The Effects of Station Enhancements on Rail Demand
J Preston, S Blainey, G Wall, TRG, University of Southampton, UK; P K Chintakayala, Accent and ITS, University of Leeds, UK; M Wardman, ITS, University of Leeds, UK
An innovative methodology that combines Revealed and Stated Preference data has been developed to determine the effects of station enhancements on rail demand.
This paper reports on work undertaken in the UK for the Association of Train Operating Companies (ATOC) by the University of Southampton in conjunction with the University of Leeds and Accent. The objective of this work was to provide a greater understanding of changes in rail demand in response to improvements in railway station facilities and to update the relevant sections of the Passenger Demand Forecasting Handbook. A novel multi-method approach was adopted which included six elements. First, an extensive literature review was undertaken that indicated that Stated Preference (SP) experiments were prone to over value station facilities due to non-commitment and part-whole biases. Second, qualitative research, based on six discussion groups held at three stations, highlighted key areas of interest. Third, analysis of the National Passenger Survey indicated that major station enhancements could increase overall satisfaction with rail services by two percentage points. Fourth, analysis of Revealed Preference (RP) data, based on LENNON ticket sales data, indicated that at smaller stations station enhancements could uplift origin traffic by 7%, but disruption during the implementation of these enhancements could reduce all traffic by 4%. A decay effect, in which demand reduced by 0.5% per period, was also detected. For larger stations, an enhancement uplift of around 8% for both origin and destination traffic was detected. Fifthly, a major market research exercise was conducted, using a combination of self-completion and internet questionnaires, with over 6,400 respondents. Detailed attitudinal and travel data were collected along with information on maximum willingness to pay. This work included a series of SP exercises which was able to provide values for 18 station upgrade attributes. These values were then combined to comprise a Station Quality Index (SQI). Lastly, the RP and SP analyses were combined by incorporating the SQI in the RP analysis. This enabled the values of station enhancement to be re-scaled and indicated the extent of upward biases in the SP results. For larger stations, an elasticity of demand with respect to station enhancements of 0.05 for origin traffic and 0.12 for destination traffic was found. On average, a station enhancement was found to uplift traffic by around 8%, but half of this uplift may be abstracted from other stations. A revised methodology for forecasting the impact of station enhancements is outlined and illustrated with practical examples. The implications for the station modernisation programme outlined in the 2007 Railway White Paper are assessed.
Association for European Transport