• Health Policy and Management
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• v.34 no.3
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• pp.261-270
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• 2024

Background: Various researchers are calculating the health adjusted life expectancy (HALE) at the regional level in South Korea using several methods, most studies merely enumerate the differences in healthy life expectancy based on social characteristics. This study aims to analyze the association between various sociodemographic factors and HALE at the regional level. Methods: To calculate HALE, we utilized the various data sources, including National Health Insurance claims data, and applied the Sullivan's method. We conducted multiple linear regression with regional socioeconomic variables from Korean Statistical Information Service. For the multiple linear regression analysis, we designed three regression models. Model 1 comprised solely socioeconomic variables, model 2 involved both socioeconomic variables and individual health behaviors, and model 3 integrated model 2 with healthcare utilization. Results: The analysis shows that an increase in financial independence (p<0.05), population density (p<0.1), and the number of doctors (p<0.05) associated with an increase in HALE, whereas an increase in the number of beds (p<0.01) was associated with a decrease in HALE. In case of the obesity rate, in model 2 (p<0.1) and model 3 (p<0.05), there was a negative association between HALE and obesity rate. Conclusion: Amidst various variables, it was observed that increased financial independence in specific regions had association with an increase in HALE, highlighting the need for stronger local governance in South Korea. Additionally, the inverse association between hospital beds and HALE suggests several implications, such as the appropriate deployment of healthcare resources. To gain a deeper understanding of the relationship between hospital beds and HALE, further analysis distinguishing different types of hospital beds across healthcare institutions seems necessary.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.159-168
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• 2013

This study analyze the business efficiency of securities company based on the 2011 performance of 29 securities firms which engage in domestic investment brokerage by applying a combination model of BSC and DEA. And we evaluate business state focused on efficiency which is based on logical system of BSC as business innovation method. The analysis of result is that companies with high customer efficiency index appeared that business efficiency composite index tended to be higher and we identified that customer perspective have an important factor to calculate business efficiency composite index of korea security company. In addition, based on the results of the efficiency analysis we analyze correlation analysis between traditional financial ratio and business efficiency composite index. We confirmed that company of high business efficiency level in terms of BSC have a good record in terms of profitability. BSC-DEA combination model expect to be utilized in security industry sector as well as other industrial sectors as good business indicator to determine the business efficiency and to be used a model can be evaluated the integrated firm valuation of tangible and intangible assets.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Journal of Distribution Science
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• v.13 no.11
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• pp.111-121
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• 2015

Purpose - This study's purpose is to investigate the impact of supply chain management (SCM) factors among targeted Korean distribution firms. Antecedents are established for supply chain orientation (SCO) for the management and organization of cultural assets. The research sets up SCO corresponding to management cultural assets and to organizational factors in the results. The research model is created to examine the SCO based on a strategic perspective and the operational performance of the SC and SCM. In addition, an integrated model is constructed to analyze the moderating effect by setting partner cooperation as a relational capital factor. The main aim of this study is to analyze the characteristics of the supply chain structure as a source of competitive advantage for distribution service firms participating in the supply chain. In the moderating effects analysis, the role of partner cooperation as relational capital is examined in detail. Research design, data, and methodology - The study examined the existing research related to supply chains, discussing the antecedents of the performance of SCM and SCO. SCM was established with the partner's cooperation as relational capital. Including the moderating effects of the partner cooperation, the research proposed a seven hypotheses path analysis model. The samples were collected from the Korean export enterprises in the distribution service sector, with 185 samples selected for the final analysis. To try and measure the four latent variables presented in the analysis model based on existing studies, 22 measurement items were used. The empirical analysis used the appropriate PLS (partial least squares) method on the path analysis reliability and validity and for common method bias. After testing the seven hypotheses, the research tested the moderating effects to the path analysis. Using PLS as structural equation modeling, the seven hypotheses were tested including the moderating effects of the partner relational capital on the 185 samples. Results - In the results, the SCO had a positive impact on both SCM and the relational capital of partner cooperation. The SCM had a significant impact on the operational performance of the SC. Further, partner cooperation also had a significant impact on SCM and the operational performance of the SC. The moderating effect analysis of the SCM and partner cooperation found a significant impact on the operational performance of the SC. On the other hand, the moderating effect of the SCO and partner cooperation did not affect the SCM. Conclusion - The results of this research show that the existing supply chain-related research can be applied to the operational performance of the SC for a Korean distribution service firm. In view of the fact that SCO is a source of competitive advantage, it should be taken into account when a firm wants to improve the performance of the SCM of the distribution service. This is because it can be assumed that SCO plays a role in supply chain management for the distribution firm.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.4 no.1
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• pp.31-42
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• 2000

