Using Local Review Data to Analyze Shifting “Catchment Areas” of Gentrifying Businesses

Keywords: Gentrification, Location-Based Services, Big Data, Digital Geographies
Session Type: Virtual Paper Abstract
Day: Monday
Session Start / End Time: 2/28/2022 03:40 PM (Eastern Time (US & Canada)) - 2/28/2022 05:00 PM (Eastern Time (US & Canada))
Room: Virtual 7

Abstract

Millions of people rely on digital location-based services (LBS), local review and digital mapping platforms, to navigate their world and make decisions about where to spend time and money in cities around the world. While a growing literature uses anonymized LBS data to understand human mobility patterns (see Chen and Poorthuis 2021), little of this work centers local businesses and their place in shifting urban and regional economies. Drawing on Richard Ocejo’s research on the transterritorial nature of “taste communities” brought together at upscale consumption sites like gourmet restaurants, coffee shops, and cocktail bars (Ojeco 2014), this paper uses spatiotemporal analysis of LBS review activity to depict and analyze the shifting “catchment areas” of local businesses as measured through the locations of their reviewers over time.

This paper focuses on “scale-jumping” of businesses attracting external taste communities, whether tourists or newer (typically wealthier and whiter) residents in gentrifying neighborhoods, though the widespread usage of LBS platforms in both familiar and unfamiliar locations has eroded some of the differences between these groups. Put crudely, a craft cocktail bar may draw reviewers from around the country and the world, where a fast food restaurant may reach a much more targeted local audience. When one type of business succeeds the other, the changing geography of the new establishment’s customer base can be compared to other measures of neighborhood change, and even used as an advance metric for communities concerned about a potential influx of wealthier residents and development interests.