• Journal of Distribution Science
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• v.15 no.1
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• pp.123-130
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• 2017

Purpose - This research aims to examine the effect of e-business adoption on firm's growth and profitability in the distribution industry. The value added from the distribution industry acts as the cost of other industries. As the distribution industry develops, its stage becomes shorter and the distribution margin becomes smaller. Therefore, e-business is expected to have a different effect on the distribution industry than other industries. Research design, data and methodology - The previous research generally used e-business adoption as an independent variable and firm's performance as a dependent variable. This study elaborated the model using a dynamic panel model that includes the performance variable of the previous year as an independent variable. By employing system GMM (Generalized Method of Moments), the endogeneity problem in the dynamic panel model can be solved. For the analysis, I extracted the distribution companies as the raw data in the National Statistical Office's Business Activity Survey over the period 2006 to 2012. Results - The growth rate of firms adopting e-business was 0.299%p higher than that of the non-adopter. However, only ERP (Enterprise Resource Planning), KMS (Knowledge Management System) and SCM (Supply Chain Management) contributed positively to the growth rate. In the case of profitability, it was 0.04%p higher than the distribution companies that did not adopt e-business. ERP and LMS (Learning Management System) improve profitability, while SCM reduces profitability. Consequently, while ERP improves both growth and profitability, SCM improves growth but reduces profitability. In addition, KMS improves firm's growth only, and LMS does only profitability, showing that each e-business has a differentiated effect. Conclusions - Since the distribution industry has different characteristics from manufacturing and other service industries, the introduction of e-business may not guarantee the growth and profitability of distribution companies. Careful introduction considering the characteristics of the distribution industry is required. In particular, it is necessary to select an e-business meeting the characteristics and needs of a distribution company, and thereafter, it is required for the company's own efforts to internalize it within the system.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1
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• pp.36-42
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• 2006

A Principal component analysis (PCA)-based Mel-Frequency Discrete Wavelet Coefficients (MFDWC) feature Parameters for speaker verification system is Presented in this Paper In this method, we used the 1st-eigenvector obtained from PCA to calculate the energy of each node of level that was approximated by. met-scale. This eigenvector satisfies the constraint of general weighting function that the squared sum of each component of weighting function is unity and is considered to represent speaker's characteristic closely because the 1st-eigenvector of each speaker is fairly different from the others. For verification. we used Universal Background Model (UBM) approach that compares claimed speaker s model with UBM on frame-level. We performed experiments to test the effectiveness of PCA-based parameter and found that our Proposed Parameters could obtain improved average Performance of $0.80\%$compared to MFCC. $5.14\%$ to LPCC and 6.69 to existing MFDWC.

• Journal of Korea Trade
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• v.27 no.3
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• pp.161-178
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• 2023

Purpose - purpose of this paper is to analyze the effects of the investment facilitation levels of 11 RCEP countries (excluding Myanmar, Brunei, and Laos due to lack of data) on China's outward foreign direct investments(OFDI) using balanced panel data from 2010 to 2019. Design/methodology - First, four investment facilitation measurement indicators (regulatory environment, infrastructure, financial market, ease of doing business) were selected,investment facilitation scores of the 11 countries were obtained using the principal component analysis, an investment gravity model was established with nine explanatory variables (investment facilitation level, market size, population, geographic distance, degree of opening, tax level, natural resources, whether the country is an APEC member or not, and whether a valid bilateral investment treaty with China has been concluded) were used to establish an investment gravity model, and regression analyses were conducted with OLS and system GMM. Findings - The results of the regression analyses showed that investment facilitation levels had the greatest effect on China's OFDI, all four first-level indicators had positive effects on China's OFDI, and among them, the institutional environment had the greatest effect. In addition, it was shown that explanatory variables such as market size, population, geographical distance, degree of openness, natural resources, and whether or not a valid bilateral investment treaty has been concluded would have positive effects on China's OFDI, while tax levels and APEC membership would impede China's OFDI to some extent. Originality/value - Since the Regional Comprehensive Economic Partnership (RCEPT) came into effect not long ago, there are not so many studies on the effects of investment facilitation levels of RCEP member states on China's OFDI, and the investment facilitation measurement index constructed in this paper is relatively systematic and scientific because it includes all the contents of investment facilitation related to the life cycle of company's foreign direct investments.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.531-548
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• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• Knowledge Management Research
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• v.21 no.1
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• pp.137-150
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• 2020

