Finite Mixture Partial Least Squares Analysis: Methodology and Numerical Examples

By Christian M. Ringle, Sven Wende, Alexander Will. 2010

192 citations recorded by the source corpus.

Subfields: Food Science, Organizational Behavior and Human Resource Management, Tourism, Leisure and Hospitality Management

View Paper: https://www.semanticscholar.org/paper/6fb749670dcdf322c1456cbb337d0c84f9039aec

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Food Science

1. Jörg Henseler
2. Pauline Ash Ray
3. Geoffrey S. Hubona
4. Asyraf Afthanorhan
5. Zainudin Awang
6. Giancarlo Ragozini
7. Domenico Vistocco
8. Giovanni Camillo Porzio

In Organizational Behavior and Human Resource Management

1. Asyraf Afthanorhan
2. Geoffrey S. Hubona
3. Pauline Ash Ray
4. Zainudin Awang
5. Giancarlo Ragozini
6. Domenico Vistocco
7. Jörg Henseler
8. Giovanni Camillo Porzio

In Tourism, Leisure and Hospitality Management

1. Pauline Ash Ray
2. Geoffrey S. Hubona
3. Giancarlo Ragozini
4. Domenico Vistocco
5. Jörg Henseler
6. Giovanni Camillo Porzio
7. Marko Sarstedt
8. Christian M. Ringle

Citations in the corpus

• PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement (2010, unknown): “Ringle et al. (2010) consider this value as a moderate level for a PLS Path Model.”
• On the use of archetypes as benchmarks (2008, methodology): “To the authors’ knowledge, three methods exist for handling unobserved heterogeneity by response-based techniques in a PLS-PM framework: FIMIX-PLS [11, 17], PLS-TPM [12, 18] and PATHMOX [19].”
• Parametric and Non Parametric Approach in Structural Equation Modeling (SEM): The Application of Bootstrapping (2015, methodology): “According to Ringle et al. (2010), the non-parametric procedure of SEM can execute the analysis using small sample size, and does not require normal distribution.”
• Using PLS path modeling in new technology research: updated guidelines (2016, background): “Prominent examples include finite mixture PLS (Ringle et al., 2010a, c), PLS prediction-oriented segmentation (Becker et al., 2013b), and PLS genetic algorithm segmentation (Ringle et al., 2010b, 2014).”