• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2238-2249
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• 2015

The purpose of this study is to analyze the relations of innovation and productivity following the introduction of ICT and the effects in the process of innovative investments activity-innovation-productivity, not only by finding causes and effects. For this purpose we conducted surveys of SMEs classified into 7 categories by type of business. To put it concretely, this study was performed to find out the foactors which allow companies to secure competitiveness by enhancing of innovative measures through ICT, and to further analyze the political implications for the development of small and medium-size business by conducting an empirical analysis of the process, from the determination of innovative investments all the way through to production. Analysis model used CDM model using econometric methods such as multiple regression analysis and multinominal logit analysis to produce results. Also we established and analyzed models of innovation investment determinants, innovation determinants and productivity determinants to analyze specifically the relations between ICT and productivity.

• Journal of Intelligence and Information Systems
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• v.16 no.1
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• pp.93-116
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• 2010

Ensemble approach is applied to the detection modeling of illegal cash accommodation (ICA) that is the well-known type of fraudulent usages of credit cards in far east nations and has not been addressed in the academic literatures. The performance of fraud detection model (FDM) suffers from the imbalanced data problem, which can be remedied to some extent using an ensemble of many classifiers. It is generally accepted that ensembles of classifiers produce better accuracy than a single classifier provided there is diversity in the ensemble. Furthermore, recent researches reveal that it may be better to ensemble some selected classifiers instead of all of the classifiers at hand. For the effective detection of ICA, we adopt ensemble size reduction technique that prunes the ensemble of all classifiers using accuracy and diversity measures. The diversity in ensemble manifests itself as disagreement or ambiguity among members. Data imbalance intrinsic to FDM affects our approach for ICA detection in two ways. First, we suggest the training procedure with over-sampling methods to obtain diverse training data sets. Second, we use some variants of accuracy and diversity measures that focus on fraud class. We also dynamically calculate the diversity measure-Forward Addition and Backward Elimination. In our experiments, Neural Networks, Decision Trees and Logit Regressions are the base models as the ensemble members and the performance of homogeneous ensembles are compared with that of heterogeneous ensembles. The experimental results show that the reduced size ensemble is as accurate on average over the data-sets tested as the non-pruned version, which provides benefits in terms of its application efficiency and reduced complexity of the ensemble.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.541-549
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• 2017

This research investigates the quantitative screening methods for the Grant Funding system and seeks for the efficient evaluation of a number of proposals. We search foreign cases of Grand Funding, but we found no appropriate model for using in Korea. Thus, we had to develope our own model for better screening. First, we analyse the existing evaluation system and find some problems and challenges. Second, we suggest a quantitative screening system for Grant Funding with a numeric model, and operates a tedious simulation by using the previous data and our suggested model. Third, we test the suggested model and find the optimal model by using simulation method The number of data analysed for simulation is larger than 200 thousands. Last, we suggest some brief policy implications based on the results in the paper.

• Land and Housing Review
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• v.12 no.4
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• pp.31-40
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• 2021

In the present article we examine life-cycle housing demand for Korea. Distinguished in this work from prior research is the consideration of non-monocinity in the life-cycle housing demand. To this end, we adopt spline logistic regression models. Our findings suggest that life-cyclicity is most clear in Korean housing demand; namely, 1) small (mid-large) house ownership falls (grows) dramatically as households age into middle aged; 2) middle aged households do not participate in the rental or purchase market actively; 3) elderly population does not dispose of their housing to the same extent as younger generations acquire housing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.565-577
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• 2020

This study empirically examined how a firm size affects the determinants of innovative activities using the data of the Korean Innovation Survey (KIS) 2016. With data from 2,003 firms in the manufacturing sector, we performed logistic regression analysis and zero-inflated negative binomial regression analysis. R&D expenditure and patent applications were used as proxies for innovative activity. The independent variables included the firm's characteristics variables such as the firm's age, tech-level industry, RDemp (R&D employee ratio), venture, export, and industrial characteristics variables such as networking, appropriability, and spillovers. The empirical findings are that there are some differences in firms' innovative activity determinants among the firms' size groups. Next, strategic appropriability has negative impacts on small firms' R&D expenditure and medium-firms' patents. Networking is an important determinant of innovative activity for all firms, except for large firms. Furthermore, in deciding R&D activities, small and medium-sized firms were significantly influenced by industrial characteristics as compared to that of large firms. Our findings suggest some R&D promotion policies. Policies fostering firms' technological interaction would allow firms to take advantage of technological spillovers and thus raise the probability of investing in R&D.

