Response-based segmentation using finite mixture partial least squares: theoretical foundations and an application to American customer satisfaction index data

CM Ringle, M Sarstedt, EA Mooi - Data mining: Special issue in annals of …, 2009 - Springer
When applying multivariate analysis techniques in information systems and social science
disciplines, such as management information systems (MIS) and marketing, the assumption …

Finite mixture partial least squares analysis: Methodology and numerical examples

CM Ringle, S Wende, A Will - Handbook of partial least squares: Concepts …, 2009 - Springer
In wide range of applications for empirical data analysis, the assumption that data is
collected from a single homogeneous population is often unrealistic. In particular, the …

Assessing heterogeneity in customer satisfaction studies: across industry similarities and within industry differences

EE Rigdon, CM Ringle, M Sarstedt… - … and Research Methods …, 2011 - emerald.com
Purpose–Revisiting Fornell et al.'s (1996) seminal study, this chapter looks at the evidence
for observed and unobserved heterogeneity within data underlying the American customer …

Approaches to customer segmentation

B Cooil, L Aksoy, TL Keiningham - Journal of Relationship …, 2008 - Taylor & Francis
Customer segmentation has virtually unlimited potential as a tool that can guide firms toward
more effective ways to market products and develop new ones. As a conceptual introduction …

Customer satisfaction study via a latent segment model

JRS Fonseca - Journal of retailing and consumer services, 2009 - Elsevier
The aim of this study is to apply a new conceptual model, and a new technique as an
approach to the modelling of customers' satisfaction, and to develop an overall satisfaction …

Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach

CM Ringle - University of Hamburg research paper on marketing …, 2006 - papers.ssrn.com
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 …

Finding groups in structural equation modeling through the partial least squares algorithm

M Fordellone, M Vichi - Computational Statistics & Data Analysis, 2020 - Elsevier
The identification of different homogeneous groups of observations and their appropriate
analysis in PLS-SEM has become a critical issue in many application fields. Usually, both …

Market basket analysis–a data mining application in Indian retailing

M Hemalatha - International Journal of Business …, 2012 - inderscienceonline.com
Data mining has become a widely accepted process for organisations to enhance their
organisational performance and gain a competitive advantage. Because the data mining …

Capturing and treating unobserved heterogeneity by response based segmentation in PLS path modeling. a comparison of alternative methods by computational …

V Esposito Vinzi, CM Ringle… - Cergy Pontoise …, 2007 - papers.ssrn.com
Segmentation in PLS path modeling framework results is a critical issue in social sciences.
The assumption that data is collected from a single homogeneous population is often …