scholarly journals Segmentation for Path Models and Unobserved Heterogeneity: The Finite Mixture Partial Least Squares Approach

2006 ◽  
Author(s):  
Christian M. Ringle
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Unobserved Heterogeneity ◽  
Finite Mixture ◽  
Path Models ◽  
Least Squares Approach

scholarly journals ANTECEDENTS OF ONLINE PURCHASE INTENTION AND BEHAVIOUR: UNCOVERING UNOBSERVED HETEROGENEITY

2019 ◽  
Vol 20 (1) ◽  
pp. 131-148 ◽  
Author(s):  
Joaquim Silva ◽  
José Carlos Pinho ◽  
Ana Soares ◽  
Elisabete Sá
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Perceived Risk ◽  
Purchase Intention ◽  
Unobserved Heterogeneity ◽  
Causal Chain ◽  
Finite Mixture ◽  
Payment Methods ◽  
Online Purchase ◽  
The Relationship

The paper aims at exploring the antecedents of customers’ online purchase intention and behaviour, and at uncovering sources of heterogeneity. A sample of customers was surveyed to measure perceived risk and benefits, trust, online purchase intention and behaviour. The study confirmed the causal chain of perceived risks-trust-perceived benefits-online purchase intention-actual purchase. A Finite Mixture Partial Least Squares (FIMIX-PLS) was performed to uncover sources of heterogeneity. It found that the level of security of the payment methods is relevant to understand the relationship between purchase intention and behaviour, while the level of previous experience with the online medium clarifies the relationship between perceived risk and trust. The study contributes to understanding the antecedents of online purchase intention and their relationship with actual purchase behaviour. Additionally, it offers evidence of heterogeneity in the proposed causal relations, particularly, concerning the level of trust in the payment methods and the level of Internet experience.

Controlling in der Produktentwicklung

Controlling ◽  
2020 ◽  
Vol 32 (3) ◽  
pp. 45-50
Author(s):  
Marc Janka
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Finite Mixture

Gemeinhin gilt die Annahme, dass das Controlling für viele deutsche Unternehmen auch oder besonders in der Produktentwicklung von großer Bedeutung ist und vor allem unter Umfeldunsicherheit ein wesentlicher Erfolgsfaktor sein kann. Der vorliegende Beitrag zeigt unter Anwendung einer für die Controlling-Forschung neuartigen Methode zur Schätzung von Mischverteilungen mittels partieller Regressionen (englisch finite mixture partial least squares [FIMIX-PLS]), ob diese Annahme für alle Unternehmen gleichermaßen gilt.

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