Analysis of airport weather impact on on-time performance of arrival flights for the Brazilian domestic air transportation system

Air traffic operations are significantly impacted by weather conditions. These external factors may impose operational constraints and generate demand-capacity imbalances, leading to reduced on-time performance, additional airline costs and inconveniences to passengers. Efficient management of such disruptions requires an understanding of the main causes of flight delays towards increasing their predictability. In this study, we investigate the impacts of airport surface weather conditions on the likelihood of flight delays for the Brazilian domestic air transportation system. We use historical flight schedule, on-time performance and weather data and estimate a logit model to analyze how different meteorological variables at the airport of destination affect the probability of a delayed arrival. We obtain empirical evidence for the impacts of low ceiling and visibility conditions, precipitation and wind gusts on the likelihood of arrival delays for the set of Brazilian airports analyzed.     

Modeling the flight departure delay using survival analysis in South Korea

The air transportation industry in South Korea has been growing since the 2000s. Although the number of air passengers has continuously increased, the flight delay rate has fluctuated from year to year. In this study, a survival analysis was conducted to compare each flight delay in terms of airport/time slot and to evaluate the actual impacts of major variables on flight delays. We performed multiple analyses using survival analysis methodologies, including the Kaplan–Meier estimator, log-rank test, and Cox proportional hazards model. In particular, we applied a turnaround buffer as a key variable in Cox proportional hazards model analysis. The survival curve showed that more international flights departed earlier than scheduled or with minimal delay than domestic flights. However, international flights tended to have more long-term delays. The log-rank test indicated that international flights had a wider distribution of delay times than domestic flights. In the Cox proportional hazards analysis, under the condition in which the actual flight turnaround time was less than 120 min, the results indicated that the longer the actual turnaround buffer was, the less frequently the delays occurred. By using these analyses, we could numerically verify the actual delay trends in South Korea. The results can be used as fundamental resources for political and economic decision-making processes in the aviation industry.     

Introducing connecting flights in LCCs' business model: Ryanair's network strategy

In light of the ‘hybridization’ process characterizing airlines' business models, this work contributes to the literature by analyzing the rationale underpinning the decision to introduce connecting flights into the typical point-to-point networks of low-cost carriers (LCCs). By referring to the network of the largest European LCC, Ryanair, we provide evidence on how its new inter-connecting strategy is influenced by market, supply, and leg characteristics. Applying a probit model, results suggest that Ryanair is offering connecting flights on both non-directly offered markets and on markets that it already serves directly. The likelihood to observe a connecting flight increases at higher level of legs' frequency and at lower levels of Ryanair's legs' market share. Eventually, this new connecting strategy is negatively correlated with market distance, routing factor, direct frequency, and Ryanair's current O&D market share.     

An Exploratory analysis of flight delay propagation in China

Delay propagation is the flight departure delay caused by the arrival delay of pre-segment flight. Chinese airline market has suffered very poor on-time performance (OTP) in recent years. It is, however, unclear whether delay propagation prevails as one major source for such problem. This study first aims to empirically quantify delay propagation in the Chinese airline market. Specifically, we shed light on heterogenous levels of delay propagations across different airports and airlines. Then, the distinct delay propagation patterns in China are also discussed and compared with other developed airline markets (e.g., the US and Europe). Our estimation is based on OTP data for over 12 million Chinese flights covering the 2015–2017 period. Specifically, it is found that 10 min arrival delay of pre-segment flight within 1 hr before the departure lead to an average of 7.49 mins delay propagation for subsequent departure flight. Arrival delay of earlier pre-segments (1–2 and 2–3 hr before the departure) leads to much less delay propagation, due to longer ground buffer. Chinese airlines arrange longer ground and flight buffer than that of the US airlines to prevent the delay propagation from accumulating along the subsequent flights in a day. Thus, unlike the US market, delay propagation is not the major reason for poor OTP in China. In addition, delay propagation is less prevailing at the Chinese hub airport. This is because China has relied on point-to-point network, which does not require sophisticated schedule coordination. And the local passengers at these Chinese hub airports have higher time value such that the Chinese airlines also try to improve OTP at these hub airports to better serve these lucrative but time-sensitive local passengers. Unlike the European LCCs, Spring Airlines, the largest low-cost carrier (LCC) in China, outperforms major full-service carriers (FSCs) in controlling delay propagation. This finding may also apply to other Northeast Asian LCCs sharing common operational characteristics as Spring Airlines. Last, we find that airlines purposely tolerate moderate departure delays of up to 15 min, which is the threshold that defines delays, no matter whether the pre-segment flight arrives late or on-time. The relevant policy and managerial implications are also discussed.     

