Ein Letzetes Mal: ein Einakter / One Last Time: A One-Act Play

Letztes Mal / One Last Time: A One-Act Play is the Honors Project of Sean Puckett

Road User Charging: The Global Relevance of Recent Developments in the United Kingdom

Charging users of the roads for the costs they impose on the system is not new. Economists have been promoting its virtues for as long as arguments about economic efficiency have been in print. What is different today is that a growing number (but by no means all) of decision makers are showing a greater interest and commitment to finding ways to improve the efficiency of the road system, be it through infrastructure expansion and/or other means. Of special interest is the growing level of traffic congestion, and a feeling of almost helplessness, that we seem to have failed in finding a way forward to maintain traffic congestion at levels that are acceptable to the public, and are consistent with principles of good economic practice. The literature abounds with suggestions on how this might be achieved, focused primarily on various pricing regimes that say as much as about levels of charges as they do about the role of the revenue raised, the latter as controversial as the former. The current state of technology provides a capability to introduce sophisticated charging mechanisms. We are at a stage in the evolution of ‘solutions’ to dealing with inefficient road use and provision of road funds that offers real prospects of delivering outcomes that can align with political, social and user demands and expectations. This paper provides a global perspective on the road to efficiency, using the UK contributions in the special issue as a backdrop of what can be done. The issues and challenges are sufficiently global to enable the contributions to be of immediate relevance beyond the UK

Freight Distribution in Urban Areas: The role of supply chain alliances in addressing the challenge of traffic congestion for city logistics

The distribution of freight is a major contributor to the levels of traffic congestion in cities, yet it is much neglected in the research and planning activities of government, where the focus is disproportionately on passenger vehicle movements. Despite the recent recognition of the contribution of freight transportation to the performance of urban areas under the rubric of city logistics, we see a void in the study of how the stakeholders in the supply chain associated with the distribution of goods (whose destination is an urban location) might cooperate through participation in distribution networks, to reduce the costs associated with traffic congestion. Given that transport costs are typically over 45% of all distribution costs, with congestion contributing a substantial amount of cost in the urban setting, the importance of establishing ways in which supply chain partnerships might aid in reducing the levels of freight vehicle movements in urban areas has much merit. This paper sets out a framework to investigate how agents in the supply chain might interact more effectively to reduce their costs of urban freight distribution. We propose an interactive agency choice method as a way of formalising a framework for studying the preferences of participants in the supply chain to support specific policy initiatives. Such a framework is a powerful way of investigating the behavioural response of each agent to many policies including congestion pricing as a way of improving the efficient flow of traffic in cities

Revealing the extent of process heterogeneity in choice analysis: An empirical assessment

Choice analysts increasingly use a mix of revealed preference and stated choice data paradigms to identify preferences of samples of individuals that are used to infer behavioural response and willingness to pay for specific attributes. These data are in a sense artificial constructs that are developed to approximate real choice settings of the way that individuals process relevant information in making choices. As such all data designs formalized through a survey instrument seek information through questions that become descriptions of events and as such the probabilities of choice that are of interest are strictly probabilities attached to event descriptions and not choice probabilities of events per se. The recognition of this distinction, initially noted by Kahneman et al. (1982), can be captured, at least in part, through the idea of process heterogeneity as a way of recognizing and accounting for the many ways in which individuals process information, and in part is influenced by the way the analyst describes the context in which preference data is sought. Building on previous contributions on attribute processing, this paper draws on recent empirical evidence to further reinforce the importance of joint modelling of process and outcome in choice analysis. This study adds to the evidence of a trend emerging on the upward bias of mean estimates of marginal willingness to pay when ignoring process heterogeneity

Behavioural responses of freight transporters and shippers to road user charging schemes: An empirical assessment

Heavy goods vehicles not only have a non-marginal impact on the performance of the road network in terms of traffic congestion, exposure to risk and accidents, they also provide an essential service in the distribution chain. Both sellers and purchasers of goods rely on an efficient transport system to ensure that goods are available at a time and location that meets the demands of end users. As congestion on the road network grows, especially in urban areas, the calls for ‘solutions’ increase. Although many of the suggestions to resolve delays due to traffic avoid the call for reform of road pricing, there is a growing recognition that user charges have to be more closely aligned to user cost and user benefit. Aiding this call is a technological capability now in place to facilitate a fine tuning of variable users charges that is inter-operable across networks and almost seamless to the customer. The major challenge we face is behavioural – a need to understand more fully the role that specific charging regimes might play in the distribution of freight and who in the supply chain is affected by specific charges in terms of willingness to pay for the gains in network efficiency. This chapter investigates the potential influence of variable user charges, relative to fuel prices (the current main source of charging), in the freight distribution chain. A choice modelling framework is presented that identifies potential responses from the freight distribution sector to variable user charging within the context of the wider spectrum of costs imposed on the sector, as well as the potential benefits (e.g. time savings) from alternative pricing regimes. We highlight the role that agents in the distribution chain play in influencing sensitivity to variable user charges

