The effects of using different output measures in efficiency analysis of public transport operations
place - europe, economics - willingness to pay, planning - surveys, planning - methods, operations - performance
Public transport, Efficiency, Benchmarking, Cost function, Stochastic frontier analysis
There is growing interest in measuring efficiency and productivity in the public sector. Most commonly this is done using data envelopment analysis (DEA) or Stochastic frontier analysis (SFA) to determine the level of (in)efficiency of different decision-making units. These methods have also been applied to public transport. However, in this context their application presents some problems, including how to define what is produced and how that should be measured. Several options have been suggested including vehicle-kilometres, number of trips, number of passenger-kilometres, and scores in passenger satisfaction surveys.
The primary aim of this paper is to discuss how production of public transport should be defined and measured in efficiency studies. It is argued that output should be measured by number of trips and vehicle-kilometres as these together represent consumers' willingness to pay for public transport services.
A proposed model for evaluating the efficiency of public transport operations is presented and estimated. This model is evaluated by comparing its results to those obtained from competing models estimated using the same data from 27 Swedish counties from 1986 to 2015. The data are used to estimate stochastic cost frontier models and it is concluded that the models using only vehicle-kilometres or only passenger trips tend to underestimate efficiency compared to a model using both at the same time. It is also concluded that smaller models (using only a single output measure) result in different rankings of the decision-making units.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Holmgren, J. (2018). The effects of using different output measures in efficiency analysis of public transport operations. Research in Transportation Business & Management, Available online 2 March 2018. In Press, Corrected Proof.