The impact of flight delays on passenger demand and societal welfare

US airline passengers increasingly have access to flight delay information from online sources. As a result, air passenger travel decisions can be expected to be influenced by delay information. In addition, delays affect airline operations, resulting in increased block times on routes and, in general, higher carrier costs and airfares. This paper examines the impact of flight delays on both passenger demand and airfares. Delays are calculated against scheduled block times as well as against more idealized feasible flight times. Based on econometric estimations, welfare impacts of flight delays are calculated. We find that flight delays on a route reduce passenger demand and raise airfares, producing significant decreases in both consumer and producer welfare. Since producer welfare effects are estimated to be three times as large as consumer welfare effects, we conclude that from an economic efficiency rationale, airlines should be required to pay for the bulk of flight delay remediation efforts.     

空铁联运协同下的跨域航空服务网络优化

为解决各机场竞相开设航班所导致的空域航班密度过大及与之相伴的航班延误问题,从需求管理的角度研究空铁联运网络优化及空铁协调下的客运组织问题。在建立由航班、高速铁路和空铁换乘系统构成的复合网络的基础上,以城市圈为区域单元,构建考虑公平性约束和高速铁路对航班喂给条件的上层空铁联运跨域航空服务网络优化模型和下层乘客路径选择模型的双层优化模型,旨在最小化区域间的出行总时间。在实证分析部分,对研究区域进行计算结果分析,并分析公平性指数对区域间运输系统效率的敏感性,为跨域航空服务网络优化研究提供参考依据。     

An optimization model for gate reassignment in response to flight delays

In this paper, a binary integer program is formulated for the optimal reassignment of planes to gates in response to day-of flight delays. This program minimizes the total walking distance of those passengers either connecting or originating at an airport whose boarding passes for affected flights were issued prior to the reassignment of gates. A numerical illustration using operations of Continental Airlines at the George W. Bush Intercontinental Airport in Houston, Texas demonstrates the speed and efficiency of this program in both a real world and real time setting.     

Determinants of flight delays at East Asian airports from an airport,route and network perspective

Previous studies on determinants of flight delays have been limited to the attributes of departure and arrival airports and routes and experiences in North America and Europe. This research extends the existing discussions by considering a network perspective to explore East Asian airports. A total of 4611 routes among 318 airports in the second half of 2017 are analyzed using panel data regressions. Results show that the attributes of airports and routes linked with the departure and arrival airports of a flight are the essential determinants of flight delays in East Asia. However, the congestion internalization and hubness effect of departure and arrival airports suggested in previous research are not observed in this region. The associations of slot control levels and route attributes with delays are varying between airports inside and outside China and domestic and international routes. This research supplements a new perspective to understand the determinants of flight delays in existing literature and provides a rarely observed knowledge to encourage East Asian airport operators and carriers developing management strategies for minimizing flight delays.     

How do carriers price connecting flights? Evidence from intercontinental flights from Europe

In civil aviation, hub-and-spoke (HS) networks are used by all large carriers. The importance of this system implies that many travelers use connecting flights. Nevertheless, only scarce knowledge is available on price formation of these trips. In this paper, we focus on the fares of connecting intercontinental flights, with one stop and at least one competing direct flight. We develop a simple model of a HS network, with imperfect substitutability between direct and indirect flights and Cournot competition on every route in the network. We test the model empirically, using reported fares for flights from seven European origins, including the five major airports in Europe, to five non-European destinations. We find that the fare of a connecting flight can be expressed as the weighted average of the fare of its direct competitor, the travel times of both flights its costs and the monetary value of the utility attached to the trip. The weight of the direct fare decreases as product diversity increases.     

