• Journal of Distribution Science
• /
• v.12 no.4
• /
• pp.31-39
• /
• 2014

Purpose - This study investigates the following two issues. First, we attempt to find the important determinants of housing investment and to identify their significance rank using survey panel data. Recently, the expansion of global uncertainty in the real estate market has directly and indirectly influenced the Korean housing market; households demonstrate a sensitive reaction to changes in that market. Therefore, this study aims to draw conclusions from understanding how the impact of financial strength of the household is related to house investment. Second, we attempt to verify the effectiveness of diverse indices of financial strength such as DTI, LTV, and PIR as measures to monitor the housing market. In the continuous housing market recession after the global crisis, the government places top priority on residence stability. However, the government still imposes forceful restraints on indices of financial strength. We believe this study verifies the utility of these regulations when used in the housing market. Research design, data, and methodology - The data source for this study is the "National Survey of Tax and Benefit" from 2007 (1st) to 2011 (5th) by the Korea Institute of Public Finance. Based on this survey data, we use panel data of 3,838 households that have been surveyed continuously for 5 years. We sort the base variables according to relevance of house investment criteria using the decision tree model (DTM), which is the standard decision-making model for data-mining techniques. The DTM method is known as a powerful methodology to identify contributory variables for predictive power. In addition, we analyze how important explanatory variables and the financial strength index of households affect housing investment with the binary logistic multi-regressive model. Based on the analyses, we conclude that the financial strength index has a significant role in house investment demand. Results - The results of this research are as follows: 1) The determinants of housing investment are age, consumption expenditures, income, total assets, rent deposit, housing price, habits satisfaction, housing scale, number of household members, and debt related to housing. 2) The impact power of these determinants has changed more or less annually due to economic situations and housing market conditions. The level of consumption expenditure and income are the main determinants before 2009; however, the determinants of housing investment changed to indices of the financial strength of households, i.e., DTI, LTV, and PIR, after 2009. 3) Most of all, since 2009, housing loans has been a more important variable than the level of consumption in making housing market decisions. Conclusions - The results of this research show that sound financing of households has a stronger effect on housing investment than reduced consumption expenditures. At the same time, the key indices that must be monitored by the government under economic emergency conditions differ from those requiring monitoring under normal market conditions; therefore, political indices to encourage and promote the housing market must be divided based on market conditions.

• The Journal of Engineering Geology
• /
• v.23 no.2
• /
• pp.137-147
• /
• 2013

For the effective management of groundwater resources, it is necessary to predict groundwater level fluctuations in response to rainfall events. In the present study, time series models using artificial neural networks (ANNs) and support vector machines (SVMs) have been developed and applied to groundwater level data from the Gasan, Shingwang, and Cheongseong stations of the National Groundwater Monitoring Network. We designed four types of model according to input structure and compared their performances. The results show that the rainfall input model is not effective, especially for the prediction of groundwater recession behavior; however, the rainfall-groundwater input model is effective for the entire prediction stage, yielding a high model accuracy. Recursive prediction models were also effective, yielding correlation coefficients of 0.75-0.95 with observed values. The prediction errors were highest for Shingwang station, where the cross-correlation coefficient is lowest among the stations. Overall, the model performance of SVM models was slightly higher than that of ANN models for all cases. Assessment of the model parameter uncertainty of the recursive prediction models, using the ratio of errors in the validation stage to that in the calibration stage, showed that the range of the ratio is much narrower for the SVM models than for the ANN models, which implies that the SVM models are more stable and effective for the present case studies.

• Journal of Distribution Science
• /
• v.11 no.8
• /
• pp.5-14
• /
• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Journal of Korea Technology Innovation Society
• /
• v.19 no.1
• /
• pp.48-79
• /
• 2016

Recently, to overcome the global economic recession and stimulate the sluggish economy, Korea government has adopted various policies designed to strengthen the innovative capabilities of its small or medium sized enterprises (SMEs). With our focus on ICT technology companies, this study empirically analyzes both the potentials and the limitations of the R&D information support programs which are part of these governmental efforts. Our goal is to generate insights and help develop policies based on evidence. In this study, we used statistics from 2014 on small or medium business technologies to analyze the effect that the government's R&D information support policy has had on the technological or economic performance of small or medium businesses. According to these research results, R&D support programs (assistance with R&D planning and provision of technological information) made available to small or medium businesses did have a significant correlation to technological investment. By contrast, R&D information supporting programs were found to have no direct, significant correlation to technological or economic performance. One exception was that programs that gained the benefits of R&D planning support did have a significant correlation to technological performance in the case of companies engaged in ICT research. The results of this study will provide various insights for policymakers designing policies to support technologically-driven small or medium businesses, including ICT-based companies. We anticipate that this study will be a particularly helpful guide to policy development for corporations or researchers that provide supportive information to small or medium businesses.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.58 no.4
• /
• pp.21-35
• /
• 2016

