Accounting for Inertia in Modal Choices: Some New Evidence Using a RP/SP Dataset

People often exhibit the tendency to stick with a choice they have made in the past even when another alternative becomes more appealing; this effect is called inertia. This study uses a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to examine if the inertia effect is stable along the SP experiments. The authors test and compare several ways of measuring inertia, including measures that have been proposed for both short and long RP panel datasets. New measures of inertia to test for the effect of “learning” (i.e., acquiring experience or familiarity) along the SP experiment are explored and so the authors can separate this effect from the pure inertia effect. The authors use a mixed logit model that can account for both systematic and random taste variations in the inertia effect and for correlations among RP and SP observations. The relation between the utility specification (especially in the SP dataset) and the role of inertia in explaining current choices is also considered. The findings from this study suggest that it is important to test different ways of measuring inertia, since they are based on different behavioral assumptions. The effect of inertia is significantly affected by the model specification adopted, and the inertia effect might change during the SP experiment.

• Record URL:
  • https://doi.org/10.1007/s11116-011-9338-9
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00494488
• Supplemental Notes:
  • This paper originally was presented at the Annual Meeting of the Transportation Research Board in January 2011.
• Authors:
  • Cherchi, Elisabetta
  • Manca, Francesco
• Publication Date: 2011-7

Language

• English

Media Info

• Media Type: Print
• Features: References; Tables;
• Pagination: pp 679-695
• Serial:
  • Transportation
  • Volume: 38
  • Issue Number: 4
  • Publisher: Springer
  • ISSN: 0049-4488
  • EISSN: 1572-9435
  • Serial URL: http://link.springer.com/journal/11116

Subject/Index Terms

• TRT Terms: Choice models; Consumer preferences; Logits; Mode choice; Travel behavior
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01355080
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Oct 25 2011 11:46AM