Title: Forecasting consumer satisfaction for vehicle ride using a multivariate measurement system
Author: Elizabeth A. Cudney, Rajesh Jugulum, Kioumars Paryani
Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, 217 Engineering Management Rolla, 65409, MO, USA.
GWIM Q&P, Bank of America, 1 Federal Street, Boston, MA 02110, USA; Department of Mechanical Engineering and Engineering Systems Division, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA.
College of Management, Lawrence Technological University, Southfield, Michigan 48075, USA
Abstract: Consumers perceive quality and performance at the vehicle level. Consumers evaluate vehicle attributes such as ride, handling, roominess, braking and acceleration. Vehicle level attributes are influenced by factors at all levels of the vehicle architecture, and these factors are often correlated. The goal of this research is to efficiently forecast consumer satisfaction measured as a function of vehicle level performance data by developing a multivariate measurement system using the Mahalanobis-Taguchi Gram-Schmidt approach. The Mahalanobis-Taguchi Gram-Schmidt technique is applied to construct the measurement scale and identify a reduced set of useful variables for vehicle ride sufficient to make effective predictions.
Keywords: MTS; Mahalanobis-Taguchi system; multivariate measurement; diagnosis; forecasting; consumer satisfaction; orthogonalisation; quality; Gram-Schmidt; multicollinearity; customer satisfaction; vehicle ride; vehicle performance; vehicle comfort.
Int. J. of Industrial and Systems Engineering, 2009 Vol.4, No.6, pp.683 - 696
Available online: 26 Jun 2009