基于GM (1, 1)–马尔可夫模型的贵州省电商物流需求预测研究

Research on Demand Forecasting of E-Commerce Logistics in Guizhou Province Based on GM (1, 1)-Markov Model

摘要: 本文构建灰色GM (1, 1)与马尔可夫链相结合的组合预测模型，实现了对贵州省电商物流需求量的精准测算。该模型适配区域物流需求“贫信息、强波动”的预测场景，可为电商物流布局、冷链资源配置、供应链调度提供量化决策依据，助力电子商务与现代物流协同发展，具有重要的理论价值与实践意义。

Abstract: This paper constructs a combined forecasting model integrating the grey GM (1, 1) model and the Markov chain, realizing the accurate measurement of the e-commerce logistics demand in Guizhou Province. Adapting to the forecasting scenario of regional logistics demand characterized by “poor information and strong volatility”, the model can provide quantitative support for the layout of e-commerce logistics networks, precise allocation of cold chain resources, and dynamic scheduling of supply chains. It facilitates the collaborative empowerment of the e-commerce industry and modern logistics industry, and has both theoretical innovation value and practical application significance.