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.     

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.     

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.     

‘Africanisation’ of South Africa’s international air links, 1994–2003

In the first decade of democratic rule in South Africa scheduled commercial passenger flights across the country’s borders more than doubled. Additional flights served new African air passenger markets and secondary airports in established markets. Overseas flights increased more slowly, serving a diminishing number of overseas countries and cities. In 1994 the Republic was linked directly by air with more overseas than African countries and cities; within a decade the pattern reversed. The changing geography of South Africa’s international air links reflects developments in the international airline industry, and South Africa’s increasingly prominent political and commercial role in Africa.     

An airline's management strategies in a competitive air transport market

Over the last decade, the demand for domestic and international flights in Korea has increased substantially. To meet the strong flight demands, several low cost carriers have begun to offer flight services. In addition, full service carriers have been motivated to establish their own subsidiary low cost carriers to maintain their market share against rival low cost carriers. This paper studies the management strategies of three kinds of airlines - full service carrier, its subsidiary low cost carrier and rival low cost carrier - based on game theory in the competitive air transport market. Each airline is assumed to act as a player and chooses strategies regarding airfare, flight frequency, and the number of operating aircrafts for specific routes while maximizing its own profits. Demand leakages between the airlines are considered in the flight demand function according to the selected strategies of all airlines. Through various game situations reflecting realistic features, this study provides managerial insights that can be applied in the competitive air transport market.     

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.     

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.     

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.     

The effect of flight distance on fuel mileage and CO2 per passenger kilometer

In this study, the effect of distance on fuel mileage (fuel burn per nautical mile) and CO₂ intensity, based on a large amount of actual flight data, is discussed for narrow-body commercial aircraft performing domestic flights for flight distances of between ～200 and ～800 NM, in Turkey. For twenty-nine domestic routes, the average CO₂ intensity is calculated to be 88 gr/pa-km, with an 80% load factor, ranging from between 112 gr/pa-km (207 gr/pa-NM) for the shortest route and 78 gr/pa-km (145 gr/pa-NM) for the longest route. An overall runway-to-runway analysis reveals that the average flight fuel consumption increases by 5.1 kg for each additional nautical mile. The discussion is extended to cover wind effect, through westbound and eastbound flights, on fuel consumption. The average fuel mileage of the eastbound flights, above 30 kft, is found to be 11.2% lower than those for the westbound flights. A sensitivity analysis is also carried out to reveal the effects of three main flight performance parameters, namely, cruise altitude, cruise speed and aircraft mass on the cruise CO₂ intensity.     

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.     

Effect of airline choice and temporality on flight delays

The civil aviation industry is critical to the economic development of any nation. Being a key infrastructure service, the performance of the civil aviation industry spills over to other segments of the economy. We investigate service failure among US airlines, using departure delay, and model its likelihood using mixed-logit regression. We characterize arrival performance for delayed departures using a service recovery/double deviation framework. We model the likelihood of different arrival possibilities using multinomial logistic regression. We use the chosen airline, temporality, and flight duration as predictors. Our key results include: (i) Afternoon/evening flights, and longer duration flights are more likely to depart late; (ii) Delta Airlines is most likely to depart on time; (iii) Southwest Airlines is best in recovering from delayed departures; (iv) United Airlines is most likely to aggravate delays.     

Measuring imported case risk of COVID-19 from inbound international flights --- A case study on China

With COVID-19 spreading around the world, many countries are exposed to the imported case risk from inbound international flights. Several governments issued restrictions on inbound flights to mitigate such risk. But with the pandemic controlled in many countries, some decide to reopen the economy by relaxing the international air travel bans. As the virus has still been prevailing in many regions, this relaxation raises the alarm to import overseas cases and results in the revival of local pandemic. This study proposes a risk index to measure one country's imported case risk from inbound international flights. The index combines both daily dynamic international air connectivity data and the updated global COVID-19 data. It can measure the risk at the country, province and even specific route level. The proposed index was applied to China, which is the first country to experience and control COVID-19 pandemic while later becoming exposed to high imported case risk after the epidemic centers switched to Europe and the US afterward. The calculated risk indexes for each Chinese province or region show both spatial and temporal patterns from January to April 2020. It is found that China's strict restriction on inbound flights since March 26 was very effective to cut the imported case risk by half than doing nothing. But the overall index level kept rising because of the deteriorating pandemic conditions around the world. Hong Kong and Taiwan are the regions facing the highest imported case risk due to their superior international air connectivity and looser restriction on inbound flights. Shandong Province had the highest risk in February and early March due to its well-developed air connectivity with South Korea and Japan when the pandemic peaked in these two countries. Since mid-March, the imported case risk from Europe and the US dramatically increased. Last, we discuss policy implications for the relevant stakeholders to use our index to dynamically adjust the international air travel restrictions. This risk index can also be applied to other contexts and countries to relax restrictions on particular low-risk routes while still restricting the high-risk ones. This would balance the essential air travels need and the requirement to minimize the imported case risk.     

