Flight Cancellations Research Articles

Financial and Administrative Measures for the Development of Tourism after COVID-19

The recent decades demonstrate that tourism is one of the sectors that develop the most consistently and form the backbone of the economies of many developed and developing countries. In this context, one of the main problems hindering the promotion of tourism services is the relatively high probability of force majeure situations. Whereas forced flight cancellations, floods, or hurricanes are local events, the consequences of the COVID-19 pandemic have taken their toll on the entire tourism sector. Today, the tourism sector is one of the most affected by the COVID-19 pandemic. This may provoke further regression given the weak global economy, geopolitical, social, and trade tensions, and uneven performance among major outbound travel markets. At the same time, over many years, tourism has been consistently proving its resilience and ability not only to recover from economic crises but also to contribute to a broader economic and social recovery. The goal of the present study is to develop proposals for the introduction of financial and administrative measures for the development of the tourism industry in the post-pandemic period. Data for the study are collected by means of document analysis and an expert survey. The study concludes that in order to overcome the adverse economic effects of the COVID-19 pandemic in the sphere of tourism, a number of financial and administrative measures need to be developed and implemented at the level of state and local government institutions, particularly in Kazakhstan, to support the development of the tourism sector and stimulate the activities of tourism enterprise. For their part, the authors propose the key measures that should improve the financial sustainability and organization of the tourism sector in Kazakhstan.

Collaborative slot secondary allocation based on flight wave operation

PurposeFlights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.Design/methodology/approachTaking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.FindingsComparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.Originality/valueBased on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

Refund Policy Due to Flight Cancellations Caused by the Covid-19 Pandemic: Consumer Protection Law’s Perspective

<span lang="EN-ID">The Covid-19 pandemic affects various aspects, including air transportation activities e.g., the Government of Indonesia has to impose travel restrictions to prevent the spread of the Covid-19 virus. In accordance with this policy, the airline canceled flights and issued travel vouchers for reimbursements. This study aims to analyse the refunds by airlines to airplane passengers because of flight cancellations due to the Covid-19 pandemic, as an impact of Government policies in perspective of the Consumer Protection Law. This research was conducted using a normative juridical method and the research specification is analytical-descriptive, because this article describes the implementation of the ticket refund by Garuda Indonesia (GIAA) to then be analysed to see if it has the potential to cause a violation of the Consumer Protection Law. The results showed that the implementation and handling of flight cancellations by rescheduling tickets and then refunding tickets by providing travel vouchers basically did not violate the provisions of laws and regulations in the field of aviation, and there were no violations of consumer rights. Furthermore, prospective passengers who experience financial losses can demand a refund in the form of cash to GIAA.</span>

An Optimized Solution to Long‐Distance Flight Routes Under Extreme Cosmic Radiation

AbstractDuring extraordinary space weather, cosmic radiation can be significant enough to pose a threat to aircrew health. Traditional methods of reducing massive cosmic radiation exposure include flight cancellation, lowering flying altitudes, and flight rerouting. However, flight cancellation can result in additional financial expenditures, while lowering flight altitudes and rerouting can consequently cause more fuel consumption or even violation of airspace rights. As a result, we use a multi‐objective optimization model to assign optimal flight altitude and speed to reduce the overall weighted sum of cosmic radiation and fuel consumption. The simulation scenario is based on a space weather event with dramatically increased cosmic radiation that occurs during a routine international flight from Tokyo to London. Our results show that the proposed model can reduce fuel consumption while satisfying cosmic radiation limits recommended by the Council of the European Union if the forecasts of cosmic radiation are sufficiently accurate. In addition, a Pareto frontier is provided as a tactical air traffic management guideline. Our study provides insight into future policymaking for air transportation during harsh space weather conditions.

The personalized recommendation for OTA flight cancellation and change services during the pandemic

The COVID-19 pandemic has had a dramatic impact on people’s travels. Due to the recurrent pandemic and regionally different policies in China, travelers must pay a lot for flight cancellations and changes. To accommodate this, online travel agencies (OTA) can provide a more flexible ancillary as a supplement to the airline company's services. Here, we introduced the upgraded all-in-one (AIO) service package, which offers compensation for flight delays, changes, or refund. We also designed a dynamic recommendation engine (DRE), which can make real-time personalized recommendations. Backed by AB testing, the machine learning-based DRE not only raises the package attach rate without interrupting the flight ordering process, but also helps the customers cut cost when making flight cancellations or changes.

