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Interrelationships between retail clusters in different hierarchies, land value and property development: A panel VAR approach

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  • Yoon, Heeyeun

Abstract

Retail clusters do not remain static, but change their size and density, influenced by factors that affect business operations. They also interact with, compete with, or complement others in different hierarchies for customer shares. This study aims to unfold the interrelationship between district- and neighborhood-level retail clusters in a catchment area by investigating how the growth (or decline) of one influences the other, and whether these two retail cluster types differ in their reactions to or impacts on certain external changes—land value and property development—occurring in the catchment areas, in the context of Seoul, South Korea, from 2000 to 2014, using Huff modeling and panel vector autoregressive modeling. Findings suggest that once a district-level retail cluster attracts more retail outlets, it not only continues to grow, but also contributes to the growth of neighborhood-level retail clusters for up to three to four years. Then excessive competition within district-level clusters leads to their own short-term decline before stabilization. The growth of neighborhood-level retail clusters also further spurs their continuing growth, whereas such shock does not influence the district-level retail clusters. Land value is influenced only by district-level retail clusters, and the converse does not hold true. An increase in neighborhood-level retail clusters is one of the stimuli of residential and commercial property developments, while that of the district-level retail clusters only encourages the commercial while discourages residential developments. Conversely, when residential property developments occur in the catchment area, neighborhood retail clusters respond positively and experience short-term growth.

Suggested Citation

  • Yoon, Heeyeun, 2018. "Interrelationships between retail clusters in different hierarchies, land value and property development: A panel VAR approach," Land Use Policy, Elsevier, vol. 78(C), pages 245-257.
    • Handle: RePEc:eee:lauspo:v:78:y:2018:i:c:p:245-257
    DOI: 10.1016/j.landusepol.2018.06.032
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    1. Gu, Donghwan & Newman, Galen & Kim, Jun-Hyun & Park, Yunmi & Lee, Jaekyung, 2019. "Neighborhood decline and mixed land uses: Mitigating housing abandonment in shrinking cities," Land Use Policy, Elsevier, vol. 83(C), pages 505-511.
    2. Dongjun Kim & Jinsung Yun & Kijung Kim & Seungil Lee, 2021. "A Comparative Study of the Robustness and Resilience of Retail Areas in Seoul, Korea before and after the COVID-19 Outbreak, Using Big Data," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    3. Xinyu Hu & Huiya Yang & Junyan Yang & Zhonghu Zhang, 2019. "Spatial Correlation Network of Format in the Central Districts of a Megacity: The Case of Shanghai," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    4. Pengnan Xiao & Chong Zhao & Yong Zhou & Haoyu Feng & Xigui Li & Jinhui Jiang, 2021. "Study on Land Consolidation Zoning in Hubei Province Based on the Coupling of Neural Network and Cluster Analysis," Land, MDPI, vol. 10(7), pages 1-16, July.

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