Analysis and Forecast of Demand for Cold Chain Logistics of Agricultural Products in Shanghai in the Context of The Covid Pandemic

Abstract

Forecasting the demand for cold chain logistics of agricultural products will help to achieve the balance between supply and demand of agricultural products and promote the healthy development of the cold chain logistics industry of agricultural products. This paper collects relevant data from 2015 to 2020 in Shanghai, and uses grey correlation analysis to conduct correlation analysis on the factors influencing the demand for cold chain logistics of fresh agricultural products. The traditional GM (1,1) model, the new information GM (1,1) model and the metabolism GM (1,1) model are used to forecast the demand for cold chain logistics of agricultural products in Shanghai in the next five years respectively. The grey correlation analysis shows that the employees of the tertiary industry and the total import and export of goods have the greatest impact on the market demand of cold chain logistics and the results of the three GM (1,1) models show that the sum of squared errors of using the new information GM (1,1) model is smaller. Finally, using the new information GM (1,1) model to forecast the demand for cold chain logistics of agricultural products in Shanghai from 2021 to 2025, and it is found that the overall demand for agricultural cold chain in Shanghai is on an upward trend.