Tony Fowkes

Freight mode choice and adaptive stated preferences

This paper presents empirical results from a survey of determinants of mode choice for freight in India. The Leeds Adaptive Stated Preference software was used for the main survey which was carried out in summer 1998 on the Delhi to Bombay corridor. The survey results show that frequency of service is an important attribute determining mode choice. Valuation of reliability is generally lower than expected. Value of time is quite similar across different product segments. Given prevailing costs, the results suggest that intermodal services can be viable for high value and finished goods.

NOVEL APPROACHES TO FORECASTING THE DEMAND FOR NEW LOCAL RAIL SERVICES

Revealed Preference(RP) studies based on actual behaviour suffer from a number of statistical problems. Furthermore, RP methods are of little use when the effects of a new or radically altered service need to be considered. As a result, for a case study of demand forecasting for new passenger rail services, a new approach has been developed. Our starting point is to seek what we call Stated Intentions (SI) responses as to the likely usage of a new rail service. However, due to a combination of systematic biases, these responses may be taken to be gross overestimates. A check on the biases of this SI data may be supplied by a Stated Preference (SP) survey. Respondents are asked to make hypothetical choices which are sufficiently complex for there to be little chance of policy bias. It is ensured that choices presented contain useful ‘boundary values,’ being the relative valuation for which respondents would be indifferent between two offered alternatives. It is, however, crucial to ensure that the SP survey is simple enough for respondents to manage, since excessive error variability in the responses will cause the calibrated coefficients to be rescaled, presenting problems for forecasting. From the SP surveys, it is estimated that SI data overstates usage of new rail services by around 50%, even if it is assumed that nonrespondents to the SI survey are nonusers. It is concluded that an SI/SP approach can potentially provide accurate forecasts, but there are a number of practical constraints that may prevent this.

Amending the Incentive for Strategic Bias in Stated Preference Studies: Case Study in Users' Valuation of Rolling Stock

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.

Model for Integrating Home-Work Tour Scheduling with Time-Varying Network Congestion and Marginal Utility Profiles for Home and Work Activities

The existing literature on activity-based modeling emphasizes that individuals schedule their activities by keeping the whole-day activity pattern in mind. Several attempts have been made to integrate this with network congestion; however, for explicit explanation of travel behavior of individuals, further improvements are required. The proposed model is a combined model that addresses the scheduling of the home–work tour with time-varied network congestion in a fixed-point problem framework. Marginal utility profiles that represent individual time-of-day preferences and satiation effect of the activities are incorporated for the measurement of the utility of activity engagement along with the disutility of travel. Consideration of only time-of-day dependent marginal utility profiles of activities in the utility function does not appropriately integrate activities and travel within the tour. The proof is shown analytically and numerically. This finding contradicts earlier research into integration of morning and evening commutes with network congestion. Additionally, the results of two numerical experiments are presented. In the first experiment, an arbitrary dynamic tolling strategy is assumed, and then a detailed analysis is performed to show variation in the balance of trade-offs involved in the process. The second experiment assesses the sensitivity of the combined model through incorporation of different dynamic traffic loading models. Some meaningful observations are drawn from these experiments and are discussed with the identification of avenues for future research.