DocumentCode :
126969
Title :
Sealed-bid multi-attribute reverse auction strategies and revenue analysis
Author :
Zeng Xian-ke ; Feng Yu-qiang
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol., Harbin, China
fYear :
2014
fDate :
17-19 Aug. 2014
Firstpage :
200
Lastpage :
206
Abstract :
Sealed-bid multi-attribute reverse auction has been widely used in government procurement and corporate mass purchase. Bidding strategies and auction revenue are the main concerns of buyer and sellers. In this paper, firstly, we propose an improved sealed-bid multi-attribute reverse auction model. Further, we give the bidding and auctioning strategies and the expected revenue of bidders and auctioneer respectively through the mathematical analysis methods based on the improved model. Lastly, we analyze the mathematical properties of the bidder´s optimal bidding price and expected revenue, and explain their practical economic meaning. These explicit mathematical solutions can provide the efficient and effective decision support for the auction participants during the period of online bidding, and it is also helpful to the realization of online automatic e-procurement.
Keywords :
commerce; mathematical analysis; auction revenue; auctioning strategies; bidding strategies; corporate mass purchase; effective decision support; expected revenue; government procurement; mathematical analysis methods; mathematical properties; online automatic e-procurement; online bidding; optimal bidding price; revenue analysis; sealed bid multiattribute reverse auction strategies; Analytical models; Cost function; Economics; Mathematical model; Procurement; Product development; Production; auction expected revenue; bidding strategies; multi-attribute reverse auction; sealed-bid;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science & Engineering (ICMSE), 2014 International Conference on
Conference_Location :
Helsinki
Print_ISBN :
978-1-4799-5375-2
Type :
conf
DOI :
10.1109/ICMSE.2014.6930229
Filename :
6930229
Link To Document :
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