The University of Southampton
University of Southampton Institutional Repository

Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation

Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation
Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation
Research in marketing, and business in general, involves understanding when effect-sizes are expected to be large and when they are expected to be small. An example is the understanding of the level-effect in marketing, where the effect of product attributes on utility is positively related to the number of levels present among choice alternatives. Knowing when consumers are sensitive to the competing levels of attributes is an important aspect of merchandising, selling and promotion. In this paper, we propose a model and a method for studying the level-effect in conjoint analysis. The model combines perceptual theories in psychology to arrive at a non-linear specification of hyper-parameters in a hierarchical model. The method applies an experimental design criterion for efficient estimation of hyper-parameters. The proposed model and method are validated using a national sample of respondents.
1570-7156
69-93
Liu, Qing
83a2f342-7e29-4277-a3a8-800c7d034287
Dean, Angela
9c90540a-cdf4-44ce-9d34-6b7b495a1ea3
Bakken, David
804ff1d2-83c3-4c19-8a09-1eec92a185bf
Allenby, Greg
9803260e-de0c-425e-8d57-92bab1e6eff6
Liu, Qing
83a2f342-7e29-4277-a3a8-800c7d034287
Dean, Angela
9c90540a-cdf4-44ce-9d34-6b7b495a1ea3
Bakken, David
804ff1d2-83c3-4c19-8a09-1eec92a185bf
Allenby, Greg
9803260e-de0c-425e-8d57-92bab1e6eff6

Liu, Qing, Dean, Angela and Bakken, David et al. (2009) Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation. Quantitative Marketing and Economics, 7 (1), 69-93.

Record type: Article

Abstract

Research in marketing, and business in general, involves understanding when effect-sizes are expected to be large and when they are expected to be small. An example is the understanding of the level-effect in marketing, where the effect of product attributes on utility is positively related to the number of levels present among choice alternatives. Knowing when consumers are sensitive to the competing levels of attributes is an important aspect of merchandising, selling and promotion. In this paper, we propose a model and a method for studying the level-effect in conjoint analysis. The model combines perceptual theories in psychology to arrive at a non-linear specification of hyper-parameters in a hierarchical model. The method applies an experimental design criterion for efficient estimation of hyper-parameters. The proposed model and method are validated using a national sample of respondents.

Text
design_paper_Aug2010.pdf - Author's Original
Download (283kB)
Text
OptimalXExperimentalXDesignXforXHyperXDecX2007.pdf - Author's Original
Download (357kB)

More information

Published date: March 2009
Organisations: Statistics

Identifiers

Local EPrints ID: 352212
URI: http://eprints.soton.ac.uk/id/eprint/352212
ISSN: 1570-7156
PURE UUID: 6fb7a8a4-50fb-4bf0-b13b-ed6eee32f2ef

Catalogue record

Date deposited: 07 May 2013 15:32
Last modified: 14 Mar 2024 13:48

Export record

Contributors

Author: Qing Liu
Author: Angela Dean
Author: David Bakken
Author: Greg Allenby

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×