• Journal of Korean Port Research
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• v.12 no.1
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• pp.55-64
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• 1998

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

• Journal of the Korean Regional Science Association
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• v.37 no.1
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• pp.15-27
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• 2021

This study investigates the difference in income trajectories of the working poor and the non-working poor and explains the effects of socio-demographic (marriage, education) and regional (living in large cities) factors on intergroup differences. We use Seoul Survey data collected between 2009-2018 and the latent growth modeling approach. It was found that the trajectory difference between groups was statistically significant. Since 2016, the income gap widened as the income of the working poor stagnated. The three variables included in this model better explained the income trajectory of the working poor compared to the working non-poor. In particular, the change in income growth rate was positively related to whether they live in large cities. This suggests the possibility that living in a large city would act as an economic premium for the working poor. It is necessary to conduct follow-up studies on urban premiums for the working poor.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.721-732
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• 2008

The purpose of this study is to explore latent variables that affect users' satisfaction of mobile internet and to estimate a composite relationships among parameters. In order to examine causative significance between dependent variables and each of the independent variables, we redefined the variables, the quality of information, system and service derived from the DeLone and McLean's model. And we found out the new independent variables: security and service charge. Prior research adopted mainly TAM(Technology Acceptance Model) to investigate the user acceptance of information services or system. Therefore, it is significant that we developed our research model to appropriate on mobile internet's inherent nature and that focused on the important variables like service charge and security. In empirical approach, we surveyed 435 samples and conducted structural equation modeling and multi-regression analysis to estimate the regression parameters. The results of the study illustrated that our hypotheses covering the quality of information, system and service, security and service charge were supported.

• KDI Journal of Economic Policy
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• v.39 no.3
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• pp.43-62
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• 2017

This paper proposes an integrated risk-management framework that includes 1) measuring the risk of credit portfolios, 2) implementing a (macro) stress test, and 3) setting risk limits using the estimated systematic latent factor specific to capture the housing market cycle. To this end, we extract information from a set of real-estate market variables based on the FAVAR methodology proposed by Bernanke, Boivin and Eliasz (2005). Then, we show the method by which the estimated systematic factor is applied to risk management in the housing market in an integrated manner within the Vasicek one-factor credit model. The proposed methodology is well fitted to analyze the risk of slow-moving and low-defaultable forms of capital, such as alternative investments.

• 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 the Korean Statistical Society
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• v.30 no.4
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• pp.613-635
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• 2001

This paper proposes a skewed multivariate probit model for analyzing a correlated binary response data with covariates. The proposed model is formulated by introducing an asymmetric link based upon a skewed multivariate normal distribution. The model connected to the asymmetric multivariate link, allows for flexible modeling of the correlation structure among binary responses and straightforward interpretation of the parameters. However, complex likelihood function of the model prevents us from fitting and analyzing the model analytically. Simulation-based Bayesian inference methodologies are provided to overcome the problem. We examine the suggested methods through two data sets in order to demonstrate their performances.

• Journal of the Korean Society of Safety
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• v.34 no.6
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• pp.58-64
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• 2019

Over the past decades there has been a growing body of researches that examines the psychological traits related to safety outcomes. After briefly reviewing the relationships between psychological dispositions and safety outcomes, we empirically examine the relationships with 2 samples of 1,102 participants. Fifteen psychological dispositions (big 5 personality, locus of control, cognitive failure, affection from job and relations, 4 achievement goal orientations, self-efficacy, fatigue, and depression) and four psychological outcomes (safe behavior, unsafe behavior, accidents, and injuries) are examined. After covariance structure modeling variances of safety outcomes are well explained by simple 4 dispositions of consciousness, mastery-approach goal orientation, self-efficacy, and depression. We name them 'core safety disposition', and name four psychological outcomes 'safety consciousness', and the relationships between those latent variables are stronger than between measurement variables. We propose core safety disposition as a cause of safety consciousness, and discuss implications for research and practices.

• The Journal of Information Systems
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• v.26 no.3
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• pp.211-228
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• 2017

Purpose This study proposes a research model based on Expectation-Confirmation theory in order to investigate impacts of three variables(expectation confirmation, social interaction, and perceived usefulness) on continuous intention to uss SNS in MICE industry. Design/methodology/approach A survey approach was used in order to measure each latent variable in the research model. A total of 140 responses were collected from actual users of SNS in MICE industry. A structural equation modeling with SmartPLS 2.0 was conducted in order to analyze each relationship in the proposed research model. Findings The results indicated the expectation confirmation had a positive impact on the perceived usefulness, social interaction, and satisfaction. Second, perceived usefulness had a significant positive impact on satisfaction and continuous intention to use SNS in MICE industry. Thrid, social interaction had a positive influence on both satisfaction and continuous intention to use SNS in MICE industry. Finally, the relationship between satisfaction and continuous intention in SNS of MICE industry was fully supported.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.897-911
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• 2021

This study aims to analyze the important role of business analytics capability, information quality, and innovation capability in influencing organization agility and organization performance during the Covid-19 pandemic. Data was collected from 76 companies from various sectors in Indonesia. Structural Equation Model-Partial Least Square (SEM-PLS) analysis was conducted to analyze the relationship between variables and test a series of hypotheses. Importance-Performance Matrix Analysis (IPMA), a useful analysis approach in PLS-SEM, is used, which extends the results of the estimated path coefficient (importance) by adding a dimension that considers the average values of the latent variable scores (performance). The IPMA approach examines not only the performance of an item but also the importance of that item. The results show that business analytics capability has a significant effect on information quality and innovation capability which then affects organization agility. Organizational performance is influenced by organizational agility. IPMA results show that organizational agility has the highest level of impact on organizational performance. This study will assist companies in planning business analytics, improving information quality, increasing innovation capability, and ultimately increasing agility and performance during the Covid-19 pandemic. This study will add to existing knowledge about previous literature, especially in the Covid-19 pandemic situation.

• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.22-29
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• 2008

The objective of this study is to provide useful information for the establishment of efficient policy implementation strategies of forest road construction policy in South Korea. Data needed for the analysis was collected by a questionnaire survey. For the analysis, policy evaluation model was constructed based on theories of public policy. Evaluation model contains three independent variables (policy initiative factor, policy content, policy environment) and two dependent variables (policy result, policy impact). Since, these variables are unobservable latent variables, observable indicators are needed as proxy measures. LISREL (Linear Structural Relationships) was employed for the analysis since it is a useful measure for analysing linear structural model which consists of structural and measurement equations. It was confirmed that forest road construction is an effective policy mean for the development of rural region and activating forest resources management. The policy outcome, however, was not satisfactory. To improve the effectiveness of forest road construction policy some modification of policy contents are needed such as increased construction budget, allowing more flexibility and participation to the implementation personal and providing technical support.