Title: Dynamic Pricing in Electronic Commerce using Neural Network

Abstract: There exist intelligent agents to aid online sellers to
dynamically calculate a competitive price for the products in online
markets. However, the intelligent agents make few assumptions for dynamic
pricing. Few intelligent agents assume that sellers consist of prior
knowledge about the online market parameters, while some agents assume
that price is the only attribute that determines consumers' purchase
decision. On the contrary, in real life sellers have limited or no prior
knowledge about the market parameters. In addition, now a day along with
price other attributes like after sale service, product quality etc.
contribute in determining consumers' purchase decision. Here, I propose an
approach where it has been considered that sellers have no knowledge on
market parameters. I also assumed that buyers' purchase decisions are
based on multi-attribute. I used neural network for calculating a
competitive price dynamically to maximize the sellers’ revenue.