five methods tested in this study.

• Journal of the Korea Safety Management & Science
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• v.4 no.4
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• pp.109-118
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• 2002

Such effects would be paid off in the right way only when management of the firms perform marketing activities focusing on long term effectiveness, which would drive company profits up and keep them for long. Demands of customers are being changed and varied. In this result with the advantage of mass marketing and database marketing have been drawing attentions from company. To fulfill these demands of customer, they need a concept of eCRM(Web based Customer Relationship Management), and go from selling products and services, or gathering customer requests, up to the phase of solving customer's problem by real time or previous action. With the help of internet, the frequency and speed of the problem solving has improved greatly. For these purposes, we try to determine the most important and most urgent factors in eCRM: utilization by using SN Ratio Decision making, one of the Multi-criteria decision-making methods SN Ratio Decision making is widely used for determining relative magnitude per evaluation item, i. e. priority on problems and is expected to make more systematic and objective evaluations than conventional methods do. Even in the present situation where any general criterion on eCRM dose not exist, utilization of eCRM is expected to be actively continued, which will cause many problems. In this regard, evaluating eCRM counts.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.85-95
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• 2016

Recently, deep learning and machine learning have attracted considerable attention and many supporting frameworks appeared. In artificial intelligence field, a large body of research is underway to apply the relevant knowledge for complex problem-solving, necessitating the application of various learning algorithms and training methods to artificial intelligence systems. In addition, there is a dearth of performance evaluation of decision making agents. The decision making agent that can find optimal solutions by using reinforcement learning methods designed through this research can collect raw pixel data observed from dynamic environments and make decisions by itself based on the data. The decision making agent uses convolutional neural networks to classify situations it confronts, and the data observed from the environment undergoes preprocessing before being used. This research represents how the convolutional neural networks and the decision making agent are configured, analyzes learning performance through a value-based algorithm and a policy-based algorithm : a Deep Q-Networks and a Policy Gradient, sets forth their differences and demonstrates how the convolutional neural networks affect entire learning performance when using pixel data. This research is expected to contribute to the improvement of artificial intelligence systems which can efficiently find optimal solutions by using features extracted from raw pixel data.

• Journal of the Korean Society of Costume
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• v.50 no.5
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• pp.103-115
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• 2000

There are various presentation methods of apparel products on the internet shopping mall. The objective of this study was (a) to identify the effect of information supply about the criteria to evaluate a garment according to presentation methods and (b) to investigate the relation between the consumer's evaluation of presentation methods and confidence in purchase decision. For this experiment. 4 presentation methods of jean were selected from internet shopping mall. They were rotating appearance on the body, enlarged product picture, apparel items coordination method and just picture of wearing appearance. Each presentation method was evaluated by panels using questionnaire. Consumer's evaluation of presentation methods were developed 5 point likert scale. The major findings drawn from this study were as follows : 1. There were significant differences in degree of information supply about product criteria according to presentation methods. Enlarged product picture introduction was good for confirmation of sewing state, fabric and detail. Apparel items coordination method was good for judgement of styling and current fashion suitability. 2. Dimension of information evaluation was composed of providing pleasure, utility of information, reliability & attractiveness, negative emotions. All of these factors affect confidence in purchase decision and intention of revisiting the site. The most important factor for confidence in purchase decision making was reliability & attractiveness. as compared to this, intention of revisiting the site was more influenced by providing pleasure.

• Korean Journal of Adult Nursing
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• v.26 no.4
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• pp.403-412
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• 2014

Purpose: The purpose of this study was to validate the Korean version of shortened Nursing Decision-Making Instrument developed by Lauri & $Salanter{\ddot{a}}$(2002). Methods: The subjects were 247 nurses working in eight hospitals of Korea. Data were collected by questionnaires from June to July, 2012 and were analyzed by Principal Component Analysis for construct validity and Cronbach's ${\alpha}$ coefficient for reliability. Results: Factor loadings of the four subscales ranged from .32 to .73. The explained variance from the four factors was 48.54% of the total variance. The factors were named 'implementation of plan, monitoring and evaluation', 'plans of action', 'data collection', and 'data processing and identification'. The first factor consisted of 6 items which explained 13.21% of the total variance and the second factor contained 8 items. The Cronbach's ${\alpha}$ coefficients of the four subscales were from .64 to .81. Conclusion: The Korean version of the shortened Nursing Decision-Making Instrument has satisfactory construct validity and reliability. However, that the scores of the analytic items weren't reversed unlike the analysis method of the original tools is the biggest limitation of this study. In addition, based on the fact that there were several discrepancies for item interpretation of Korean comparing to the findings of the instrument development study, repetitive researches would be suggested.

• Journal of Families and Better Life
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• v.11 no.1
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• pp.203-217
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• 1993

The purpose of this study was to investigate relations of decision-making power of the elderly to home management and life satisfaction by applying a social behavior theory and exchange theory and to find out the device which improve the elderly life satisfaction at the home management view. For these research tasks the data was collected through the questionaire and interview those respondents were 273 woman elderly living with one of their married children in Seoul. It was analyzed by various statistical methods such as Frequency Percentile ANOVA F-test t-test Pearson's Corrdlation Analysis Multiple Regression Analysis. The results of this study are as follows: 1) Decision-making power of the elderly to home management had significant differences according to all of th variables except for religion job status of the elderly and education income of the children. 2) Decision-making power of the elderly to home management had the significant differences according to the variable such as income of the elderly solidarity between the elderly and their adult children age of the elderly The most influencial factor was income of the elderly. 3) Elderly life satisfaction had significant differenced according to all of the variables except for age job status of the elderly and education income of the children inmate children 4) In the result of analyzing the elderly life satisfaction the most influencial factor was decision-making power to home management and the explanary power to home management and the explanary power of those variables for the elderly life satisfaction was 56.2%.

• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.3
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• pp.393-402
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• 2012

Purpose: This study was conducted to test the effect of a Career Search Program on career search efficacy, career search behavior, and career decision making for nursing students. Methods: A non-equivalent pre-post test of a quasi-experimental design was used. Fifty first grade nursing students participated in the study with 22 in the experimental group and 28 in the control group. We used a Career Search Program which was held 6 times over 6 weeks, 90 minutes per session. Descriptive statistics, ${\chi}^2$-test, and independent t-test were used for statistical analysis with SPSS 19.0. Results: There were significant increases in career search efficacy (t=2.07, p=.044) and career search behavior(t=2.65, p=.011) in the experimental group compared to the control group. However, career decision making was not significantly changed (t=0.96, p=.342). Conclusion: These results suggest that a Career grade Search Program has an effect on increasing career search efficacy and career search behavior in first grade nursing students. In addition, more programs to impact career decision making should be developed for nursing college students.