A pricing method of online group-buying for continuous price function

被引:6
|
作者
Zhu, Junwu [1 ]
Teng, Ling [1 ]
Zhu, Zhengnan [1 ]
Lu, Huimin [2 ]
机构
[1] Yangzhou Univ, Coll Informat Engn, Yangzhou, Jiangsu, Peoples R China
[2] Kyushu Inst Technol, Kitakyushu, Fukuoka, Japan
来源
NEURAL COMPUTING & APPLICATIONS | 2020年 / 32卷 / 09期
基金
中国国家自然科学基金;
关键词
Incentive compatibility; Group-buying; VCG; Pricing;
D O I
10.1007/s00521-019-04017-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Group-buying has become a popular commodity trading mode in current business modes. However, the existing unified price of group-buying often determines the price by setting the ladder function according to the final quantities. This method not only ignores the contributions of participants to group-buying, but also leads to the phenomenon of buyers' false reports. In this paper, a pricing method of online group-buying based on continuous price function is proposed. We adopt an algorithm called Vickrey-Clarke-Groves for group-buying; buyers' payments are the sum of commodities' price and the extra amount by purchase quantity. The mechanism motivates buyers to report truthful preference through the compensatory payment. We prove that the mechanism has economic attributes such as incentive compatibility through theoretical proof and simulation experiments.
引用
收藏
页码:4453 / 4461
页数:9
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