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 5: Choice context

Konstadinos G. Goulias and Ram M. Pendyala


Context in choice models is often treated in a narrow space with a focus on limited contextual dimensions of interest that may influence the choices under study. Over time, however, the field of choice modeling has matured recognizing the need to consider the many behavioral facets where choice among alternatives is important and the contexts within which predictive models need to be developed are identified. In fact, today there is a need to develop behavioral models encompassing the entire life span of individuals because the policies models are asked to analyze require the development of model systems spanning a wider net of relationships that go far beyond the narrowly developed mode choice of the seventies. Context in this chapter is defined as the entire framework and set of factors describing the objective and subjective circumstances that surround and influence action by an individual and/or a group. To describe context, dimensions of interest include: (a) time, in terms of the life course of an individual, historical time and time scale; (b) space, that includes locations, groups of locations (for example, shopping centre), neighborhood, city, region and country; and (c) society, that includes the household and other social networks; and the entirety of laws, rules, and regulations. Factors emerging from these dimensions (for example, barriers) are sometimes separable and can be used as explanatory variables in behavioral equations or variables to manipulate in experiments (Oppewal and Timmermans, 1991; Swait et al., 2002).

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