An interactive computer-based interface to support the discovery of individuals' mental representations and preferences in decisions problems: An application to travel behavior

  • Authors:

  • Diana Kusumastuti;Els Hannes;Benoít Depaire;Koen Vanhoof;Davy Janssens;Geert Wets;Benedict G. C. Dellaert

  • Affiliations:

  • Transportation Research Institute, Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium;Transportation Research Institute, Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium and Architecture Department, PHL University Collage, Belgium;Transportation Research Institute, Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium;Transportation Research Institute, Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium;Transportation Research Institute, Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium;Transportation Research Institute, Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium;Department of Business Economics, Marketing Section, School of Economics, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands

  • Venue:
  • Computers in Human Behavior
  • Year:
  • 2011

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Abstract

Growing emphasis is currently given in decision modeling on process data to capture behavioral mechanisms that ground decision-making processes. Nevertheless, advanced applications to elicit such data are still lacking. The Causal Network Elicitation Technique interview and card-game, both face-to-face interviews, are examples of a behavioral process method to obtain individuals' decision-making by eliciting temporary mental representations of particular problems. However, to portray and model these representations into formal modeling approaches, such as Bayesian decision networks, an extensive set of parameters has to be gathered for each individual. Thus, data collection procedures for large sample groups can be costly and time consuming. This paper reports on the methodological conversion and enhancement of the existing elicitation methods into a computer-based interface that allows to not only uncover individuals' mental representations but also to automate the generation of preference parameter elicitation questions. Results of such studies can be used to understand individuals' constructs and beliefs with respect to decision alternatives, predict individuals' decision behavior at a disaggregate level, and to assess behavioral changes due to differences in contexts and constraints.