The dry deposition velocities and fluxes of air pollutants such as SO2(g), O3(g), HNO3(g), sub-micron particulates, NO3(s), and SO42-(s) were estimated according to local meteorological elements in the atmospheric boundary layer. The model used for these calculations was the multiple layer resistance model developed by Hicks et al.1). The meteorological data were recorded on an hourly basis from July, 1990 to June, 1991 at the Austin Cary forest site, near Gainesville FL. Weekly integrated samples of ambient dry deposition species were collected at the site using triple-fiter packs. For the study period, the annual average dry deposition velocities at this site were estimated as 0.87$\pm$0.07 cm/s for SO2(g), 0.65$\pm$0.11 cm/s for O3(g), 1.20$\pm$0.14cm/s for HNO3(g), 0.0045$\pm$0.0006 cm/s for sub-micron particulates, and 0.089$\pm$0.014 cm/s for NO3-(s) and SO42-(s). The trends observed in the daily mean deposition velocities were largely seasonal, indicated by larger deposition velocities for the summer season and smaller deposition velocities for the winter season. The monthly and weekly averaged values for the deposition velocities did not show large differences over the year yet did show a tendency of increased deposition velocities in the summer and decreased values in the winter. The annual mean concentrations of the air pollutants obtained by the triple filter pack every 7 days were 3.63$\pm$1.92 $\mu\textrm{g}$/m3 for SO42-, 2.00$\pm$1.22 $\mu\textrm{g}$/m-3 for SO2, 1.30$\pm$0.59 $\mu\textrm{g}$/m-3 for HNO3, and 0.704$\pm$0.419 $\mu\textrm{g}$/m3 for NO3-, respectively. The air pollutant with the largest deposition flux was SO2 followed by HNO3, SO42-(S), and NO3-(S) in order of their magnitude. The sulfur dioxide and NO3- deposition fluxes were higher in the winter than in the summer, and the nitric acid and sulfate deposition fluxes were high during the spring and summer.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.47-59
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• 2017

This study aims to assess offshore wind energy resources around Jeju Island using the InVEST Offshore Wind model. First the wind power density around the coast of Jeju was calculated using reanalysis data from the Korean Local Analysis and Prediction System (KLAPS). Next, the net present value (NPV) for the 168MW offshore wind farm scenario was evaluated taking into consideration factors like costs (turbine development, submarine cable installation, maintenance), turbine operation efficiency, and a 20year operation period. It was determined that there are high wind resources along both the western and eastern coasts of Jeju Island, with high wind power densities of $400W/m^2$ calculated. To visually evaluate the NPV around Jeju Island, a classification of five grades was employed, and results showed that the western sea area has a high NPV, with wind power resources over $400W/m^2$. The InVEST Offshore Wind model can quickly provide optimal spatial information for various wind farm scenarios. The InVEST model can be used in combination with results of marine ecosystem service evaluation to design an efficient marine spatial plan around Jeju Island.