Airport and route classification by modelling flight delay propagation

Flight delay can be divided into the root and propagated delays for identification and analysis of airports/routes that have a great influence on actual flight delay using flight operations raw data (tower logs) for South Korean domestic flights. In addition, the presented concept of “generated delay” classifies airports as affecting other airport delays or affected by other airport delays. The generated delay refers to the delay time at a particular airport/route, and this delay thereafter actually propagates to other airports/routes. In this study, the generated and propagated delays were displayed on a two-dimensional graph, and the airports/routes were grouped according to delay characteristics. Group A represented airports with high generated and propagated delays, and group B represented airports that are highly affected by delays of preceding airports/routes. Group C represents airports where newly formed delays affect other airport delays, but these airports mitigate delays from other airports. Airports in group D have relatively low delays and propagation. Thus, we targeted airports belonging to groups A and C because of their delay propagation impact on other routes/airports, which must be reduced by decreasing the root delay from targeted routes/airports. Among the airports, Jeju international airport (CJU) had the highest average delay time and propagated flight delay time with similar averaged generated delay times. Among the routes, departure flights from various airports to CJU had significant propagation effects on the subsequent flights. CJU and related routes have a very large impact on domestic flight delays because South Korean domestic airline routes are concentrated on CJU. However, there has been no quantitative analysis, and it is meaningful that the quantitative analysis results were presented in this study. In addition, we suggest that other airports such as GMP (Gimpo), CJJ (Cheongju), WJU (Wonju), and KUV (Gunsan) have a significant impact on domestic flight delays.     

Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We demonstrate our approach for strategic flight schedules in the period 2013–2018 at London Heathrow Airport. Together with the development of dedicated strategic flight schedule optimization models, our proposed approach supports an integrated strategic flight schedule assessment, where schedules are evaluated with respect to flight delays and cancellations.     

Detecting periodic patterns of arrival delay

This study identifies the periodic patterns of arrival delay for non-stop domestic flights at the Orlando International Airport during 2002–2003. Cyclic variations in air travel demand and weather at the airport were observed and their consequent effects on flight delay were investigated. This study detected the frequencies of any regularly repeating delay patterns and then identified the factors associated with the detected frequencies of delay. These sequential tasks called the “two-stage approach” were performed using a mathematical frequency analysis and statistical analysis techniques. The results of the frequency analysis showed that arrival delay displayed daily, weekly and seasonal patterns of variation. The results of the statistical analysis showed that time of day, day of week, season, flight distance, precipitation at MCO and scheduled time intervals between successive flights were significantly correlated with arrival delay.     

Optimizing flight equencing and gate assignment considering terminal configuration and walking time

Operating airline hub-and-spoke networks (HSN) rather than direct flights among city pairs may significantly reduce supplier cost; however, passengers' travel time may significantly increase due to increased transfer and in-flight time. The costs considered in this study are hub-related and incurred by passengers and aircraft (i.e., passenger transfer, flight dwelling, and gate occupancy). The objective is to minimize the total cost by optimizing flight sequence (i.e., arrivals and departures) and gate assignment, while considering transfer speed, transfer demand, flight size, gate size and terminal configuration. A real-world HSN whose hub airport (HA) is located at Xianyang International Airport (XIY) in Xi'an, China is analyzed. The optimized solutions and their relations to various model parameters are explored.     

User-Driven Prioritisation Process (UDPP) from advanced experimental to pre-operational validation environment

When the European Air Traffic Management Network (EATMN) approaches its capacity limits at certain airports, generating increasingly costly delays to flights and for passengers, reducing the impacts on airlines and passengers will be essential. There are two ways to address such increases in delay and costs. One is to strive to augment the capacity to reduce both delays and costs. The other one, adopted in this paper, is to reduce the impact of the delay on airlines and passengers.The User Driven Prioritisation Process (UDPP) provides airlines with additional flexibility in planning within constrained situations where delays are allocated, beyond the current slot swapping process already implemented by the EUROCONTROL Network Manager (NM).The paper presents recent validation results. It summarizes earlier results in a simplified EATMN with one constraint and several AUs showing that UDPP could reduce the impact of that delays on AUs' direct operational costs by 58% on average, and improves passengers’ connections. The paper then describes a parallel validation activity including several trials with SWISS. It focuses on the most recent validation results in a pre-operational environment close to SWISS Operations Control Centre (OCC). The results revealed overall operational benefit up to 65% improvement for the airline; and an initial impact assessment on the EATMN -although limited to one UDPP in the EATMN and one airline using it- shows promising results for the on-going integration closer to operations.While limited due to the simplified network context, these results are encouraging to undertake more complete network impact studies as well as to move forward to environments that are more realistic, bridging towards deployment.     

