Revealing additional dimensions of preference heterogeneity in a latent class mixed multinomial logit model
Latent class models offer an alternative perspective to the popular mixed logit form, replacing the continuous distribution with a discrete distribution in which preference heterogeneity is captured by membership of distinct classes of utility description. Within each class, preference
homogeneity is usually assumed, although interactions with observed contextual effects are permissible. A natural extension of the fixed parameter latent class model is a random parameter latent class model which allows for another layer of preference heterogeneity within each class. This
article sets out the random parameter latent class model and illustrates its applications using a stated choice data set on alternative freight distribution attribute packages pivoted around a recent trip in Australia.
Keywords: C10; C25; C51; C90; L92; freight distribution; latent class mixed multinomial logit; preference heterogeneity; random parameters; stated choice experiment
Document Type: Research Article
Affiliations: 1: Department of Economics,Stern School of Business, New York University, New York 10012, USA 2: The Business School, Institute of Transport and Logistics Studies, The University of Sydney, NSW 2006, Australia
Publication date: 01 May 2013
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites
- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content