Passenger satisfaction is a primary driver of ridership for rail services, yet most customer satisfaction programs emphasize descriptive scores and year-to-year percent changes without clearly identifying which service attributes should be prioritized for improvement. A low satisfaction score does not necessarily indicate a high-impact problem if the attribute is not important to passengers. While Importance–Performance Analysis (IPA) is widely used to guide prioritization, it has key methodological limitations—most notably the arbitrary placement of quadrant crosshairs and the assumption that all attributes in the same quadrant are equally critical—leading to inconsistent and sometimes misleading prioritization.
This project will develop an evidence-based prioritization and investment framework centered on a continuous metric: the Importance–Performance Deviation Index (IPDI). IPDI integrates (i) each service attribute’s relative importance to passengers and (ii) its performance deviation from the best-observed performance within a rider group or system. The resulting index produces a defensible, rank-ordered list of improvement priorities without relying on quadrant boundaries. Building on IPDI, the project will also develop an investment translation module that links changes in attribute performance (e.g., reliability, crowding, cleanliness, information quality) to expected changes in overall satisfaction and loyalty intent. Using estimated response functions (marginal satisfaction gains per unit of improvement) and agency-provided unit cost ranges, the framework will quantify how much funding is required to reduce high-IPDI gaps and will optimize budget allocation to maximize satisfaction gains under constrained resources.
The final outcome will be a practical toolkit and guidance that rail agencies can use for ongoing performance tracking, prioritization, and cost-effective investment planning.