数据质量、数量与数据资产定价：基于消费者异质性视角

doi:10.16381/j.cnki.issn1003-207x.2022.0444

Abstract

Abstract:

The data resource is expected to be "combustion promoter" driving the construction of "Digital China". How to transform data resources into data assets， realize the market-oriented allocation of data assets and improve the efficiency of resource allocation is not only the need to realize the high-quality development of China's economy and the modernization of national governance capacity， but also an important embodiment of the spirit of a series of central meetings， which has important theoretical and practical significance.The concept of comprehensive score of data assets covering data quality， quantity and their interaction factors is put forward in this paper for the first time， then a utility function based on comprehensive score is constructed， multi-dimensional influencing factors are considered， and a multi-dimensional factor pricing model suitable for consumers with heterogeneous efficiency sensitivity is constructed from the perspective of profit maximization. Taking the air quality data set assets of 31 cities in China as an example， KNN machine learning classification algorithm is used to fit the utility function， and the constructed model is used for simulation pricing analysis. The results show that：（1） utility and utility sensitivity are the key factors of data production and data asset pricing， the division of consumer utility sensitivity heterogeneity has a key impact on the optimal pricing. （2） Considering the retention level and saturation level of consumer utility sensitivity， the comprehensive score covering the quality and quantity level of data assets has an important impact on the production and pricing decision of data platform. （3） For a given comprehensive score level of data assets， the profits of the data platform tend to rise first and then fall with the change of price. The optimal price can be solved through the profit maximization model to realize the pricing of data assets.The pricing model constructed in this paper is universal for the pricing of data assets of all transactions on the data platform. It is not only an innovative attempt and important supplement to the data asset pricing theory and method， but also has important practical significance for stimulating the economic driving force of data elements.

Key words: data quality, data quantity, consumer heterogeneity, data asset pricing

CLC Number:

F014.31

Juanjuan Lin, Zhigang Huang, Yong Tang. Data Quality, Quantity and Data Asset Pricing: Based on the Perspective of Consumer Heterogeneity[J]. Chinese Journal of Management Science, 2025, 33(5): 88-98.

Figures/Tables 10

References 37

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Data Quality, Quantity and Data Asset Pricing: Based on the Perspective of Consumer Heterogeneity

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