• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.784-792
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• 2018

In this study, we designed the area except the development market and the traditional market, where large scale shops were concentrated by realizing the real estate center of the alley commercial area. In addition, we have developed an area setting method for the alley area where reliability and rationality can be ensured by utilizing the actual data such as the business statistics, the survey data of the business, and the store business DB, which are managed by the local government or the state. The alley commercial areas were classified into five groups according to density. It is thought that users can distinguish the commercial areas from dense commercial areas to the commercial areas in order to utilize various commercial areas.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.101-109
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• 2023

According to data released by the Covid 19 Self-Employed Emergency Response Committee, 95.6% of small business sales due to Covid 19 have decreased over the past two years, and the damage has further increased due to social distancing for quarantine. However, as all social distancing guidelines have rebeen lifted, and the commercial district has been revitalized, the Seoul Metropolitan Government is pushing for a project to foster local brand commercial districts so that small business owners or prospective founders who have closed their businesses due to the prolonged COVID-19. Therefore, this study propose the model that recommends alley commercial districts suitable for founders among the five alley commercial districts selected for the project to foster local brand commercial districts in Seoul. The Seoul Metropolitan Government's local brand alley commercial recommendation system recommends major population age groups and major industries in the commercial district by combining the population perspective model using Xgboost and the commercial district characteristic model using Decision Tree.

• Journal of the Korean Regional Science Association
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• v.39 no.1
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• pp.53-66
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• 2023

Due to COVID-19, the external activities of urban residents have greatly shrunk, causing a lot of damage to the commercial district, such as a decrease in population and sales. The downturn in commercial districts means the collapse of the infrastructure of the national economy, and can have serious side effects on the local economy and individual lives. Therefore, it is necessary to look at the alley commercial area, which is closely related to the national local economy, and pay attention to the damage and stagnation of the alley commercial area where small business owners are concentrated. The purpose of this study is to classify alley commercial districts into growth commercial districts and decline commercial districts by using commercial sales time series data and DTW time series group analysis for the pre- and post-COVID-19 period. The main findings of the study are as follows. First, using the time series data on commercial sales before and after COVID-19, the alley commercial districts were divided into growth commercial districts and decline commercial districts, and it was confirmed that the distribution of growth commercial districts and decline commercial districts was regionally different. Therefore, it is necessary to actively manage commercial districts in areas where many declining commercial districts are distributed, and it is required to prepare policies for each region in consideration of the spatial distribution of declining commercial districts. Second, during the COVID-19 period, face-to-face essential industries, density of guest facilities, and population density negatively affected the sustainability of commercial districts, which is the opposite of previous studies. This is the result of empirically confirming the specificity of the COVID-19 period and the negative effects of the integrated economy, and can be used as basic data for effective commercial district management and policy preparation in the event of a national disaster in the future. Third, the characteristics of the background of the commercial district had a significant effect on the sustainability of the commercial district, and the negative effect of the attracting facilities inducing population concentration in the background area was found. This suggests that it is necessary to consider the characteristics of the background as well as the inside of the commercial district when establishing policies to revitalize the commercial district and support small business owners in a national disaster situation.

• Journal of Biosystems Engineering
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• v.25 no.4
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• pp.279-286
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• 2000

Most of the domestic cold storage rooms are inefficient for agricultural products because of temperature gradients inside the storage rooms. Temperature gradients are developed mainly by improper airflow pattern inside the storage room, which is a main cause of the spoilage of the agricultural products. There proper airflow pattern is essential to minimize these temperature gradients and the spoilage. The performance and characteristics of a cold storage room were determined as a function of airflow pattern and temperature distribution in forced circulation cold storage room. A commercial CFD(computational fluid dynamics) code was used to simulate 3-D airflow in the cold storage room. Solving the flow equations for the storage room, a standard k-$\varepsilon$ turbulent model was implemented to calculate steady state turbulent velocity distribution. The CFD prediction results were compared with temperature measurements inside the cold storage room. In case of pallet storage, Temperature gradients inside pallet storage was reduced because the contact area of cold air expanded through an alley of airflow in storage. But is case of bulk storage, the last temperature of storage considerably rose more than the initial temperature of storage. The reason was that bulk storage didn't include any alley of airflow in storage.

• 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.

• 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.