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

In: Business Applications Of Neural Networks The State-of-the-Art of Real-World Applications

Author

Listed:
  • 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.)

Abstract

The 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

Suggested Citation

  • A. Vellido & P. J. G. Lisboa & K. Meehan, 2000. "Characterising and Segmenting the Business-to-Consumer E-Commerce Market Using Neural Networks," World Scientific Book Chapters, in: Business Applications Of Neural Networks The State-of-the-Art of Real-World Applications, chapter 3, pages 29-54, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812813312_0003
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