• Preventive Nutrition and Food Science
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• v.6 no.1
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• pp.73-78
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• 2001

The elevation of total plasmahomocysteine is now an established risk factor for cardiovascular disease. Plasma folate and vitamin {TEX}$B_{12}${/TEX} influence Hcy metabolism as cofactors. In this study, we studied the relationship of major risk factors for cardovascular disease, including advanced age, male gender, obesity, hypertension, hyperglycemia, and dislipidemia and plasma homocyteine, folate and vitamin {TEX}$B_{12}${/TEX} levels in Koreans. A total of 195 adult Koreans participated. The subjects were divided into three groups according to how many major conventional risk factors of cardiovascular disease they had: no risk, low risk (1~3 risk factors) and high risk (>3 risk factors) groups. As the number of risk factors increased, the plasma homocysteine levels significantly increase, while the plasma folate levels significantly decreased. The plasma homocysteine levels re higher in males than in females. The subjects with hyperglycemia had higher plasma homocysteine levels than the subjects without the risk factor. Also the subjects with dislipidemia had higher plasma homocysteine levels than the subjects without the risk factor. The plasma folate and vitamin {TEX}$B_{12}${/TEX} levels were significantly lower in males tan females. However, there were no significant differences in plasma folate and vitamin {TEX}$B_{12}${/TEX} levels between the subjects with or without other risk factors. These results indicate that plasma homocysteine levels were positively related with risk factors for cardiovascular disease and plasma folate levels were negatively related with the risk factors for cardiovascular disease. Also, we conclude that plasmahomocysteine levels might be related to the combination of risk factors, rather than an individual risk factor.

• Fashion & Textile Research Journal
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• v.6 no.1
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• pp.93-101
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• 2004

The purpose of this study is to examine consumers' risk perception in internet clothing shopping and its relation with technology readiness and the frequency of purchase. Thereafter, this study examines how consumers' risk perception affect service quality and satisfaction at the apparel shopping sites. An on-line survey was made to collect data, and the replies from 785 people, who had an experience of apparel shopping on line, were used in data analysis. From factor analyses, risk perception comprised 3 factors of product related risk, delivery related risk, and security related risk, and technology readiness comprised 4 factors of optimism, innovativeness, discomfort, and insecurity. Based on cluster analysis, consumers were classified into 3 types in terms of the internet risk perception: low risk group, medium risk group, and high risk group. From path analysis, risk perception was decreased with high frequency of purchase and low discomfort and insecurity of technology readiness, and risk perception and service quality had an influence on consumers' satisfaction with the shopping sites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3039-3056
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• 2020

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.29-46
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• 2019

This study analyzed the factors influencing the technology acceptance of the general public in the drones and ARs, one of the key technologies of the industry 4.0. The theoretical basis was the extended unified theory of acceptance and use of technology model(UTAUT2), which uses performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation as factors common to both services. The price value factor was excluded considering that most ARs were free, and the perceived risk factors, including privacy, which were not in UTAUT2, were included because they are important factors for ICT technology acceptance. The hypothesis was tested by structure equation model. Social influence and hedonic motivation had a positive(+) effect on intention to use technology. On the other hand, in the case of effort expectancy, neither the AR nor the drone had a significant influence on intention to use technology. Furthermore, performance expectancy had a positive(+) effect on intention to use in AR, but no significant influence was found out in drones. On the contrary, in the case of the facilitating conditions, the influence of the drones was positive (+), but the relation of AR was not investigated. The perceived risk was tested for the negative (-) influence of use intention of AR, but no significant relationship was found out for the drones. Among the significant influencing factors, hedonic motivation was the most powerful factor in AR and drones. Theoretical and practical implications are presented based on these results.

• Journal of Distribution Science
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• v.21 no.5
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• pp.43-51
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• 2023

Purpose: The current research investigates the beneficial impacts of supply chain innovation and risk management on the competitive advantage of organizations, based on the resource-based theory (RBT) framework. Research Design, Data, and Methodology: 14 survey items were included in the study's questionnaire, utilizing a random sampling technique to gather data from 239 leaders and managers employed by various steel trading firms in Vietnam. In order to validate the data and examine relationships, the collected data is analyzed using structural equation modeling, confirmatory factor analysis, and reliability analysis via SPSS 22.0 and AMOS 22.0 software. A fictitious system has been suggested. Results: According to the findings, the most positive influence on competitive advantage is supply chain innovation, followed by risk management capability, having the second greatest positive influence. Conclusions: Some conclusions are drawn based on the research's findings in order to assist managers in realizing the significance and necessity of giving attention to supply chain innovation and improving risk management capabilities, both of which are essential components for achieving the competitive advantage of an organization.

