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Dataset
Data Files: Applying an Equity Lens to Automated Payment Solutions for Public Transportation
TREC Datasets and Databases
  • Aaron Golub, Portland State University
  • John MacArthur, Portland State University
  • Candace Brakewood, University of Tennessee – Knoxville
  • Anne Brown, University of Oregon
Document Type
Dataset
Publication Date
1-1-2021
Subjects
  • Local transit -- Fares -- Automation,
  • Smart cities,
  • Transportation -- Planning,
  • Local transit accessibility
Abstract

The research team carried out intercept surveys in Portland, Gresham, Eugene and Denver in July, August and September of 2019. In total, 2,303 riders completed intercept surveys across the three regions. Our surveys were designed to take place during short “intercept” interviews between the research staff and the rider, typically at transit stations and bus stops. The surveys focus on current fare payment behavior, access to banking, Internet and smartphone resources, and potential fare payment behavior in the absence of cash options.

Survey questions included current fare payment methods, travel behavior, and technology access. Demographic information was also collected in order to perform an equity analysis. A copy of the survey instrument can be found in Appendix 2 of the final report.

Description

Project PI - Aaron Golub, Associate Professor, PSU

Survey data support a final report published, Applying an Equity Lens to Automated Payment Solutions for Public Transportation, NITC Project Number 1268.

List of Files
NITC 1268 Automated Fare Equity survey data - An Excel file containing 2,303 survey responses.

Rights

This work is marked with CC0 1.0 Universal

DOI
10.15760/TREC_datasets.14
Persistent Identifier
https://archives.pdx.edu/ds/psu/36462
Citation Information
Golub, A., J. MacArthur, C. Brakewood and A. Brown. Data File: Applying an Equity Lens to Automated Payment Solutions for Public Transportation. NITC-RR-1268. Portland, OR: Transportation Research and Education Center (TREC), 2021. https://doi.org/10.15760/TREC_datasets.14