广州市果蔬冷链物流需求预测及影响因素研究——基于灰色理论

Study on Demand Forecast and Influencing Factors of Fruit and Vegetable Cold Chain Logistics in Guangzhou City—Based on Grey Theory

摘要: 通过对区域内果蔬冷链物流需求进行细致分析和准确预测，可有效规避冷链物流供给过剩或不足的情况，对于加速推动该区域内果蔬冷链物流的发展具有显著的战略意义。文章一方面利用2013年至2022年广州市果蔬类生鲜农产品人均消费量乘以居民人口数量作为果蔬类生鲜农产品冷链物流需求的预测指标，建立灰色GM(1,1)预测模型并进行预测精度分析，分析未来的发展趋势；另一方面以农产品供给、社会经济水平、冷链支撑水平、居民规模与消费能力4个因素作为一级指标，构建需求影响因素指标体系，采用灰色关联法分析广州市果蔬冷链物流需求发展主要影响因素。结果表明，灰色GM(1,1)预测精度为98.33%，能够较为准确地预测出广州市果蔬冷链物流需求量；灰色关联分析得出社会经济水平与居民规模以及消费能力对果蔬冷链物流需求影响最大，其次是农产品供给，而冷链支撑条件水平的影响则相对最弱。

Abstract: By conducting detailed analysis and precise predictions of the demand for cold chain logistics of fruits and vegetables in a specific region, we can effectively prevent situations of oversupply or deficiency in the cold chain logistics system. This approach is crucial for strategically boosting the progression of cold chain logistics for fruits and vegetables within the region. On the one hand, the article takes the per capita consumption of fruits and vegetables and fresh agricultural products multiplied by the number of population in Guangzhou from 2013 to 2022 as the forecast indicator of fruits and vegetables and fresh agricultural products cold chain logistics demand, establishes a gray GM(1,1) forecast model, and carries out the analysis of forecasting accuracy and analyzes the development trend in the future; on the other hand, it takes the four factors of agricultural products supply, socio-economic level, cold chain supporting level, and the population size and consumption capacity as the first-level indicators. On the other hand, the four factors of agricultural products supply, social economic level, cold chain supporting level, population size and consumption ability are used as the first-level indicators to construct the index system of demand influencing factors, and the gray correlation method is used to analyze the main influencing factors of the development of the demand for fruit and vegetable cold chain logistics in Guangzhou. The results show that the gray GM(1,1) prediction accuracy is 98.33%, which can predict the cold chain logistics demand of fruits and vegetables in Guangzhou City more accurately; the gray correlation analysis concludes that the socio-economic level and population size as well as the consumption ability have the greatest impact on the cold chain logistics demand of fruits and vegetables, followed by the supply of agricultural products, while the level of the cold chain supporting conditions has the weakest impact, which provides a feasible paradigm for the research of the related fields.