• Journal of Korea Technology Innovation Society
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• v.21 no.1
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• pp.385-419
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• 2018

This study suggests an integrated model composed of factors of industrial environments and technology capacity for corporate diversification decision based on industrial organization theory and resource based perspectives. We examine the proposed model using patents and financial data of 272 applicants for 6 years (2010~2015) in the smart factory ICT convergence technology (application and platform field) sectors. The result of analyzing the fixed effect panel model shows that technological competitiveness has a positive effect on corporate diversification. Also, the additional result of analyzing the two-stage least square fixed effect model indicates that the convergence patent ratio increases technological competitiveness. Based on the results, we provide implications for corporate diversification strategies and government R & D policies for commercialization of corporate convergence technology resources and competencies.

• Journal of Distribution Science
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• v.18 no.1
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• pp.71-83
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• 2020

Purpose: Because the energy consumption, economic growth and logistics development are still the heated topics which have attracted many scholars' interests. Therefore, this paper attempts to analyze the effect of logistics development on the economic growth, explore the effect of the economic growth on energy consumption and to discuss the effect of the logistics development on energy intensity. Research design, data and methodology: Using the panel data over the period 2000-2017 of 156 countries and employing the country & year fixed effect model, system generalized method moments and random effect model, the empirical analyses of this propositions are performed. Results: The empirical findings present that the logistics development is positively related to the economic growth. The energy consumption in the t-1 period and economic growth are positively related to the current energy consumption. The logistics development is negatively related to the energy intensity. Meanwhile, the empirical findings also indicate that there is a great difference about these effects among the four sub-samples (low income 18 countries, low middle income 49 countries, upper middle income 44 countries, high income 49 countries). Conclusions: Based on the evidences in this paper provided, we can find that these variables can affect each other.

• Safety and Health at Work
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• v.2 no.2
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• pp.148-157
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• 2011

Objectives: Although compensation for occupational injuries and diseases is guaranteed in almost all nations, countries vary greatly with respect to how they organize workers' compensation systems. In this paper, we focus on three aspects of workers' compensation insurance in Organization for Economic Cooperation and Development (OECD) countries - types of systems, employers' funding mechanisms, and coverage for injured workers - and their impacts on the actual frequencies of occupational injuries and diseases. Methods: We estimated a panel data fixed effect model with cross-country OECD and International Labor Organization data. We controlled for country fixed effects, relevant aggregate variables, and dummy variables representing the occupational accidents data source. Results: First, the use of a private insurance system is found to lower the occupational accidents. Second, the use of risk-based pricing for the payment of employer raises the occupational injuries and diseases. Finally, the wider the coverage of injured workers is, the less frequent the workplace accidents are. Conclusion: Private insurance system, fixed flat rate employers' funding mechanism, and higher coverage of compensation scheme are significantly and positively correlated with lower level of occupational accidents compared with the public insurance system, risk-based funding system, and lower coverage of compensation scheme.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.23-31
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• 2022

The study investigates the effect of trade openness on the economic growth of agricultural countries. The information of export, import, gross domestic product (GDP), Gross Fixed Capital Formation (GFCF), and population of 72 agrarian nations generated by the World Bank from 2011 until 2020 is used for data examination. Then, before panel data analysis, a preferred model is chosen from among common-effects, fixed-effects, and random effects. The best model turns out to be a fixed-effect model. The result reports that from 2011 to 2020; 16 out of 72 nations have succeeded in experiencing positive economic growth, the value of GFCF was US$ 2,859.04 billion, and later grew by 19 percent to US$ 3,393.73 billion, the population tends to increase continuously year by year, and 2 out of 72 countries experienced export plus import exceed their GDP. Moreover, trade openness is positively associated with economic growth, with a coefficient of 3.81. Besides that, an increase in GFCF may boost economic growth by approximately 3.32 percent. On the contrary, one percent additional population significantly delivers around 25.46 percent negative economic growth. To sum up, the higher intensity of products or services sold and bought abroad may enhance the economic performance.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.3
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• pp.306-320
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• 2010

Modern ultra-large container carriers can be exposed to the unprecedented springing excitation from ocean waves due to their relatively low torsional rigidity. Large deck opening on the deck of container carriers tends to cause warping distortion of hull structure under wave-induced excitation, eventually leading to the higher chance of resonance vibration between its torsional response and incoming waves. To handle this problem, a higher-order B-spline Rankine panel method and Vlasov-beam FE model was directly coupled in the time domain, and the coupled equation was solved by using an implicit iterative method. In order to capture the complicated behavior of thin-walled open section girder, a sophisticated beam-based finite element model was developed, which takes into account warping distortion and shear-on-wall effect. Then, the developed beam model was directly coupled with the time-domain Rankine panel method for hydrodynamic problem by using the fixed-point iteration method. The developed computational scheme was validated through the comparison with the frequency-domain solution on the container carrier model in linear springing regime.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.9-12
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• 2019

