• The Journal of the Korea Contents Association
• /
• v.12 no.2
• /
• pp.461-471
• /
• 2012

The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.

• Journal of Korean Academy of Nursing
• /
• v.53 no.4
• /
• pp.426-438
• /
• 2023

Purpose: Walking practice is a representative indicator of the level of physical activity of local residents. Although the world health organization addressed reduction in prevalence of insufficient physical activity as a global target, the rate of walking practice in Korea has not improved and there are large regional disparities. Therefore, this study aimed to explore the spatial variations of walking practice and its associated factors in Korea. Methods: A secondary analysis was conducted using Community Health Outcome and Health Determinants Database 1.3 from Korea Centers for Disease Control and Prevention. A total of 229 districts was included in the analysis. We compared the ordinary least squares (OLS) and the geographically weighted regression (GWR) to explore the associated factors of walking practice. MGWR 2.2.1 software was used to explore the spatial distribution of walking practice and modeling the GWR. Results: Walking practice had spatial variations across the country. The results showed that the GWR model had better accommodation of spatial autocorrelation than the OLS model. The GWR results indicated that different predictors of walking practice across regions of Korea. Conclusion: The findings of this study may provide insight to nursing researchers, health professionals, and policy makers in planning health programs to promote walking practices in their respective communities.

• Journal of Korean Society of Forest Science
• /
• v.97 no.1
• /
• pp.45-52
• /
• 2008

The objectives of this study are to explain a supply plan of domestic softwood log by long-term prospect of MDF production to stably promote industry of MDF. For it, we developed the long supply function as Ordinary Least Squares Method. Between 2005 and 2050, it was estimated that quantity of domestic production of MDF increased from 1,653 thousand $m^3$ to 2,041 thousand $m^3$. In 2050, quantities of domestic softwood log used by raw materials to product MDF of 2,041 thousand $m^3$ were estimated to be used about 1,355 thousand $m^3$. Exampling Pinus rigida used presently by raw materials to product MDF, cutting area of it is estimated to be 10,828 ha per year. And larch is cutted about 9,160 ha per year. This study estimated annual softwood log cutting amount and total afforestation area at 2050 year by 3 scenarios which are 35%, 45% and 55% about use of domestic softwood log for MDF production. If we do a criterion of cutting area, we advantage to plant larch. But the species of trees are use and growth property. We think that the afforestation policy must be performed on the base of those to supply raw materials of MDF. Although government plans hardwood afforestation policy after cutting Pinus rigida, it needs to support and manage certainly afforestation area of softwoods to need to supply raw materials of MDF to stably promote industry of MDF.

• The Journal of Fisheries Business Administration
• /
• v.40 no.1
• /
• pp.27-49
• /
• 2009

Recently, the Korea's economy concerns the second money crisis because of the rapid increase of the exchange rate. The Korea's economy which is very dependent on the foreign trade is more sensitive to the change of exchange rates. There are many literatures which analyze the effects of variations of the exchange rates on the secondary and tertiary industries such as the manufacturing industry and IT(Information Technology). But there have been no studies which try to figure out the effects of variations of exchange rate on the primary industries, especially, fisheries' industry. Therefore this paper tries to analyze the effect of price competition structure and the change of exchange rate on foreign fisheries exporting prices in Korea's fisheries import market. This study utilizes OLS(Ordinary Least Squares Analysis) for the analysis in the market of frozen yellow corvina, hairtail, angler fish which are major fisheries importable in Korea. The results show that the exporting country which has the highest market share is more sensitive to the change of the exchange rates itself than that of the other exporting countries' price when it starts to set up its exporting price. And the exporting countries which have low market share are more sensitive to the change of price which country has the highest market share than that of price whose countries have low market share and those of their exchange rate. Also we can find out that the countries which have similar market share try to set up price-setting strategy in the opposite direction. In other words, one country tries to bid up its price, other countries response to rival country by lowering their prices. In the consideration of the fact that most exporting countries aren't affected by Korea's fisheries' prices, the exporting countries in Korea's fisheries import market are more sensitive to the prices of other exporting countries than that of Korea's. This result indicates that the price leader-follower model could be applicable to the Korea's fisheries import market.

• Spatial Information Research
• /
• v.20 no.4
• /
• pp.1-16
• /
• 2012

There is no doubt that the urban heat island (UHI) is a mounting problem in built-up environments, due to energy retention by the surface materials of dense buildings, leading to increased temperatures, air pollution, and energy consumption. To investigate the UHI, three-dimensional (3-D) information is necessary to analyze complex sites, including dense building clusters. In this research, 3-D building geometry information is combined with two-dimensional (2-D) urban surface information to examine the relationship between urban characteristics and temperature. In addition, this research introduces spatial regression models to account for the spatial spillover effects of urban temperatures, and includes the following steps: (a) estimating urban temperatures, (b) developing a 3-D city model, (c) generating urban parameters, and (d) conducting statistical analyses using both Ordinary Least-Squares (OLS) and Spatial Regression Models. The results demonstrate that 3-D urban characteristics greatly affect temperatures and that neighborhood effects are critical in explaining temperature variations. Finally, the implications of the results are discussed, providing guidelines for policies to reduce the UHI.

