• Journal of the Korean Regional Science Association
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• v.34 no.1
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• pp.31-47
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• 2018

This study examines the locational characteristics and change of business type in the residental areas that have commercial gentrification issues in Seoul, Korea, using the logistic regression model. The analysis results indicate that the gentrification occurrence areas are strongly associated with low-density and old residential areas. In addition, those areas are more likely to have great accessibilities to highway ramp, subway station, colleges, and other facilities that attract people. Regarding the characteristics of the road, gentrification occurrence areas are associated with longer road length, lower rate of road areas, higher local integration of road network, and higher rate of three-way intersections. This finding indicates that low-density and old residential areas with organic road networks have strong links with commercial gentrification. This study also finds that the business type has been substantially changed from 2006 to 2014 in the commercially gentrified residential areas. While the coffee shops and drinking places have been increased, but neighborhood-living facilities have been decreased. This study also shows that the business life-cycles of drinking places or Korean restaurant are getting short. Finally, this study discusses the commercial gentrification issues and policy implications in the residential districts in Seoul, Korea.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

• Journal of the Korean association of regional geographers
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• v.5 no.2
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• pp.47-117
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• 1999

This study concern with the pattern of Pusan Station shopping district within Pusan City, Korea, one of the special functioned shopping district within Pusan City. This paper will serve as a part of series studies which attempt to clarify the internal structure of Pusan as a whole. Part(II) of this study deals with the functions including living related, restaurants and others. The pattern of floors, size of shops, street corners and widths of streets were also analysed. The results are as follows: 1. In terms of numbers of firms in living related function, Pusan Station shopping district is the $7{\sim}8th$ ranked central place among nine the highest centers within Pusan City. Pusan Station shopping district has not much promoted vertical spatial differentiation comparatively, and also it's intensity of land use is the lower among nine the highest centers. It is presented that intimate relationship between intensity of vertical land use and classes of central places within the city. The ratio of inns and hotels in Pusan Station shopping district is third ranked in Pusan City. And the size of inns and hotels in this area is the most largest among the nine highest ranked central places within Pusan City. These presented that the traditional characteristics of station area as a special functioned shopping district. Inns and hotels mainly located along the narrower and back street. And it forms agglomerated areas or 'an alley of inns' at the inner parts of blocks, some like a 'hidden flower'. In Korea, 'alley' means that an area of specialization gains the prestige, traditionally. 2. Restaurants mainly locate along the narrower and back streets. And agglomerated areas of restaurants coincide with the agglomerated area of drinking places. It shows that these two kinds of functions need the same locational conditions. The ratio of Chinese restaurants is the highest in the Pusan Station shopping district. It's due to the agglomerated area these kinds of restaurants at the 'China town'. 3. Pusan Station shopping district has been formed along the streets within the residential areas. It's means that this shopping district now at the initial or middle growth era in development stage of shopping areas. 4. In general, wholesales and light manufacturing are located at peripheries within shopping district. But in Pusan Station shopping district, it dose not appear these spatial pattern. It shows that this area is lower ranked central place and not much progressed in spatial differentiation. 5. Particular firms which customers and workers have stayed more longer period of time are located at the far from the first floor. This vertical spatial differentiation is similar to the horizontal sequences. 6. Firms which have more ability of rental payment are located at street comers such as banks and pharmacies. In Pusan Station shopping district commercial facilities could not invade into the second third floors at narrower streets and first floor of back streets, still now.