Allowing for Heterogeneous Decision Rules in Discrete Choice Models: An Approach and Four Case Studies

Although recent research in choice modeling has allowed for differences in the utility specification across respondents in the context of looking at heterogeneous information processing strategies, there remains an underlying assumption that all respondents employ the same choice paradigm. However, there is evidence that different choice paradigms may fit better on certain datasets. This study suggests that these differences may also extend to respondents within a single dataset. These differences are accommodated in a latent class model, where individual classes make use of different underlying paradigms. Four case studies are presented using three different datasets, showing mixtures between “standard” random utility maximization models and lexicography based models, models with multiple reference points, elimination by aspects models and random regret minimization models. The behavioral mixing model in each case showed significant improvements in fit over the base structure where all respondents are hypothesized to use the same rule. The findings also suggest that what is retrieved as taste heterogeneity in standard models actually may be heterogeneity in decision rules. Insights into the behavioral patterns of respondents and directions for future research are discussed.

• Record URL:
  https://doi.org/10.1007/s11116-011-9365-6
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00494488
• Authors:
  • Hess, Stephane
  • Stathopoulos, Amanda
  • Daly, Andrew
• Publication Date: 2012-5

Language

• English

Media Info

• Media Type: Print
• Features: References; Tables;
• Pagination: pp 565-591
• Serial:
  • Transportation
  • Volume: 39
  • Issue Number: 3
  • Publisher: Springer
  • ISSN: 0049-4488
  • EISSN: 1572-9435
  • Serial URL: http://link.springer.com/journal/11116

Subject/Index Terms

• TRT Terms: Behavior; Case studies; Choice models; Data files; Decision making
• Subject Areas: Passenger Transportation; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01446314
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 17 2012 8:54AM