Observed efficiency of a d-optimal design in an interactive agency choice experiment

There have been a number of recent calls within the choice literature to examine the role of social interactions upon preference formation. McFadden (2001a,b) recently stated that this area should be a high priority research agenda for choice modellers. Manski (2000) has also came to a similar conclusion and offered a plea for better data to assist in understanding the role of interactions between social agents. The interactive agency choice experiment (IACE) methodology represents a recent development in the area of discrete choice directed towards these pleas (see e.g., Brewer and Hensher 2000). The study of the influences that group interactions have upon choice bring with them not only issues that need to be overcome in terms of modelling, but also in terms of setting up the stated choice experiment itself. Currently, the state of practice in experimental design centres on orthogonal designs (Alpizar et al., 2003), which are suitable when applied to surveys with a large sample size. In a stated choice experiment involving interdependent freight stakeholders in Sydney (see Hensher and Puckett 2007, Puckett et al. 2007, Puckett and Hensher 2008), one significant empirical constraint was difficulty in recruiting unique decision-making groups to participate. The expected relatively small sample size led us to seek an alternative experimental design. That is, we decided to construct an optimal design that utilised extant information regarding the preferences and experiences of respondents, to achieve statistically significant parameter estimates under a relatively low sample size (see Rose and Bliemer, 2006). The D-efficient experimental design developed for the study is unique, in that it centred on the choices of interdependent respondents. Hence, the generation of the design had to account for the preferences of two distinct classes of decision makers: buyers and sellers of road freight transport. This paper discusses the process by which these (non-coincident) preferences were used to seed the generation of the experimental design, and then examines the relative power of the design through an extensive bootstrap analysis of increasingly restricted sample sizes for both decision-making classes in the sample. We demonstrate the strong potential for efficient designs to achieve empirical goals under sampling constraints, whilst identifying limitations to their power as sample size decreases

Power, concession and cooperation in freight distribution chains subject to distance-based user charges

Freight transport plays an important role within the functions of the road network, yet little is understood about the potential impacts of some travel demand management strategies on freight transport activity. This arises, in part, due to the interdependent nature of decision making within supply chains. To contribute to this shortcoming, this paper offers empirical results from a method designed to estimate attribute-specific measures of relative influence within decision making groups. A choice modelling framework is utilised to consider the relative concession decision makers are willing to make toward the preferences of other group members when attempting to reach group choice equilibrium. The estimated influence measures highlight the relative power each type of decision maker holds with respect to each attribute within the candidate alternatives from which to choose. The alternatives represent supply chain strategies for adjusting to a hypothetical distancebased road user charging system in Sydney, Australia. The measures can be utilised in subsequent transport distribution models to account for the impact each decision maker may have on the decisions made at the group (i.e., supply chain) level in response to a given policy. The results are also useful in gaining a greater normative understanding of the decision-making dynamics within transporter-shipper dyads

Modelling heterogeneity in scale directly: implications for estimates of influence in freight decision-making groups

The state of practice in the modelling of heterogeneous preferences does not separate the effects of scale from estimated mean and standard deviation preference measures. This restriction could lead to divergent behavioural implications relative to a flexible modelling structure that accounts for scale effects independently of estimated distributions of preference measures. The generalised multinomial logit (GMNL) model is such an econometric tool, enabling the analyst to identify the role that scale plays in impacting estimated sample mean and standard deviation preference measures, including confirming whether the appropriate model form approaches standard cases such as mixed logit. The GMNL model is applied in this paper to compare the behavioural implications of the minimum information group inference (MIGI) model within a study of interdependent road freight stakeholders in Sydney, Australia. MIGI estimates within GMNL models are compared with extant mixed logit measures (see Hensher and Puckett, 2008) to confirm whether the implications of the restrictive (with respect to scale) mixed logit model are consistent to those from the more flexible GMNL model. The results confirm the overall implication that transporters appear to hold relative power over supply chain responses to variable road-user charges. However, the GMNL model identifies a broader range of potential group decision-making outcomes and a restricted set of attributes over which heterogeneity in group influence is found than the mixed logit model. Hence, this analysis offers evidence that failing to account for scale heterogeneity may result in inaccurate representations of the bargaining set, and the nature of preference heterogeneity, in general

Selective developments in choice analysis and a reminder about the dimensionality of behavioural analysis

Developments in data and modeling paradigms in choice analysis are occurring at a fast pace. A review of activity leading up to each IATBR conference shows progress on many fronts. This paper takes a selective view of some of these developments, especially those that have been close to the research program of the authors. We focus on four broad themes – information processing strategies, especially in the context of stated choice studies; agency interdependency (with a strong applied focus), developments in the design of choice experiments, and a smorgasbord of themes centered on expanding the behavioral capabilities (and longer term forecasting accuracy) of discrete choice models, especially in terms of their recognition of ways of accommodating the other themes in the paper