Touristification and Retail Change: An Ecological Perspective on the Transformation of Urban Shopping Streets

The increasing prominence of tourism in urban areas has led to significant transformations in urban landscapes and economies. One crucial aspect of this transformation is the impact on the retail sector. While gentrification driven by tourism has been acknowledged, its effect on retail diversity remains under-theorized. This study addresses this gap by examining how touristification influences the composition and spatial distribution of retail outlets in urban centers. The research questions focuses on understanding the specific mechanisms through which tourism shapes retail change and the consequent impact on the social and economic fabric of neighborhoods. The study employs an ecological lens, drawing parallels between ecological processes and the dynamics of retail environments under touristic pressure. The importance of this study lies in its potential to inform urban planning strategies aimed at promoting both economic vitality and community resilience in the face of touristification.

Existing literature extensively documents the negative consequences of touristification, including displacement of residents and the homogenization of cultural experiences. Studies have explored the links between tourism, gentrification, and socio-spatial restructuring, focusing primarily on residential displacement and the replacement of local businesses by larger commercial entities. However, the impact of touristification on retail diversity remains under-researched. While some studies have touched upon the role of retail change in gentrification processes, a comprehensive understanding of the interplay between touristification and retail diversity is lacking. This research aims to fill this gap by providing an ecological perspective on the transformation of urban retail landscapes, and examining the empirical evidence in Hong Kong.

The study uses Hong Kong as a case study, a city known for its vibrant tourism and diverse retail environments. The researchers collected data on the types and spatial distribution of retail outlets in a selected area of Hong Kong, specifically Sheung Wan. They then applied two clustering methods: k-means and DBSCAN, to identify distinct retail clusters based on spatial proximity and density. K-means clustering is used to establish a primary understanding of the overall retail distributions. To ensure the robustness of the analysis, a secondary clustering method, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), was used as a sensitivity test. DBSCAN is particularly useful for identifying clusters of arbitrary shapes and sizes, common in urban settings and better handles outliers than k-means. The study employs the Species-Area Relationship (SAR) framework, to analyze the relationship between retail diversity and the area of the retail district. By treating different retail types as 'species' and the retail area as 'habitat', the authors examine how touristification affects the overall diversity of retail outlets. The results from both clustering methods are compared and analyzed alongside the SAR data to give a comprehensive understanding of how touristification impacts retail environments.

The study found a strong correlation between the intensity of touristification and the transformation of retail landscapes. Areas with high tourist footfall exhibited a decline in the diversity of retail businesses. Traditional, locally-owned shops were often replaced by tourist-oriented businesses, resulting in a homogenization of retail offerings. This mirrors ecological succession, where native species are replaced by invasive species. K-means and DBSCAN clustering identified distinct retail clusters, revealing spatial patterns consistent with the SAR model. The initial analysis using k-means identified a number of distinct clusters which were further refined with the DBSCAN approach, resulting in 85 distinct retail clusters allowing for a more granular understanding of the impact of touristification on retail diversity. The DBSCAN results align with known commercial distributions and the spatial distributions highlight the process of how touristification transforms local retail landscapes.

The findings support the hypothesis that touristification significantly impacts retail diversity, leading to a shift towards businesses that cater primarily to tourists. The use of the SAR framework provides a novel and insightful perspective on understanding these dynamics. The study highlights the need for urban planning strategies that balance the economic benefits of tourism with the preservation of local retail diversity and cultural character. The analogy of ecological succession underscores the potential for irreversible changes in urban retail environments if not carefully managed. The use of DBSCAN clustering provides a robust method for analyzing complex retail landscapes, while the SAR model adds depth to the analysis of retail diversity.

This study offers a valuable contribution to the understanding of the impact of touristification on urban retail environments. The findings underscore the need for proactive urban planning that considers the preservation of retail diversity alongside economic growth driven by tourism. Future research could explore the specific socioeconomic impacts of this retail transformation on local communities and explore the effectiveness of policy interventions to mitigate the negative effects of touristification.

The study is limited to a single case study in Hong Kong, Sheung Wan specifically. The generalizability of the findings to other urban contexts may be limited. Future research should expand the geographical scope to explore the cross-cultural applicability of the model. Additionally, the data collected might not fully capture the dynamic nature of retail changes, given the rapid pace of business openings and closures in urban environments.