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

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

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

Extending stated choice analysis to recognise agentspecific attribute endogeneity in bilateral group negotiation and choice: A think piece

This paper is a think piece on variations in the structure of stated preference studies when modelling the joint preferences of interacting agents who have the power to influence the attribute levels on offer. The approach proposed is an extension of standard stated choice methods. Known as ‘stated endogenous attribute level’ (SEAL) analysis, it allows for interactive agents to adjust attribute levels off a base stated choice specification that are within their control, in an effort to reach agreement in an experimental setting. This accomplishes three goals: (1) the ability to place respondents in an environment that more closely matches interactive settings in which some attribute levels are endogenous to a specific agent, should the modeller wish to capture such behaviour; (2) the improved ability of the modeller to capture the behaviour in such settings, including a greater wealth of information on the related interaction processes, rather than simply outcomes; and (3) the expansion of the set of situations that the modeller can investigate using experimental data

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

Role of Port Authorities in Australia, Canada and the European Union

This paper provides a comparison of systems of management and governance within a focus on seaports in Australia, Canada and the European Union. The centrepiece of the research is a survey of port authority representatives and private body managers comparing their attitudes in the area of port strategies and container terminal development projects. The goal of the research is to illustrate regional differences in port policy management. The study compares the level of private sector involvement, areas of control by port authorities, importance of long-term objectives of port policy, and relative advantages of private sector investment seen by port management representatives in Australian, Canadian and European ports. Due to the concentration of container shipping activity within a relatively small number of ports, the approach of the validation is case study based. Through coverage of a large proportion of container activity within the survey, this paper offers an important disaggregate approach in the qualitative analysis of regulatory systems in ports within and across regions. 1

Congestion and variable user charging as an effective travel demand management instrument

Interest at the political level in congestion charging is gaining pace as cities struggle with ways to reduce the effects of growing traffic congestion on the liveability of cities. Despite a long history of promotion of a wide array of travel demand management (TDM) initiatives, very few have had a noticeable impact on the levels of traffic on the road networks of metropolitan areas. TDM success in this context has almost become a \u27band-aid\u27 in the absence of a pricing strategy that not only promotes efficient use of the system but also hypothecates revenues to support essential complementary infrastructure and services such as public transport. This paper takes a look at the stream of pricing consciousness that is surfacing around the world. Although very few jurisdictions have implemented congestion charging, or any form of efficient variable car and truck user charging, the winds of change are well in place. The adage it is not a matter of if but of when seems to be the prevailing view. Our overview of global trends in positioning the debate and hopefully follow-through commitment to implementation provides a backdrop to papers submitted for this special issue on travel demand management. The predominance of papers on pricing is indicative of the priority that must be given to efficient charging and revenue disbursement

Understanding mode choice decisions: A study of Australian freight shippers

This research paper examines the Australian domestic freight transport market, focusing on the decision-making process by which cargo interests and their agents make mode choice allocation decisions between land-based transport and sea. It evaluates the willingness to pay for various attributes of modal options on specific transport corridors. Such understanding lays the groundwork for being able to assess the likely impact of changes to transport prices arising from the introduction of carbon pricing or other regulatory factors. Reporting the results of a stated choice experiment, this paper identifies and quantifies freight shippers’ preferences for components of services offered by freight transport providers across modes with distinct characteristics (i.e., mixes of speed (transit time), frequency of departure, reliability (two measures) and cost) in three corridors. There are seven variables examined: frequency, transit time, freight distance, direction (headhaul/backhaul), reliability as measured by delivery window, reliability as measured by delay, and price offered by the operator. The paper concludes by providing guidance on what trade-offs are relevant in shippers’ choice of mode on the specific corridors under investigation in a more complex mode choice model than explored in previous research. It also examines what will likely happen if price rises as a result of carbon pricing regulation

Refocusing the Modelling of Freight Distribution: Development of an Economic-Based Framework to Evaluate Supply Chain Behaviour in Response to Congestion Charging

Despite the recent recognition of the contribution of freight transportation to the performance of urban areas under the rubric of city logistics, little research has been done on how the stakeholders in the supply chain might cooperate through participation in distribution networks to reduce freight vehicle movements and the costs associated with traffic congestion. This paper sets out a framework to investigate how agents in a retail supply chain might interact more effectively to reduce the costs of urban freight distribution. This approach proposes: (1) a behaviorally rich framework within a theoretical framework of preferences, choices and constraints; (2) an econometric modeling structure and relevant stated choice data across agents for the economic situation of interest; and (3) a set of key behavioral relationships that have a relatively longer shelf life than physical transport data. This framework can be used to complement existing freight models in investigating the behavioral response of each agent to policies, including congestion charging, aimed at improving urban traffic flow