Quotation Hackl, Peter, Anders H., Westlund, 2000. On Structural Equation Modeling for Customer Satisfaction Measurement. Total Quality Management. 11 820-825.




Latent variable structural equation models have found a rather new field of application: the modeling of national customer satisfaction measurements. For example, the European Customer Satisfaction Index (ECSI) is based on a structural model that links latent variables such as quality factors, customer satisfaction, and performance factors together. To derive values for the ECSI from data, the partial least squares (PLS) technique is applied to the structural equation model. This technique has the advantage that the estimation results depend much less on distributional assumptions than, e.g. ML-techniques. An alternative approach that can be applied to fit structural equation models to data is to see them as an artificial neural network (ANN) and to use the learning methods developed for neural network analysis to obtain the estimated model. This technique is insofar quite natural as the concept of latent variables is a central element of such models. Moreover, ANNs allows for certain generalizations, e.g., in the functional form of the connections between variables of the model. The paper discusses how structural equation models can be imbedded into the ANN framework and which alternative specifications are feasible on this basis.


Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Total Quality Management
Language English
Title On Structural Equation Modeling for Customer Satisfaction Measurement
Volume 11
Year 2000
Page from 820
Page to 825
URL https://www.tandfonline.com/doi/abs/10.1080/09544120050008264
DOI https://doi.org/10.1080/09544120050008264
Open Access N


Hackl, Peter (Former researcher)
Anders H., Westlund, (Handelshögskolan, Sweden)
Research areas (ÖSTAT Classification 'Statistik Austria')
1113 Mathematical statistics (Details)
5323 Econometrics (Details)
5701 Applied statistics (Details)
Google Scholar: Search