Linking Satisfaction to Behavior: Can (Dis)satisfaction Predict Transit User Attrition Over Time?

Many large transit agencies regularly conduct customer satisfaction surveys, but to date, little is known about the link between satisfaction and transit rider loyalty. Previous research has shown that satisfaction affects travelers' intentions to remain transit users in the future, but those studies have generally collected satisfaction and loyalty measurements at the same time. This paper uses a novel panel dataset where satisfaction on multiple dimensions and changes in transit use were measured one year apart, allowing the authors to quantify observed behavior changes and to understand which aspects of satisfaction were most predictive. The results of an exploratory factor analysis and a structural equation model presented in this paper show that the 13 measures of satisfaction with different aspects of the service are caused by two underlying latent factors - satisfaction with operations and satisfaction with the travel environment - and that overall satisfaction is mainly driven by the former. Two integrated binary choice and latent variable models are then developed to test the relationship between satisfaction, intentions, and loyalty. The results show a significant effect of satisfaction with operations on the probability of using transit less or having stopped completely after a year. On the other hand, a significant relationship between intentions and future behavior was not found. A sensitivity analysis with the model demonstrates how satisfaction can be used to predict transit rider attrition. Lastly, users' self-reported reasons for attrition are presented, generally corroborating the finding that satisfaction with operations is the key driver but offering some additional nuance.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AP030 Standing Committee on Public Transportation Marketing and Fare Policy.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 6p

Subject/Index Terms

Filing Info

  • Accession Number: 01698001
  • Record Type: Publication
  • Report/Paper Numbers: 19-04581
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 1 2019 3:51PM