In this paper, an analysis framework in which attitudinal data are used to support service design decisions for a public transportation system is described. An analysis of the riders' ratings identified the rail service performance weaknesses that limit ridership. The identification of strong monotonic relationships linking objective measures of rail performance to rider perceptions made it possible to forecast the impact of service improvements on travelers' service ratings and on mode choice to predict ridership changes. The analysis framework provides transit agencies with a tool both to diagnose deficiencies in the service provided to travelers and to evaluate the ridership impact of service improvements and marketing changes aimed at increasing ridership levels. The framework was applied to Chicago area commuter rail service to demonstrate its feasibility.
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