• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.251-276
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• 2014

This study scrutinizes the common sense in the field of disability employment that the bigger the size of a firm, the lower the employment rate of people with disabilities. This common sense has been established by conventional cross-tabulation and multiple regression analyses without taking into account possible interactions between the sizes of firms and the industries in which they operate. This study shows that the distribution of the disability employment rate violates the linearity and homoscedasticity assumptions of the OLS. In an effort to find models that explain the data better, this study fits the OLS model, the weighted linear regression model, and the multinomial logit model as well as the path analysis which is meant to examine the relationships between firm size and other variables relevant to disability employment. The result shows that, when an interaction term between firm size and industry is added to the model, firm size does not have any significant effect on disability employment rate for those firms with 100 or more regular employees, to the contrary of the findings of prior studies. It also demonstrates that other factors such as job setting, the extent of helpfulness of disability employment employers perceive, employers' care for disability, and employers' awareness of disability policies may matter more than does firm size. This study proposes that future research and policy implementation for disability employment should pay no less attention to industry and other factors mentioned above than to firm size.

• Korean Security Journal
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• no.39
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• pp.217-239
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• 2014

The purpose of this study is to compare with three juvenile delinquency theories on adolescents' status offenses including Hirschi's social bonding theory, Agnew's general strain theory, and Akers' social learning theory. The data derived from a sample of 2,337 middle school students taken from National Youth Policy Institute in 2011-2012. Multiple OLS regression analysis revealed that variables from social learning theory were strongly supported as an explanation for adolescents' status offenses, while variables from general strain theory were not supported. The social learning model explained 12.0% of the variance in adolescents' status offenses. However, general strain variables explained 2.6% of the variance in the dependant variable and 6.2% of the variance in adolescents' status offenses were explained by the social bonding variables. The present research made important contributions the further utilization of social learning in investigating many of the damaging forms of social deviance which exist in our society.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.917-934
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• 2014

Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.794-807
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• 2021

The purpose of this study is to examine the effect of family poverty on the school adjustment of multi-cultural adolescents in Korea. For this purpose, the 7th data of Multi-cultural Adolescents Panel Study(MAPS) was used and the OLS multiple regression models ware applied. to the analyses. From the result of the OLS model analyses, we found out that family poverty affect significantly on the school adjustment of multi-cultural adolescents. Especially, family poverty has the significant negative(-) effects on academic achievement and friend relationships. These results of this study show that family poverty is an important factor influencing the school adjustment of multi-cultural adolescents. And they confirm that family poverty during period of the adolescent has an important meaning and influence on the aspect of school adjustment as to the multi-cultural adolescents. Implications of this study may be that policy attentions are necessary to not only multi-cultural characteristics but also family background such as poverty in oder to improve the school adjustment of the multi-cultural adolescents. In addition, results of this study suggest that more special support and interventions are requested to the multi-cultural adolescents from poverty families who are suffering dual difficulties such as multi-cultural problems and poverty problem.

• 한국노년학
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• v.27 no.2
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• pp.393-408
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• 2007

This study examines the impact of retirement on psychological well-being of the elderly and identifies whether associative factors of psychological well-being differ between retired and non-retired persons. Psychological well-being is measured by the PGCMS developed by Lawton. The sample includes 1,625 older adults aged 60 and over, which derived from the cross-sectional data of the "Aging and the Quality of Life of the Elderly in Korea: A Longitudinal Study" living in Seoul and Chuncheon in 2003. Multivariate OLS regression results show that retirement is not associated with psychological well-being after controlling socio-demographic characteristics, economic status, health status, family and social relations, participation in social activities, and satisfaction with hobbies and learning needs. Also, associative factors of psychological well-being differ between retired and non-retired persons. For retired persons, greater social activities and higher satisfaction with hobbies are associated with the higher level of psychological well-being whereas higher satisfaction with learning needs has a positive relationship with the higher level of psychological well-being for non-retired persons. Discussion and implications of the findings are presented, and limitations of this study are acknowledged.

