Research on the Demand Forecasting of the Air Cargo Market Based on the ARIMA Model

在全球化和国际贸易扩张背景下，航空货运市场全球地位成为关键，需求预测对企业战略规划意义重大，而传统预测方法难以适应市场变化。本文基于ARIMA模型进行航空货运市场需求预测。先提出采用该模型并阐述建模原理和实施流程，数据采集自权威渠道并预处理，模型构建经平稳性等检验，再定阶、估计和优化参数形成预测模型。依据模型输出结果，需求增长可增加运力或优化航线，需求下降则调整运营策略。实证研究和数据模拟表明，ARIMA模型在航空货运需求预测中的精度和稳定性具优势。该模型基于2010~2024年相关数据，纳入历史趋势和周期性特征，结合指数平滑模型，虽需综合多因素分析，但对航空货运企业市场规划和运营决策有重要参考价值。Against the backdrop of globalization and the expansion of international trade, the global position of the air cargo market is crucial, and demand forecasting is of great significance for enterprises’ strategic planning. However, traditional forecasting methods are difficult to adapt to market changes. This paper conducts demand forecasting for the air cargo market based on the ARIMA model. Firstly, it proposes the adoption of this model and elaborates on the modeling principles and implementation procedures. The data is collected from authoritative channels and preprocessed. During the model construction process, after undergoing tests such as stationarity, white noise, and zero-mean tests, the model is ordered, parameters are estimated, and optimized to form a forecasting model. According to the output results of the model, if the demand grows, the transportation capacity can be increased or the flight routes can be optimized; if the demand declines, the operation strategy should be adjusted. Empirical research and data simulation show that the ARIMA model has advantages in terms of accuracy and stability in air cargo demand forecasting. This model is based on the relevant data from 2010 to 2024, incorporates historical trends and periodic characteristics, and combines with the exponential smoothing model. Although it is necessary to conduct a comprehensive analysis considering multiple factors such as economic and political factors, it still has important reference value for the market planning and operation decision-making of air cargo enterprises.