• Korean Journal of Construction Engineering and Management
• /
• v.13 no.2
• /
• pp.128-136
• /
• 2012

In this study, we investigated the macroeconomic variables that affect housing prices thus creating a large impact on people's lives as well as the real estate market. For the study, the macroeconomic variables able to influence the House Rental Price (housing price by lease or deposit) were used for an analysis as follows: housing sales price index, household loans rate, total household savings, the number of employees and a multiple regression analysis was performed using a time series for each macroeconomic variable. As a result of the analysis, the House Rental Price was affected by all of four macroeconomic variables. The House Rental Price increased as each variable enlarged. In conclusion, this study may be useful for finding a solution for stabilizing the House Rental Price as well as for the establishment of efficient and sustainable policies for the housing market.

• Journal of Distribution Science
• /
• v.12 no.3
• /
• pp.65-73
• /
• 2014

Purpose - Aging and fewer economically active people have challenged the assumption of continuous population increases. A new real estate valuation methodology reflecting changes in population structure is thus needed. Research design, data, and methodology - The relationship between demographic change and changes in real estate prices is analyzed using ordinary least squares (OLS) to estimate the parameters, and a population structure change (PSC)-Binomial Option Model is developed to assess the volatility of the estimated parameters. Results based on Seoul and Shanghai data are compared. Results - Results of the DCF method indicate that investing in Seoul is better than investing in Shanghai, but the binomial option indicates the opposite. The PSC-binomial option model, reflecting changes in population structure, yields higher values (24.6 million won in Seoul and 43.3 million won in Shanghai) than those given by the binomial option model. Conclusions - This study indicates that applying changes in population structure to existing research, such as in the binomial option model, represents a more accurate real estate valuation method. Results demonstrate that the new model is more accurate than existing models such as the DCF or binomial option.

• Stress
• /
• v.26 no.4
• /
• pp.327-331
• /
• 2018

Background: For efficient management of an organization's human resource, it is crucial to increase the job satisfaction of women managers, since it is closely related to an individual's job performance and company's one. In this regard, this research explores how women managers' job stress and managerial efficacy affect their job satisfaction. Methods: This research uses the fifth wave of Korean Women Manager Panel (KWMP) collected in 2015. The 1,537 women managers who work at a company with 100 or more employees are employed and the data are analyzed using ordinary least squares (OLS). Results: Income, job stress, and managerial efficacy have a statistically significant effect on job satisfaction. In addition, managerial efficacy has a moderating effect between job-related stress and job satisfaction. Conclusions: This study suggests the meaningful findings that in terms of boosting women manager's job satisfaction, it is requested to promote their managerial efficacy at the human resource management level.

• Journal of Service Research and Studies
• /
• v.8 no.3
• /
• pp.25-35
• /
• 2018

Initiatives for corporate social responsibility (CSR) have often served as sources of competitive advantage in the business world. Although the adoption of CSR practices in the hotel industry continues to increase, empirical research on the relationship between them and financial performance in the industryremains scarce. The purpose of this study was to ascertain the effects of various dimensions of CSR on the financial performance of corporations in the U.S. hotel industry. Data include Kinder, Lydenburg & Domini social performance scores and Compustat data of hotels from 1991 to 2015 identified using a Standard Industrial Classification code. Results of ordinary least squares regression using Stata revealed that efforts toward CSR have significantly affected the financial performance of numerous hotels. Such findings can initiate discussions and inspire future research on CSR in the hospitality industry.

• Journal of Korean Society of Transportation
• /
• v.32 no.6
• /
• pp.638-650
• /
• 2014

The objective of this study is to identify the causes of pedestrian volume path to the destination by investigating the influential levels of regional and planning features in the central area of Seoul. Regional characteristics can be classified from the result of the analysis and through the spatial characteristics of pedestrian volume. For global scale analysis, Ordinary Least Squares (OLS) regression is used for the degree of influence of each characteristics to pedestrian volume. For the local scale, Geographically Weighted Regression (GWR) is used to identify regional influential factors with consideration for spatial differences. The results of OLS indicate that boroughs with transportation facilities, commercial business districts, universities, and planning features with education research facilities and planning facilities have a positive effect on pedestrian volume path to the destination. Correspondingly, transportation hubs and congested areas, commercial and business centers, and university towns and research facilities in the Seoul central area can be identified through the results of GWR. The results of this study can provide information with relevance to existing plans and policies about the importance of regional characteristics and spatial heterogeneity effects on pedestrian volume, as well as significance in the establishment of regional development plans.