The Effect of Survey Methodology on The Collection of Attitudinal Data

Surveys continue to be critical sources of data for making informed decisions about transportation plans and policies and understanding the evolutionary dynamics of the population. However, challenges associated with deploying surveys and obtaining representative survey data suggest that respondent samples are likely to differ from the general population not only on observables (socio-economic and demographic characteristics), but also on many unobservables (mobility choices, attitudes, values, preferences, and perceptions) for which census data is not available and does not exist. This study relies on two recent surveys conducted in the United States to examine sample representativeness. One survey, conducted in 2019, gathered data about people’s lifestyle preferences as well as attitudes, values, and perceptions of emerging transportation technologies. The second survey, conducted in 2020, gathered data about people’s lifestyle preferences and activity-travel responses to (and attitudes towards) COVID-19. The survey samples have been weighted to match population-wide census distributions along several socio-economic and demographic dimensions. Results show that descriptive statistics (means, standard deviations, median values) of attitudes and values for weighted survey samples are likely to be of limited value in drawing population-wide inferences necessary for designing transportation plans and policies.


  • English


  • Status: Completed
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Center for Teaching Old Models New Tricks (TOMNET)

    Arizona State University
    Tempe, AZ  United States  85287
  • Project Managers:

    Pendyala, Ram

  • Performing Organizations:

    Arizona State University, Tempe

    Tempe, AZ  United States 
  • Principal Investigators:

    Pendyala, Ram

  • Start Date: 20200801
  • Expected Completion Date: 0
  • Actual Completion Date: 20210731
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01877156
  • Record Type: Research project
  • Source Agency: Center for Teaching Old Models New Tricks (TOMNET)
  • Contract Numbers: 69A3551747116
  • Files: UTC, RIP
  • Created Date: Mar 25 2023 10:01AM