• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.251-266
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• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.611-620
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• 2018

With the revitalization of alley market area becoming a major goal of the urban regeneration project, an understanding on customer characteristics that affect the sales of alley market areas is needed. As spatial heterogeneity appears to exist in alley market areas, the use of GWR (Geographically Weighted Regression) is required as an alternative to OLS (Ordinary Least Squares) regression. This study analyzes effects of customer characteristics on sales of 1007 alley market areas in Seoul. Comparing R squared and AICc, results show that GWR is better than OLS regression. According to OLS regression, the ratio of female, the ratio of 40's and 50's, the number of employees, the opening rate of establishment, the density of building and the size of alley market area have positive effects on sales, while the ratio of 20's and 30's, the distance of bus stop and that of subway station have negative effects. As a result of comparing local regression coefficients of geographically weighted regression analysis, the ratio of female customers has the greatest effect on the northwestern region, followed by the southwestern region, the central region and the northeastern region. The ratio of 20's and 30's and that of 40's and 50's effect on the southeastern and northeastern regions, and then the southwestern region. It is expected that this study will help to identify marketing target for each alley market area.

• 한국사회정책
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• v.23 no.1
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• pp.95-123
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• 2016

As Korean society grows rapidly older, a systematic analysis of the determinants of labor supply behavior among the elderly becomes a prerequisite for designing more effective senior employment policies and income security regime for the elderly. Literatures review shows that a majority of previous researches have been ignoring the problem of "endogenous predictor" especially when it comes to the estimation of the effects of the two key variables, education and non-labor income, on labor supply decisions among older people. They have failed to take into consideration the unobserved heterogeneities which might affect both labor supply decisions of the elderly and their levels of education and non-labor income, which means, according to some econometric literatures, that the estimated coefficients of the two predictors can be inconsistent. The paper tries to redress the endogeneity problem by employing a panel logit model with data from the 1st. to 4th. wave of the KLoSA(Korean Longitudinal Survey of Ageing) to estimate the effects of key predictors on the probability of getting jobs among older people(ages of 60 or older). Both a random effects and a fixed effects model reaffirms that non-labor income has a negative effect on the chances of being employed. And a random effects model shows that the effect of education is also negative, as has frequently been reported by previous studies. That means the effects of education and non-labor income on elderly employment remain negative after the effect of unobserved heterogeneities is controled for and the problem of endogenous predictors is redressed through an appropriate panel data analysis. These findings mean, in turn, that when Korean baby-boomers, who had acquired an unprecedentedly higher level of education and were expected to enjoy ever-larger amount of non-labor income than their preceding generations, retires in near future, their incentives to work will become much weaker and the lack of labor-force and the burden of financing increased public pension expenditure will become more troublesome. The paper concludes with recommending some policy initiatives helpful to solve these expected problems.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.148-156
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• 2018

The integrity assessment of the bridge behavior is generalized by field data of a static load-deformation curve and dynamic properties such as impact factors and natural frequencies. Evaluating it with numerical analysis is a reasonable method. The results of the mockup test and the numerical analysis are corresponded with each other since the behavior of service load proceeds in elastic region. In case of the dynamic behavior of structure, especially for the analysis of vibration, the result of the mockup test differs from the result of numerical analysis a little due to the geometric shape and non-homogeneous materials. In order to converge on these tolerances, this study suggested several numerical models, analyzed the sensitivity and finally offered a practical modeling method for the estimation of bridge on the basis of the result of mockup test. Based on the model substituted concrete section for strands section, the natural frequency of the model composed with axial stiffness of strands or the model applied the modified modulus of elasticity was closest with the result of the mockup test.

• The Korean Journal of Financial Management
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• v.18 no.1
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• pp.43-66
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• 2001

본 연구는 투자자 집단에 따라 그 매매에 있어서 주가와의 관련성을 분석하고자 하였다. 투자자 집단의 매매 성향은 월별 순매매율로 측정하였으며 주가의 대용변수는 한국종합주가지수(KOSPI)의 월별 수익률로서 분석에 사용된 기간은 1992년 1월부터 1999년 12월까지이다. 분석을 위한 방법론으로 상관분석과 회귀분석을 이용하였다. 상관분석은 스피어만 순위상관분석을 이용하여 KOSPI와 각 투자자 집단의 순매매 비중의 상관계수를 도출하였으며 그 결과 KOSPI와 개인투자자의 순매매와는 음의 유의적 상관관계를, KOSPI와 외국인 투자자의 순매매율과는 양(+)의 유의적 상관관계를 알 수 있었다. 그러나 기관투자자의 경우 기관투자자 전체 범주로 볼 때 유의적 상관관계가 없었으나 세분화된 기관투자자 일부는 유의적 상관관계를 보였다. 또한 본 연구는 KOSPI와 각 투자자 집단의 매매에 대한 인과관계를 추론한 바 외국인 투자자의 매매는 KOSPI에 영향을 주며 개인투자자의 매매는 오히려 KOSPI에 영향을 받는 것으로 보였다. 그러나 기관투자자의 경우 세부기관마다 그 매매의 성격을 달리하는 것으로 보였다. 이러한 분석결과를 바탕으로 회귀분석을 실시하였으며 그 분석결과 외국인 투자자와 기관투자가 가운데 증권사와 투신사의 경우, 순매수가 늘어날수록 주가는 상승하고 순매도가 늘어날수록 주가는 하락하는 것을 확인할 수 있었으며 반면 개인투자자의 매매는 KOSPI 주가에 따라 영향을 받는 것으로 나타났다. 즉 주가가 상승할수록 매도에 치중하고 주가가 하락할수록 매수에 치중하는 것으로 분석되었다. 기관투자자 가운데 보험사의 매매 역시 주가에 영향을 받는 것으로 나타났다. 본 연구의 성과로는 특정 투자자 집단이 주가의 움직임에 따라 매매를 하는 수동적 전략의 의미보다는 적극적으로 주가를 움직이는 주체로서 외국인투자자와 일부 기관투자자의 존재를 확인할 수 있었다는 점이며, 주가 움직임에 따른 개인투자자와 일부 기관 투자자의 수동적 매매 스타일과 기관투자자 사이의 투자스타일의 이질성을 통계적으로 확인할 수 있었다는 데에 있다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.3
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• pp.199-206
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• 2014

