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      국내 도시쇠퇴와 교통사고 분석 및 논의 = Analysis and Discussion of urban decline and traffic accident in Korea

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      https://www.riss.kr/link?id=A106020947

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      다국어 초록 (Multilingual Abstract)

      Since 1960s, such the urban problems as industry decay, doughnut phenomenon, traffic accident and others come from fast urbanization and industrialization. The purpose of this study is to analyze and discuss the relations between urban decline and traffic accident. In order to develop the models, 2007-2015 accident data from TAAS (traffic accident analysis system) and urban decline data from urban regeneration information system are collected. The main results are the followings. First, the null hypotheses that there are no differences in number of accidents and accident densities by region (Si, Gun and Gu) are rejected. Second, 4 negative binomial (count data) models (Rho-squares of 0.239~0.346) and 4 multiple linear regression models (R-squares of 0.613~0.714) which are all statistically significant are developed. Finally, the main explanatory variables are analyzed to be ratio of elderly people, elderly person living alone, employment, ratio of manufactural employment and wholesale/retail employment. This study can be expected to give some implications to making regional accident reduction policy.
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      Since 1960s, such the urban problems as industry decay, doughnut phenomenon, traffic accident and others come from fast urbanization and industrialization. The purpose of this study is to analyze and discuss the relations between urban decline and tra...

      Since 1960s, such the urban problems as industry decay, doughnut phenomenon, traffic accident and others come from fast urbanization and industrialization. The purpose of this study is to analyze and discuss the relations between urban decline and traffic accident. In order to develop the models, 2007-2015 accident data from TAAS (traffic accident analysis system) and urban decline data from urban regeneration information system are collected. The main results are the followings. First, the null hypotheses that there are no differences in number of accidents and accident densities by region (Si, Gun and Gu) are rejected. Second, 4 negative binomial (count data) models (Rho-squares of 0.239~0.346) and 4 multiple linear regression models (R-squares of 0.613~0.714) which are all statistically significant are developed. Finally, the main explanatory variables are analyzed to be ratio of elderly people, elderly person living alone, employment, ratio of manufactural employment and wholesale/retail employment. This study can be expected to give some implications to making regional accident reduction policy.

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