• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.45-60
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• 2014

We introduce a MCMC sampling for a generalized linear normal random effects model with the ordered probit link function based on latent variables from suitable truncated normal distribution. Such models have proven useful in practice and we have observed numerically reasonable results in the estimation of fixed effects when the random effect term is provided. Applications that utilize Korean Welfare Panel Study data can be difficult to model; subsequently, we find that an ordered probit model with the random effects leads to an improved analyses with more accurate and precise inferences.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.143-154
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• 2014

PURPOSES : This study drew factors affecting motorcycle accidents in Seoul by severity using an ordered probit model and aimed to analyze and verify the drawn influence factors. METHODS : As the severity of the accidents could be classified into three types (fatal injury, serious injury and minor injury), this study drew the factors affecting accidents by a comparative analysis employing an ordered probit model, removed the variables that would not secure significance sequentially to construct a model with high explanatory power regarding the factors affecting the severity of motorcycle accidents, and calculated the marginal effect of each factor to understand the degree of each factor's impact on the severity. First, Model 1 put in all variables; Model 2 was constructed by removing the variables of the road surface conditions that could not meet the level of significance (p=0.608); Model 3 was constructed by removing gender variable (p=0.423); and Model 4 was constructed finally by removing age variable (p=0.320). RESULTS : As a result of an analysis, statistically significant variables were time of occurrence, type of accident, road alignment and motorcycle displacement, and it turned out that the impacts on the severity were in the following order: a road alignment of left downhill, the type of motorcycle-to-vehicle accidents and a road alignment of a flatland on the left. The significance of the models was tested using the likelihood ratio, the level of significance and suitability statistics about them, and as a result of the test, the significance level and suitability of the constructed models were all excellent. In addition, the model accuracy indicating the accuracy of a predicted value compared to that of the value actually observed was 70.3% for minor injury; 70.1% for serious injury; and 68.6% for fatal injury, and the overall accuracy was 70.2%, which was very high. CONCLUSIONS : As a result of an analysis of motorcycle accidents in Seoul through the ordered probit model and the marginal effect, it turned out that their severity increased in nighttime accidents as compared to daytime ones and gradually increased in the order of motorcycle-to-vehicle accidents, motorcycle-to-person ones and the ones involving motorcycle only. As a result of an analysis, the severity of accidents in road alignments of left downhill, left flatland and straight downhill increased as compared to those in a road alignment of straight flatland and that the severity of accidents of motorcycles with a displacement larger than 50cc was higher than that of those with a displacement smaller than 50cc.

• The Korean Journal of Community Living Science
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• v.25 no.4
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• pp.567-579
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• 2014

Housing environments of individuals and families can have considerable influence on their quality of life. This study examines the factors influencing housing satisfaction and compares them between rural and urban areas. A total of 3,958 households collected from a nationwide survey were analyzed using an ordered probit model. The results indicate that housing satisfaction was influenced by individual, housing, and neighborhood attributes. The factors that differentiated between rural and urban models were sex, housing type, and relationships with neighbors. The results have important policy issues for improving rural housing.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.85-95
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• 2015

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

• 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.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.13-22
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• 2018

Buses, one of the representative public transportation modes, are divided into a vareity of service types according to the purpose of operation, operating distance, and management agencies. Although bus-involved crashes may cause large amount of damage due to the higher number of passengers boarded on a bus, prior research has little focused on crash severity according to bus service types. This study aims to investigate factors influencing crash severity in bus-involved crashes and to present policy implications to reduce crash severity by bus service type. To do this, bus-involved crash data from the Traffic Accident Analysis System (TAAS) during five-year period are used. Ordered probit models for three types of bus service, i.e., city bus, suburban and express buses, and charter buses, are estimated to analyze the factors of accident severity. The results show that there are significant differences of factors affecting crash severity among the types of bus services while speed and road surface influence all the types of buses. In case of local buses, time of day, roadway alignment, and installation of a traffic signal are found to be statistically significant factors. Seat belt and road class have significant effects on injury severity of the intercity and express buses. Chartered buses have time of day, driving experience, seatbelt, traffic signal, and day of week as the significant factors. The results of this study are expected to contribute to the reduction of the crash severity by each bus service type.

• 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 Rural Planning
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• v.23 no.3
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• pp.53-60
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• 2017

In order to export Korean spray roses to the China, it is needed to analyse chinese preferences, rose attributes, and purchase intentions. The purpose of this study is to present the implications on the production and distribution of roses for export by analyzing the quality preference attributes and purchase intention of Korean rose for Chinese flower experts. A survey on the preference and purchase intention of Korean flower roses by Chinese flower experts was conducted through face - to - face interviews with flower show participants in China. Approximately 100 Chinese flower experts who participated in the Flower Show in 2016 received the questionnaire, and 86 survey results could be used for analysis. Survey data were analyzed using ordered probit and bivariate probit models. As a result of an analysis, it was found that Chinese flower experts were more likely to buy Korean roses than Chinese roses even if they consider flower color, leaf shape and size and color diversity. The probability of purchasing more than twice the price was higher than that of the color diversity considering the flower shape, leaf shape and size, but the bivariate order probit model was larger than that of flowers, leaves and size, and the order of probability size was changed. In order to increase the export of Korean spray roses to the Chinese market, We need to increase Chinese experts' preferences and satisfaction. For this purpose, it is very important to develop export varieties of roses with large flower buds and shape / coloring, and to apply the useful post-harvest technology that can extend freshness and distribution period of export roses.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.101-115
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• 2008

This study reports UTIS(Urban Traffic Information System), which has been generalized in developed countries through brisk research and development and is being promoted for introduction by National Police Agency and Road Traffic Authority to reduce the astronomical amount of social expenses including traffic congestion expenses. Also this study investigates the proper charges for using by the preestimate of demand and contentment according to methods of payment after the service is introduced. The results of this study are as follows. First, demand forecast model is constructed by Binary Logit Model. Second, forecast models of using aspects of UTIS service according to methods of payment are established by Ordered Probit Model. Third, the proper charges for using of UTIS service according to methods of payment are presented to the supplier in the aspects of users. For this, preferences by using aspects and methods of payment are captured. And unit elasticity of coefficient of utilization is understood through responsiveness analysis according to methods of payment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4328-4336
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• 2011

The aim of this study is to find changes of the attributes that influence the purchase of cut roses during recent five years(2007~2011) and suggest some implications on ways to promote cut roses marketing. For this purpose, a survey was conducted through the Internet among 1,100 randomly chosen people living in Seoul, Inchon and Gyeonggi Province in 2011. A total of 1,023 valid replies were received for the analysis of the survey which was carried out by the subsidiary consulting firm. The survey panels and estimation models to analyze changes of consumers' preference attributes during recent five years are same to them of Kim, et al.(2007). That is, empirical analysis tools such as ordered probit model, multinomial logit model, and conjoint analysis were used according to Kim, et al.(2007). This paper suggests several policy implications to set up the target market of cut roses and marketing mix strategy to specify the best 4P(product, price, place and promotion).