Replication Data for: How E-Scooters Impact Shared Mobility and Consumer Safety

This dataset accompanies the article “How E-scooters Impact Shared Mobility and Consumer Safety” submitted to the Journal of Marketing. It provides census tract-level panel data and supporting replication materials used to analyze the effects of e-scooter entry on shared mobility and consumer safety. The core dataset (data_main.csv) is structured at the census tract × week level and includes rideshare trips, bikeshare trips, crime counts, demographic variables, and controls. Supplementary datasets capture specific mechanisms: retail and dining visits (data_visit.csv), time- and day-of-week variations in rideshare and bikeshare trips (mechanism_rideshare.csv, mechanism_bikeshare.csv), disaggregated crime outcomes (mechanism_crime.csv), trip distance distributions (rideshare_binned_trip.csv, bikeshare_binned_trip.csv), and close vs. far trip shares relative to e-scooter locations (rideshare_close_vs_far.csv, bikeshare_close_vs_far.csv). Replication materials include a master analysis script (replication.Rmd), rendered output with tables and figures (replication.html), and associated code. Standard errors are computed via bootstrap with 1,000 replications, with results replicable by fixing the random seed. The dataset allows researchers to replicate all reported results, tables, and figures.