Abstract

This study investigates the effect of Wild Your Weekends, an “all-you-can-fly” flight pass program launched by China Eastern Airlines during the COVID-19 pandemic in 2020 - 2021. We leverage the Propensity Score Matching (PSM) method to estimate the causal effect of the flight pass on travelers’ spending behavior based on observational data. To reduce confounding bias, the PSM method pairs flight pass holders with individuals who are very similar to them but did not purchase the flight pass and compares the expenditures of the two groups. This study is one of the few studies that directly addresses flight passes and lays the groundwork for understanding the socioeconomic effects of the flight pass. The results could not only help the airlines to understand the utility of flight passes for travelers, but also provide policymakers with guidance to make policies that sustainably promote travels to underdeveloped regions with the help of refined flight pass programs.

Abstract

In response to the increasing report intake and the need for more efficient and effective safety event detection and monitoring in the national airspace system (NAS), this work proposes an automated and sustainable workflow that collectively applies natural language processing (NLP) techniques to the Aviation Safety Reporting System (ASRS) report narratives. The proposed workflow utilizes latent Dirichlet allocation (LDA), a probabilistic model for uncovering hidden topics within text documents, to perform topic modeling and construct topic trajectories based on Document Frequency-Inverse Document Frequency (DF-IDF). By applying spectral analysis to the constructed trajectories, we identify multiple periodic and aperiodic topics in unfiltered ASRS report narratives from 2011-2021 with minimal human input. Through validation, we confirm that the periodic and aperiodic topics detected can be linked to actual safety events trending in the aviation community and are valuable for safety improvement. Beyond existing topic modeling applications on ASRS reports, this work could deliver more relevant and practical information to safety management experts, not only filling the gap between the topic model output and practical applications but also providing safety management experts with a holistic view of the entire report intake to oversee commonalities. With little modification. The proposed workflow, with appropriate modifications, has the potential to be adapted to other safety reporting systems proposed workflow can also be adapted to other safety reporting systems.