• Journal of the Economic Geographical Society of Korea
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• v.26 no.4
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• pp.421-442
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• 2023

This research focuses on the fact that the characteristics of migration types of the youth in non-metropolitan areas vary by region and has the primary objective of comparing and analyzing the differences in determinants of each migration type. First, An exploratory analysis of the migration status and characteristics of the youth in non-metropolitan areas was conducted, and then a hierarchical logit model was used to estimate the determinants of migration types separately. The results showed that the characteristics of migration types vary by region, and each determinant of migration types is composed of different bundles of variables(individual and regional levels). In the future, policies aimed at securing young workforce in non-metropolitan areas will be more effective when they take into account various determinants of migration choices and reflect the regional context.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.119-127
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• 2009

It has been known that bus route and company related characteristics have influences on punctuality, but fewer research have been conducted. Independent variables used in this study were selected using correlation analysis, and OLS(Ordinary Least Square) and HLM(Hierarchical Linear Model) were employed to identify factors affecting bus punctuality(headway deviation). The results showed that ICC(intraclass Correlation Coefficient) is 0.10, indicating that hierarchical linear models are more adequate for these data because there is effective variation in the subjects between companies. Punctuality was found to be negatively associated with the number of vehicles, the number of persons per vehicle, and total travel time. On the other hand, average headway and company size have a positive relationship with punctuality. Therefore, the number of vehicles per route, average headway, and the number of vehicles managed by a company should be considered for more accurately evaluating the management of piunctuality.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.627-644
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• 2009

In the knowledge-based economy highlighting the importance of human capital, there has been a growing interest in human capital externalities as a fundamental engine of growth and development of a region. The purpose of this study is to analyze human capital externalities using 3-level hierarchical linear model(3-HLM), decomposing determinants of wages into three levels involving workers(level-1) nested within firms(level-2) nested within regions(level-3). This study separately estimates the effect of the average education level on the wages by three different schooling groups on the assumption that the intensity of knowledge spillovers varies with each group's schooling level. The main results are as follows; First, the coefficient of the average education level of a region shows 0.044, indicating that one-year increase in the average level of schooling could increase average individual earnings by 4.4%. Secondly, the external effects of human capital on three different schooling groups are considerably different, raising less than high school graduates' wages by 3.0%, college graduates' wages by 4.7%, and graduate schools' wages by 11.8%, respectively. Thirdly, well educated workers are much more sensitive to the variation of the regional education level than less educated ones when we apply the shares of each schooling group as alternative measures for the average level of education. Such findings of this study draw an implication that local governments could speed up regional economic growth in the knowledge-based economy by not only raising total human capital stock in a region but building the close networks that promote productivity-enhancing human capital external effects.

• Journal of Korean Society of Transportation
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• v.6 no.2
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• pp.57-82
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• 1988

본 연구는 도시규모 결정에 관해 수요 또는 공급측면만을 중시하는 재래식 접근 방 법을 통합, 개선하는 일반균형의 모형을 제시하고 이에 따라 국가 도시규모체계의 효율성을 이해하는데 그 목적이 있다. 이 모형의 주요한 요소는 도시집적이익 및 불이익, 산업구조 그 리고 도시간 자원이동 및 무역을 통한 상호의존성 등이다. 엄밀한 이론적, 절대적 적정 도시 규모체계는 모든 도시가 완전자립 하에 단위도시 적정규모를 이루어 동일규모일 때 가능하 며 시민의 복지가 극대화된다. 그러나 실제 인적, 물적 이동성이 완벽하지 않은 현실 하에서 는 도시규모간 위계성이 생기게 되며 이는 도시간 무역을 가능케하여 상대적 도시규모의 적 정성을 대변해 준다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.12-28
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• 2019

Road geometry is one of the many factors that cause crashes, but the effect on traffic accident depends on weather conditions even under the same road geometry. This study identifies the variables affecting the crash severity by matching the highway accident data and weather data for 14 years from 2001 to 2014. A hierarchical ordered Logit model is used to reflect the effects of road geometry and weather condition interactions on crash severity, as well as the correlation between individual crashes in a region. Among the hierarchical models, we apply a random intercept model including interaction variables between road geometry and weather condition and a random coefficient model including regional weather characteristics as upper-level variables. As a result, it is confirmed that the effects of toll, ramp, downhill slope of 3% or more, and concrete barrier on the crash severity vary depending on weather conditions. It also shows that the combined effects of road geometry and weather conditions may not be linear depending on rainfall or snowfall levels. Finally, we suggest safety improvement measures based on the results of this study, which are expected to reduce the severity of traffic accidents in the future.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.695-704
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• 2020

