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

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.33-44
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• 2019

The Indonesian government launched a new people's business credit program as part of a package of economic policy and deregulation. The interest rate is set lower than the average of the current loan interest rates, especially when compared with rural bank interest rates. To capture the social spatial aspects, quota sampling is applied to ten areas that divided based on the social culture. Further, the method utilized in this research is logit models, which designed to analyse the determinants of asymmetric information particularly on the rural bank and small micro enterprises. The study was conducted in East Java as the province with the largest number of rural banks in Indonesia. Based on the estimation of asymmetric information model to the respondent of rural banks and small businesses, the result shows that adverse selection can be avoided by strengthening the information about prospective borrowers. Regarding moral hazard, rural banks and small businessmen argued that the imposition of the collateral to the debtor has an important role to avoid moral hazard. Rural bank respondents stated that the KUR program with low-interest rates has affected their business development. The results implied the need of broadening the collaboration schemes between this people's business credit program and rural banks.

• East Asian Economic Review
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• v.25 no.1
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• pp.3-31
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• 2021

This paper estimates the effects of transport (road and rail) & energy and ICT infrastructure (telephone, mobile, and broadband) on GDP growths in neighboring countries as well as own countries. We confirm positive direct contributions of infrastructure, access to Internet, and human capital on economic growth. The spatial panel regression models indicate that there exist positive externalities of the broadband infrastructure and human capital, and these results are robust regardless of the choice of spatial weight matrices. Our findings on spillover effects of infrastructure suggest the key role of neighboring countries' infrastructure on own country's economic growth.

• Environmental and Resource Economics Review
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• v.14 no.4
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• pp.923-941
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• 2005

Odor problem of livestock operation is important issue in a local community. I quantified the property price impact of 199 livestock operations for 3,355 housing sales in the U.S (Colorado). Spatial hedonic model was adopted to deal with spatial autocorrelation in housing market. Small beef and dairy operations, which are the traditional agricultural sector, seem to create a positive rural lifestyle amenity effect. However, the impact of livestock operation on rural residential sales turns to negative if the operation is over a certain size and species. Large hog and sheep operation seems to bring fatal economic loss from the local community perspective if it close to residential area. Livestock odor is one of the negative externality, the results provide the potential social cost of the livestock sector in the region. Policy makers may incorporate this social cost in the regional planning to minimize the social and maximize the development effect. Therefore, local officials and private individuals should carefully consider the location and characteristics of new residential properties and livestock operations alike.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.1-11
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• 2024

Farmland transaction prices are affected by various factors such as politics, society, and the economy. The purpose of this study is to identify multiple factors that affect the farmland transaction price due to changes in the actual transaction price of farmland by farmland unit from 2016 to 2020. There are several previous studies analyzed the determinants of farmland transaction prices by considering spatial dependency. However, in the case of land transactions where the time and space of the transaction affect simultaneously, if only spatial dependence is considered, there is a limitation in that it cannot reflect spatial dependence that occurs over time. In order to solve these limitations, To address these limitations, this study builds a spatio-temporal autoregressive model that simultaneously considers spatial and temporal dependencies using farmland transactions in Jinju City as an example. As a result of the analysis, it was confirmed that there was significant spatio-temporal dependence in farmland transactions within the previous 30 days. This means that if the previous farmland transaction was carried out at a high price, it has a spatio-temporal spillover effect that indirectly affects the increase in the price of other nearby farmland transactions. The study also found that various location attributes and socioeconomic attributes have a significant impact on farmland transaction prices. The spatio-temporal autoregressive model of farmland prices constructed in this study can be used to improve the prediction accuracy of farmland prices in the farmland transaction market in the future, and it is expected to be useful in drawing policy implications for stabilizing farmland prices

• International Journal of Human Ecology
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• v.14 no.1
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• pp.87-102
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• 2013

This study investigated residents' preferences for spatial features of sitting areas in assisted living facilities, and provides recommendations for planning sitting areas to support residents' spatial preferences and social interaction. The study participants were 69 residents of eight assisted living facilities (30+ resident capacity), located in south central Texas. A photographic comparison method was used, in which residents were shown 20 matched pairs of photos, with a single feature digitally modified in each pair, and asked to select which environmental representation they preferred. The hypothesized spatial characteristics were identified in practice based literature as those that may encourage usage of sitting areas: viewability, variety, homelikeness, and privacy. Most of the hypothesized features were preferred by participants, with the highest preference found for non-institutional furniture arrangements and naturalness, followed by increasing enclosure and variety of seating. Preference was less significant for domestic cues such as carpeted floors, divided light windows, and boundaries defined by different colored material or columns, possibly due to their physical impairments or preference for visual openness. Participants' level of mobility assistance was significantly related to their preference for some features, such as seating with people-watching capability, and carpeted floors. The findings have implications for facility architects and administrators engaged in resident-oriented spatial planning.

• Human Ecology Research
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• v.54 no.2
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• pp.131-139
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• 2016

This study analyzes the welfare services and spatial composition of social welfare centers that represent complex welfare facilities in order to provide basic information for the spatial planning of social welfare centers. We examined 15 social welfare centers built in the 2000s. A literature review and case study were used as research methodology. The findings are as follow. First, services provided at the surveyed facilities overlapped for seniors and the handicapped. Most social welfare centers provided welfare services for seniors, young children, and teenagers. Second, the proportion of common area, program rooms was high for spatial composition. Third, front access by car was most common (used at nine centers) for the design of the access area and used by. Fourth, shared entry and exit was most common (used at 10 centers) for the design of the entrance. Fifth, regarding space combining style, a mixed style was most frequently used (observed at seven centers) where different private areas for different service users were partly mixed on certain floors. Sixth, a corridor type was most common (used at seven centers) for the design of a corridor space where visitors could walk along the corridor to access individual rooms. Based on the findings, we propose spatial composition of social welfare centers to promote mingling and exchanges among users of different generations.

• Journal of Korean Society of Rural Planning
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• v.16 no.1
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• pp.9-20
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• 2010

The aim of this paper is to identify Korean agricultural and agri-manufacturing cluster using a multi-regional input-output model. This paper derives a representative set of five agricultural and agri-manufacturing clusters in Korea in terms of spatial and industrial interdependency. The results show that agriculture and agri-manufacturing clusters agglomerated in Seoul Metropolitan Area and Chungcheong Area are linked both production and manufacture functions, whereas Gangwon Area is more focused on production and Jeolla Area is more concentrated on manufacture.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.461-471
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• 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 Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.