Demand Forecasting for Rural E-Commerce Logistics: A Gray Prediction Model Based on Weakening Buffer Operator

Abstract

With the advancement of Internet technology and the widespread use of mobile smartphones, urban e-commerce is becoming increasingly saturated. Rural e-commerce ushered in a new era of development. How to improve rural logistics carrying capacity to keep up with the development of rural e-commerce and better serve the development of rural e-commerce has become a hot topic. The purpose of this study is to predict logistics demand in the context of the development of rural e-commerce. We develop an indicator system for forecasting rural logistics demand in Guangdong Province. The GM (1,1) gray forecasting model with a weakening buffer operator was used to forecast rural logistics demand in Guangdong Province. According to the results, the prediction model has good matching and precision. It was also found that demand for rural logistics in Guangdong Province will generally rise in the short to medium term. Based on the findings of this study, the government should stimulate demand for rural consumer goods, encourage technological innovation, develop an Internet-rural logistics mode, and meet the supply requirements of rural logistics based on the situation of each region.