• Journal of vocational education research
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• v.35 no.4
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• pp.47-61
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• 2016

The purpose of this study is to analyze student and university features affecting outcome in labor market after university graduates. For accomplish this, multi-level analysis modeling with HLM(Hierarchical Linear Modeling) was adopted. GOMS(Graduates Occupational Mobility Survey) 2013 data were used for this study, and we added the Information Service of Education data for university information. The result of analysis were as follows. (a) Factors affecting outcome in labor market after university graduate were both student and university features. Significant features were house income, gender, academic major, GPA, and satisfaction in view point of student level. In university level, there were significant variables likes foundation, location, education costs, school type, and satisfaction. (b) We found the different significant variables between student and school level in the participations on the university career program. Significant features were job-experience and job-exhibition in student level, but there were no significant after adding variable in school level. In the school level, there were significant in subjects related career and job, job-exhibition, and consulting.

• Korean Journal of Social Welfare
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• v.61 no.3
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• pp.103-127
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• 2009

This study examined the relationships among the case management implementation factors, client satisfaction and quality of life among the persons with mental illness. The survey and interviews were conducted to the 18 community-based mental health service agencies which were implementing case management, and the 381 mentally ill persons who were living in the community and were receiving services from the agencies. The path analysis and the hierarchical linear modeling were used to examine the association among the independent, mediator, and dependent variables. The major finding of this study were that the caseload had the direct relationship with the quality of life. The case management team approach had the direct relationship with the client satisfaction. The suggestions were made that more focus should be on the maintenance of the appropriate caseload, the increase of the number of the case manager, and the team approach.

• International Area Studies Review
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• v.21 no.4
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• pp.173-194
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• 2017

The research study conducted logistics regression analysis through HLM (Hierarchical Linear Modeling) and presented the value of the outcome in order to investigate characteristic factors of demanders which influence the intention to move into public rental housing. (1) The results of the regression analysis of characteristic factors of household and housing were analyzed as having the significant effect on the intention to move in public rental housing, according to residents moving in monthly rent housing, residents' occupations, rental housing, the number of household, the location of surrounding public rental housing, monthly average income, children's educational level, the number of children, the types of housing and one's own house, in order, out of the types of housing tenure. (2) The results of the regression analysis of characteristic factors of the conditions of location were analyzed that out of the conditions of location of the top five areas in public rental rates, what influences significant effects on the intention to move in public rental housing is the location of surrounding rental housing, income, the number of household and children, children's educational level, job state, housing types, ones' own house, rent housing, monthly rent housing, in order. (3) In case of Seoul, Expanding public rental housing is inevitable in order to stabilize ordinary people's housing stability, owing to the high and rental prices of private housing. Nevertheless, an accurate analysis of the intention to move in public rental housing has not been conducted. Eventually, the research was, thus, conducted, based on the fact that the preference on public housing is low. According to the analytic results of the study, it is required for the government institutions and agencies should consider individual and local characteristics and provide an alternative that meets the real situation, in order to help ordinary citizens with low incomes stabilize housing.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.29-34
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• 2008

This study examines the effects of information and communication technologies on individual performance. The literature has paid a considerable amount of attention to social influence as a determinant of individual behavior. We combine task-technology fit with concepts from adaptive structuration theory to specify social influence. In our model, we suggest that individuals should receive support from proper social construction to have additional performance improvement. Empirical data from 317 individuals across 43 teams in 10 companies is used to assess the theoretical model. Our theoretical model received support from the data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.625-631
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• 2021

This study examined the effects of self-critical perfectionism on organizational citizenship behavior (OCB) and the moderating effects of gender in the relationship to understand deeply the dilemmatic situation resulting from OCB at the individual level. In other words, based on the conservation of resources theory, this study examined how self-critical perfectionism influences the OCB and how gender moderates the relationship between self-critical perfectionism and OCB. More specifically, this study predicts that self-perfectionism will be negatively related to OCB. Furthermore, this negative relationship between self-critical perfectionism and OCB will be strengthened in men compared to women. To test these hypotheses, the supervisor-subordinate survey was conducted, and 150 dyad data were analyzed. The analytical results of HLM (Hierarchical Linear Modeling) showed that self-critical perfectionism negatively influenced the OCB, and this negative effect was strengthened in men compared to women. This paper suggests implications and limitations for the literature on OCB.

