Describing Customer Loyalty to Spanish Petrol Stations Through Rule Extraction
Globalization and deregulation are modifying the competitive framework in the majority of economic sectors and, as a result, many companies are changing their commercial model to focus on the preservation of existing customers. Understanding customer loyalty therefore represents an element of competitive advantage. In this brief paper, we investigate loyalty in the Spanish petrol station market, according to the customer satisfaction and switching barriers constructs. Satisfaction and behavioural intentions are analysed within a classification framework using Bayesian neural networks. The necessary interpretability and actionability of the results is achieved through the use of a feature selection process embedded in the network training and a novel rule extraction method.
KeywordsArtificial Neural Network Artificial Neural Network Model Customer Satisfaction Customer Loyalty Rule Extraction
Unable to display preview. Download preview PDF.
- MacKay, D.J.C.: Bayesian Methods for Back-Propagation Networks. In: Domany, E., van Hemmen, J.L., Schulten, K. (eds.) Models of Neural Networks III, pp. 211–254. Springer, New York (1994)Google Scholar
- Etchells, T.A., Jarman, I.H., Lisboa, P.J.G.: Empirically derived rules for adjuvant chemotherapy in breast cancer treatment. In: IEE Proc. of the MEDSIP Int. Conf., pp. 345–351. Malta (2004)Google Scholar
- Etchells, T.A., Nebot, A., Vellido, A., Lisboa, P.J.G., Mugica, F.: Learning what is important: feature selection and rule extraction in a virtual course. In: Proc. of the 14th ESANN, Bruges, Belgium, pp. 401–406 (2006)Google Scholar