With the Chinese government's attention to the artificial intelligence industry, the Chinese government has invested a lot in it recently. Of course, the importance of artificial intelligence industry for China's economic development is increasingly significant. The advent of artificial intelligence boom has also triggered a large number of scientists to analyze the impact of artificial intelligence on economic growth. Therefore, this paper use 31 China's cross-province panel data to study the effect of artificial intelligence on economic growth. Via empirical analyses under a series of econometric methods such as the province and year fixed effect model, the empirical result shows that artificial intelligence has a positive and significant effect on economic growth. Namely, the artificial intelligence is a new engine for economic growth. Meanwhile, the empirical results also indicate that the investment and consumption has a significant and positive effect on economic growth. Oppositely, the inflation and government purchase have a significant negative effect on economic growth. These findings in this paper also provide some important evidences for policy-makers to perform precise behaviors so as to promote the economic growth. Moreover, these finding enriches existing literature on artificial intelligence and economic growth.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.45-60
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• 2014

We introduce a MCMC sampling for a generalized linear normal random effects model with the ordered probit link function based on latent variables from suitable truncated normal distribution. Such models have proven useful in practice and we have observed numerically reasonable results in the estimation of fixed effects when the random effect term is provided. Applications that utilize Korean Welfare Panel Study data can be difficult to model; subsequently, we find that an ordered probit model with the random effects leads to an improved analyses with more accurate and precise inferences.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3417-3426
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• 2012

This study aims to determine how ownership structure (share-holding ratio of insiders, foreigners) affects agent costs (the portion of asset efficiency or non-operating expenses) through empirical analysis. However, as existing studies on correlations between ownership structure and agent costs adopted Pooled OLS Model, this study focused on additionally formulating Fixed Effect Model and Random Effect Model aimed to reflect the time of data formation and corporate effects as study models based on verification results on the suitability of Pooled-OLS Model before comparative analysis for the purpose of improvement of credibility and statistical validity of the results of empirical analysis based on the premise that the Pooled OLS Model is not reliable enough to verify massive panel data. The data has been accumulated over 10 years from 1998 to 2007 after the IMF crisis hit the nation, from a subject 331 companies except for financial institutions. As a result of the empirical analysis, verification of the suitability of model has determined that the Random Effect Model is appropriate in terms of asset efficiency among agent costs items. On the other hand, the Fixed Effect Model is appropriate in terms of non-operating costs. As a result of the empirical analysis according to the appropriate model, no hypothesis adopted in the Pooled OLS Model has been accepted. This suggests that developing an appropriate model is more important than other factors for the purpose of generating statistically significant empirical results by showing that different empirical results are produced according to the type of empirical analysis.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.121-131
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• 2020

This study aims to investigate the interplay between education and local roads on Foreign Direct Investment (FDI) in the Philippines, using economic growth as an instrument. The study used the quantitative research design applying both descriptive and inferential statistics. A combination of Two Stage Least Square Regression Model and three approaches in Panel Regression Model such as Pooled Least Square, Fixed Effect Model, and Random Effect Model were utilized in order to study the effects of education and local roads on foreign direct investment of the Philippines. Based on Fixed Effect regression results, higher education graduates and local road investments, as conditioned by economic growth, were significant factors in order to increase the foreign direct investment in the Philippines. Accordingly, a unit increase in higher education graduates, as conditioned by economic growth, leads to 8.758 unit increases in the foreign direct investment. While, a unit increased in local road investments, as conditioned by economic growth, leads to a 0.002 decrease in foreign direct investment. The regression results of the study suggest that the Foreign Direct Investment in the regions such as CAR, I, II, IV-B, V, VIII, IX, X, XI, XII, XIII, and ARMM are higher compared to Region IV-A.

• Korean Journal of Social Welfare
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• v.68 no.3
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• pp.105-125
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• 2016

School absenteeism is considered one of the early predictors of school drop-out and serious delinquency or criminal behavior. The primary goal of the current study was to explore the protective and risk factors related to changing school absenteeism over time based on the ecological-systemic perspective. The data was derived from the Korean Children and Youth Panel Survey (KCYPS) using the 2011 and 2012 survey waves collected from 2,378 elementary school students. Using this data, Panel Fixed Effects Analysis was conducted. Major findings indicated that daily computer usage, parental abuse, school activity attendance, and school grades had an effect on students missing school days over time. Specifically, high levels of computer usage and parental abuse were related to increased school absenteeism, while high levels of school activity attendance and school grades were associated with decreased school absenteeism. These findings emphasized the importance of predictive intervention for children and suggested the need to construct a school absenteeism monitoring system in South Korea.