• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1077-1085
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• 2017

In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1099-1107
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• 2017

In this study, we analyzed the determinants of wages of college graduates by using the data of "2014 Graduates Occupational Mobility Survey" conducted by Korea Employment Information Service. In general, wages contain two complex pieces of information about whether an individual is employed and the size of the wage. However, in many previous researches on wage determinants, sample selection bias tends to be generated by performing linear regression analysis using only information on wage size. We used the Heckman sample selection models for analysis to overcome this problem. The main results are summarized as follows. First, the validity of the Heckman's sample selection model is statistically significant. Male is significantly higher in both job probability and wage than female. As age increases and parents' income increases, both the probability of employment and the size of wages are higher. Finally, as the university satisfaction increases and the number of certifications acquired increased, both the probability of employment and the wage tends to increase.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1317-1325
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• 2016

The purpose of this paper is to explain the factors affecting the wage of the vocational high school graduates. We particularly examine the effectiveness of controlling sample selection bias by employing the Tobit model and Heckman sample selection model. The major results are as follows. First it is shown that the Tobit model and Heckman sample selection model controlling sample selection bias is statistically significant. Hence all the independent variables seem to be statistically consistent with the theoretical model. Second, gender was statistically significant, both in the probability of employment and the wage. Third, the employment probability and wage of Maester high school graduates were shown to be high compared to all other graduates. Fourth, the higher parent's income, the higher are both the employment probability and the wage. Finally, parents education level, high school grade, satisfaction, and a number of licenses were found to be statistically significant, both in the probability of employment and wages.

• Knowledge Management Research
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• v.24 no.4
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• pp.63-85
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• 2023

This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.

• Informatization Policy
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• v.27 no.1
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• pp.36-54
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• 2020

This study empirically analyzes the impact of digital divide between digital device usage motivation and operational skills on online political participation. The analysis was performed using the National Information Society Agency's 2018 digital divide survey data from September to December 2018 and applying the Heckman selection model to control the sample selection bias that may occur between internet users and non-users. The result shows the gap in motivation and device operational skills of individual citizens using digital devices has significant impact on online political participation. In socio-economic terms, it shows the age, education level and regional factors also have significant impact on online political participation, while gender and income levels do not. This study holds significance in that there are different patterns of digital divide between digital devices, identifying the motivation to use a digital device as an important factor for mobile device users, and the device operational skills, for personal computer users.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.733-749
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• 2018

Sample selection arises as a result of the partial observability of the outcome of interest in a study. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. Recently sample selection models for binomial and Poisson response variables have been proposed. Based on the theory of symmetry-modulated distribution, we extend these to a model for overdispersed count data. This type of data with no sample selection is often modeled using negative binomial distribution. Hence we propose a sample selection model for overdispersed count data using the negative binomial distribution. A real data application is employed. Simulation studies reveal that our estimation method based on profile log-likelihood is stable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.76-91
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• 2019

There have been many studies to examine the patterns in innovations reflecting industry-specific characteristics from an evolutionary economics perspective. The purpose of this study is to identify industry-specific differences in product innovation patterns and determinants of innovation performance. For this, Korean manufacturing is classified into high-tech industries and low-tech industries according to technology intensity. It is also pointed out that existing research does not reflect the decision-making process of firms' R&D implementations. In order to solve this problem, this study presents a Heckman sample selection model and a double-hurdle model as alternatives, and analyzes data from 1,637 firms in the 2014 Survey on Technology of SMEs. As a result, it was confirmed that the determinants and patterns of manufacturing in small and medium-size enterprise (SME) product innovation are significantly different between high-tech and low-tech industries. Also, through an extended empirical model, we found that there exist a sample selection bias and a hurdle-like threshold in the decision-making process. In this study, the industry-specific features and patterns of product innovation are examined from a multi-sided perspective, and it is meaningful that the decision-making process for manufacturing SMEs' R&D performance can be better understood.

• Journal of the Korean Regional Science Association
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• v.40 no.3
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• pp.43-61
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• 2024

The purpose of this study is to identify the difference of regional characteristics affecting 'marriage stage' and 'childbirth stage' and to compare how these factors differ between metropolitan and non-metropolitan areas using a heckman two-stage selection model. The main findings are as follows. First, regional characteristics affecting marriage stage and childbirth stage are different. Second, in the metropolitan area, regional characteristics such as population density, the proportion of female employee, and housing prices have a relatively greater impact on 'marriage', and in the non-metropolitan area, regional characteristics such as population density and unemployment rate have more impact on 'childbirth'. The empirical analysis suggests that marriage and childbirth stage need to be distinguished when establishing low fertility policies, and these approaches should be differentiated at regional level.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.57-65
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• 2019

If aging apartments are left unimproved through remodeling, the city will be eventually slum. As the government recognizes remodeling as an alternative to reconstruction, the law has been revised mainly to increase the housing area, increase the number of house and allow the vertical extension for making remodeling costs. However, the remodeling is still not activated yet in the market. Therefore, this study analyzes the decision factors of apartment remodeling in Seoul metropolitan area based on Heckman two-stage analysis considering sampling error. Research findings indicate that the decision for remodeling is determined by the characteristics of the household, housing, and time-lapse variables. And also the number of household members, net assets, housing satisfaction, the 11-20, 21-30, and more than 30 years of building are identified as the significant variables as a result of remodeling choice probability analysis. It is noteworthy that the significant variables from then remodeling cost analysis are net assets, area, more than 30 years of building, and unit housing price. It is also notable that the policy, which extend the housing area to cover remodeling cost, are not actually effective to activate the remodeling, and the age in the case of elderly people in Seoul and Gyeonggi-do who are expected to have high net assets and income is not significant variables. This study is expected to provide more objective and reliable implication to the policy makers, the home owner and the investors on the decision making process related to the remodeling project.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.427-434
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• 2018

As noted by Pavitt (1984) and Malerbar (2002), previous studies have focused on identifying differences in industry characteristics between the machinery industry and other manufacturing industries. This study considered quantitative and qualitative aspects of performance of product innovation in analyzing what factors determine those outcomes. In particular, this study examined stepwise selection processes embedded in innovation activities by applying a hurdle negative binomial model as well as the Heckman two-step selection model. Results show that factors affecting performance improvement and patents differ, and the threshold effect and the intensity effect of innovation were also distinguished. These results imply that the R&D capability should be enhanced and external innovation is required to be effectively embodied in the organization. Furthermore, motivating employees plays a pivotal role in this technology and skill-intensive sector.