Abstract
In this paper, we propose an approach where feed-forward neural network is used for dynamically calculating a competitive price of a product in order to maximize sellers’ revenue. In the approach we considered that along with product price other attributes such as product quality, delivery time, after sales service and seller’s reputation contribute in consumers purchase decision. We showed that once the sellers, by using their limited prior knowledge, set an initial price of a product our model adjusts the price automatically with the help of neural network so that sellers’ revenue is maximized.
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© 2009 Springer-Verlag Berlin Heidelberg
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Ghose, T.K., Tran, T.T. (2009). Dynamic Pricing in Electronic Commerce Using Neural Network. In: Babin, G., Kropf, P., Weiss, M. (eds) E-Technologies: Innovation in an Open World. MCETECH 2009. Lecture Notes in Business Information Processing, vol 26. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01187-0_18
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DOI: https://doi.org/10.1007/978-3-642-01187-0_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01186-3
Online ISBN: 978-3-642-01187-0
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