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

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Abstract

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.

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Authors and Affiliations

  1. University of Naples “Federico II”, Monte S. Angelo, 80126, Naples, Italy

    Vincenzo Esposito Vinzi & Silvia Squillacciotti

  2. ESSEC Business School, Avenue Bernard Hirsch, B.P. 50105, 95021, Cergy-Pontoise, France

    Vincenzo Esposito Vinzi

  3. EDF R&D – Département ICAME, 1, avenue du Général de Gaulle, BP 408, 92141, Clamart, France

    Silvia Squillacciotti

  4. CE.R.I.E.S., Biometrics and Epidemiology Unit, 20 rue Victor Noir, 92521, Neuilly-sur-Seine, France

    Christiane Guinot & Silvia Squillacciotti

Authors
  1. Vincenzo Esposito Vinzi
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  2. Christiane Guinot
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  3. Silvia Squillacciotti
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Correspondence to Silvia Squillacciotti.

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Vinzi, V.E., Guinot, C. & Squillacciotti, S. Two-step PLS regression for L-structured data: an application in the cosmetic industry. Stat. Meth. & Appl. 16, 263–278 (2007). https://doi.org/10.1007/s10260-006-0028-2

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  • DOI: https://doi.org/10.1007/s10260-006-0028-2

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