This study analyzes not only the direct impact of R&D investment on corporate growth for 578 private firms in 2007-2016, but also whether corporate innovation activities play a role as a mediating parameter between R&D investment and corporate growth. For this purpose, we classify companies into IT and non-IT companies and measure the mediating effect by dividing innovation activities into the number of registered patents, applied patents, and sum of them. In addition, this study is based on both the systemGMM which is considered to be effective in solving the endogenous problems caused by the cross-sectional analysis in previous studies and ML-SEM which is a new method recently, and then compares two results. According to the empirical results, innovation activities has a role as partly mediating parameter on sales growth in non-IT companies. On the other hands, in IT companies, the increase in R&D investment leads to a decrease in sales of the company, and the increase in innovation activities increases the sales of the company. However, it was confirmed that IT companies also had positive effects by adjusting the lag of the R&D. In other words, this suggests that securing patents is more important than R&D investment for direct sales growth of IT companies. It is also evidence that immediate introduction of technology is necessary to respond to the speed of technological change since the cycle time of technologies of the IT field is relatively shorter compared to that of other fields.

• 한국사회정책
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• v.24 no.4
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• pp.185-222
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• 2017

The purpose of this study is to investigate the effect of labor market policy on fiscal soundness of welfare state. The analysis was carried out using cross-sectional panel data regression analysis, stepwise mediating effect analysis and system GMM designed by Baron and Kenny(1986) based on the data from 1985 to 2015 for 20 OECD countries. In setting up the analysis model, this study considers the interaction effect between active and passive labor market policies as well as the time sequence of the outcomes which have been overlooked in the previous studies. The result shows that labor market policies have significant impacts on the fiscal condition of welfare states, which is measured as the levels of national debt in this study. Especially the expenditure on active labor market programs has a positive effect on improving the fiscal soundness of welfare states by promoting the employment rate. In contrast, passive labor market programs expenditure is negatively associated with employment rate growth and it exacerbates the burden of national debt in the short-term. However, when active labor market programs and passive labor market programs are combined, the negative impacts by passive pabor market policies on the fiscal soundness of welfare states are off-set. Therefore this study addresses that although the expansion of the labor market policies can be inimical to the fiscal soundness of welfare states in the short-term, in the long run, they can have effective roles in securing and promoting the fiscal soundness of the welfare states by promoting the employment rate.

• Management & Information Systems Review
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• v.37 no.1
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• pp.123-138
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• 2018

In this paper, we use panel dataset from Korean linked worker-firm to analyse the effects of the workforce age structure on the productivity or labor costs. We measure 'labor productivity' as added value per capita, 'cost of labor' as labor cost per capita and estimate a dynamic panel model to study the effects of the workforce age structure on the productivity or labor costs. Empirical analysis results show that the workforce age structure is positively related to productivity and labor costs, but only up to the aged of 35-39. That is, we find that an increase in the proportion of younger workers or elder workers rather than the aged 35-39 has a negative effect on productivity and labor cost. In particular, the difference between the estimation coefficient of productivity and labor cost when the share of workers aged 50 or older is increased instead of the aged 35-39 is higher than the difference between the estimation coefficient of productivity and labor cost when the share of workers aged 30 or younger is increased instead of the aged 35-39. Our results exhibit that it is reasonable for firms to worry about declining productivity of elderly workers, whereas firms already used older workers efficiently, such as by adjusting their labor costs.