Behavioral studies based on attitude survey questionnaires with numerous variables may be tainted with repetitions and correlations. To overcome these deficiencies, a factor analysis approach is demonstrated that produces clusters of uncorrelated factors. From 47 observable variables contained in the Ottawa-Carleton Transportation Commission (OC Transpo) attitude survey, only 8 underlying/actors have emerged. Bus information service is the most important factor. In addition to factor analysis, this article reports on a logistic regression model, based on key factors, for estimating the odds of ridership.
Syed, Sharfuddin I & Khan, Ata M.
Factor Analysis for the Study of Determinants of Public Transit Ridership.
Journal of Public Transportation, 3 (3): 1-17.
Available at: https://scholarcommons.usf.edu/jpt/vol3/iss3/1