• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.263-271
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• 2024

This paper analysis of spatial differences in the efficiency of regional industrial enterprises in China from 2011 to 2021. The efficiency analysis uses the DEA-CCR model. The input variables for efficiency analysis are total assets and annual average employees, and the output variables are revenue from principal business and total profits. Using trend surface analysis and gravity center model, to analysis the spatial differences of efficiency in different regions. From the results of the gravity center model, the coordinates of the gravity center of China's regional industrial enterprise efficiency in 2011 are 112.303°E & 34.239°N, and 2021 are 111.753°E & 33.791°N, which indicates that the gravity center of the efficiency of China's regional industrial enterprises in the 2011-2021 period generally moves to the southwest. From the results of the trend surface analysis, the efficiency of industrial enterprises in China's regional industrial enterprises appears to show spatial differences in both the eastwest and the northsouth directions.

• Journal of the Korean Regional Science Association
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• v.9 no.1
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• pp.107-111
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• 1993

• Information Systems Review
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• v.1 no.2
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• pp.89-96
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• 1999

• Journal of the Korean Regional Science Association
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• v.6 no.1
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• pp.91-105
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• 1990

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.75-82
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• 2018

Recently, emerging countries have been paying attention to Korean economic development policy, trying to adopt the Korean regional innovation model. Korea is also interested in exporting its regional innovation model and enhancing economic cooperation with those countries. This paper aims to analyze the capacity-building programs of the Korean regional innovation model for emerging countries and suggests policies for it. For this purpose, the local innovators' participation patterns in the process of collaborative learning/networking/interaction are investigated with a focused group-interview method. From an analysis of the programs supported by Korean organizations, this study finds that the correlation coefficient between the training time of capacity building and the participation rate of local members' collaborative learning is very high (0.975). Since the correlation coefficient between the participation rates of collaborative learning and networking is relatively low (0.667), a policy to link local collaborative learning to networking should be provided. As the correlation coefficient between the participation rates of networking and interaction is high (0.950), networking is a key to regional innovation. This study recommends activity programs to promote networking among local innovators, rather than training and consulting programs. As introduced in the Chungnam Techno Park case, this study suggests that the capacity-building program should include programs to initiate a collaborative learning network, to create a local-demand, regional innovation model, and to operate the regional innovation platform, which should be done by local innovators in the emerging countries.

• Atmosphere
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• v.16 no.4
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• pp.259-267
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• 2006

In the present study, the neural network (NN) model with cluster analysis method was developed to predict storm surge in the whole Korean coastal regions with special focuses on the regional extension. The model used in this study is NN model for each cluster (CL-NN) with the cluster analysis. In order to find the optimal clustering of the stations, agglomerative method among hierarchical clustering methods was used. Various stations were clustered each other according to the centroid-linkage criterion and the cluster analysis should stop when the distances between merged groups exceed any criterion. Finally the CL-NN can be constructed for predicting storm surge in the cluster regions. To validate model results, predicted sea level value from CL-NN model was compared with that of conventional harmonic analysis (HA) and of the NN model in each region. The forecast values from NN and CL-NN models show more accuracy with observed data than that of HA. Especially the statistics analysis such as RMSE and correlation coefficient shows little differences between CL-NN and NN model results. These results show that cluster analysis and CL-NN model can be applied in the regional storm surge prediction and developed forecast system.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.2
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• pp.142-158
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• 2009

The purpose of this paper is to identify determinants of regional export in Korea using the interregional input-output table and SUR(Seemingly Unrelated Regression) model. Regional exports are classified into four groups; intraindustry intraregional export, interindustry intraregional export, intraindustry interregional export and interindustry interregional export. Labor productivity, scale economies, market size, and international trade volumes have positively influenced regional exports while the interregional distances having a negative effect on them. These results imply that it is necessary to operate regional strategies to enhance productivities and market size and to reduce transportation and distribution costs for revitalize a regional economy by increasing regional exports.

• The Journal of Fisheries Business Administration
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• v.42 no.2
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• pp.15-30
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• 2011

This study is designed to measure the relative efficiency of regional fishery cooperatives based on Data Envelopment Analysis(DEA) methods. Selecting 40 regional fishery cooperatives in Busan as Decision Making Units (DMUs), the study uses their panel data from 2007 to 2008 to rank the relative efficiency of the DMUs. First, the efficiency score of the DMUs are calculated using CCR, SBM, and super-SMB model. Within the model, input variables are the number of employees and area of fishery cooperatives. Output variables are the amount of deposit money, loan and profit. Based on the efficiency scores calculated from super-SMB model, the efficiency ranking of the DMUs is determined. Second, the differences in average efficiency calculated from the three DEA models are tested using a pair-wise mean comparison test. The results based on the efficiency scores evaluated from super-SMB model show that seven out of the forty DMUs are efficient; among the efficient DMUs, the DMUs that can be benchmarked for inefficient DMUs through the frequency analysis of reference set being identified. Third, the differences in average efficiency of the three DEA models between 2007 and 2008 are tested using pair-wise mean comparison test and the study estimates the efficiency change of the DMUs between 2007 and 2008 using Malmquist productivity index(MPI). Finally, the paper suggests an improved composite DMU superior to the inefficient DMUs evaluated by Super-SBM model.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.287-287
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• 2023

Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.349-361
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• 2008

There has been abundant empirical research undertaken on the technical efficiency of Korean ports. Most studies have focused on the use of parametric and non-parametric techniques to analyse overall technical efficiency. This paper utilizes data for the period 2000-07 to offer a heterogeneous perspective on the overall efficiency of Korean ports. The framework assumes that ports use one input to produce one output; the output and input include port export(import) and regional export(import). This paper also employs panel analysis and heteroscedastic Tobit model to show the effect of the explanatory variables on the port efficiencies. The panel analysis shows that the regional export/total export has negative effect on the export efficiency while the regional import/total import has not any relations with the import efficiency. The heteroskedastic Tobit model shows that both regional export ratio and regional import ratio have negative effects on the efficiency while the gross regional domestic product has not any significant relations with the import efficiency.