Equilibrium Analysis of Price Discrimination Economic Phenomenon Based on Big Data Monitoring of Netizen Sensors

Abstract

With the wide application of sensors, people's behavior in life has been transformed into data resources. The emergence of big data can more effectively deal with a large amount of information generated. Network big data is increasingly applied to the analysis of economic problems. By analyzing the common phenomenon of price discrimination in life, we can better solve the differences between buyers and sellers. Because both businesses care about the number of vested interests, it is necessary to find a way to balance the two psychologically. Sellers feel that they have made a profit, while buyers feel that they have not lost, and then they will feel that this is a fair deal. In fact, this is not absolutely fair, only their own ideas. The main purpose of this paper is to analyze the economic phenomenon of price discrimination. On this basis, this paper proposes to use the combination of big data that netizens pay attention to and network sensors to detect price changes under the background of big data. Through the analysis of the collected sample data and related economic models, the experimental data show that when $p>v$ , if buyers choose to trade at this time, they will bring negative material returns to themselves. There was a significant negative correlation between second-class buyers and whether they accepted the transaction $\left(P<0.01\right)$ . In the case of bringing negative material returns to themselves, vulnerable buyers are more likely to choose to refuse the transaction.