• Korea journal of population studies
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• v.29 no.1
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• pp.57-70
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• 2006

Patterns and changes of marriage have drawn much attention as they have been pointed out a key factor of low fertility. Nonetheless, systematic studies on marriage have been quite limited. This study, using recent nationwide survey on marriage and fertility, attempts to explain whether and how intention of marriage would differ between never married men and never married women. The logit regression analysis reveals that the likelihood of planning marriage between both sexes are still different even after controlling demographic characteristics, economic status, household and family background, and attitudes toward sex and premarital cohabitation. Furthermore, important factors affecting the likelihood of planning marriage turns out to be different between men and women. For instance, men with a job is more likely than men without a job to plan marriage. However, for women, the effect of having a job is not found. Such result, with other sex differential effects of living arrangement and attitudinal variable, suggests that the mechanism through which men and women transit from singlehood to marriage would differ. More attention on gender differential should be paid in developing conceptual arguments and conducting empirical analysis regarding marriage and its related topics.

• Land and Housing Review
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• v.13 no.1
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• pp.55-65
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• 2022

This paper investigates the distinct characteristics of freehold and leasehold households living in the seven largest cities and the other areas. We employ the two-stage logit regression analysis to identify the marginal effects of wealth and income after controlling for the other one. We document the following results. First, households with more net wealth are more likely to reside in their own houses, regardless of living areas. Second, the pure income effect after controlling for wealth and other variables lowers the tendency of freeholders to live in the seven largest cities while increasing the tendency to live in the other areas. Furthermore, the income effects reduce the tendency to live in the former regions. Our results suggest that the pure income effects enhance preferences for a better living environment (e.g., larger spaces, better school districts, etc.), whereas the wealth effect increases the likelihood of freeholds.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.92-105
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• 2020

This study was aimed to identify factors affecting the purchase of indemnity private health insurance and analyze its effect on healthcare utilization by gender. This study analyzed data of the 2010-2016 Korea Health Panel Survey using panel logit model and panel regression model. Men were less likely to purchase indemnity private health insurance than women. Self-rated health and unmet need for healthcare in women were related to insurance purchases. In men, married people and residents of the metropolitan area were more likely to purchase. The indemnity private health insurance did not affect the women's outpatient expenses per visit, but for men it increased. The indemnity private health insurance significantly increased women's inpatient expenses per admission, but it did not affect men's inpatient expenses. This study confirmed gender differences in the factors affecting the purchase of indemnity health insurance and the impact of indemnity health insurance on healthcare utilization. This suggests that gender differences should be taken into account in private health insurance research and institutional operation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.232-241
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• 2019

This study examines one of the conventional and controversial issues in modern finance. Specifically, this study identifies financial determinants of corporate R&D intensity for firms belonging to Korean Chaebols. Empirical estimation procedures are applied to derive more robust results of each hypothesis test. Static panel data, Tobit regression and stepwise regression models are employed to obtain significant financial factors of R&D expenditures, while logit, probit and complementary log-log regression models are used to detect financial differences between Chaebol firms and their counterparts not classified as Chaebols. Study results found the level of R&D intensity in the prior fiscal year, market-value based leverage ratio and firm size empirically showed their significance to account for corporate R&D intensity in the first hypothesis test, whereas the majority of explanatory variables had important power on a relative basis. Assuming that the current circumstances in the domestic capital market may necessitate gradual changes of Korean Chaebols in terms of their socio-economic function, the results of this study are expected to contribute to identifying financial antecedents that can be beneficial to attain optimal level of corporate R&D expenditures for Chaebol firms on a virtuous cycle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.248-258
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• 2021

The study analyzed the financial determinants of corporate R&D intensity that require more attention from academics and practitioners in the Korean capital market. Domestic small and medium enterprises (SMEs) may face with developing substitutes by making more R&D investments in scale and scope, given the unprecedented economic conditions such as the limitation of importing core components and materials from other nation(s). KOSDAQ-listed SMEs were selected as sample data, whose R&D expenditures may be less than those of large firms during the post-global financial turmoil period (2010~2018). Static panel data model was applied, along with Tobit and stepwise regression models, for examining the validity of results. Logit, probit, and complementary log-log regressions were also employed for a relative analysis. R&D expenditures in the prior year, the interaction effect between the previous R&D intensity and high-tech sector, firm size, and growth rate were significant to determine R&D intensity. Moreover, a majority of explanatory variables were found to change between the years 2011 and 2018, while time-lagged effects between the R&D intensity and growth rate exist. Results of the study are expected to be used for future research to detect optimal levels of R&D expenditures for the value maximization of SMEs.