Airline response to changing economics and policy

Abstract

Industry strategists, government regulators, and the media have focused on addressing concerns over the performance of the air transportation system with respect to delays. One of the strategies proposed has been to limit the scheduled operations at an airport to a-priori feasible capacity limits. This approach has been criticized on the basis that it would reduce the number of markets served and increase airfares. This paper describes a comparison of the behavior of the air transportation system (e.g. markets served, airfares, delays, load factors, aircraft size) during the recent run-up in fuel prices at capacity-limited New York airports and non-slot controlled San Francisco and Philadelphia airports. The implications of these results are discussed in this paper.

Projection of Flight Cancellations and Economic Losses Caused by Future Climate Change

“…, 악천후에 대한 대응 전략 연구 (Ferguson et al, 2010;Yoo, 2018) (Jung et al, 2021). 기후변화 시나 리오에 대한 축소기법에서도 Gementic Programming (GP), K-Nearest neighbor (K-NN), Artificial Neural Networks (ANNs), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Machine (GBM) 등 다양한 머신러닝 기법들이 활용되었으며, 축소기법이 적용된 결과에서 준수 한 성능을 보여주었다 (Ghosh, 2010;Pour et al, 2016;Sachindra et al, 2018;Xu et al, 2020)…”