Recently, There has been an increasing of utilization IT, and studies have been conducted on predicting learning results. In this study, Learning activity data were collected that could affect learning outcomes by using learning analysis. The survey was conducted at a university in South Chung-Cheong Province from October to December 2018, with 1,062 students taking part in the survey. First, A Hierarchical regression analysis was conducted by organizing a model of individual, academic, and behavioral factors for learning results to ensure the validity of predictors in machine learning. The model of hierarchical regression was significant, and the explanatory power (R²) was shown to increase step by step, so the variables injected were appropriate. In addition, The linear regression analysis method of machine learning was used to determine how predictable learning outcomes are, and its error rate was collected at about 8.4%.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.957-970
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• 2015

The purpose of this study was to analyze records of Korean pro-basketball using general linear model (two-way ANOVA and hierarchical multiple regression analysis). Korea Basketball League (KBL) informed the records (2014-2015 season) of this study. The eight variables (TA, 2PA, 3PA, 2P, 3P, Ast, TFB, CH) were selected in content validity. SPSS program was used to analyze general linear model. All alpha level was set at 0.05. Major results were as follow. 3PA had significant interaction effect between victory & defeat variable and home & away variable. Victory teams showed that 3PA was higher in home games than away games, and defeat teams was the other. 2PA, AS, TFB, and CH were selected significant variables affecting victory and defeat. In result of hierarchical regression, Ast had significant moderation effect between 3PA and TS. TFB also had significant moderation effect between AS between 2P. The other construct (Ast between 2PA and TS; TFB between AS between 3P) had no significant moderation effect. In the effect of 2PA, 3PA and Ast to TS, CH also had no significant moderation effect.

• Journal of the Korean housing association
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• v.25 no.6
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• pp.39-47
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• 2014

The background of this study is to examine the structure of housing price of which characteristics are not equal but hierarchical in the apartment complexes. So, the purpose of this study is to analyze the influences of apartment complex characteristics on the housing price within the same regional boundary by HLM. The data used as dependent variables were the market prices of 938 units from 29 apartment complexes by stratified sampling. The 2nd level independent variables is the Housing complex characteristics which are composed of the housing complex & locational variables and the 1st level independent variables are the unit characteristics. The results are as follows. First, the first model shows that the 2nd level variables explains 68% of the housing prices. Second, the influential variables of the 1st level unit variable are 'dwelling exclusive area', 'floor of dwelling' and 'direction of dwelling'. Third, the influential variables of the housing complex variables in the 2nd level are 'lot area', 'the building-to-land ratio', 'the number of unit', 'the number of parking lots per unit', 'Green space area' and 'open space area per unit'. The last, the influential variables of the housing locational variables in the 2nd level are 'distance to subway and park' and the number of school and park within a radius of 1km.

• Korean Journal of Social Welfare
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• v.68 no.1
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• pp.5-22
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• 2016

We examined how public social expenditure and individual socio-demographic factors affect individual voluntary activities(volunteering, giving). Hierarchical linear model(HLM) was employed to a nested data set with 37,648 individual subjects and 16 local governments in Korea. HLM analyses yield an insignificant direct effect of public expenditure to volunteering and giving, while individual factors all have significant effects on them. Finally, this study discussed why public social expenditure factor does not have significant influence in this data, and suggested policy implications for promoting volunteering and giving.

• Journal of the Society of Disaster Information
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• v.11 no.4
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• pp.506-514
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• 2015

In this study, a new analytical techniques is proposed for seeking policy alternatives aimed at objectives of TDM, increasing the transit rideshare. Determinants of travel mode such as personal characteristics, lifestyle, and urban spatial characteristics are interdependent and have combined effect on decision. In addition, individuals, groups, and regional characteristics have interdependencies at different levels. Unlike traditional regression analysis, hierarchical analysis model has the advantage of identifying interdependencies and complex relationship between the combined impact factors. This analysis technique is expected to be a significant contribution to seek a more efficient TOD policy.