A feasibility study on scheduled commercial air service between capital cities in South and North Korea

Scheduled commercial air service between capital cities in South and North Korea will greatly facilitate exchanges between people and transactions involving materials, and subsequently promote the opening of North Korean society by increasing the connectivity of Pyongyang to the outside world. This paper reviews the circumstances, identifies the problems, and suggests a solution to the problems with respect to starting regular flight service between South and North Korea. The study argues that the government of South Korea may need to compensate airlines for the financial feasibility of commercial flight operations between South and North Korea.     

Spatial concentration and connectivity of international passenger traffic at Brazilian airports

This paper examines concentration and connectivity of international passenger airport traffic in Brazil. The analysis considers seat supply and scheduled flights from 1999 to 2012. The 2000–2005 period was marked by concentration and limited international flight links, which was followed by the movement to recover capacity and connectivity from 2005 to 2010. Brazil started to liberalize bilateral agreements in 2002, and eventually moved towards the “open skies” concept in 2010, facilitating the process of operational de-concentration and increasing seat supply. The Brazilian government's liberalisation policy through bilateral agreements did not spark off a significant turnaround for national airlines; rather, the revived traffic growth was led by foreign airlines. This movement brought significant changes in the composition of international passenger traffic in Brazil, although changing little in terms of concentration and connectivity. The real change was the dominance of foreign airlines and seat distribution by regions, with the Latin America and Caribbean region shrinking to less than half of the market.     

Estimating the impact of COVID-19 on air travel in the medium and long term using neural network and Monte Carlo simulation

The COVID-19 pandemic has had a substantial impact on the airline industry. Air travel in the United States declined in 2020 with significantly lower domestic and international flights. The dynamic change and uncertainty in the trend of COVID-19 have made it difficult to predict future air travel. This paper aims at developing and testing neural network models that predict domestic and international air travel in the medium and long term based on residents' daily trips by distance, economic condition, COVID-19 severity, and travel restrictions. Data in the United States from various sources were used to train and validate the neural network models, and Monte Carlo simulations were constructed to predict air travel under uncertainty of the pandemic and economic growth. The results show that weekly economic index (WEI) is the most important predictor for air travel. Additionally, daily trips by distance play a more important role in the prediction of domestic air travel than the international one, while travel restrictions seem to have an impact on both. Sensitivity analysis results for four different scenarios indicate that air travel in the future is more sensitive to the change in WEI than the changes in COVID-19 variables. Additionally, even in the best-case scenario, when the pandemic is over and the economy is back to normal, it still takes several years for air travel to return to normal, as before the pandemic. The findings have significant contributions to the literature in COVID-19's impact on air transportation and air travel prediction.     

Aircraft operational costs and turnaround efficiency at airports

The aim of this paper is to investigate the relationship between flight schedule punctuality and aircraft turnaround efficiency at airports, in order to minimise system operational costs and meanwhile to maintain a required level of schedule punctuality. Investigations of aircraft operational costs, passenger delay costs and airline schedule time-opportunity costs are carried out in this paper. A mathematical model is applied to simulate aircraft turnaround operations by considering the stochastic effects of schedule punctuality as well as aircraft turnaround performance. Two numerical examples demonstrate the performance of the aircraft turnaround model. Results show the significance of a proper use of schedule buffer time in maintaining schedule punctuality performance.     

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.     

Monitoring social network formation and information content analysis of transport anomalies: The case of airline crashes

Airliners' industry corresponds to an extremely sensitive and volatile sector, especially subject to information related to flight safety. Possible negative publicity on such issues may result to sudden and abrupt fluctuations of air travel demand, accompanied with phenomena of panic or feelings of generalized insecurity. The proliferation of social media platforms that offer a direct and immediate two-way communication channel contributes to the overall information propagation related to flights security (as exposed in the recent airlines crashes) and can be viewed as a proxy of the social network formation of such paradigms. The current paper aims to offer a framework for quantitatively analyzing social network formation, based on comprehensive network metrics, valuable in cases of commercial airliners accidents. Moreover, the use of data from social media connectivity offers one more extremely valuable piece of information related to the messages that connected users exchange, mention or are exposed to. Such large datasets are quantitatively analyzed here based on methods used in content analysis, exposing valuable information on the interest of the general public (potential airliners users) of anomalies in the airline industry. The analysis is based on data from two real events (airliners’ crashes), which attracted the international public interest and significantly affected air travel demand. Finally, the results are analyzed and presented in detail such as to contribute to the air demand treatment, especially in terms of optimal communication operational management in cases of crises.     

Identifying flight fatigue factors: An econometric modeling approach

The paper looks at responses of crewmembers of six Taiwan air carriers who were asked to report their levels of fatigue before takeoff and after landing. Ordinal probit models are employed to estimate three fatigue models for different flight operations and serve as vehicles to investigate flight fatigue factors and identify their relative significance. The top three factors for long haul flights are found to be sleep quality at home, sleep quality on aircraft and “nod-off “experiences; for regional flights, age, extra non-flying tasks on the ground, and experiences of fatigue during flight operations are important; and for domestic flights poor cockpit environment, age, and experiences of fatigue during flight operations are relevant.