Characterising and Segmenting the Business-to-Consumer E-Commerce Market Using Neural Networks

A. Vellido, P. J. G. Lisboa and K. Meehan
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A. Vellido: http://www.cms.livjm.ac.uk/research/snc/neural.htm School of Computing and Mathematical Sciences, Liverpool John Moores University, Byrom St. Liverpool L3 3AF, UK
P. J. G. Lisboa: http://www.cms.livjm.ac.uk/research/snc/neural.htm School of Computing and Mathematical Sciences, Liverpool John Moores University, Byrom St. Liverpool L3 3AF, UK
K. Meehan: Business School, Liverpool John Moores University, Mount Pleasant, Liverpool L3 5UZ, U.K.

Chapter 3 in Business Applications of Neural Networks:The State-of-the-Art of Real-World Applications, 2000, pp 29-54 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThe following sections are included:IntroductionThe latent dimensions underlying the Internet users' opinions of online shoppingDescription of the data used in this studyFactor analysis rationale and methodologyFactor analysis results and their interpretationSummaryPrediction of the propensity to buy from the Internet channelVariable selectionQuantitative prediction of online purchasing behaviourSummarySegmentation of the e-commerce consumer marketDescription of the dataThe GTM as a principled model for data visualization and market segmentationExperimentsConclusionsReferences

Keywords: Artificial Neural Networks; Rule Extraction; Segmentation; Credit Card Fraud; Customer Profiling; Bankruptcy Prediction; Risk Assessment; Money Laundering (search for similar items in EconPapers)
Date: 2000
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