This paper investigates the evolving causal mechanisms of flight delays in the U.S. domestic aviation network from 2010-2024. Utilizing a three-level hierarchical Bayesian model on Bureau of Transportation Statistics (BTS) on-time performance data, we decouple the marginal contribution factors of weather, national aviation system (NAS), security delays, and late-arriving aircraft, using carrier delays as the baseline reference. Our findings suggest a structural shift: during the pre-pandemic decade (2010-2019), security delays functioned as an operational stabilizer with negative causal leverage (beta approx -1.307). However, in the post-pandemic period, they shift to a statistically marginal effect (beta approx -0.130). While the total volume of security delays remains a marginal fraction of the overall system latency, this structural shift points toward a potential change in the operational sensitivity of the system to security-related frictions. We show that while causal neutralization is characteristic of high-volume hubs (n >= 100), a discernible directional shift into a positive delay driver (beta approx 0.118) is observed as the analysis scales down to include the broader network (n >= 30). Our model identifies a significant change in how security delays propagate through high-volume nodes, evolving from an internalized operational buffer into a statistically discernible contributor to delay probability in the post-pandemic era.

翻译：本文研究了2010-2024年间美国国内航空网络中航班延误的演化性因果机制。利用基于美国运输统计局（BTS）准点运行数据的三级分层贝叶斯模型，我们以承运人延误为基准参照，分解了天气、国家航空系统（NAS）、安检延误以及飞机晚到这四个因素的边际贡献。我们的发现揭示了一种结构性转变：在疫情前的十年（2010-2019）中，安检延误作为一种运营稳定器发挥作用，其因果杠杆为负值（β约-1.307）。然而，在后疫情时期，其效应转变为统计学上的边际影响（β约-0.130）。尽管安检延误的总量仍占整个系统延迟的极小部分，但这种结构性转变指向系统对安检相关摩擦的运营敏感性可能发生了变化。我们表明，虽然因果中和是大流量枢纽（n≥100）的特征，但在将分析范围扩展至包含更广泛的网络（n≥30）时，可以观察到其向正延误驱动因素（β约0.118）的明显方向性转变。我们的模型识别出安检延误通过大流量节点传播方式的显著变化：它已从一种内化的运营缓冲演变为后疫情时代统计上可辨识的延误概率贡献因素。