Original Article

Statistical Methods and Applications

, Volume 16, Issue 2, pp 263-278

First online:

Two-step PLS regression for L-structured data: an application in the cosmetic industry

  • Vincenzo Esposito VinziAffiliated withUniversity of Naples “Federico II”ESSEC Business School
  • , Christiane GuinotAffiliated withCE.R.I.E.S., Biometrics and Epidemiology Unit
  • , Silvia SquillacciottiAffiliated withUniversity of Naples “Federico II”EDF R&D – Département ICAMECE.R.I.E.S., Biometrics and Epidemiology Unit Email author 

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The present paper proposes a PLS-based methodology for the study of so called “L” data-structures, where external information on both the rows and the columns of a dependent variable matrix is available. L-structures are frequently encountered in consumer preference analysis. In this domain it may be desirable to study the influence of both product and consumer descriptors on consumer preferences. The proposed methodology has been applied on data from the cosmetic industry. The preference scores from 142 consumers on 9 products were explained with respect to the products’ physico-chemical and sensory descriptors, and the consumers’ socio-demographic and behavioural characteristics.


Partial least squares (PLS) regression Preference data External information L-structures