Abstract

This paper provides an overview of the study 'Provision of market research for value of time savings and reliability' undertaken by the Arup/ITS Leeds/Accent consortium for the UK Department for Transport (DfT). The paper summarises recommendations for revised national average values of in-vehicle travel time savings, reliability and time-related quality (e.g. crowding and congestion), which were developed using willingness-to-pay (WTP) methods, for a range of modes, and covering both business and non-work travel purposes. The paper examines variation in these values by characteristics of the traveller and trip, and offers insights into the uncertainties around the values, especially through the calculation of confidence intervals. With regards to non-work, our recommendations entail an increase of around 50% in values for commute, but a reduction of around 25% for other non-work-relative to previous DfT 'WebTAG' guidance. With regards to business, our recommendations are based on WTP, and thus represent a methodological shift away from the cost saving approach (CSA) traditionally used in WebTAG. These WTP-based business values show marked variation by distance; for trips of less than 20 miles, values are around 75% lower than previous WebTAG values; for trips of around 100 miles, WTP-based values are comparable to previous WebTAG; and for longer trips still, WTP-based values exceed those previously in WebTAG.

Stated preference (SP) methods have been used extensively in transport research and elsewhere, both to forecast demand and to value the importance attached to different product features and travel attributes. Before introducing new or refurbished rolling stock as part of their franchises, British Train Operating Companies (TOCs) have often carried out SP surveys to investigate passenger preferences and to test whether the improvement of the fleet and services is enough to recover the cost through increased fares and patronage and thus to evaluate the costs and benefits of this investment. The rolling stock value derived from SP results is used not only for welfare appraisal and pricing but also for rail demand forecasting. Alongside the broader acceptance and wider application of SP methods, some practitioners have argued for greater openness in discussing what they have seen as significant concerns surrounding SP. The issue of the strategic biasing of SP responses was specifically addressed by examining the incentive compatibility of SP responses related to task complexity and the presence of specific antibias warnings in the questionnaire. Methods to amend incentive to bias were suggested. Adding cheap talk script reduces the overestimation of valuation of improved rolling stock in the case study; however, bias may remain. Adding more attributes to the SP experiment does not show a significant impact on the estimation bias, but contributes to a higher error variance in responses.

-A bi-level modelling approach is proposed to represent the interaction between the vehicle loading practices of road freight transport carriers, and the decisions of a road planning authority responsible both for road maintenance and for the enforcement of overloading control. At the lower (reactive) level, the overloading decisions of the carriers impact on road maintenance expenditure, while at the upper (anticipatory) level the planner decides fine and enforcement levels by anticipating the responses of the carriers. A case study using data from Mexico is used to illustrate the method.

Article:Fowkes, A.S. (2007) AbstractThis paper considers how best to establish user valuations of the benefits for freight traffic from reducing both scheduled journey times and the variability of actual journey times. It first looks at who receives these benefits and establishes a case for delving further. A theoretical discussion then shows that estimated 'values of time' are likely to be conflations of several different effects, most probably varying from study to study. Results are then given from a case study where special care was taken to separate out these effects. As an Adaptive Stated Preference method is used, arguments are presented that counter the suggestion that resulting estimates will necessarily be biased. The paper ends with some conclusions.