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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/4776

Title: Applying Bayesian networks in practical customer satisfaction studies
Authors: JARONSKI, Waldemar
BLOEMER, Johanna
WETS, Geert
Issue Date: 2004
Publisher: Singapore World Scientific
Citation: Tan, K. C. & Lim, Meng Hiot & Yao, Xin & Wang, Lipo (Ed.) Recent advances in simulated evolution and learning. p. 486-505.
Series/Report: Advances in Natural Computation, 2
Abstract: This chapter presents an application of Bayesian network technology in an empirical customer satisfaction study. The findings of the study should provide insight to the importance of product/service dimensions in terms of the strength of their influence on overall (dis)satisfaction. To this end we apply a sensitivity analysis of the model's probabilistic parameters, which enables us to classify the dimensions with respect to their (non) linear and synergy effects on low and high overall satisfaction judgments. Selected results from a real-world case study are shown to demonstrate the usefulness of the approach.
URI: http://hdl.handle.net/1942/4776
Link to publication: http://books.google.be/books?id=Vn4bdMbo488C
ISI #: 000231262700026
ISBN: 9812389520
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2006
Appears in Collections: Research publications

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