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Structural Neural Networks for Modeling Customer Satisfaction

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Abstract

The aim of this paper is to provide a Structural Neural Network to model Customer Satisfaction in a business-to-business framework. Neural Networks are proposed as a complementary approach to PLS path modeling, one of the most widespread approaches for modeling and measuring Customer Satisfaction. The proposed Structural Neural Network allows to overcome one of the main drawbacks of Neural Networks because they are usually considered as black boxes.

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Correspondence to Cristina Davino .

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Davino, C. (2010). Structural Neural Networks for Modeling Customer Satisfaction. In: Palumbo, F., Lauro, C., Greenacre, M. (eds) Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03739-9_17

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