Big Data Research ›› 2021, Vol. 7 ›› Issue (6): 89-102.doi: 10.11959/j.issn.2096-0271.2021063
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Nan LIU1, Xuejing HAO1, Yuhong CHEN2
Online:
2021-11-15
Published:
2021-11-01
Supported by:
CLC Number:
Nan LIU, Xuejing HAO, Yuhong CHEN. A review and comparative analysis of domestic and foreign research on big data pricing methods[J]. Big Data Research, 2021, 7(6): 89-102.
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定价方法 | 定价原理 | 适用范围 | 优点 | 缺点 |
成本法 | 依据是成本价值论,将重新获取相同数据的重置成本作为数据的评估价值 | 价值难以量化且成本容易计量的情况;不以交易为目的的情况,如政务数据 | 容易把握和操作 | · 成本量化较难,无法计算成本在单位数据上的均摊; |
· 成本和收益对应性弱,价格估算偏低 | ||||
协议定价 | 基于博弈论,数据买卖双方通过协商,对价格达成共识 | 成本和收益难以量化的情况、买卖双方价值估值不一致的情况、数据针对性较强的情况 | 操作简单方便、易被双方接受、成交率较高 | ·交易效率低; |
·由卖方主导,忽视数据效用; | ||||
· 买卖双方信息不对称,估值易出现偏差 | ||||
市场法 | 依据均衡价值论,以市场中可比参照物的市场价格为基础进行调整得到估值 | 市场成熟、活跃、交易案例多、易找到可比案例的情况 | 能 反映供求关系等真实市场情况,定价公平客观 | · 目前数据市场不成熟,交易案例少; |
· 数据产品个性化程度高,难以寻找可比案例; | ||||
· 修正系数难确定且难以修正全面 | ||||
收益法 | 依据效用价值论,将数据的预期收益现值作为数据估值 | 预期收益确定且可量化的情况,更适用于数据买方对数据估值 | 考虑数据使用价值和时间价值因素,反映真实数据价值 | ·预期收益难预测、难量化; |
·定价偏主观,折现率确定困难 | ||||
基于质量的定价方法 | 依据效用价值论,将数据质量作为数据成本和消费者效用的决定性因素 | 适用于对质量维度要求较低且质量维度容易量化的数据 | 考虑了数据自身的价值和消费者效用,定价透明公平 | ·质量非价值唯一的决定因素; |
· 数据质量维度以及质量维度间的关系难以量化 | ||||
基于查询的定价方法 | 本质是差异化定价,设定元组价格,由元组生成满足用户查询的最小视图,实现任意查询定价 | 存储在结构化或者非结构化数据库中的待交易数据 | 定价灵活,对任意查询自动定价,保证了用户的自由购买权 | · 数据单元本身几乎无价值,以此生成的数据价格缺乏说服力; |
·算法复杂,可操作性低; | ||||
· 预先设置的视图无法覆盖新生成的数据 |
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