Priority Intervention Evaluation of Community Regeneration in Megacities Based on the Business Improvement District (BID) Model: A Case Study of Tianjin, China

• Published in: Buildings (Basel) 2024-08, Vol.14 (8), p.2263
• Main Authors: Bai, Wenjia, Chen, Mingyu, Bai, Fazhong, Huang, Jingtao
• Format: Article
• Language: English
• Subjects: Agglomeration; business improvement district; Business improvement districts; Case studies; City centres; Clustering; Community development; Evaluation; Identification methods; Intervention; Literature reviews; Megacities; multi-source data analysis; Noise measurement; older communities; Parameter identification; Population density; Population studies; Priorities; Residential communities; Residential density; Retail industry; Roads; Service areas; Urban regeneration; Urban renewal
• ISSN: 2075-5309; 2075-5309
• DOI: 10.3390/buildings14082263

This study aims to start from the macroscale of the megacity, explore a top-down operational technical path from the identification of community regeneration units as the evaluation objects to the BID priority intervention evaluation, and then propose differentiated community regeneration strategies based on the BID model. In the post-epidemic era, it is necessary for global megacities to take new measures in urban regeneration to respond to worldwide changes and challenges. As an innovative tool to promote central city revitalization, the BID model has played an important role in community transformation. In the context of the continuous decentralization of population and industry in China’s megacities, it is urgent to explore the technical path to apply the BID model to local community regeneration. Given the shortcomings of existing studies in the method to identify the scope of BID implementation and evaluate intervention priorities, this study takes Tianjin, a megacity in China, as an example and uses DBSCAN (density-based spatial clustering of applications with noise) and service area analysis to define the community regeneration units with commercial agglomeration characteristics as the objects. Then, the BID priority intervention evaluation system is constructed from the two measurement aspects of the intervention potential and the necessity of community regeneration to classify the BID intervention priorities of community regeneration units. The main conclusions are as follows: 1. When the DBSCAN analysis parameters take the minimum number of elements as 30 and the search distance as 120 m, the result is most suitable for identifying community units with commercial agglomeration of the study area; 2. Population vitality, especially working and residential population density, is the key factor affecting BID intervention potential, while road network density is an important indicator for determining the necessity of community regeneration; 3. Community regeneration units with high BID priority levels need to develop differentiated regeneration strategies combining their BID intervention potential, regeneration necessity characteristics, and location attributes. These conclusions can provide references for the governments of megacities to screen and establish BIDs.