分析美国3900条航线的本地乘客比例,揭示经济与航空公司策略如何影响客流结构。
Examining the Dynamics of Local and Transfer Passenger Share Patterns in Air Transportation
- 用时间序列聚类方法分析超3900条航线的本地乘客占比变化模式。
- 发现低成本航司兴起与传统航司战略调整使本地乘客比例整体上升。
- 识别出不同航线间的共性趋势,适合航空规划与政策制定者参考。
航空运输中的本地乘客份额(即本地乘客占总乘客的比例)是反映经济增长、承运商策略与市场力量共同作用下需求结构的关键指标,尤其适用于分析行业结构性变化及大规模突发事件(如新冠疫情)的影响。本研究对美国航空运输系统中超过3900个始发地-目的地(O&D)组合的本地份额模式进行了深入分析,揭示了经济扩张、低成本航空公司(LCC)的出现以及主流航司的战略调整,共同推动了本地乘客份额的提升。为高效识别数千个O&D的本地份额特征并分类具有相似行为的组合,采用了多种时间序列聚类方法。通过可视化、性能指标评估与案例分析,结果呈现出从量级分层到趋势分组的显著模式。研究还发现不同O&D组合间存在模式共性,表明宏观因素(如经济周期、人口结构变化或疫情等冲击)可同步影响分散市场的变化。这些洞察为本地份额的预测建模奠定基础,有助于指导航空公司网络规划与基础设施投资。本研究结合定量分析与灵活聚类,助力利益相关方预判市场变动,优化资源配置,增强航空运输系统的韧性与竞争力。
原文摘要 · Abstract (English)
The air transportation local share, defined as the proportion of local passengers relative to total passengers, serves as a critical metric reflecting how economic growth, carrier strategies, and market forces jointly influence demand composition. This metric is particularly useful for examining industry structure changes and large-scale disruptive events such as the COVID-19 pandemic. This research offers an in-depth analysis of local share patterns on more than 3900 Origin and Destination (O&D) pairs across the U.S. air transportation system, revealing how economic expansion, the emergence of low-cost carriers (LCCs), and strategic shifts by legacy carriers have collectively elevated local share. To efficiently identify the local share characteristics of thousands of O&Ds and to categorize the O&Ds that have the same behavior, a range of time series clustering methods were used. Evaluation using visualization, performance metrics, and case-based examination highlighted distinct patterns and trends, from magnitude-based stratification to trend-based groupings. The analysis also identified pattern commonalities within O&D pairs, suggesting that macro-level forces (e.g., economic cycles, changing demographics, or disruptions such as COVID-19) can synchronize changes between disparate markets. These insights set the stage for predictive modeling of local share, guiding airline network planning and infrastructure investments. This study combines quantitative analysis with flexible clustering to help stakeholders anticipate market shifts, optimize resource allocation strategies, and strengthen the air transportation system's resilience and competitiveness.
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