Analysis of Quantitative Research on Quality Attributes for Trams



Analysis of Quantitative Research on Quality Attributes for Trams

Authors

D Johnson, P Abrantes, M Wardman, N Chadwick, L Albanese, ITS, University of Leeds, UK

Description

The primary aim of this study to identify the importance of various factors which comprise a measure of quality of journey experience on Trams making it distinct from other modes.

Abstract

This paper reports findings from an ongoing study undertaken on behalf of Transport for London alongside the UK Tram Work Group. The primary aim of this study to identify the importance of various factors which comprise a measure of quality of journey experience on Trams, making it distinct from other modes, and which are not captured in time or cost related estimated parameters from Stated Preference (SP) or Revealed Preference (RP) exercises.


Quality attributes for Light Rail Transit (LRT) can be broken down into 2 categories.

? Vehicle quality ? including smoothness of ride, provision of step free boarding, seating and storage space, air conditioning and CCTV.

? Service quality ? including quality of waiting environment, safety and security issues, information provision, staffing and reliability,

In addition to evidence on these attributes, we will also discuss findings on:

? Variations in the values of in vehicle time and other journey time components, both generic and by mode where appropriate.
? Consideration of the validity of SP methods in this context will also be made, including discussion of the impact of the ?package? effect , ie where individual attributes considered in isolation have different valuations than when considered as part of a package of attributes.

We have a raft of literature at our disposal, ranging from academic papers to consultancy reports from which we draw on. All findings will be anonymised and no individual study identified. We will also draw on literature from outside UK and other modes particularly Bus Rapid Transit.

Many of the studies looked at different segments (through separate SP exercises or use of interaction terms) including peak/off-peak, journey purpose and car availability. By encoding the key findings and valuations relating to the quantitative empirical evidence for each study and segment in a database, we will highlight the quality attributes which are consistently found to be important in surveys.

We will also undertake numerical analysis to identify patterns of valuations of LRT provision captured by the Tram mode constant against bus (and other modes where appropriate) across the studies and different segments. Given the relatively small number of appropriate studies, we do not feel a conventional meta-analysis regression type approach would be feasible although we will highlight any important correlations.

On the basis of specific studies which we have examined and also our analytical review of the literature, we will provide a set of recommended valuations, or ranges, for ?generic? mode specific constants for use in forecasting and appraisal, and rankings for key soft factors. Our findings will help inform policy makers and stakeholders as to the important aspects of LRT transit provision. We will also identify shortcomings that should be addressed, gaps in existing knowledge and opportunities for new research in the field of LRT.

Publisher

Association for European Transport