Project title
The Spatial Segregation of Neighborhood Organizations and Entrepreneurs: Connecting Urban Inequality to the Built Environment
Project description
Local organizations and entrepreneurs play a crucial role in urban neighborhoods, connecting and empowering residents by providing resources and access to various aspects of urban life. Integrating the built environment into our understanding of organizations/entrepreneurs in the geo-social landscape is an underexplored area, despite its potential to directly influence social connectivity.
Through an integrated interdisciplinary approach, the NIAS-Lorenz theme group aims to gain a deeper understanding of the mechanisms underlying the relationship between the built environment, social processes, and neighborhood organizations/entrepreneurs. Amsterdam provides the ideal setting for this research, considering its demographic context and data availability.
As a member of the group, Mingshu Wang aims to provide a comprehensive understanding of the built environment’s features and establish quantitative connections between these characteristics and various aspects of organizational vitality and social networks. He will utilize diverse geospatial data at various scales, combined with spatial models and explainable machine learning techniques.
Selected publications
Wang, M., Vermeulen, F. (2021) Life between buildings from a street view image: What do big data analytics reveal about neighborhood organizational vitality? Urban Studies, 58(15), 3118-3139. DOI: https://doi.org/10.1177/0042098020957198
Wang, M. (2021) Polycentric urban development and urban amenities: Evidence from Chinese cities. Environment and Planning B: Urban Analytics and City Science, 48(3), 400-416. DOI: https://doi.org/10.1177/2399808320951205
Wang, M., Chen, Z., Rong, HH, Mu, L., Zhu, P., Shi, Z. (2022) Ridesharing accessibility from the human eye: Spatial modeling of built environments with street-level images. Computers, Environment and Urban Systems, 97, 101858. DOI: https://doi.org/10.1016/j.compenvurbsys.2022.101858