• Korean Journal of Construction Engineering and Management
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• v.13 no.2
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• pp.128-136
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• 2012

In this study, we investigated the macroeconomic variables that affect housing prices thus creating a large impact on people's lives as well as the real estate market. For the study, the macroeconomic variables able to influence the House Rental Price (housing price by lease or deposit) were used for an analysis as follows: housing sales price index, household loans rate, total household savings, the number of employees and a multiple regression analysis was performed using a time series for each macroeconomic variable. As a result of the analysis, the House Rental Price was affected by all of four macroeconomic variables. The House Rental Price increased as each variable enlarged. In conclusion, this study may be useful for finding a solution for stabilizing the House Rental Price as well as for the establishment of efficient and sustainable policies for the housing market.

• 한국노년학
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• v.32 no.3
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• pp.777-800
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• 2012

This paper aims to estimate the effects of environmental variables on volunteering among older persons and decide relationships between independent and dependent variables. The thesis conceptually points out that the integrated theory of resources too much emphasizes the important roles of human, social and cultural capital, but overlooks the influences of ecological environments in explaining volunteering among the older persons. And the thesis tries to apply the general ecological theory of aging to explaining volunteering of older people together with resource frameworks, and to estimate the effects of ecological environment variables on volunteerism for senior citizens. Using a micro data of 2009 National Social Survey by Statistics Korea, the paper screens out 10,268 subjects who are believed to socially retire and be above 55 years older. The multiple OLS regression and binomial logistic regression techniques are used to estimate the effects of ecological environments and resources on volunteering. The analysis results show that all of environmental and resource variables are related to volunteering at the level of p<.000. This means that environmental variables have independent effects on the volunteerism, controlling for resource variables. This results suggest that both theories have empirical evidences in explaining volunteerism in Korea. Also, at the end of paper, theoretical and policy implications for practices and future studies are discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.281-293
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• 2020

Recently, large and small fires have been happening more often in Korea. Fire is one of the most frequent disasters along with traffic accidents in korean cities, and this frequency is closely related to the land use and the type of facilities. Therefore, in this study, the significance of fires was analyzed by considering land use, facility types, human and social factors and using 10 years of fire data in Jinju city. Based on this, OLS (Ordinary Least Square) regression analysis, SLM (Spatial Lag Model) and SEM (Spatial Error Model) using space weights, were compared and analyzed considering the location of the fire and each factor, then a statistical model with high suitability was presented. As a result, LISA analysis of spatial distribution patterns of fires in Jinju city was conducted, and it was proved that the frequency of fires was high in the order as follow, central commercial area, industrial area and residential area. Multiple regression analysis was performed by integrating demographic, social, and physical variables. Therefore, the three models were compared and analyzed by applying spatial weighting to the derived factors. As a result of the significance test, the spatial error model was analyzed to be the most significant. The facilities that have the highest correlation with fire occurrence were second type neighborhood facilities, followed by detached house, first type neighborhood facilities, number of households, and sales facilities. The results of this study are expected to be used as significant data to identify factors and manage fire safety in urban areas. Also, through the analysis of the standard deviation ellipsoid, the distribution characteristics of each facility in the residential area, industrial area, and central commercial area among the use areas were analyzed. In, the second type neighborhood facility with the highest fire risk was concentrated in the center. The results of these studies are expected to be used as useful data for identifying factors and managing fire safety in urban areas.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.935-946
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• 2016

In this paper, we analyzed wage determinants of the vocational high school graduates utilizing both individual-level and work region-level variables. We formulate the models in the way wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and work region-level (level-2) variables. To incorporate dependency between individual wages into the model, we utilize hierarchical linear model (HLM). The major results are as follows. First, it is shown that the HLM model is better than the OLS regression models which do not take level-1 and level-2 variables simultaneously into account. Second, random effects on sex, maester dummy and engineering dummy variables are statistically significant. Third, the fixed effects on business hours and mean wage of regular job for level-2 variables are statistically significant effect individual-level wages. Finally, parental education level, parental income, number of licenses and high school grade are statistically significant for higher individual-level wages.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.