Effect of Adverse Weather on Air Transport: Port Harcourt International Airport in Focus

This work focuses on the effect of adverse weather on air transport in Port Harcourt International Airport, Omagwa. Among the weather elements considered in this article are, rainfall, cloudage, relative humidity, sunshine duration and intensity, wind speed, temperature and other weather-related variables like thunderstorm, clear air turbulent etc. These conditions are diurnal and temporally checked in the airport. In an attempt to understand the effect of adverse weather on air transport, a questionnaire that covers all stakeholders was designed and administered to the relevant stakeholders. The study among other things observed that adverse weather is a challenge to aviation industry. It causes low visibility, can increase the rate of plane crash and can even lead to damages of plane parts. The study shows that the effect of adverse weather in the study area is seasonal. It was also observed that adverse weather leads to flight delay, diversions and cancellations, which cause passengers to spend more money. Finally, the study discovered that announcement of sudden adverse weather condition triggers health issues among passengers. This work used tables’ graphs and simple % for analysis. This work suggests the installation of latest weather monitoring devices in the airport, construction of paved runway and reliable weather forecast report should be made available to passengers’ days and hours before travelling to minimize flight delay and cancellations.

Projection of Flight Cancellations and Economic Losses Caused by Future Climate Change

The aviation industry plays an important role in daily life because of the increase of demand attributable to the development of air logistics as well as domestic and foreign tourism. However, the higher frequency of extreme weather caused by climate change has a large adverse effect on the operation of aircraft. As this effect is expected to increase, measures to reduce flight cancellation are needed. Therefore, in this study, the number of future flight cancellations and related economic losses were calculated for 1 3 domestic airports and six domestic airlines. To calculate the future climate of the airports, we used the recently released Shared Socioeconomic Pathways (SSP) climate change scenario. Then, we applied machine learning and the nearest neighbor with genetic algorithm method for spatial and temporal downscaling, respectively. The calculated results were applied to aircraft cancellation criteria and a damage estimation formula. Depending on the scenario, rainfall intensity increased by 2.02 to 3.54 times and wind speed increased by 1.16 to 1.24 times during 2100 to 2081. Economic losses from aircraft cancellations attributable to future climate increased by up to approximately 8.29 times. The results of this study highlight the necessity of preparing for and responding to climate change within the airline industry.

Deterrence of birds with an artificial predator, the RobotFalcon.

Collisions between birds and airplanes can damage aircrafts, resulting in delays and cancellation of flights, costing the international civil aviation industry more than 1.4 billion US dollars annually. Driving away birds is therefore crucial, but the effectiveness of current deterrence methods is limited. Live avian predators can be an effective deterrent, because potential prey will not habituate to them, but live predators cannot be controlled entirely. Thus, there is an urgent need for new deterrence methods. We developed the RobotFalcon, a device modelled after the peregrine falcon, and tested its effectiveness to deter flocks of corvids, gulls, starlings and lapwings. We compared its effectiveness with that of a drone, and of conventional methods routinely applied at a military airbase. The RobotFalcon scared away bird flocks from fields immediately, and these fields subsequently remained free of bird flocks for hours. The RobotFalcon outperformed the drone and the best conventional method at the airbase (distress calls). Importantly, there was no evidence that bird flocks habituated to the RobotFalcon over the course of the fieldwork. We conclude that the RobotFalcon is a practical and ethical solution to drive away bird flocks with all advantages of live predators but without their limitations.

Natural Language Processing of Aviation Safety Reports to Identify Inefficient Operational Patterns

With the growth in commercial aviation traffic and the need for improved environmental performance, strategies to lower emissions that can be implemented in the near term are necessary. Since novel technology takes time to enter the market, operational improvements that employ existing aircraft and require no new infrastructure are fit for this goal. While quantified data collected throughout aviation, such as arrival/departure statistics and flight data, have been well-utilized, text data collected through safety reports have not been leveraged to their full extent. In this paper, a methodology is presented that can use aviation text data to identify high-level causes of flight delays and cancellations, using delays as a metric of operational inefficiency. The dataset is extracted from the Aviation Safety Reporting System (ASRS), which includes voluntary safety incident reports in text narrative and metadata formats. The methodology uses natural language processing tools, K Means clustering, and dimensionality reduction by t-Distributed Stochastic Neighbor Embedding (t-SNE) to categorize and visualize narratives. The method identified 7 major clusters and a total of 23 sub-clusters. A comparison between the subclusters’ topics and the causes of flight delays revealed by the quantified data shows that the ASRS database provides a unique safety perspective to delay cause identification, as illustrated by the method’s identification of maintenance as the main cause of delays, rather than weather.

