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.     

A delay estimation technique for single and double-track railroads

To route and schedule trains over a large complex network can be computationally intensive. One way to reduce complexity could be to “aggregate” suitable sections of a network. In this paper, we present a simulation-based technique to generate delay estimates over track segments as a function of traffic conditions, as well as network topology. We test our technique by comparing the delay estimates obtained for a network in Los Angeles with the delays obtained from the simulation model developed by Lu et al. [Lu, Q., Dessouky, M.M., Leachman, R.C., 2004. Modeling of train movements through complex networks. ACM Transactions on Modeling and Computer Simulation 14, 48–75], which has been shown to be representative of the real-world delay values. Railway dispatchers could route and schedule freight trains over large networks by using our technique to estimate delay across aggregated network sections.     

Towards the optimisation of the schedule reliability of aircraft rotations

A cost minimisation model is developed to optimise the scheduling of aircraft rotation by balancing the use of schedule time, which is designed to control flight punctuality, and delay costs. A case study is conducted using schedule and punctuality data from a European airline. Optimisation shows that the operational performance of an aircraft rotation schedule is improved in terms of: schedule regularity, mean delays and expected delays of aircraft rotation. Although the total schedule time of the study rotation is increased by 5%, a system cost saving of some $9.3 million/1000 aircraft rotations is gained after schedule optimisation. Three schedule reliability surrogates—mean delay time of aircraft rotation, expected delay time of aircraft rotation and schedule regularity—are employed to evaluate the reliability of aircraft rotation schedules. It is found that the reliability and robustness of schedule implementation is significantly improved after optimisation.     

Characterization of delay propagation in the air traffic network

We build a delay propagation network based on Bayesian Network approach to study the complex phenomenon of delay propagation within a large network consisting of the 100 busiest airports in the United States. Through topological analysis and probability analysis, we investigate the characterization of delay propagation among airports and the impact of different types of airports on delay propagation. Results indicate that the cumulative degree distribution of the delay propagation network follows an exponential function and flight delays take at most one transhipment to go from each airport to any other airports on average. For each individual airport, the effects of delay propagation are associated with airports size (traffic flow), small airports are easily affected by other airports while large airports are more affecting downstream airports but fewer affected by upstream airports. Finally, we show how the number of affected airports changes as a function of the delayed airports based on different simulation strategies.     

Connectivity of the European airport network: “Self-help hubbing” and business implications

This paper investigates the connectivity of the European air transportation network. A time-dependent minimum path approach is employed to calculate the minimum travel time between each pair of airports in the network, inclusive of flight times and waiting times. The connectivity offered by each alliance's network is compared with that of the overall network. The results show that roughly two-thirds of the fastest indirect connections are not operated by the alliance system; this could be exploited to enable a new passenger strategy of “self-help hubbing”.     

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.     

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.     

Do market-concentrated airports propagate more delays than less concentrated ones? A case study of selected U.S. airports

Airport congestion and widespread passenger discontent with airlines' poor on-time performance have recently led the Federal government to reduce peak-time operations at large airports such as Chicago O'Hare and New York John F. Kennedy. This paper proposes a methodology to compute delay propagation based on the discrete Fourier transform (DFT) at a sample of ten U.S. airports in summer 2000, 2007 and 2008. The sampled airports are different in terms of size, location and index of concentration.In this research, a flight is considered to be late if it arrives more than fifteen minutes past its schedule. Delay propagation is defined as the hourly ratio of two amplitudes: the one of late arrivals at a sampled airport to that of late arrivals at the final destinations served from that same sampled airport. The purpose of this study is to determine whether delay propagation differs at market-concentrated airports from less concentrated ones. Based on nonparametric tests and proximity analysis, there is no clear evidence that market-concentrated airports are different from less concentrated ones in terms of propagated delays.     

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.     

Airline emissions charges and airline networks

Emissions charges are an effective tool to control aviation carbon dioxide emissions. This paper investigates how airline emissions charges affect a monopoly airline's network choice. By considering simultaneously fully-connected, hub-spoke and mixed networks, we find that the impact of emissions charges on airline network configuration depends crucially on some relevant parameters, for example, the marginal benefit of the reduction of schedule delays and the disutility of additional travel time of connecting flights. Welfare analysis shows a discontinuity in the network configuration from the social planner's perspective and an inefficiency related to the airline's choice on mixed network.     

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.     

