The Evaluation of Factors Influencing Flights Delay at Czech International Airports

Zámková, Martina; Prokop, Martin

doi:10.11118/actaun201563062187

Cited by 5 publications

(7 citation statements)

References 8 publications

(6 reference statements)

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“…Our survey shows that delayed previous flights of individual planes are precisely the most common cause of delays; they comprise of about 90 % of all delayed flights. As Zámková, Prokop (2015a) and Zámková, Prokop (2016) suggested in their research, the delay caused by the delay of the preceding flight occurs generally very often. Even though the findings in this case apply specifically to European airports, Zámková, Prokop (2016) have also revealed that the delays caused by the delays of preceding flights at airports situated in popular Czech tourists' destinations occur the least frequently at night.…”

Section: Resultsmentioning

confidence: 99%

“…As Zámková, Prokop (2015a) and Zámková, Prokop (2016) suggested in their research, the delay caused by the delay of the preceding flight occurs generally very often. Even though the findings in this case apply specifically to European airports, Zámková, Prokop (2016) have also revealed that the delays caused by the delays of preceding flights at airports situated in popular Czech tourists' destinations occur the least frequently at night. While an article by Skorupski, Wierzbinska (2015) deals with the problems arising from waiting for belated passengers, our analysis shows that late passenger does not represent an important issue at Czech airports.…”

Section: Resultsmentioning

confidence: 99%

“…The paper by Zámková, Prokop (2015a) focused on financial impacts of delayed flights on airlines. Zámková, Prokop (2016) later focused on factors influencing flight delays, but their analysis was limited to the airports located near Czech tourists' favourite destinations only.…”

Section: Introductionmentioning

confidence: 99%

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Factors Influencing Flight Delays of a European Airline

Zámková¹,

Prokop²,

Stolín³

2017

Acta Univ. Agric. Silvic. Mendelianae Brun.

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The main aim of the paper was to investigate factors influencing flight delays of a European airline. Besides the identification and analysis of those factors the paper offers possible suggestions on how to eliminate the delays. The research is based on data acquired over the period of time spanning from June to September in 2008 -2014. Analysis of contingency tables, including Pearson's chi-squared test, has been used for data processing. The dependencies have been presented in graphical form by using correspondence maps. The proportion of delayed flights reaches approx. 50 % during nearly the entire monitored period only in September the proportion drops to 45 %. Flight delays are most frequently caused by delays of previous flights of the same plane. These previous delayed flights are the main culprit of long delays and the frequency of delay occurrence caused by this reason increases significantly during the day. Longer delays of flights appear also due to technical maintenance or aircraft defects. On the contrary other factors such as operational control and crew duty norms, air traffic control and airport limitations tend to cause rather shorter delays of flights with the air traffic control encountering more problems with coordination of flights in the early morning. The supply and service companies also manage to eliminate long delays.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Factors Influencing Flight Delays of a European Airline

Zámková¹,

Prokop²,

Stolín³

2017

Acta Univ. Agric. Silvic. Mendelianae Brun.

Self Cite

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“…The literature review shows up that all most all similar size and activity airports, the main delay factors are weather, technical problems, and reactionary delay. In Zamkova's paper [ 14 ] the main goal was an examination of factors influencing flight delay at three most important international airports in the Czech Republic (Praha, Brno, Ostrava). 5777 flights are investigated in the overall period.…”

Section: Related Workmentioning

confidence: 99%

Prediction of Flight Time Deviation for Lithuanian Airports Using Supervised Machine Learning Model

Stefanovič

Štrimaitis

Kurasova

2020

Computational Intelligence and Neuroscience

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In the paper, the flight time deviation of Lithuania airports has been analyzed. The supervised machine learning model has been implemented to predict the interval of time delay deviation of new flights. The analysis has been made using seven algorithms: probabilistic neural network, multilayer perceptron, decision trees, random forest, tree ensemble, gradient boosted trees, and support vector machines. To find the best parameters which give the highest accuracy for each algorithm, the grid search has been used. To evaluate the quality of each algorithm, the five measures have been calculated: sensitivity/recall, precision, specificity, F-measure, and accuracy. All experimental investigation has been made using the newly collected dataset from Lithuania airports and weather information on departure/landing time. The departure flights and arrival flights have been investigated separately. To balance the dataset, the SMOTE technique is used. The research results showed that the highest accuracy is obtained using the tree model classifiers and the best algorithm of this type to predict is gradient boosted trees.

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“…A delayed flight may propagate delays to the next flight through shared resources, such as aircraft, crew, and passengers [23]. This, in turn, may also lead to new delays to other flights through shared airport resources during the ground phase [24]. Baspinar and Koyuncu [25] have successfully applied the SIS model into an air transportation network to study the spreading of flight delay.…”

Section: Flight-based Susceptible-infected-susceptible Modelmentioning

confidence: 99%

A Network Modelling Approach to Flight Delay Propagation: Some Empirical Evidence from China

Zhang

Feng

et al. 2019

Sustainability

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This paper examines flight delay propagation in air transport networks. Delays add to additional costs, inefficiencies, and unsustainable development. An integrated flight-based susceptible-infected-susceptible (FSIS) model was developed to analyse the flight delay process from a network-based perspective. The probability of flight delay propagation was determined using a translog model. The model was applied to an airline network consisting of thirty-three routes involving three airlines. The results show that the propagation probability is network-related and varies across different routes. The variation is related to the flight frequencies at airports, route distances, scheduled buffer times, and the propagated delay time. Whereas buffer time has a greater impact on smaller airports, flight movement has a greater impact on larger airports. Having a better understanding of how delays happen can help the development of strategies to avoid them. This will lead to less costs, higher efficiencies, and more sustainable airport and airline development.

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The Evaluation of Factors Influencing Flights Delay at Czech International Airports

Cited by 5 publications

References 8 publications

Factors Influencing Flight Delays of a European Airline

Factors Influencing Flight Delays of a European Airline

Prediction of Flight Time Deviation for Lithuanian Airports Using Supervised Machine Learning Model

A Network Modelling Approach to Flight Delay Propagation: Some Empirical Evidence from China

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