• Journal of the Korean Society of Safety
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• v.28 no.6
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• pp.84-89
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• 2013

The main causes of traffic accidents can be classified by 3 factors - human error, vehicle deficiency and road environmental problem and most accidents occurs not only 1 factor but combination of 2 or 3-factors. Among these factors, road environmental factor is the most important factor due to influence the behavior of cars and road users and road environmental factor affects 30% of total accidents approximately. The 5 years traffic accidents data analyzed to verify the accidents severity on Korea National Highways. In order to analyze the severity, Ordered Probit Model was used. As a independent variables of this model the number of lane, neighbor road environments, sight distance, vertical grade, lane width, shoulder width and traffic volume were used and as a dependent variables the minor injuries, serious injuries and fatalities were used. Research results shows that sight distance and lane width are identified as significant factors for the traffic accident severity and lesser sight distance and lane width shows greater traffic accident severity.

• Journal of Integrative Natural Science
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• v.8 no.4
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• pp.305-312
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• 2015

The present study showed WHtR to be significantly better than BMI and WC for prediction of metabolic-related diseases in the middle-aged and older people in Korea, based on Bayesian ordered probit model analysis. The variations of WC, BMI and WHtR were compared according to the number of metabolic-related diseases such as hypertension, dyslipidemia, stroke, myocardial infarction, angina pectoris and diabetes. It was found that the three measures showed the similar variation except a very few extreme cases for age less than 40. For subjects over the age of 40, WC was not significant and WHtR gave more influence in greater variability than BMI on the number of metabolic diseases. Also, the rate of change for WHtR was higher than for BMI as the number of metabolic-related diseases increased. Specifically, the difference of the marginal effect of WHtR between no disease and only one disease was 1.81 times higher than that of BMI. Moreover, it was pointed out that the threshold value of WHtR for obesity should be considered differently by age.

• Journal of Korean Society of Rural Planning
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• v.20 no.3
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• pp.89-100
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• 2014

The purpose of this study is to investigate whether the effect of the Strong Small Farm Development Project by Rural Development Administration is positively associated with participating farmers. The data that used in this study is a survey data that targets 442 farming households who have participated in the strong small farm development project. This study applies ordered-probit model to evaluate level of the participants' satisfaction of the project. This study found that participants' level of satisfaction is closely associated by satisfaction level of project contents that contains education and consulting, friendly attitude toward the project, active participation of the project, and understanding of the project's contents and their importances. Based on research findings, this research provides some implications of future upbringing policy for strong small farms and the principal point of the policy that leads to succeed in implementing the project when formulating agricultural policy in participants view. the strong small farms.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.41-53
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• 2016

According to the price-decline effect, the art auction prices are known to decrease with the order of auction sale. Our empirical study investigates the presence for the price-decline effect using the data for Korean antique art hosted by the Seoul Auction in September, 2015. We apply the Hedonic price model to the data and examine the relation between the sale order and auction price. Our empirical evidences show that the well-known price decline effect is not present for the case of Korean antique auction in 2015. We confirm our results by estimating the ordered probit model. From the view of the price-decline effect, our results suggest that the Korean antique auction data exhibits different characteristics from most of the foreign art auction data.

• Journal of Labour Economics
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• v.31 no.1
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• pp.135-162
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• 2008

This paper analyzes the impact of the mother's employment on her time investment in children's career decisions. Parental conversations with high school children and the parents' effects on children's career decisions are used as the proxies for the quantity and quality of time investment, respectively. For the empirical analysis, IV ordered-probit regressions are fitted to the KLIPS data. Other things being equal, the mother's employment does not cast any statistically significant impact on the quantity and quality of time input for children in high school. The effect of mother's employment on her time investment in children is positive for professional jobs while negative for nonprofessional jobs, but both lack the weight of statistical significance.

• Health Policy and Management
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• v.19 no.1
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• pp.62-80
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• 2009

The purpose of this study was to examine the factors influencing the attitude toward the increasing role of private health insurance(PHI). In the Korea Welfare Panel Data 2007, a sample of 1,675 (adjusted by weight value: 1,607) respondents on an opinion on promoting PHI was used in the study. With independent variables including socio-demographic characteristics, health status, health-related behavior, and opinions on welfare service, ordered-probit model was used to analyze the attitude toward PHI. Negative opinion on the increasing role of PHI were responded by 54.6%(n=877) of the respondents, whereas 22.2%(n=373) were positive and 23.2%(n=357) were neutral. Old people, the better off, those with worse self-assessed health status, and those having an experience of health examination tend to have the positive attitude toward the increasing role of PHI. Women, those with chronic diseases or disorders and those who do not agree that comprehensive welfare benefits reduce work incentive showed negative attitude toward PHI. When comparing the needs for PHI before and after medical utilization, ex-ante need tends to strengthen the tendency to support private health insurance. This study will contribute to the discussion on the optimal mix of public and private health insurance in Korea by a better recognition of attitude toward PHI and health care system.

