X. Guan, L. Zhen

Pages: 221-234

Abstract
In recent years, China’s macroeconomic environment is stable, and the prosperity of e-commerce has brought new opportunities for the development of logistics enterprises. As an important part of the industrial chain and supply chain, the logistics industry plays an important role in promoting China's economic development, but also faces various opportunities and challenges. Based on the demand data of express logistics in Beijing from 2003 to 2022, this paper uses multiple linear regression model to analyze the impact of six factors on the demand of express logistics in Beijing: gross domestic product (GDP), per capita disposable income, permanent resident population, total import and export value of goods, total retail sales of social goods and total value of tertiary industry. Using EViews software to conduct regression and test, it is determined that the permanent population and the total value of the tertiary industry in Beijing are the main influencing factors. The GM (1,1) model is used to predict the dependent variable data in the next five years, and the independent variable data is predicted by combining multiple linear regression, and then the future data of the dependent variable is obtained. The comparison shows that GM (1,1) model is more stable and accurate for single prediction of dependent variable. The forecast results show that the demand for express logistics in Beijing will continue to increase with the economic development of Beijing, the popularity of e-commerce, the permanent population of Beijing and the improvement of traffic and other factors. This study provides scientific basis and reference for relevant government departments and enterprises, which can help them better optimize resource allocation and improve service quality, so as to promote the healthy development of the express logistics industry in Beijing.
Keywords: GM (1,1) model; express logistics needs; multiple linear regression