This study is to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for multi-purpose dams and multi-function weirs operation in Namhan river basin ($12,577km^2$) of South Korea. The SWAT was calibrated (2005 ~ 2009) and validated (2010 ~ 2014) considering of 4 multi-purpose dams and 3 multi-function weirs using daily observed dam inflow and storage, evapotranspiration, soil moisture, and groundwater level data. Firstly, the dam inflow was calibrated by the five steps; (step 1) the physical rate between total runoff and evapotranspiration was controlled by ESCO, (step 2) the peak runoff was calibrated by CN, OV_N, and CH_N, (step 3) the baseflow was calibrated by GW_DELAY, (step 4) the recession curve of baseflow was calibrated by ALPHA_BF, (step 5) the flux between lateral flow and return flow was controlled by SOL_AWC and SOL_K, and (step 6) the flux between reevaporation and return flow was controlled by REVAPMN and GW_REVAP. Secondly, for the storage water level calibration, the SWAT emergency and principle spillway were applied for water level from design flood level to restricted water level for dam and from maximum to management water level for weir respectively. Finally, the parameters for evapotranspiration (ESCO), soil water (SOL_AWC) and groundwater level fluctuation (GWQMN, ALPHA_BF) were repeatedly adjusted by trial error method. For the dam inflow, the determination coefficient $R^2$ was above 0.80. The average Nash-Sutcliffe efficiency (NSE) was from 0.59 to 0.88 and the RMSE was from 3.3 mm/day to 8.6 mm/day respectively. For the water balance performance, the PBIAS was between 9.4 and 21.4 %. For the dam storage volume, the $R^2$ was above 0.63 and the PBIAS was between 6.3 and 13.5 % respectively. The average $R^2$ for evapotranspiration and soil moisture at CM (Cheongmicheon) site was 0.72 and 0.78, and the average $R^2$ for groundwater level was 0.59 and 0.60 at 2 YP (Yangpyeong) sites.

• Journal of Periodontal and Implant Science
• /
• v.29 no.1
• /
• pp.51-63
• /
• 1999

Exposure of the root surface due to gingival recession after periodontal surgery, elicit pain response when exposed to mechanical, heat, chemical or osmotic irritation. Especially patients treated with periodontal surgery, show high frequency. There have been reports that the 1 out of 7 patients complains of dentinal hypersensitivity. There have been many studies on the clinical effects of various materials on the treatment of dentinal hypersensitivity. The purposes of this study were to evaluate the effect of sodium chloride and potassium oxalate and to observe the relationship between the dentinal hypersensitivity and surface characteristics such as dentinal tubule size and number. This study included 20 teeth which were scheduled for extraction and had no pulpal disease. These teeth were divided into Root planing group, EDTA group, NaCl group and Oxalate group. Dentinal hypersensitivity is measured by tactile, pressured air and cold water using NRS (Numerical Rating Scales). Teeth were extracted under local anesthesia and each specimen was sectioned to a size about 3 X 5 mm and was examined under the scanning electron microscope (X2,000) The results were as follows, 1. The EDTA group exhibited significantly increased dentinal hypersensitivity comparing with the other groups. 2. The NaCl and Oxalate groups showed significantly reduced dentinal hypersensitivity comparing with the EDTA group. 3. As a method for dentinal hypersensitivity measurement, it was presumed thet tactile sensitivity test was not sensitive method but air blast test and cold water test were adequate method. 4. In a SEM study, the root planing group exhibited amorphous smear layer and showed no dentinal tubule orifice, but the EDTA group showed the large number of dentinal tubules. On the other hand, the NaCl and Oxalate groups did not show exposed dentinal tubules. The NaCl group showed more rough root surface than the EDTA group, and the Oxalate group showed many participates to be presumed as calcium oxalate particle. As the results from this study, root planing couldn't expose the dentinal tubule and NaCl and potassium oxalate occluded exposed dentinal tubule effectively. Dentinal hypersensitivity has close relationship with the exposure of dentinal tubules, especially with it's size and number.