In this paper, a scheme to evaluate the response variability for functionally graded material (FGM) beam with varying sectional area is presented. The randomness is assumed to appear in a spatial domain along the beam axis in the elastic modulus. The functionally graded material categorized as composite materials, however without the drawbacks of delamination and occurrence of cracks due to abrupt change in material properties between layers in the conventional composite materials. The functionally graded material is produced by the gradual solidification through thickness direction, which endows continuous variation of material properties, which makes this material performs in a smooth way. However, due to difficulties in tailoring the gradients, to have uncertainty in material properties is unavoidable. The elastic modulus at the center section is assumed to be random in the spatial domain along the beam axis. Introducing random variables, defined in terms of stochastic integration, the first and second moments of responses are evaluated. The proposed scheme is verified by using the Monte Carlo simulation based on the random samples generated employing the spectral representation scheme. The response variability as a function of correlation distance, the effects of material and geometrical parameters on the response variability are investigated in detail. The efficiency of the proposed scheme is also addressed by comparing the analysis time of the proposed scheme and MCS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.85-93
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• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.

• Journal of Climate Change Research
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• v.1 no.1
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• pp.59-73
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• 2010

One of the most important issues for projecting future water resources and establishing climate change adaptation strategies is 'uncertainty'. In Korea, climate change research results were very heterogeneous even in a same basin, but there have been few climate change studies dealt with the uncertainty reduction. This is because emission scenarios, GCMs, downscaling, and rainfall-runoff models that were used in the previous studies were almost all different. In this research, fifty one GCM scenarios based A and B emission scenarios were downloaded and then compared with the observed values for a period from January 2001 to December 2008. The downloaded GCM scenarios in general simulated well the observed but did not simulated well the observed precipitation especially for the flood season in Korea. The accuracy of each GCM scenario was measured with the model efficiency, PDF-based, and Relative Entropy methodology. Among the selected GCM scenarios with three methodologies, the four common GCM scenarios(CGCM2.3.2(MRI-M, B1), MIROC3.2medress(NIES, B1), CGCM2.3.2(MRI-M, A2), CGCM2.3.2(MRI-M, A1B) were finally selected. Results of the four selected GCMs were heterogeneity and projected increases of precipitation for the Korean Peninsula by from 27.36% to 12.49%, respectively. It seems very risky to rely a water planning or a management policy on use of a single climate change scenario and from this research results. Therefore, the four selected GCM scenarios proposed quantitatively were considered firstly for the water supply in the dry season and the drought management strategy in the Korean Peninsula for the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.3
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• pp.207-221
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• 2020

This study conducted a meta-analysis on the effects of innovation, risk-taking, and enterprising on entrepreneurship. From 2013 to 2020, 392 papers, which were judged as quantitative research from doctoral and master thesis, and academic journals published in Korea were selected as research subjects. 28 duplicates of thesis and thesis are excluded. A total of 52 papers were finally selected, excluding 312 papers that were insufficient to be used as research data because there were no statistical values such as correlation coefficients. For the 52 selected papers, the homogeneity of the variables was first verified. As a result of the homogeneity test, the innovativeness, risk-taking, initiative, and entrepreneurship education all showed great effects on heterogeneity, and the average effect size was analyzed by random effect model. The average effect size analyzed was 0.38 ~ 0.49, and all four variables showed moderate average effect size. As a result of analyzing the average effect size by forest plot, all showed proper results. From the results of funnel plot analysis of entrepreneurship education, published errors were confirmed asymmetric. Research data on entrepreneurship education shows that it cannot represent the whole. It is a structural equation model with entrepreneurship and entrepreneurial intention as a parameter. Iinnovation and risk-taking have an impact on entrepreneurship by taking entrepreneurship education as a parameter. Initiative had an effect on the entrepreneurial intention a business, regardless of entrepreneurship education. In a number of studies, university entrepreneurship education has had an impact on the entrepreneurial intention. It should be changed to entrepreneurship education that combines theory and practice. Entrepreneurship education should be transformed into continuous and field-oriented education.