Using partial least squares regression for conjoint analysis

Giorgio Russolillo (1) , Gilbert Saporta (1)

1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage

After a presentation of the classical methodology of conjoint analysis we advocate the use of PLS regression instead of classical regression in order to obtain a better accuracy in the estimation of utilities. PLS regression provides also interesting graphical representations allowing quick and easy interpretation of the relations among preferences, attributes and profiles.

Keywords: Conjoint analysis; Consumer choice; Data visualization; Partial Least Squares; Optimal Scaling

Domains: Statistics [stat]

Giorgio Russolillo, Gilbert Saporta. Using partial least squares regression for conjoint analysis. Statistica Applicata - Italian Journal of Applied Statistics, 2020, Conjoint Analysis and Decision Making, 32, pp.67-84. ⟨10.26398/IJAS.0032-005⟩. ⟨hal-02941462⟩