Micro-level analysis of airport delay externalities using deterministic queuing models: a case study

We analyze runway delay externalities at Los Angeles International Airport (LAX) using a deterministic queuing model. The model allows us to estimate the delay impact of each specific arriving flight on each other specific arriving flight. We find that, despite being only moderately congested (average queuing delay only 4 min per arriving flight), individual flights can generate as much as 3 aircraft-hours of external delay impact on other flights, with an average impact of 26 aircraft-minutes and 3400 seat-minutes. About 90 percent of this impact is external to the airline as well as the flight, a consequence of the lack of a dominant airline at LAX. We then compare the delay impact of each individual flight to its contribution to schedule convenience by determining the amount of “schedule delay” that would result if the flight were eliminated and its passengers forced to use the previous flight flown by the same airline from the same origin. We find that a number of commuter flights serving high density, short-haul segments generate much more queuing delay than they save in schedule delay, with the ratio exceeding 10 in several cases. We argue that social welfare would increase if such flights were eliminated, upsizing others as necessary to accommodate the displaced loads.     

Freight train scheduling with elastic demand

A train slot selection model based on multicommodity network flow concepts is developed for determining freight train timetables for scheduling rail services along multiple interconnected routes. The model seeks to minimize operating costs incurred by carriers and delays incurred by shippers while ensuring that the schedules and demand levels are mutually consistent. A column generation-based methodology is proposed for train slot selection to meet frequency requirements. This methodology is embedded in a simulation-based iterative framework, where demand for rail services is re-computed in accordance with the train schedule obtained by solving the freight train scheduling problem.     

Dynamic routing of time-sensitive air cargo using real-time information

The route planning of time-sensitive air-cargo is becoming more important with the growing air-network congestion and delays. We consider a freight forwarder’s routing of a time-sensitive air-cargo in the presence of real-time and historical information regarding flight availability, departure delays and travel times. A departure delay estimation model is developed to account for real-time information inaccuracy. A novel Markov decision model is formulated and solved with online backward induction. Through synthetic experiments and case studies, we demonstrate that dynamic routing with real-time information can improve delivery reliability and reduce expected cost.     

CO2 emissions associated with hubbing activities in air transport: an international comparison

Hubbing is an important operational practice in air transport. Many studies have been conducted to examine the benefits and impacts of hubbing from an economic perspective. However, its impact on CO₂ emissions, especially across different air spaces, is not well understood. This paper explores the impact of hubbing activities in air transport from an environmental perspective. With a detailed methodology and data from the Greek and Hong Kong/Sanya flight information regions (FIRs), three levels of CO₂ emissions are estimated: airport-based, airspace-based and flight-based. After contrasting the CO₂ emission efficiencies of Athens International Airport (AIA) and the Hong Kong International Airport (HKIA), aircraft type and flight distance are examined to explain their emission efficiency differences. It is found that HKIA is associated with poorer CO₂ emission efficiency at the airport and airspace levels because of the larger aircraft and longer flight distance. However, when CO₂ emission efficiency at the flight level is considered, HKIA, with a higher passenger load factor, performs better. Major international hub airports should implement additional environmental measures to minimize the impact of hubbing activities on CO₂ emissions at the airport and airspace levels.     

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.     

The pain persists: Exploring the spatiotemporal trends in air fares and itinerary pricing in the United States, 2002–2013

In the United States, the Airline Deregulation Act of 1978 prompted higher levels of service frequency between large and/or popular markets, lowering associated fares, on average. However, deregulation also increased financial instability within the commercial air transport industry, reduced quality of service, increased passenger fees and accelerated changes in the operational configurations of networks through hubbing, dehubbing, mergers and acquisitions. Over time, these market forces have squeezed service to/from smaller communities through schedule reductions and higher fares, creating “pockets of pain” in the air transport landscape. The purpose of this paper is to explore the uneven spatiotemporal distribution of air fares, by airports and associated flight segments, examining both symmetries and asymmetries in fare patterns over time and across space. Results suggest that several significant pockets of pain still exist within the U.S., and that asymmetries in air fares creates a lopsided fare structure for many smaller markets, further aggravating the fare imbalances spawned by deregulation.     

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.     

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.     

Improving the IATA delay data coding system for enhanced data analytics

Aviation delays inconvenience travelers and result in financial losses for stakeholders. Without complex data pre-processing, delay data collected by the existing IATA delay coding system are inadequate to support advanced delay analytics, e.g. large-scale delay propagation tracing in an airline network. Consequently, we developed three new coding schemes aiming at improving the current IATA system. These schemes were tested with specific analysis tasks using simulated delay data and were benchmarked against the IATA system. It was found that a coding scheme with a well-designed reporting style can facilitate automated data analytics and data mining, and an improved grouping of delay codes can minimise potential confusion at the data entry and recording stages.