• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.437-444
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• 2017

The purpose of this study is to analyze the factors affecting the reverse mortgage utilization and satisfaction of the elderly. Based on the survey data of the reverse mortgage demand in 2016, we carried out empirical analysis using the binary logit model and the ordered logit model. First of all, as a result of the empirical analysis using the binary logit model, the determinants of using the reverse mortgage were age, region, assets, household member, children with financial help, and education level. As a result of the empirical analysis using the ordered logit model, the determinants of the satisfaction level of the reverse mortgage were estimated to be age, gender, and region. Based on the results of the empirical analysis, it is necessary to find a way to increase the participation rate of the reverse mortgage and to improve the satisfaction of the user.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.189-195
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• 2006

For the past decades, vehicle emissions has been a major source of air pollution in urban areas Vehicle inspection and maintenance (I/M) test programs were developed for major metropolitan areas to reduce urban air pollution. However. there are a few studies of exploring major factors to influence I/M test failure. This study develops a logit model to identify key factors affecting overall test failure, using the vehicle I/M test data from California in October 2002. The model results indicate that vehicle age, odometer reading, engine size, vehicle make, presences of emissions control equipment, and test types have significant effects on the probability of I/M test failure.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.17-27
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• 2007

Since early 1990s, several developed countries have applied the Electronic Toll Collection System (ETCS) to toll roads in order to solve traffic congestion and delay problems at toll plazas. For the successful operation of the ETCS, it is important to correctly forecast the ETCS using rate. In this study, it was conceived to develop a sophisticated demand forecasting model of the ETCS for toll roads in Changwon City The Binary Logit and neural network models were tested for the model considering 11 explaining variables. The best results in prediction accuracy and goodness-of-fit were obtained on the neural network model. However, because of the difficulty in predicting the 11 variables and its fitness in wide range, the Binary Logit model which considers three policy variables only is recommended as the model to forecast the ETCS using rate.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.151-161
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• 1997

An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.51-61
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• 2010

The main objective of this paper is to analyze change of travel patterns according to public transportation reform. The paper uses data collected from Gyeongsan City. So far few researches, especially using before-and-after individual travel survey, have been conducted on analyzing effects of public transportation reform. For this research, some descriptive statistical analyses and statistical hypotheses tests were conducted. Furthermore, some empirical logit models were estimated for analyzing the individual effects of the public transportation reform. Finally, some important foundings, policy implications, and limitations of this research are discussed.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.129-140
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• 2018

In this study, we analyzed the electric vehicle (EV) purchasing behavior with market segmentation in Seoul using the binary logit model. For the model estimation, the experimental design of SP survey generated 24 scenarios with purchase price, charging station availability, and driving range of EVs. The results of market segmentation analysis indicated that the owners of subcompact and compact size cars were primarily affected by the purchasing price while those of mid and full size cars were more sensitive to the charging station availability. By housing type, the charging station availability was the most important factor for the residents of apartment while the purchase price was the most important factor to choose the EVs. These results presented that the EV supply strategy of the automobile manufacturer should be diversified according to the marketing target and the expansion of the public charging infrastructure should be the top priority in the government policy.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.923-932
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• 2013

This paper proposes a method to predict the number of foodborne disease outbreaks by microbes. The weekly data of food poisoning occurrences by microbes in Korea contain many zero-valued observations and have dependency between outbreaks. In order to model both phenomena, the number of food poisonings is predicted by an autoregressive model and the probabilities of food poisoning occurrences by microbes (given the total of food poisonings) are estimated by the baseline category logit model. The predicted number of foodborne disease outbreaks by a microbe is obtained by multiplying the predicted number of foodborne disease outbreaks and the estimated probability of the food poisoning by the corresponding microbe. The mean squared error and the mean absolute value error are evaluated to compare the performances of the proposed method and the zero-inflated model.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.660-675
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• 2012

This paper aims at, analyzing the characteristics of immigration path, residential status and residential location preference of Korean immigrants in Washington State of United State. The main results of this study are as follows. Firstly, according to the questionnaire survey results, respondents tend to prefer own housing as their incomes are higher. Secondly, Location factors which respondents most prefer are safety, natural environment and school district. Thirdly, household income influences the housing ownership rate of respondents, according to the result of binomial logistic regression analysis on the impact of individual characteristics of the respondents on the housing ownership structure. Finally, according to the results of logistic regression analysis on the impact of individual characteristics and housing ownership structure of the respondents on the residential location preferences, (1) respondents who own housings more prefer school district as residential location factor, (2) respondents their age are over 40 years old prefer safety/amenity as residential location factor, (3) respondents their immigration period are more than 10 years prefer safety/amenity as residential location factor, (4) respondents their initial immigration region are not Washington state prefer safety/amenity as residential location factor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.253-268
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• 2020

This study examined the effectiveness of policy measures in a growth management plan by analyzing empirically the influence of regulations and incentives in a non-urban growth management plan of Sejong City using the binomial logistic model. The parcel unit data related development location of Sejong City from 2012 to 2017 was used in the model. The analysis showed that time regulation in the growth management plan has a negative (-) impact on the spread of development, which means it is effective in slowing urban sprawl by lowering the profits of developers. The time regulation applied in Sejong City needs to be used actively in other cities in Korea to prevent urban sprawl. Nevertheless, floor ratio incentives had no influence in inducing development within the growth management area, which means a new incentive policy to meet the local characteristics is needed to strengthen the effectiveness of the growth management plan. This study is meaningful because it attempted an empirical analysis of the effects of the growth management plan at The National Territory Act, and this study could encourage further studies.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.173-188
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• 2017

This paper aims to analyze the effects of the residential area and personal characteristics of households on the preference of residential location factors. The main results of this study are as follows. Firstly, considering the results of multiple regression analysis, it can be seen that preference of location factors is differentiated according to the residential area and personal characteristics of households by individual location factors. Secondly, considering the results of binomial logistic regression analysis, it can be also elucidated that the preferred location factors are differentiated according to the residential area and personal characteristics of the households. Therefore, it is judged that the residential area and personal characteristics of household and the location factors of the household are mutually influencing each other.