Causal Relationships Between Transportation Attitudes and Behaviors: Uncovering Latent Segments within a Heterogeneous Population

This project is concerned with exploring the relationship between attitudes, perceptions, and values on the one hand and behavioral choices on the other hand. There is a vast body of literature in a number of disciplines that has clearly demonstrated a strong inter-dependent relationship between attitudes and behaviors (Wicker, 1969; Norman, 1975; Fishbein and Ajzen, 2010; Ahn and Back, 2018). In the transportation context, attitudes about various transportation options as well as personality traits that describe the innate proclivities and preferences of the individual are likely to be strongly associated with residential and work place location choices (Cao et al., 2010; Bhat, 2015a, Ettema and Nieuwenhuis, 2017), mode choice (Heinen et al., 2011; He and Thøgersen, 2017), parking choice (Soto et al., 2018), vehicle ownership and type choice (Acker et al., 2014; Choo and Mokhtarian, 2004), activity engagement and time use patterns (Archer et al., 2013; Frei et al., 2015), and willingness to participate in the sharing economy and adopt new technologies (Astroza et al., 2017; Lavieri et al., 2018; Egbue and Long, 2012; Alemi et al., 2018). This study aims to develop a joint equations model of attitudes and behaviors that explicitly recognizes the package nature of the relationship among them. However, unlike previous studies, this research effort explicitly recognizes that there may be population heterogeneity with respect to the nature of the relationship between attitudes and behaviors. While undoubtedly mutually reinforcing, attitudes may influence behaviors for some folks and behavioral choices may affect attitudes for others at a specific cross-section in time. A multitude of directional relationships between attitudes and behaviors may exist in the population and it would be of interest to determine the extent or degree to which each of the directional relationships is prevalent in the population at a specific cross-section in time. By determining the degree to which each relationship exists in the population, and the characteristics of each market segment (in terms of socio-economic and demographic characteristics, for example), it would be possible to design policy interventions, behavioral experiences, and information campaigns that are appropriately targeted and implemented to achieve desired outcomes.


  • English


  • Status: Completed
  • Funding: $89,490
  • 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
  • Performing Organizations:

    Center for Teaching Old Models New Tricks (TOMNET)

    Arizona State University
    Tempe, AZ  United States  85287
  • Principal Investigators:

    Pendyala, Ram

  • Start Date: 20191001
  • Expected Completion Date: 20211001
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01754997
  • Record Type: Research project
  • Source Agency: Center for Teaching Old Models New Tricks (TOMNET)
  • Contract Numbers: 69A3551747116
  • Files: UTC, RIP
  • Created Date: Oct 20 2020 8:10PM