• Korean Journal of Organic Agriculture
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• v.26 no.4
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• pp.543-558
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• 2018

The purpose of this study is to analyze the amount of willingness to pay for environment-friendly agricultural processed foods by the level of consumption intention. To accomplish the objective of the study a consumer survey was conducted for quantitative analysis regarding consumption pattern. The ordered-probit selection model, Heckman-type two-stage method was employed for an empirical analysis on determining the amount of willingness to pay. The estimation results showed that in the case of consumers who are to keep their consumption at the present level, those with high quality contentment compared to price, brand contentment, and purchasing chiefly in the special store, have the higher amount of willingness. The estimation results also showed that in the case of consumers who are to increase their consumption, those with high quality contentment compared to price, brand contentment, certificate contentment, and having family members who suffer from diseases such as atopy, cancer, diabetes, high blood pressure, have the higher amount of willingness. Therefore For those who are to increase their consumption, enhancement of quality, enhancement of contentment with certificate, promotion are useful to increase the amount of willingness to pay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.860-877
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• 2013

Cloud computing has become one of the most important technologies for reducing cost and increasing productivity by efficiently using IT resources in various companies. The cloud computing system has mainly been built for private enterprise, but public institutions, such as governments and national institutes, also plans to introduce the system in Korea. Various researches have pointed to security problems as a critical factor to impede the vitalization of cloud computing services, but they only focus on the security threats and their correspondents for addressing the problems. There are no studies that analyze major security issues with regard to introducing the cloud computing system. Accordingly, it is necessary to research the security factors in the cloud computing given to public institutions when adopting cloud computing. This research focuses on the priority of security solutions for the stepwise adoption of cloud computing services in enterprise environments. The cloud computing security area is classified into managerial, physical and technical area in the research, and then derives the detailed factors in each security area. The research derives the influence of security priorities in each area on the importance of security issues according to the identification of workers in private enterprise and public institutions. Ordered probit models are used to analyze the influences and marginal effects of awareness for security importance in each area on the scale of security priority. The results show workers in public institutions regard the technical security as the highest importance, while physical and managerial security are considered as the critical security factors in private enterprise. In addition, the results show workers in public institutions and private enterprise have remarkable differences of awareness for cloud computing security. This research compared the difference in recognition for the security priority in three areas between workers in private enterprise, which use cloud computing services, and workers in public institutions that have never used the services. It contributes to the establishment of strategies, with respect to security, by providing guidelines to enterprise or institutions that want to introduce cloud computing systems.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.47-55
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• 2005

In recent years, the rapid growth of vehicles have increased traffic crashes. Since they can cause the economic losses and have put the life qualify in danger, there should be numerous efforts to reduce traffic crashes. To reduce traffic crashes, this research seeks to improve the safety of intersections by analysing causations of injury severity with Ordered Probability Model. This research applied the Ordered Probit Model, which assumes that ${\epsilon}_i$(random error) is normally distributed, for model calibration and used $p^2$ (likelihood ratio) and $x^2$ (Chi-square) for model selection. The results show that minor road traffic, heavy vehicle rates, major and minor right-turn rates, presence of lightings, speed limits, instructive line for left-turn traffic are significant factors affecting crash severities at signalized intersections.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.367-382
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• 2018

Prediction models for a corporate bond rating in existing studies have been developed using various models such as linear regression, ordered logit, and random forest. Financial characteristics help build prediction models that are expected to be contained in the assigning model of the bond rating agencies. However, the ranges of bond ratings in existing studies vary from 5 to 20 and the prediction models were developed with samples in which the target companies and the observation periods are different. Thus, a simple comparison of the prediction accuracies in each study cannot determine the best prediction model. In order to conduct a fair comparison, this study has collected corporate bond ratings and financial characteristics from 2013 to 2017 and applied prediction models to them. In addition, we applied the elastic-net penalty for the linear regression, the ordered logit, and the ordered probit. Our comparison shows that data-driven variable selection using the elastic-net improves prediction accuracy in each corresponding model, and that the random forest is the most appropriate model in terms of prediction accuracy, which obtains 69.6% accuracy of the exact rating prediction on average from the 5-fold cross validation.