The impact of hubbing concentration on flight delays within airline networks: An empirical analysis of the US domestic market

This paper explores the relationship between hubbing activities and flight delays in the United States from an airline-specific network perspective. Airline hubbing is measured with the Hubbing Concentration Index. We estimate the impact of hubbing behavior on delays, using three measures of delay, two based on delay against schedule, and the third based on buffer-corrected excess travel times. A significant (and positive) influence of hubbing concentration can only be found for the latter delay indicator. We conclude that airlines use buffer times to mitigate passenger-perceived delays against schedule that would, without buffers, arise from more complex network operations.     

The relationship between on-time performance and airline market share: a new approach

We propose a new method of modeling the relationship between on-time performance and market share in the airline industry. The idea behind the method is that the passengers’ decision to remain (use same airline) or switch (use other airlines) at time t depends on whether they have experienced flight delays at time t−1 or not. More specifically, we posit that the passengers who experienced flight delays are more likely to switch airlines for the subsequent flight than those passengers who did not experience delays. To capture such effect, we develop an aggregate-level Markovian type model that estimates the transition probability matrices separately for the passengers who experienced flight delays at time t−1 and for those who did not experience delays. The model was calibrated with the US DOT data. The study results imply that, once experiencing flight delays, passengers are more likely to switch airlines. The results also imply that on-time performance affects a carrier’s market share primarily through the passengers’ experience, and not though the “advertisement” of performance.     

Integrated airline productivity performance evaluation with CO2 emissions and flight delays

This paper evaluates the airline productivity change by applying a modified global Malmquist productivity index (GMPI) model, incorporating both CO₂ emissions and flight delays. Statistical inference is also performed on the GMPI results using the bootstrapping method. Empirical research was conducted on 15 international airlines during 2011-2017. The obtained results showed that the productivity of all airlines had been fluctuating and experienced a slight increase over 2011–2017. Most of these 15 airlines made more progress in managing punctuality than CO₂ emissions. High punctuality policy may not be the best choice for all airlines when considering financial constraints, while airlines in more liberalized aviation markets are more likely to improve productivity by reducing flight delays. Efficiency change and technological change were the major driving factors for the growth of airline productivity. European and US airlines benefitted more from superior technology, while most Asian and Oceanian airlines still benefitted from the advantage of efficiency. Based on the findings, specific management advice was given.     

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.     

Modelling of aircraft rotation in a multiple airport environment

The objective of this paper is to develop a simulation model to simulate aircraft rotation in a multiple airport environment. The developed aircraft rotation model (AR model) consists of two sub-models, namely the aircraft turnaround model, which describes the operation of aircraft turnaround activities at an airport and the Enroute model, which simulates the enroute flight time of an aircraft in the airspace between two airports. Delays due to operational disruptions from aircraft turnaround activities are modelled by stochastic variables in the aircraft turnaround model. Uncertainties from schedule punctuality are modelled by probability density functions in the Enroute model. The proposed aircraft rotation model is employed to carry out a case study by using real schedule and punctuality data from a European schedule airline. Simulation results when compared with observation data validate the effectiveness of the aircraft rotation model. The proposed model is also found suitable for airlines to serve as a schedule planning and analysis tool.     

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.     

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.     

Mitigation of airspace congestion impact on airline networks

In recent years European airspace has become increasingly congested and airlines can now observe that en-route capacity constraints are the fastest growing source of flight delays. In 2010 this source of delay accounted for 19% of all flight delays in Europe and has been increasing with an average yearly rate of 17% from 2005 to 2010. This paper suggests and evaluates an approach to how disruption management can be combined with flight planning in order to create more proactive handling of the kind of disruptions, which are caused by congested airspace. The approach is evaluated using data from a medium size European carrier and estimates a lower bound saving of several million USD.     

Impact of e-business on air travel markets: Distribution of airline tickets in Korea

Early e-business activity in the airline industry was limited to the provision of flight schedule information to customers on websites. Recently, however, many airlines have expanded the capability of their web sites for selling tickets to make use of this cheap distribution channel. Here, we explore the impacts of airline e-business on the performance of air ticket distribution channels. Through a conjoint analysis, we suggest a model to estimate the change of market sales for each distribution channel. The impact of e-business on air travel markets and some implications on e-business strategy for both airlines and travel agents are also identified through an empirical survey.     

Network-wide assessment of ATM mechanisms using an agent-based model

This paper presents results from the SESAR ER3 Domino project. Three mechanisms are assessed at the ECAC-wide level: 4D trajectory adjustments (a combination of actively waiting for connecting passengers and dynamic cost indexing), flight prioritisation (enabling ATFM slot swapping at arrival regulations), and flight arrival coordination (where flights are sequenced in extended arrival managers based on an advanced cost-driven optimisation). Classical and new metrics, designed to capture network effects, are used to analyse the results of a micro-level agent-based model. A scenario with congestion at three hubs is used to assess the 4D trajectory adjustment and the flight prioritisation mechanisms. Two different scopes for the extended arrival manager are modelled to analyse the impact of the flight arrival coordination mechanism. Results show that the 4D trajectory adjustments mechanism succeeds in reducing costs and delays for connecting passengers. A trade-off between the interests of the airlines in reducing costs and those of non-connecting passengers emerges, although passengers benefit overall from the mechanism. Flight prioritisation is found to have no significant effects at the network level, as it is applied to a small number of flights. Advanced flight arrival coordination, as implemented, increases delays and costs in the system. The arrival manager optimises the arrival sequence of all flights within its scope but does not consider flight uncertainties, thus leading to sub-optimal actions.     