Optimising flight connection times in airline bank structure through Simulated Annealing and Tabu Search algorithms

In hub and spoke airline networks, flight arrivals and departures generally have a bank structure to increase connections among spoke cities through a hub airport in order to provide cheaper service for higher volumes of air traffic. In this study, we introduce the airline bank optimisation problem with a novel mathematical model for improving flight connection times. The mathematical model aims to minimise the total connection times for transfer passengers and generates flight schedules regarding slot capacities in the hub airports. Since the problem is a combinatorial optimisation problem NP-hard and computational complexity increases rapidly for real-world problems, we employ the simulated annealing and the tabu search algorithms to achieve better solutions in a reasonable time. We generate sub-problems using real-world data and investigate the effectiveness of the algorithms. Finally, we present the results of a real case study of a Turkish airline company which has a hub airport connecting the flights between Middle Eastern and European cities.     

Airport choice and flight connectivity among domestic and international passengers – Empirical analysis using passenger movement survey data in Japan

This paper presents an empirical analysis of airport choice and passenger movement on international flights from local cities in Japan to Narita and Haneda Airports in the Tokyo metropolitan area. This is the first study to evaluate airport choice behavior in Japan empirically by using the micro data collected by Japan’s Ministry of Land, Infrastructure, Transport and Tourism in 2010 (i.e., when time slots for international long-haul flights were first assigned at Haneda). The analysis confirms that flight connectivity is a crucial element in airport choice.Further, Japanese airlines and their associated alliances are able to attract passengers arriving from local cities by using Haneda airport. Above all, we find that the introduction of long-haul international flights from Haneda has met the needs of a number of passengers arriving from local cities in Japan owing to the convenience of the domestic flight network, especially for business purpose passengers.     

Flight delay impact on airfare and flight frequency: A comprehensive assessment

This paper presents a comprehensive empirical analysis of flight delay impact on airfare and flight frequency in the US air transportation system. We model airfare and flight frequency as functions of cost and demand characteristics, competition effects, and flight delays at origin, destination, and intermediate hub airports. Estimation results confirm that airlines tend to pass delay cost onto passengers through higher fare, whereas delay has an upward effect on flight frequency. We find that proportionate airport delay reduction across the system can result in annual fare reduction in the order of billion dollars.     

Analyzing passengers’ emotions following flight delays- a 2011–2019 case study on SKYTRAX comments

The text mining technology enables researchers or enterprises to automatically and efficiently access the information in text comments. This paper obtains 24,165 reviews from SKYTRAX between September 2011 and March 2019, 5700 of which express that passengers had experienced flight delays. It uses sentiment analysis based on a sentiment dictionary to classify user reviews and uses co-occurrence analysis to identify passengers' concerns on different aspects of service in the aviation industry. The results of the user sentiment analysis show that there is a significant and negative correlation between the user's emotions and their flight delay experiences. After flight delay, passengers' attention to the service aspects has increased, while satisfaction with the airport service has dropped dramatically. This paper shed some new light on public opinion about flight delays.     

A large neighborhood search heuristic to establish an optimal ad-hoc hubbing strategy in the wake of a large-scale airport outage

Abrupt airport outages can cause diversions and fuel-critical situations for flights, leading to costly passenger misconnections. We develop a large neighborhood search heuristic to optimize the rerouting of flights bound for a disrupted airport to a hub airport that is not disrupted, with the goal of accommodating passengers on existing flights departing the non-disrupted hub. The objective of the heuristic is to identify and reroute flights to the ad-hoc hub(s) – non-disrupted hub airport(s) – that minimize the sum of passenger travel time and wait time. We minimize the passenger cost as the sum of passenger travel time to the diversion airport and wait time for a connecting flight at the ad-hoc hub airport, subject to on-board fuel and diversion airport capacity constraints. We use the heuristic to determine how a coordinated traffic management strategy could have diverted flights immediately following a real-world airport outage.     

Airline ground operations: Optimal schedule recovery with uncertain arrival times

Airline operations are subject to a number of stochastic influences which result into variable ground and block times for same flights on different days. Our research explores how airline operations control centers may benefit from an integrated decision support system for schedule recovery during aircraft ground operations. In this paper, we study the sensitivity of an optimal set of schedule recovery options towards uncertain arrival times. The calculation of recovery options is based upon an integrated and iterative scheduling and optimization algorithm, which incorporates uncertainties for arrival flights as a function of a given look-ahead time. Potential recovery options include stand re-allocation, quick-turnaround, quick passenger transfer, waiting for transfer passengers, cancellation of passenger or crew connections, and arrival prioritization. Within a case study setting at Frankfurt Airport, 20 aircraft turnarounds are analysed during a morning peak with their respective estimated arrival times (including potential arrival delays). The analysis of simulation results reveals an almost identical set of selected recovery options under high uncertainty circumstances and from post-operational point-of-view, which indicates high solution stability.