• The Journal of Korean Academic Society of Nursing Education
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• v.28 no.1
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• pp.91-100
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• 2022

Purpose: This study aimed to identify the longitudinal effects of children's temperament on maternal depression. Methods: Data from a longitudinal cohort of the Panel Study of Korean Children (PSKC) from 2010 to 2012 were analyzed using hierarchical linear modeling. The survey included 1,721 mother-child dyads. The mothers reported on their children's temperament and on maternal depression. The children's temperament was measured by the Emotionality, Activity and Sociability-Temperament Survey for Children-Parental Ratings, while maternal depression was measured by the Kessler 6 Psychological Distress Scale. Results: The results showed that both children's temperament and maternal depression were relatively stable when the children were between the ages of 2 to 4. The mean maternal depression scores were 11.83 in 2010, 11.88 in 2011, and 11.75 in 2012. There were significant negative correlations between the maternal depression scores and children's ages, and sociability and activity subdomain scores ranged from r=-.05 to -.11 (p<.05). There was a significant positive correlation between children's emotionality subdomain scores and maternal depression scores (r=.35, p<.001). Children's temperament rament (emotionality: β=0.26, activity: β=-0.07, and sociability: β=-0.03) were significant factors in maternal depression. Conclusion: These findings indicate the need for the early assessment of and intervention for children's temperament and maternal depression. The results of this study will provide basic data for the development of nursing education programs related to early assessment and intervention to improve the health and quality of life of young children and mothers.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.88-95
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• 2003

A firm's business composition and the sales volume of each business segment are subject to change depending, to a considerable extent, on the firm's business strategy. These changes were weighted and represented as a single index, referred to by scholars in strategic management and industrial organization research fields as 'firm entropy' then its impact on firms' profitability was assessed over twelve years. The performance differences between contractor and non-contractor firms, as well as focused and diversified firms, were compared through a Longitudinal Data Analysis Technique within a Hierarchical Linear Modeling framework. Hypothesis was formulated based on firm diversification theories and previous research findings. The hypothesis was tested according to the modeling outcomes, and implications are presented. The research findings indicate that the level of firms' long-term profitability supports the argument that the construction industry is highly competitive and mature.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.93-109
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• 2013

Geostatistical data or point-referenced data have the information on the monitoring stations of interest where the observations are measured. Practical geostatistical data are obtained from a wide variety of observational monitoring networks that are mainly operated by the Korean government. When we analyze geostatistical data and predict the expectations at unobservable locations, we can improve the reliability of the prediction by utilizing some relevant spatial data obtained from different observational monitoring networks and blend them with the measurements of our main interest. In this paper, we consider the hierarchical spatial linear model that enables us to link spatial variables from different resources but with similar patterns and guarantee the precision of the prediction. We compare the proposed model to a classical linear regression model and simple kriging in terms of some information criteria and one-leave-out cross-validation. Real application deals with Sulfur Dioxide($SO_2$) measurements from the urban air pollution monitoring network and wind speed data from the surface observation network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.4_1
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• pp.67-76
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• 1992

A hierarchical formulation based on p-version of the finite element method for linear elastic axisymmetric stress analysis is presented. This is accomplished by introducing additional nodal variables in the element displacement approximation on the basis of integrals of Legendre polynomials. Since the displacement approximation is hierarchical, the resulting element stiffness matrix and equivalent nodal load vectors are hierarchical also. The merits of the propoosed element are as follow: i) improved conditioning, ii) ease of joining finite elements of different polynomial order, and iii) utilizing previous solutions and computation when attempting a refinement. Numerical examples are presented to demonstrate the accuracy, efficiency, modeling convenience, robustness and overall superiority of the present formulation. The results obtained from the present formulation are also compared with those available in the literature as well as with the analytical solutions.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.453-470
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• 2013

In this paper, we consider a Bayesian analysis of the dose-effect relationship of cadmium to evaluate a benchmark dose(BMD). For this purpose, two dose-response curves commonly used in the toxicity study are fitted based on Bayesian methods to the data collected from the scientific literature on cadmium toxicity. Specifically, Bayesian meta-analysis and hierarchical modeling build an overall dose-effect relationship that use a piecewise linear model and Hill model, where the inter-study heterogeneity and inter-individual variability of dose and effect such as gender, age and ethnicity are accounted. Estimation of the unknown parameters is made by using a Markov chain Monte Carlo algorithm based user-friendly software WinBUGS. Benchmark dose estimates are evaluated for various cut-offs and compared with different tested subpopulations with with gender, age and ethnicity based on these two Bayesian hierarchical models.