Modelling airline flight cancellation decisions

In order to predict airline responses to Traffic Management Initiatives (TMIs), and reveal the underlying preference structures that shape these responses, we study US domestic airlines’ cancellation decisions in response to the Federal Aviation Administration (FAA)’s TMIs, in particular, to Ground Delay Programs (GDPs). By observing the actual flight-cancellation choices made by airline dispatchers, the airlines’ cancellation utility functions can be inferred through the use of binary choice models. The model captures how delays to a given flight and potential delay savings to other flights affect flight cancellation decisions. We also find larger, fuller, less frequent, shorter-distance, and spoke-bound flights are less likely to be cancelled, and that there is inter-airline variation in flight cancellation behaviour.     

Impact of operational performance on air carrier cost structure: Evidence from US airlines

The impact of operational performance on airline cost structure is empirically investigated using an aggregate, statistical cost estimation approach. Two distinct sets of operational performance metrics are developed and incorporated into the airline cost models as arguments. Results from estimating a variety of airline cost models reveal that both delay and schedule buffer are important cost drivers. We also find that flight activity outside schedule windows increases cost, whereas flight inactivity within schedule windows does not. Using the estimated cost models, we predict the cost savings to airlines of “perfect” operational performance, obtaining an estimate in the range of $7.1–13.5 billion for 2007.     

An analysis of Brazilian flight delays based on frequent patterns

In this paper we applied data indexing techniques combined with association rules to unveil hidden patterns of flight delays. Considering Brazilian flight data and guided by six research questions related to causes, moments, differences, and relationships between airports and airlines, we evaluated and quantified all attributes that may lead to delays, showing not only the main patterns, but also their chances of occurrence in the entire network, in each airport and airline. We observed that Brazilian flight system has difficulties to recover from previous delays and when operating under adverse meteorological conditions, delays occurrences may increase up to 216%.     

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.     

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.     

Cost savings from trajectory deviations in the European air space

Air transport deregulation has lead to an increase of air traffic, together with a reduction of air fares. Air fare reduction has narrowed operational margins of airlines, bringing financial and employment instability. This has brought airlines to pay increasing attention to flying costs reduction. Two important components of flying costs airlines can try to cut modifying the planned flight are en route charges and operational costs. We rely on Demand Data Repository (DDR2) data to calculate deviations from planned flight trajectories to analyse the extent to what airlines try to cut operational costs making shorter flights than planned if possible, and cut en route charges providing a planned flight with lower en route charges than the planned flight. Our findings show that there is no generalised strategy among airlines to reduce en-route charges asking for deviations of the planned route. On the other hand, airlines are achieving savings of operational costs regularly. Higher savings per nautical mile are obtained in night flights, with longer planned distance and operated by low cost carriers.     

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.     

Intangible resources of competitive advantage: Analysis of 49 Asian airlines across three business models

Without sustainable competitive advantage firms have limited economic reasons to exist and will decline. Competitive advantage concerns the factors which provide competitive strength. This paper is based upon the resource-based view which considers firm resources to be heterogeneous and which believes that firms only have a small bundle of core resources irrespective of their overall performance. This research establishes the role of 36 intangible resources for 49 Asian airlines across three business models: network airlines; low-cost subsidiaries from network airlines; and low-cost carriers. It uses the VRIN framework which examines whether resources are valuable, rare, inimitable, and non-substitutable. Research participants distribute points between their chosen seven resources according to their perceived role in firm performance. Resources which meet all four requirements of VRIN are considered core competences and sources of sustained advantage. Across all 49 Asian airlines, the top-three most important resources of advantage are slots, brand, and product/service reputation. While these core resources are predictable, they have not previously been proven within the context of airlines, let alone geographically and by airline model. Results show that the core bundle of resources vary for each model, which helps to explain the difference in performance across models, and that some resources which were expected to be high-ranking, such as organisational culture and customer focus, were not.     

Structuring an effective human error intervention strategy selection model for commercial aviation

Flight safety cannot be compromised. Thus, commercial airlines should constantly develop safety management strategies to mitigate the diverse hazardous factors in flight operations. Given the constraint of organizational resource, a commercial airline may not have sufficient resources to implement all the necessary strategies simultaneously. This study uses a well-structured process to develop a qualitative evaluation model that will enable airlines to identify human errors and select an intervention strategy with the highest success potential. To clarify the decision problem, the Human Factors Intervention Matrix framework is utilized to construct the decision hierarchy. The Analytic Hierarchy Process is then used to attain the priorities of potential alternative strategies for various unsafe acts. Finally, Zero-One Goal Programming models are formulated to select an optimal portfolio based on the specific target and the available organizational resources. An empirical study is presented to illustrate the application of the proposed model. According to the results of the combined model, an optimal portfolio, including the intervention approaches of organizational/administrative, human/crew, and operational/physical environment, can remediate four unsafe acts, namely, decision errors, skill-based errors, perceptual errors, and violations, under resource constraints of the organization.     

A global model for estimating the block time of commercial passenger aircraft

This paper uses a two-stage statistical model to estimate the block time of commercial passenger aircraft. The model considers many of the factors contributing to airport congestion and provides a basis for future development of multivariate statistical models of the flight operation process. The model is tested using 2 million US domestic flights by six airlines in 2004. Model analysis provided insight regarding the relative impact of weather conditions and airport utilization on block time. In particular, population, arrival time, airport utilization, ice, and the interaction of poor weather conditions and traffic were found to be significant predictors of block time.