Handbook of Choice Modelling
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Handbook of Choice Modelling

Edited by Stephane Hess and Andrew Daly

Choice modelling is an increasingly important technique for forecasting and valuation, with applications in fields such as transportation, health and environmental economics. For this reason it has attracted attention from leading academics and practitioners and methods have advanced substantially in recent years. This Handbook, composed of contributions from senior figures in the field, summarises the essential analytical techniques and discusses the key current research issues. It will be of interest to academics, students and practitioners in a wide range of areas.
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Chapter 12: Attribute processing as a behavioural strategy in choice making

David Hensher


Choosing is a complex process that is typically simplified by human beings in many ways in order to ensure that the expected benefits outweigh the assumed costs of an outcome. Regardless of whether the context entails habitual or variety seeking behaviour, individuals draw on decision rules, often referred to as heuristics, to provide guidance on making choices. Such rules might be associated with an accumulation of overt experience; but whatever the basis of rule selection, there are many forces at play, often called cognitive processes, conscious or unconscious, that dictate responses in settings that researchers use to study choice making. Despite the recognition in behavioural research, as long ago as the 1950s (see Simon, 1955; Svenson, 1992; also Busemeyer and Rieskamp, Chapter 3 in this volume), that cognitive processes have a key role in preference revelation, and the reminders throughout the choice literature (see McFadden, 2001) about rule-driven behaviour, we still see relatively little of the decision-processing literature incorporated into mainstream discrete choice modelling which is, increasingly, becoming the preferred empirical context for individual preference measurement and willingness-to-pay derivatives. There is an extensive literature outside of discrete choice modelling focusing on these matters, broadly described as heuristics and biases, and which is crystallized in the notion of process, in contrast to outcome. Choice has both elements of process and outcome, which in combination represent the endogeneity of choice in choice studies.

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