• Journal of Information Technology Applications and Management
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• v.14 no.1
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• pp.117-135
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• 2007

Globalization changes in market structures and consumer needs, as well as technology innovations force organizations to adopt new structures and collaborative networks to cope with rapidly changing environments. These Collaborative Networks are based on the Idea of virtual enterprise. A virtual enterprise(VE) is a temporary alliance of globally distributed independent enterprises that share core competencies and computer networks. This paper presents a proposal for a methodology to measure a key factor of success and risk First of all, we chose thirty experts' defines on virtual enterprise, fifteen are academic specialist and other fifteen are from industry. For this study we define twenty two factors determining VE's success and seventeen factors determining VE's risk using by Delphi method. And we built the influence model on virtual enterprise. A research model was established according to preceeding research and consensus on experts then the revised model of key factors on virtual enterprise. This survey was based on the Analytical Hierarchy Process (AHP). AHP is an approach to decision making that involves structuring multiple choice criteria into a hierarchy, the assessing the relative important of these criteria, comparing alternative for each criteria, and determining an overall ranking of the alternatives. A model was constructed as 3 level hierarchy. The hierarches are organizational, strategic, technical criteria. for success model on VE has 22 factors and 17 factors for risk model. They are selected by all 30 experts. 14 copies among 30 copies distributed to carry out on the Analytical Hierarchy Process (AHP). Consistency ratio confirm high validity and reliability of instrument and support theoretical model. The results of this study are summarized as follows. (1) This study presented success on VE influenced strategic criteria, and essential factor is Creating a value. Risk on VE influenced strategic criteria, and essential factor is Outcome/Distribution. (2) Its enable that ranking the criteria influence on VE. These are supported VE management and using guideline of VE.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.5
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• pp.13-22
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• 2015

These days, human behavior (human factor), the main cause of traffic accidents, has drawn more attention. Research on driving behavior based on DBQ(Driver Behavior Questionnaire), the analysis tool of driving behavior, has been conducted actively. In domestic previous studies, their analysis subjects were limited to researchers or military officials, and their analysis methods were based on factor analysis and regression analysis. Therefore, this study tries to find the factors of general drivers' driving behavior that influence risk driving, and to analyze their influential relationship. Regarding study scope, general drivers with driving career were asked to answer DBQ questionnaire, and 300 effective samples were analyzed. In addition, previous studies were investigated to draw the three measurable attributes of DBQ-'Lapse, Mistake, and Violation'-as main factors of traffic accidents, and structural equation model was applied to design risk driving behavior model. To identify the difference between risk driving groups, this study made use of multiple group analysis. The analysis came to the following results: First, according to the examination of the hypothesis that 'Lapse, Mistake, and Violation factors will influence risk driving behavior', all factors were found to be statistically significant. Regarding their level of influence on risk driving behavior, Violation was 0.464, Lapse 0.383, and Mistake 0.158, and thus Violation was analyzed to be the most influential. Secondly, according to the examination of the hypothesis that 'the influence of Lapse, Mistake, and Violation factors on risk driving behavior will be different by risk group', the influence of Lapse on risk driving behavior was found to be different by risk group. It is expected that the study results will be used as a fundamental program to introduce traffic accident prevention program and education that takes violation and lapse into consideration.

• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.29-34
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• 2017

This Analyzed case study of measuring displacement, implemented laboratory investigation, and in-situ testing in order to interpret ground subsidence risk rating by excavation work. Since geological features of each country are different, it is necessary to objectify or classify quantitatively ground subsidence risk evaluation in accordance with Korean ground character. Induced main factor that could be evaluated and used to predicted ground subsidence risk through literature investigation and analysis study on research trend related to the ground subsidence. Major factors of ground subsidence might be classified by geological features as overburden, boundary surface of ground, soil, rock and water. These factors affect each other differently in accordance with type of ground that's classified soil, rock, or complex. Then rock could be classified including limestone element or not, also in case of the latter it might be classified whether brittle shear zone or not.

• Korean Journal of Human Ecology
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• v.20 no.5
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• pp.1035-1046
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• 2011

The purpose of this study was to investigate the impulse buying behavior of men and women in their twenties, who have experiences of purchasing on internet shopping malls, when they buy fashion products. The data in this study was statistically analyzed using factor analysis, reliability coefficient, and multiple regression analysis using SPSS 14.0. The findings are as follows. First, factor analysis revealed five factors of impulse buying behavior during the purchase of fashion products on internet shopping malls: affective impulse buying, provocative impulse buying, situational impulse buying, reminder impulse buying, and pure impulse buying. Second, factors of perceived risk when purchasing fashion products on internet shopping malls included product quality, payment, service, and economy. Third, sources of information included personal sources of media for fashion professionals, commercials and sponsorship, and promotion. Fourth, the effect of the perceived risk on impulse buying behavior was investigated and the result showed that the perceived risk had a statistically significant influence on impulse buying behavior. Finally, the effect of the information source on impulse buying behavior was investigated and the results showed that the use of information sources had a statistically significant influence on impulse buying behavior.

• Journal of the Korean Society of Clothing and Textiles
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• v.37 no.6
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• pp.772-785
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• 2013

This study investigated the effects of fashion consumer's browsing motives and risk perception on impulse buying and purchase intention in social commerce. The online survey results of 317 customers who experienced using fashion products via social commerce were used for the final analysis. Exploratory factor analysis, reliability analysis, and frequency analysis were conducted using SPSS 18.0, and confirmatory factor analysis and path analysis were performed with AMOS 18.0. Three browsing motives (hedonic motive, rational motive, and informational motive) and three risk perceptions (products-related risk, customer service risk, and opportunity loss risk) were identified. The results from the structure equation model were as follows. 1) It was deducted that the browsing motive did not have a significant effect on risk perception due to the rejection of most of the hypotheses in regards to the browsing motive influence on risk perception. 2) Product-related risk and customer service risk had a significantly negative effect on purchase intention. Opportunity loss risk had significantly positive effect on impulse buying and purchase intention. 3) Hedonic browsing motive had a significant effect on impulse buying, and rational motive had a significant effect on impulse buying and purchase intention. The informational browsing motive had a significant effect only on purchase intention.