The need for performance indicators to monitor and evaluate the efficiency and effectiveness of transit system operations has been examined. A review of recent research on and applications of performance indicators is presented and indicates that a formalised system of performance indicators would provide a method for achieving increasing accountability with regard to assessing performance and could provide a sound basis for subsidy allocation.
The data collected by the United States Minnesota Department of Transportation on sixty-seven transit systems have been used to develop a set of performance indicators and to test their usefulness for assessing system performance. Twenty-one indicators (13 non-financial and 8 financial) have been formed from the nine service parameters available in the case study.
Correlation analysis shows that the performance indicators are effectively independent of the service parameters. However, there is substantial overlap (redundancies) in the indicators (with the exception of the two indicators, speed and cost recovery). In studying the structure of the proposed indicators, the twenty-one indicators have been reduced to six factors (dimensions) by factor analysis. These six factors, accounting for 91.30/0 of the explained variance of the data have been interpreted as 'revenue effectiveness within market environment', 'service accessibility', 'productivity', 'cost environment and service charge', 'operating environment (speed)' and 'cost recovery'.
The transit systems have been classified by the Minnesota Department of Transportation into four groups based on service type, namely, urbanised, small urban, rural and specialised groups, and into two groups based on ownership, namely, publicly- and privately-owned groups. Indicators which can differentiate the performance among the service type groups and between the public and private systems have been identified by discriminant analysis and have been successfully interpreted in terms of the six factors (dimensions) derived by the factor analysis. The resulting classification functions correctly classify 90% of the systems into service-type groups and 86% of the systems into publicly- and privately owned groups. These results therefore support the classification systems used by the Minnesota Department of Transportation. The existence of economies of scale for both public and private transit systems have been identified through regression analysis. No• differences in vehicle productivity connected with ownership were found. It was concluded that performance indicators, appropriately structured to avoid potentially misleading redundancy and overlap, can play a valuable role in assessing efficiency and effectiveness.