基于用户感知价值的大数据资产估价方法研究

[目的/意义]随着大数据交易市场的快速发展,大数据资产价格管理引起各方的关注,大数据资产估价方法是大数据资产价格管理的基础。作为一种全新且复杂的资产形态,大数据资产给传统资产估价方法带来挑战。[方法/过程]文章提出的方法基于用户感知价值的视角。首先,运用多指标多标度矩阵处理大群体用户评价信息,引入多维偏好线性规划分析(LINMAP)模型融合专家总体偏好信息和用户分项评价信息。其次,初步计算各评价对象的得分并通过影响因素修正确定综合得分。最后,计算价格质量比率,并结合综合得分和可比大数据资产价格综合确定待估大数据资产价格。[结果/结论]实例分析验证了新方法的可行性和有效性。新方法是针对大数据资产估价的尝试,也可用于其他形态资产的估价。

Research on Big Data Asset Valuation Method Based on Customer Perceived Value

[Purpose/significance] With the rapid development of big data trading market,the issue of big data asset price management has attracted the attention of all stakeholders.The valuation method of big data asset is the basic issue of big data asset price management.As a new and complex asset form,big data asset brings challenges to traditional asset valuation methods.[Method/process] The method proposed in this paper is based on the perspective of user perceived value.Firstly,multi-index multi-scale matrix is used to process the evaluation information of large group users,and the model of linear programming technique for multidimensional analysis of preference(LINMAP) is used to fuse total preference information of experts and itemized evaluation information of large group users.Secondly,the score of each evaluation object is calculated preliminarily,and the comprehensive score of each evaluation object is determined after the price influence factor is modified.Finally,the price-quality ratio is calculated,and the price of big data asset to be evaluated is determined by combining to the price-quality ratio,the comprehensive score and the price of comparable big data assets.[Result/conclusion] The feasibility and effectiveness of the new method are verified by an example.The new method is an attempt to evaluate big data asset,and it can also be used to valuate other asset forms.