• International Commerce and Information Review
• /
• v.14 no.3
• /
• pp.159-183
• /
• 2012

Promoted in places like Korea, the central government and the local governments that can provide information on which to base investment policy to attract foreign direct mutation-specific gravity model (Shift-Share Model) In this study, the decrease of foreign direct investment performance using factors looked up in the industry. The sample period of 2009, 2010, 2011 nationwide (metropolitan and non-metropolitan separated) of foreign direct investment performance for Industry Standard Industrial Classification (Division) was conducted. Factors to look at the results of the National Growth Effect(NS), the industrial structure effect (IM), local allocation effect(RS) to decrease foreign direct investment in 2010 and 2011 non-metropolitan, metropolitan national growth effect(RS) is negative(-) has a value. Because it appears to be the aftermath of the global recession, the impact on the domestic economy Metropolitan area and the Industrial Mix Effect(IM) to the development of education, culture, business, and transportation, etc. in the development of service industries than in non-metropolitan valid environment. In the sector of services (food accommodation, business services, entertainment), We did it, was able to find the function. However, the Regional Share Effect(RS) be competitive in the manufacturing sector in metropolitan areas in the metal and chemical sectors have been identified. These results seems to enhance the competitiveness of the region, such as the metropolitan area's excellent workforce. Shift-Share analysis technique based on competitive factors of the region, to find the failure has limitations.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2008.11a
• /
• pp.241-246
• /
• 2008

With construction industry recession, many construction companies are increasingly conducting the development projects by themselves. However, housing projects requested by developers still stand large portion. Although many studies on feasibility analysis were released, they mainly focused on economic feasibility and lacked research on factors and criterions of overall project. Also, because previous studies overly break downed factors related to project, they rarely used in practice. Therefore, this study developed the feasibility analysis model of housing development projects to help main contractors to easily and effectively decide if it is feasible enough to promote the projects requested by developers, and verified the reliability of the model. In this study, thirty one driving factors were identified under seven different categories and the criterion of each factor was also developed. The survey on important index of each factor found "salability", "economic feasibility", "site location" and "method of raising fund" significant. 3 projects were tested by the model and its results showed resonable reliability.

• Journal of Korea Water Resources Association
• /
• v.30 no.6
• /
• pp.777-785
• /
• 1997

This study was conducted to clarify the hydrological characteristics of subsurface flow through a soil matrix and macropores. The research facility was set up in a 20m-1ong trench excavated down to bedrock at the base of a hillslope in the Panola catchment under USGS Georgia district. 13 macropores were found on the trench face and 6 major macropores were monitored. Matrix and macropore flow were measured during 95.5mm rainfall on March, 6 to 7. 1996. Macropore flow had great influence on formation of peak flow because the delivery time to Peak flow of macropore flow were faster about 10hrs than those of matrix flow. Matrix flow continued to recess for 3 days. On the other hand, macropore flow stopped within 12hrs after the event ceased. This means that matrix flow controls the recession part. The spatial variations of matrix and macropore flow between each trough and collector were very large by a wide range of 8,655.3 $\ell$ to 17.8 $\ell$ . The bed rock surface topography relates closer with the spatial variations of the flow than the surface one.

• Journal of Navigation and Port Research
• /
• v.39 no.3
• /
• pp.261-266
• /
• 2015

Many of previous studies suggested that working capital management is an important component of firm's financial decision and efficient working capital management affects firms' profitability and it's value. Recently, Korean shipping firms have been suffering from financial distress by recession of shipping economy. In this point of view, this study tries to investigate the relationship between working capital management and shipping firm's profitability, using panel data on 46 Korean shipping firms for the period of 2004-2013. As result of panel regression, it proved that average payment period, inventory turnover, cash conversion cycle and operating cycle are significantly associated with firms profitabilities such as profit margin ratio and operating profit ratio, and the manager of shipping firm can increase firms profitability by more efficient working capital management. There are strong positive relationships between average payment period and operating cycle and firm's profitability. These results suggest that managers can create firm's value by increasing average payment period and operating cycle. Otherwise inventory turnover and cash conversion cycle have negative relationships with firm's profitability. It means that managers can increase firm's profitability by reducing these variables.