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Content Provider | IEEE Xplore Digital Library |
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Author | Chen Sheng-li Luo Yun-feng Dai Bao |
Copyright Year | 2007 |
Description | Author affiliation: Huazhong Univ. of Sci. & Technol., Wuhan (Chen Sheng-li; Luo Yun-feng) |
Abstract | In this paper, we first analyze the characteristics of online auction and propose a general analysis framework about the design of online auction. We believe that the auctions rules, the random arrival process of bidders, the auctions time, the lot size and the auctions costs need to be considered on Internet auctions. Based on the properties of online auction and a general analysis framework related to the design of online auction, then we present single-unit and multi-unit optimal auction models in order to maximize the seller' expected profits whether the reserve price is public or private respectively. In single-unit auction, when the seller with public or private reserve price gain the maximal expected profit respectively, the optimal public reserve price is higher than the optimal private reserve price. In multi-unit auction, it is shown that the seller with private reserve price can gain the bigger profits than the seller with public reserve price. Finally, numerical results for two cases are given, where we compute the maximal expected total revenue. We show that the numerical results are consistent with the theoretical analysis. |
Starting Page | 64 |
Ending Page | 70 |
File Size | 4605170 |
Page Count | 7 |
File Format | |
ISBN | 9787560322780 |
DOI | 10.1109/ICMSE.2007.4421826 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-08-20 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | HARBIN INSTITUTE OF TEC |
Subject Keyword | online auction Costs Conference management multi-period optimal design Design engineering Technology management Engineering management Aggregates Web and internet services Optimal control Systems engineering and theory Marketing and sales |
Content Type | Text |
Resource Type | Article |
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