Abstract
Using publicly available microdata sets, we show how estimates for online delivery purchases can be generated for granular areas and how the estimates vary across small geographic areas defined in our study as micro analysis zones (MAZ).With a focus on Miami-Dade County, we use both the national household travel survey (NHTS) data and synthetic data obtained from Southeast Florida Regional Planning Model (SERPM) to generate demand estimates of online delivery purchases for more than 5,300 distinct geographic units in Miami-Dade County. We validate our results by comparing our estimates with the population estimates obtained from the NHTS survey data and by benchmarking our estimates with the locations of Amazon lockers. Our approach fills a void in the area of purchases of online delivery items where rich observable data are typically unavailable and also provides the added potential benefit of easily replicating this study nationwide given its emphasis on the use of publicly available data.
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