大数据拍卖的定价策略与方法

Research on the auction strategies and pricing of big data

由于大数据具有多样性,价值稀疏性等特点,使大数据定价充满困难.以大数据拍卖为背景,针对大数据具有可复制性,传统拍卖模型无法解决卖家应该拍多少件大数据商品才能获得最大收益的问题,讨论大数据卖家在不同情境下时应该采取什么样拍卖方式才能使收益最高,将大数据拍卖给多少竞拍者合适.为此对传统的Vickrey拍卖模型和序贯拍卖模型进行修改,提出两种新的拍卖模型,适用不同条件下的大数据拍卖,最后设计出这两种拍卖模型并得出相应的收益的期望.

It is difficult to price big daga due to its diversity and sparsity,With big data auction set as background,for the problem that big data has a characteristic of replicability and that traditional auction models cannot determine how many big data items sellers should auction to get the maximum profits.A discussion is given on what auction strategies big data sellers should adopt under various circumstance to maximize their profits and on the appropriate number of winning bidders.The traditional Vickrey auction model and sequential auction model are modified,and two new auction models,which are suitable for different conditions of the auction,are proposed.Finally,the two auction models designed and relevant earnings expectations have been obtained.