Quantitative Research On The Value Evaluation And Pricing Mechanism Of Network Digital Content Resources

In the era of the digital economy,the cultural and technological fields have performed exceptionally well.Faced with the real needs of Chinese culture “going global” in the country 's“Belt and Road” initiative and the important situation of the rapid development of global informatization,digital content resources have undertaken the heavy task of promoting cultural communication with content IP(Intellectual Property).However,the ecosystem of China's digital content resource trading platform is not complete.There are phenomena such as nonstandard valuation standards,high subjectivity of pricing,and low confidence.Therefore,it is very necessary to construct a value evaluation index system for network digital content resources and conduct a reasonable value evaluation and pricing mechanism quantitative research on it.The specific contents of this study are as follows:Firstly,by combing the influencing factors of the value evaluation of digital content resources,grasp the connotation of each influential factor.Furthermore,based on the "value chain theory" as the main line,corresponding to the process structure of the value content of digital content resources,a digital content resource value evaluation index system with cost value,copyright value,market value,and communication value as the primary index was constructed.Based on this,a typical second-level indicator is sorted out for each value layer to refine the specific composition of the value chain.Among them,the secondary indicators of cost value includes equipment investment,technology investment,and human investment;the secondary indicators of copyright value include specialization,timeliness,richness,and copyright scope;the secondary indicators of market value include popularity,monopoly,network externalities;the secondary indicators of communication value include interactivity,convenience,and easy-availability.On this basis,through the empirical analysis of Jingdong ebook data,the validity and rationality of the index system was verified.In addition,through a comparative analysis of the multivariate linear regression method and the BP neural network method,it is found that the nonlinear evaluation method has a better fit to the index system.Secondly,based on the established framework of digital content resource evaluation index system,a new GCA-RFR model is proposed to realize the intelligent value evaluation of digital content resources.The empirical analysis of this method and GCA-BP method using the data of IMDb film and television works has verified the superiority of the GCA-RFR method in evaluating the effect.The study finds that the evaluation method based on the GCA-RFR model reflects the following advantages:(1)Compared with traditional economic methods and comprehensive evaluation methods,the GCA-RFR model reflects the advantages of intelligence and objectivity.(2)Compared with the intelligent evaluation method based on BP neural network,the GCA-RFR model reflects a good generalization advantage.(3)Compared with the RFR model alone,the GCA-RFR model further improves the prediction accuracy.The exploration of the GCA-RFR method has enriched the theoretical research of digital content resource value evaluation methods,provided scientific technical support for network platforms to complete digital content resource value evaluation and pricing,and laid the foundation for promoting the digital content resource transaction and the orderly development of the platform.Finally,by digging the relevant factors that affect the pricing mechanism of digital content resources and combining market power analysis of digital content resource transactions,the key factors such as viewing effects,revenue sharing ratio,and sales unit price are selected as important analysis parameters that affect the pricing mechanism,and the complete information dynamic game model is used to analyze the mutual constraints between the various factors,and interpret the equilibrium results visually with the help of simulation analysis.The study found that: First,the digital content resource publishers on the network platform use a cost-plus pricing method for per show of digital content resources,and the unit price of similar content resources on the platform is uniform,there will be no difference due to different content quality.Second,the revenue sharing ratio of digital content resource producers decreases as the cost of a single show increases.The higher unit cost reduces the price advantage of digital content resources,thereby reducing the revenue of digital content resource publishers.In order to ensure their own profits,the publishers can only reach a consensus with producers at a lower percentage of revenue sharing.Third,the viewing effect of digital content resources is affected by multiple factors such as copyright fees,investment difficulty,sales volume coefficient,unit cost,etc.,and these factors participates in the formation of pricing mechanisms through complex effects.Among them,investment difficulty and copyright fees determine the base of viewing effects,and the sales volume coefficient and unit cost modify the base through market feedback.The above factors work through the pricing mechanism of digital content resources,and reflect the viewing effect of digital content resources.The above factors work through the pricing mechanism of digital content resources through the joint effect,which reflects the particularity of digital content resources with viewing effects as the core element of pricing.