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http://dx.doi.org/10.15722/jds.20.12.202212.109

A Study on the Rent Characteristics of Small Shopping Malls  

KIM, Sun-Ju (Department of Real Estate Asset Management Graduate school, Kyonggi University)
Publication Information
Journal of Distribution Science / v.20, no.12, 2022 , pp. 109-116 More about this Journal
Abstract
Purpose: The purpose of this study is to analyze the rental determinants of a small shopping mall located in Seoul, Korea, and the characteristics of four commercial districts (CBD, GBD, YSD, etc.). Research design, data, and methodology: For the characteristics of the data, descriptive statistics and frequency analysis were used. Artificial Neural Networks (ANNs) have been used as rental determinants for small shopping malls. The characteristics of 4 commercial districts were analyzed using Analysis of variance (ANOVA) and post-hoc analysis. Results: 1) CBD 14.8%, GBD 16.7%, YSD 13.0%, others 55.6%. 2) The order of important variables affecting rent: CBD=1> GBD=1> vacancy rate> rental index> number of buildings> YBD=1> average gross floor area> conversion rate> average floor. 3) Characteristics of commercial district: Rents in CBD and GBD are high. The conversion rate is high in the GBD commercial area. The number of buildings is high in the CBD. The average area of GBD is larger than that of other commercial districts. Conclusions: 1) Several factors should be considered when investing in or renting a small shopping mall. 2) Depending on the investment and business purpose, factors such as rent, conversion rate, building, and area average should be considered.
Keywords
Small Shopping Mall; Commercial Districts; Rent; Artificial Neural Networks; Analysis of variance; Post-Hoc;
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