Segmentation for Path Models and Unobserved Heterogeneity: The Finite Mixture Partial Least Squares Approach
Abstract
Partial least squares-based path modeling with latent variables is a methodology that allows to estimate complex cause-effect relationships using empirical data. The assumption that the data is collected from a single homogeneous population is often unrealistic. Identification of different groups of consumers in connection with estimates in the inner path model constitutes a critical issue for applying the path modeling methodology to form...
Paper Details
Title
Segmentation for Path Models and Unobserved Heterogeneity: The Finite Mixture Partial Least Squares Approach
Published Date
Jan 1, 2006
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