Brewing success: a geospatial analysis of Chiang Mai's coffee shops through publicly available data sources

Purpose This study examines how spatial factors shape the popularity of coffee shops in Chiang Mai, Thailand and a mid-sized Southeast Asian city with a rapidly expanding café culture. It investigates whether proximity to urban amenities and neighboring cafés influences customer engagement reflected in online reviews and ratings. Design/methodology/approach Data were collected in June 2025 using the Google Places API, identifying 2,468 coffee shops. Each entry was enriched with OpenStreetMap (OSM) data on nearby tourist attractions, universities, coworking spaces and transport hubs. A composite popularity score was constructed from ratings and review counts. Spatial clustering methods (DBSCAN, Moran's I and LISA) and correlation analysis were used to assess how popularity relates to locational characteristics. Findings Popular cafés cluster in central districts, especially tourism areas, while proximity to general amenities shows weak associations with popularity. Newer or lower-performing cafés benefit from locating near successful peers, suggesting visibility spillovers. In contrast, top performers often succeed outside clusters, indicating differentiation or destination appeal. Practical implications New entrants may enhance visibility by co-locating near established cafés, while mature businesses can sustain engagement through distinctive positioning in lower-density areas. Policymakers may support café districts such as Nimmanhaemin and the Old City while encouraging balanced dispersal. Originality/value This study integrates digital reputation metrics with geospatial data to advance understanding of spatial embeddedness in hospitality entrepreneurship. Combining Google Places and OSM demonstrates how spatial positioning and online visibility jointly shape outcomes.