• Asia pacific journal of information systems
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• v.17 no.2
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• pp.83-95
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• 2007

We are motivated by how offline and online firms compete. The Internet made many conventional offline firms build a dynamic online business as another sales channel using their advantages such as brand equity, an existing customer base with comprehensive purchasing data, integrated marketing, economies of scale, and longtime experience with the logistics of order fulfillment and customer service. Even though the hybrid selling using both offline and online channel seems to have advantages over a pure online retailer, all the conventional offline firms are not seen to create an online business. Many conventional offline firms began to launch online business since the Internet era, however, just being online business is not likely to guarantee success. According to Bizate.com's report whether the hybrid channel strategy is successful is still under investigation. For example, consider the classic case of Barnes and Noble versus Amazon.com, Barnes and Noble was already the largest chain of bookstores in the U,S., when Amazon.com was established in 1995, BarnesandNoble.com followed suit in 1997, After suffering losses in its initial years, Amazon finally turned profitable in 2003. In 2004, Amazon's net income was $588 million on revenues of $6.92 billion, while Barnes and Noble earned $143 million on revenues of $4.87 billion, which included BarnesandNoble.com's loss of $21 million on revenues of $420 million. While these examples serve to motivate our thinking, it does not explain when offline firms should venture online. It also does not provide an analytical framework that can generalized to other competitive online-offline situations. We attempt to do this in this paper and analyze a hybrid channel model where a conventional offline firm competes against online firms using its own direct online channels. We are particularly interested in an optimal channel strategy when a conventional offline firm sells its products through its own direct online channel to compete with other rival online firms. We consider two situations where its direct online channel and other online firms are symmetric and asymmetric in the brand effect. The analysis of this paper presents several findings. In the symmetric model where a hybrid firm's online channel is not differentiated from a pure online firm, (i) a conventional offline firm will not launch its online business. In the asymmetric model where a hybrid firm's online channel is differentiated from a pure online firm, (ii) a conventional offline firm can launch its online business if its brand effect is greater than a certain threshold. (iii) there is a positive relationship between its brand effect and online customer costs showing that a conventional offline firm needs more brand effect in order to launch online business as online customer costs decrease. (iv) there is a negative relationship between its brand effect and the number of customers with access to the Internet showing that a conventional offline firm tends to launch its online business when customers with access to the Internet increases.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.91-102
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• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.655-664
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• 2005

A real-time monitoring and modeling system (RTMMS) for rainfall-induced turbidity flow, which is one of the major obstacles for sustainable use of reservoir water resources, is under development. As a prediction model for the RTMMS, a laterally integrated two-dimensional hydrodynamic and water quality model, CE-QUAL-W2 was tested by simulating the temperature stratification, density flow regimes, and temporal and spatial distributions of turbidity in a reservoir. The inflow water temperature and turbidity measured every hour during the flood season of 2004 were used as the boundary conditions. The monitoring data showed that inflow water temperature drop by 5 to $10^{\circ}C$ during rainfall events in summer, and consequently resulted in the development of density flow regimes such as plunge flow and interflow in the reservoir. The model showed relatively satisfactory performance in replicating the water temperature profiles and turbidity distributions, although considerable discrepancies were partially detected between observed and simulated results. The model was either very efficient in computation as the CPU run time to simulate the whole flood season took only 4 minutes with a Pentium 4(CPU 2.0GHz) desktop computer, which is essentially requited for real-time modeling of turbidity plume.

• Journal of Science Education
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• v.46 no.1
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• pp.80-92
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• 2022

We fitted latent growth models of attitude towards science using the Korea Education & Employment Panel 2004-2007 data with 343 high school students. The growth model show better fit indices compared to the no growth model. The intercept and slope showed significant variances, and thus, we added control variables of the number, ratio of advanced courses, and variety in science elective subjects, and the achievement percentile for middle school. In the conditional growth model, the previous achievement has significant positive effects on the intercept and the ratio of the advanced courses and variety of science subjects show significantly positive effects on the slope. Based on the results, it supports the 2022 Revised Science Curricular that high school credit system should provide students with basic 'Physics,' 'Chemistry,' 'Biology,' and 'Earth Science,' credits in 'general electives', various integrated subjects in 'converged electives', and highly advanced subjects in 'career electives.'