Interpretation of the Preferences of Automotive Customers Applied to Air Conditioning Supports by Combining GPA and PLS Regression

Abstract

A change in the behavior of the automotive customers has been noticed throughout the last years. Customers feel a renewed interest in the intangible assets of perceived quality and comfort of environment. A concrete case of study has been set up to analyze the preferences for 15 air conditioning supports. Descriptive data obtained by flash profiling with five experts on the photographs of 15 air conditioning supports are treated by Generalized Procrustes Analysis (GPA). The preferences of 61 customers are then explained by Partial Least Squares (PLS) regression applied to the factors selected from the GPA. The results provided by the XLSTAT GPA and PLS regression functions help to quickly identify the items that have a positive or negative impact on the customers’ preferences, and to define products that fit the customers’ expectations.