Research On Pricing Methods Of Data Products And Services In Big Data Industry Alliance

In recent years,with the rapid development of information technology such as cloud computing,data collection,and data mining,the demand for data collection and analysis by enterprises and governments has become increasingly prominent.At this time,data as a strategic resource,its value is increasingly highly attracted by enterprises and governments.However,data pricing issues have not yet been effectively addressed,which has largely hampered user demand for data resource transactions and sharing.At present,the transaction and circulation of data products and services are in the primary form,and no unified norms are formed.The establishment of the Big Data Industry Alliance provides a closer trust platform for member companies,and also facilitates the trading and circulation of data products and services among members of the alliance.Based on the big data industry alliance environment,this paper draws on market theory and product pricing theory,and proposes pricing models and pricing strategies for data products and services based on the characteristics of data products and services to regulate the trading behavior of data products and services among enterprises within the alliance and to improve the efficiency of the data resources of the Big Data Industry Alliance.This paper takes the Big Data Industry Alliance as the research object,and studies and analyzes the transaction pricing of data products and services in the Big Data Industry Alliance.Firstly,the basic issues such as the connotation,characteristics and organizational structure of the big data industry alliance are clarified,and the cooperation model of the members in the alliance is analyzed by using system theory.Furthermore,the connotation and characteristics of data products and services are further analyzed,and the transaction process and pricing method framework of data products and services within the alliance are constructed.Then,the in-depth analysis of the transaction characteristics and pricing influencing factors of data products and services in the Big Data Industry Alliance is carried out.The depreciation rate and customization degree of the data products are introduced into the dynamic utility function of both the supply and demand sides,and the member companies are respectively constructed.The data product pricing model under the two-sided and partial multi-sided market conditions and the data product pricing strategy is formulated;the discount factor is improved by the two factors of the perceived quality of the data service and the matching degree of the supply and demand information of the platform.The influence of the trading parties and the alliance platform on the pricing results was introduced into the bargaining,and the three-stage Rubinstein bargaining pricing model of the data service was constructed,and the corresponding pricing strategy was formulated.Finally,the Zhongguancun Big Data Industry Alliance is used as an empirical research object to verify the rationality of the pricing model constructed in this paper.The data product and service pricing met hod proposed in this paper provides an effective method and means for enterprises to realize the transaction of data products and services through the channels of the big data industry alliance,which has important practical significance for enterprises to improve the efficiency and competitiveness of data products and services.