Predicting and analyzing e-logistics demand in urban and rural areas: An empirical approach on historical data of China

Abstract

With the rapid development of the e-commerce economy in urban and rural areas, China's logistics industry has entered a stage of transformation and upgrade. First, this paper introduces the Supply-Chain Operations Reference-model as a theoretical reference for index selection. Then, after comparing the BP neural network and linear regression analysis, we chose the BP neural network analysis method, which is more stable and accurate in forecasting e-logistics demand scale in urban and rural areas. Finally, according to the results of the data analysis, this paper divides the development of e-logistics demand in urban and rural areas into two stages and discusses the reasons for the formation of these two stages in detail. This job not only provides a new perspective for the study of rural e-commerce and urban and rural e-logistics demand prediction, but also provides a theoretical reference for the formulation of government policies and farmers' participation in rural e-commerce.