Abstract
According to the characters of customer satisfaction index (CSI) models, we transformed these models into common regression models, and we find suitable iterative initial values with the constraint of a unit vector for latent variables. The convergence of the new algorithm is also illustrated in this paper. Consequently, the partial least square (PLS) algorithm for CSI models is improved greatly with the best iterative initial values. The results of this paper have been embodied into the software DASC.
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