1. Workshop III Mental representations and discrete choice behaviour
State of the art and avenues for future research

2. Background To discuss new perspectives emerging from
Chair: Theo Arentze
Presenters: Benedict Dellaert, Geert Wets
Discussants: Caspar Chorus, Harmen Oppewal
To discuss new perspectives emerging from
recent new developments in the area of models and data collection to integrate mental representations in discrete choice models
Dedicated (online) tools provide scaleability
Apporaches to integrated model development

3. Agenda Paper presentations Discussion of several key themes
An interactive computer-based interface to support discovery of individuals’ mental representations and preferences in decision problems - Geert Wets
Discussant: Caspar Chorus
Online measurement of mental representations of complex decision problems - Benedict Dellaert
Discussant: Harmen Oppewal
Discussion of several key themes
Wrap-up and conclusions

4. Traditionally New Cognition Choice Data collection
Attitudes / concepts / values not related to a specific choice task
Mental representation of a specific choice problem
Cognition
Trade-off between attributes is invariant
Situation-dependent motivations / benefits
Choice
Data
collection
Qualitative in a separate stage (e.g., focus groups)
Integrated with choice tasks
Dedicated (online) tools provide scaleability
Model developments
Joint MR and choice
model
Bayesian network model
Reveals what is underneath individuals choice behavior

5. Discussion Why this approach – what are the gains?
Improved prediction of choice behavior?
One-layer multi-attribute models may fit equally well?
Changes in behavior in (radically) new situtations
Better understanding of the behavior
Extends the idea of individual-level modeling
Particularly relevant when interpretations of consequences are a-priori unclear
MRs of risk
MRs of strategic behavior in decision questions
MRs of political program choices
Influence of group discussion / assumed role
Offers new meaningful ways for segmentation

6. Discussion cont’d Supporting policy making ‘More buttons to push’
Communication of policies – effective framing
Innovation in policy making

7. Discussion cont’d What is it that we measure? – caveats
Explanatory value of elicited cognitions?
More than just rationalisations / justifications / error-prone reconstructions?
Influence of measurement
Framing effects and order effects
Combine with additional data
Non-verbal approaches (e.g., response time)
Information search behaviour (or eye tracking)

8. Conclusions
Operational models and online data collections tools are now available to integrate mental representations and discrete choice models
Has value particularly in terms of better understanding, policy making and communication
Opened up new perspectives for application areas and further development