Comparative transit performance evaluation: cost, demand and revenue index approach with UMTA section 15 data

This study combined the traditional concepts of cost, demand, and revenue models together with performance indicators to derive a methodology to (1) measure the performance standing of a transit company within its peer-group, and (2) improve this standing with the improvement on the values of parameters and impact factors in the methodology. To enrich the existing pool of indicators, four new basic transit variables -- vehicle hour miles, vehicle revenue hour miles, revenue capacity hour miles, and passenger hour miles have been developed. On the model building side, operating expense, unlinked passenger trip, passenger fare revenue for transit service, and transportation revenue aspects have been selected as the response variables. On the data side, UMTA Section 15 second annual data were used. Many shortcomings existed in this data set have been pointed out and possible solutions were given. With a total of 170 transit variables as the potential causal variables, various techniques were employed to reduce this size. In addition, linear as well as non-linear regression models have been derived. On the performance evaluation side, a new methodology employing the index comparison concept was proposed. An index is defined as the ratio of the difference between actual and expected values over expected value. Four sub-indexes were developed for the four operating aspects, and two overall performance indexes were derived from these sub-indexes. Because the average index value is zero, so a positive index would be better than both the expected and the peer-group values. The opposite is true for the negative case. Hence, transit systems can be ranked by the performance level through the sign and the magnitude of any index. This would form a good basis for public funding based on performance level. Besides the parameters in the models, impact factors were extracted for outliers to the models. From both parameters and impact factors, an individual transit company should be able to locate its weak areas of operation, so a consorted effort can be channelled to improve them.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Civil Engineering

Department dc:contributor.department

Civil Engineering

Grantor dc:publisher

Virginia Polytechnic Institute and State University

Year dc:date.issued

1983

Author dc:creator

• Kanok-kantapong, Chakrit

Chair dc:contributor.committeechair

• Hobeika, Antoine

Committee members dc:contributor.committeemember

• Tran, Thanh K.
• Dickey, John W.
• Radwan, A.E.
• Stuart, Robert C.

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/10919/76331

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/76331