Research On Traffic Data Asset Pricing Mechanism

As a derivative of traffic engineering,the economic value of traffic data has been difficult to determine.In the context of the continuous development and maturity of the big data industry,data assets have gradually developed into an important strategic resource for enterprises.As data is listed as a new factor of production,the research on the value evaluation and pricing mechanism of data assets is becoming more and more significant for the transaction of traffic data assets.At present,the definition,scope and characteristics of data assets are still under intense discussion.The difficulty in defining data assets and the imperfect development of data trading mechanism restrict the potential value of data assets to a certain extent.Therefore,how to establish a fair and reasonable data asset pricing mechanism and choose which pricing model has become an urgent problem to be solved.In order to maximize the value of traffic data in practical application and make up for the deficiencies and defects of the current data trading market,this study discusses the factors affecting the transaction price of traffic data assets,establishes an evaluation system for the factors affecting the transaction price from the data self-value,the expectations of both parties and the mode of data transfer,constructs a core framework for the pricing of traffic data assets,and discusses the overall transaction mechanism of traffic data assets.First,classify the traffic data according to the application scenarios,characteristics,and data field contents of the traffic data.According to the classification results,the data self-value evaluation indicators are determined from the perspective of technical value and economic value,the scoring rules are formulated,and the weight of each indicator is determined by using the analytic hierarchy process.Determine the qualitative evaluation results of the data’s own value according to the score and weight of each index.Then,by analyzing the data application scenarios,determine the composition of the buyer’s future income according to the social and economic benefits that may be generated after the application of traffic data assets,mainly includes saving travel time,reducing vehicle driving costs,environmental benefits,slowing down infrastructure and other benefits.Estimate the buyer’s expected income by the income method model.Considering the risk and uncertainty of the income of traffic data assets,the option pricing model is selected to modify the calculation results of the income method,and the buyer’s expected price is determined according to the income prediction results.Then,starting from the formation and application process of traffic data assets,determine the cost composition of transaction data,mainly including the construction cost and operation and maintenance cost of data,that is,the capital investment of enterprises in equipment,manpower,data management,data maintenance,etc.during the collection,transmission,storage,transaction,and other processes of traffic data assets.The data seller determines the expected price by combining the data transfer history and the total cost.Finally,through case analysis,the paper discusses the practical application of the traffic data asset pricing framework and transaction mechanism proposed in this study under the hypothetical transaction scenario.The case analysis results show that the pricing mechanism proposed in this study has certain enforceability,and it is also helpful for the construction of the pricing system of the data trading market.