Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/117844 
Authors: 
Year of Publication: 
2005
Series/Report no.: 
45th Congress of the European Regional Science Association: "Land Use and Water Management in a Sustainable Network Society", 23-27 August 2005, Amsterdam, The Netherlands
Publisher: 
European Regional Science Association (ERSA), Louvain-la-Neuve
Abstract: 
As the demands placed on transport systems have increased relative to extensions in supply, problems of network unreliability have become ever more prevalent. The response of some transport users has been to accommodate expectations of unreliability in their decision-making, particularly through their trip scheduling. In the analysis of trip scheduling, Small's (1982) approach has received considerable support. Small extends the microeconomic theory of time allocation (e.g. Becker, 1965; De Serpa, 1971), accounting for scheduling constraints in the specification of both utility and its associated constraints. Small makes operational the theory by means of the random utility model (RUM). This involves a process of converting the continuous departure time variable into discrete departure time segments, specifying the utility of each departure time segment as a function of several components (specifically journey time, schedule delay and the penalty of late arrival), and adopting particular distributional assumptions concerning the random error terms of contiguous departure time segments (whilst his 1982 paper assumes IID, Small's 1987 paper considers a more complex pattern of covariance). A fundamental limitation of Small's approach is that individuals make choices under certainty, an assumption that is clearly unrealistic in the context of urban travel choice. The response of microeconomic theory to such challenge is to reformulate the objective problem from the maximisation of utility, to one of maximising expected utility, with particular reference to the works of von Neumann & Morgenstern (1947) and Savage (1954). Bates et al. (2001) apply this extension to departure time choice, but specify choice as being over continuous time; the latter carries the advantage of simplifying some of the calculations of optimal departure time. Moreover Bates et al. offer account of departure time choice under uncertainty, but retain a deterministic representation. Batley & Daly (2004) develop ideas further by reconciling the analyses of Small (1982) and Bates et al. Drawing on early contributions to the RUM literature by Marschak et al. (1963), Batley and Daly propose a probabilistic model of departure time choice under uncertainty, based on an objective function of random expected utility maximisation. Despite this progression in the generality and sophistication of methods, significant challenges to the normative validity of RUM and transport network models remain. Of increasing prominence in transport research, is the conjecture that expected utility maximisation may represent an inappropriate objective of choice under uncertainty. Significant evidence for this conjecture exists, and a variety of alternative objectives proposed instead; Kahneman & Tversky (2000) offer a useful compendium of such papers. With regards to these alternatives, Kahneman & Tversky's (1979) own Prospect Theory commands considerable support as a theoretical panacea for choice under uncertainty. This theory distinguishes between two phases in the choice process - editing and evaluation. Editing may involve several stages, so-called 'coding', 'combination', 'cancellation', 'simplification' and 'rejection of dominated alternatives'. Evaluation involves a value function that is defined on deviations from some reference point, and is characterised by concavity for gains and convexity for losses, with the function being steeper for gains than for losses. The present paper begins by formalising the earlier ideas of Batley and Daly (2004); the paper thus presents a theoretical exposition of a random expected utility model of departure time choice. The workings of the model are then illustrated by means of numerical example. The scope of the analysis is subsequently widened to consider the possibility of divergence from the objective of expected utility maximisation. An interesting feature of this discussion is consideration of the relationship between Prospect Theory and a generalised representation of the random expected utility model. In considering this relationship, the paper draws on Batley & Daly's (2003) investigation of the equivalence between RUM and elimination-by-aspects (Tversky, 1972); the latter representing one example of a possible 'editing' model within Prospect Theory. Again, the extended model is illustrated by example.
Document Type: 
Conference Paper

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