PARTIAL LEAST SQUARES PATH MODELLING IN MARKETING AND MANAGEMENT RESEARCH: AN ANNOTATED APPLICATION
Chapter 3 in Quantitative Modelling in Marketing and Management, 2015, pp 43-78 from World Scientific Publishing Co. Pte. Ltd.
Since Jöreskog (1967) provided an algorithm for maximum likelihood estimation of latent variables structural models, covariance-based approaches (CBSEM) are tautologically synonymous of structural equation modelling. However, when Diamantopoulos and Winklhofer (2001) alerted that formative configuration should be considered as a reasonable alternative to model certain constructs, academic realised that CBSEM had many limitations to deal with this kind of constructs. Partial least squares path modelling (PLSPM) has recently arises as an alternative to CBSEM as its algorithm easily manages formative constructs. Proposed as a soft modelling alternative to CBSEM by Jöreskog's thesis advisor Herman Wold, PLSPM has addtional properties that explained its growing use in marketing and management research: Few distribution assumptions and can be estimated with small sample sizes. The objective of this chapter is, on the basis of a practical example, to illustrate and provide guidelines regarding the use of PLSPM as a structural equation modelling (SEM) tool, revealing its strengths and weaknesses, in order to allow researchers to decide on the adequacy of this approach for their particular investigation.
Keywords: Quantitative Analysis; Modeling; Marketing Management; Statistical Modelling; Computer Modelling; Memetic Algorithm; Structural Equation Modelling; Artificial Neural Networks (search for similar items in EconPapers)
JEL-codes: M31 M37 C15 (search for similar items in EconPapers)
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