Accounting for Inertia in Modal Choices: Some New Evidence Using RP/SP Data Set

Inertia measures the effect that experiences in previous periods have on the current choice. As such it measures the tendency of sticking with the past choice or the disposition to change, when some alternative becomes particularly appealing. At the same time new situations force individuals to rethink about their choice and new preferences are formed. A learning process begins that release the effect of inertia in the current choice. In this paper the authors use a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to study if inertia is stable along the SP experiments. Inertia has extensively been studied with panel dataset but only few works used RP/SP dataset. In this paper the authors extend these previous works in several ways. The authors test and compare several ways of measuring inertia, including measures that have been proposed to test inertia in both short and long RP panel dataset. The authors explore some new measures of inertia to test for the effect of learning along the SP experiment and we disentangle this later effect from the pure inertia effect. A mixed logit model is used that allows us to account for both systematic and random variation in the inertia effect and for correlations among RP and SP observations. Finally the authors explore the relation between the utility specification (especially in the SP dataset) and the role of the inertia in explaining current choices.

Language

  • English

Media Info

  • Media Type: DVD
  • Features: References; Tables;
  • Pagination: 19p
  • Monograph Title: TRB 90th Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01332943
  • Record Type: Publication
  • Report/Paper Numbers: 11-2445
  • Files: TRIS, TRB
  • Created Date: Mar 21 2011 2:13PM