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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16142

Title: Workshop report: mental representations and discrete choice behaviour: state-of-the-art and avenues for future research
Authors: Dellaert, B.
Arentze, T.
Chorus, C.
Oppewal, H.
WETS, Geert
Issue Date: 2013
Publisher: ElgarOnline
Citation: Stephane Hess, Andrew Daly (Ed.). Choice Modeling. The state of the Art and the State of Practice, p. 107-124
Abstract: This chapter considers the measurement and modelling of mental representations underlying individuals’ choice behaviour. The premise of the study of such mental representations (MRs) is that an individual’s mental construction of a choice problem plays an important role in preference formation, especially in the context of the complex choice situations such as involved in activity-travel behaviour. The measurement of MRs is a key problem. It requires the availability of a cognitive mapping method that can take specific decision task characteristics into account. Existing cognitive mapping methods, such as proposed in Kearney and Kaplan (1997), Eden and Ackermann (1998), and Christensen and Olsen (2002), cannot readily be used for this purpose. These traditional cognitive mapping techniques focus on knowledge and values not related to a specific situation or decision task. In contrast, MRs underlying decision making concern specific cognitions that are triggered by a given decision problem and should allow the decision maker (DM) to assess outcomes of actions in terms of needs that are activated in the decision situation. To model and measure such cognitions, recently new methodology has been developed based on the concept of active causal networks. Specifically, Arentze et al. (2008) proposed the decision network (DN) as a suitable formalism. A DN is an extension of a Bayesian Network (BN).
URI: http://hdl.handle.net/1942/16142
Link to publication: http://www.elgaronline.com/view/9781781007266.00010.xml
ISBN: 978-1-78100-726-6
Category: B2
Type: Book Section
Validation: vabb, 2015
Appears in Collections: Research publications

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