| Abstract |
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This research examines sellers’ pricing strategy
oriented to bidders’ risk preferences, within the context of
an electronic auction. A business model is then proposed
to predict the probability of potential bidders’ risk
preference, which sellers can consider to set pricing
strategy to maximize their profits. A tailored intelligent
auction registry engine is constructed based upon an
initial version of our business model. Because the
eXtensible Markup Language (XML)-based Simple Object
Access Protocol (SOAP) is utilized to support interactions
with other resources, our engine is decoupled from the
underlying technology choices; therefore, it can be
deployed to different platforms.
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 Additional Information
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Citation:
Jia Zhang, Ning Zhang, Jen-Yao Chung,
"Assisting Seller Pricing Strategy Selection for Electronic Auctions,"
cec,
pp. 27-33,
2004 IEEE International Conference on E-Commerce Technology (CEC'04),
2004
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