Dynamic changes in side-street trade areas of Seoul: Using growth mixture modeling

Abstract

This study examines the dynamic changes in side-street trade areas in Seoul, focusing on their growth trajectories to propose strategies for sustainable development. Using data from 1005 side-street trade areas from 2015 to 2019, the study employs Growth Mixture Modeling (GMM) to categorize trade areas based on growth patterns. The findings reveal that over half of these trade areas have experienced sustained decline. Incorporating initial store density, a probabilistic analysis highlights the significant role of initial conditions in shaping future trends.

Spatial autocorrelation analysis using 2015 initial store density data revealed statistically significant clustering patterns in approximately 10 % of trade areas. Both high-density and low-density areas exhibited a tendency to cluster, with high-density clusters occasionally displaying localized synergistic effects, suggesting potential for continuous growth in specific cases.

Additionally, the study explores industry-specific density changes across restaurant, service, and retail sectors, identifying distinct growth patterns and their interactions with overall trade area trends.

Key recommendations include designating critical commercial hubs as density management zones to regulate overall and industry-specific density levels. Policies such as subsidies or tax benefits for underrepresented sectors are proposed to encourage industry diversification. Furthermore, rent control measures are suggested to mitigate the adverse effects of gentrification, preserving the unique character of trade areas.

This research provides actionable insights for policymakers and entrepreneurs, contributing to the development of more sustainable and adaptive strategies for urban commercial districts.