Operational Constraints on Flight Navigation due to Fog and Consequent Economic Implications at the Rajiv Gandhi International Airport, Hyderabad, Telangana, India

Fog is a frequent deterrent during the winter season. The reduction in horizontal visibility and other adverse conditions results in flight delays, cancellations, and flight de-route/diversions, leading to economic implications for rescheduling plans by the air-travellers. Clear skies, calm/light winds, a good amount of relative humidity, and fall in temperatures due to radiation cooling during winter nights are conducive. The intensity and duration of fog constrain flight operations. In the light of a fair number of fog occurrences compelling flight delays and diversions over Hyderabad Airport (RGIA, Shamshabad), the present study is undertaken to analyse the meteorological aspects of fog, and its frequency, duration, and economic implications. During the period 2014-2019, 74 instances of fog occurrence were recorded over the RGIA. The majority of the incidents (45.9%) were shallow fog events. The dense fog (2) and very dense fog (1) events were rare. Maximum fog occurrences (26 out of 74 events) were reported in December. The onset of fog was observed between 1800 UTC and 0400 UTC, while most of them (43.2%) occurred between 0000 UTC and 0200 UTC. Most of the fog events lasted up to 1 hour, and there were six instances of fog lasting between 2-3 hrs.

A Safety-Aware Real-Time Air Traffic Flow Management Model Under Demand and Capacity Uncertainties

Inherent uncertainties of the air transportation system (ATS) can induce unexpected anomalies in its operations such as deviations in flight schedules, sudden imbalances of demands and capacities, etc.. Current air traffic flow management (ATFM) models rarely consider both demand and capacity uncertainties in their algorithms, and generally focus on minimizing the flight delays under deterministic constraints. Thus, to bridge this gap, we propose a framework for en-route ATFM while scrutinizing uncertainties in en-route capacity and demand and their imbalance, via a chance constraint based probabilistic approach. The proposed framework plays a key role in ensuring the safety of the overall ATS in terms of maintaining the safety separation between flights and constraining the capacity of the sectors as well. Moreover, flight level assignments scheme is proposed based on the Base of Aircraft Data (BADA) of the European Organization for the Safety of Air Navigation (EUROCONTROL) with the objective of minimizing the fuel consumption. The model further minimizes the overall expected delay of the system using the control actions of ground holding, speed control, rerouting, and flight cancellations. At the implementation stage, two phases of ATFM as pre-tactical and tactical are considered, in which the former focuses on generating optimal trajectories and the latter focuses on real-time updates of flight plans. The computational complexity is reduced by shrinking the feasibility region and decomposing the problem into maximum weighted independent sets. The experimental results of realistic large-scale problems demonstrate the effectiveness and computational feasibility of our ATFM framework.

Potential Impact of GNSS Positioning Errors on the Satellite‐Navigation‐Based Air Traffic Management

AbstractThe traditional air traffic management (ATM) is transforming to the Communication, Navigation, Surveillance/ATM, which relies on accurate Global Navigation Satellite System (GNSS) navigation service, particularly during the final approach and landing phases. However, in the event of adverse space weather, there may be a significant increase in total electron contents (TECs) and irregularities in the ionosphere, which may cause considerable GNSS positioning errors. As a result, the aircraft navigation mode has to be switched from satellite navigation to ground navigation, which will reduce the airport acceptance rate and cause an imbalance between flight demands and airport capacity. The ATM authority will have to make tactical measures to remedy the problem, such as flight rescheduling and even cancellations. Hong Kong International Airport (HKIA) is one of the busiest airports in the world and Hong Kong, located in the equatorial ionosphere anomaly region, is prone to impacts of space weather. Thus, we have created a hypothesis scenario in this study by analyzing projected flight data from the HKIA during a simulated geomagnetic storm. Calculation results show that without an ionospheric delay forecast, the potential financial costs related to airlines due to flight delays, cancellations, and diversions could be over 2 million Euros. These costs decrease with an increased lead time of ionospheric delay forecast and the inaccurate ionospheric delay forecast can also result in significant extra costs. We also estimate the time cost of flight delays to passengers can be between 1.7 and 3.0 million Euros.

GROSS DOMESTIC PRODUCT OF KERALA- A STUDY ON THE IMPACT OF COVID-19 ON KERALA ECONOMY

Novel Coronavirus (COVID-19), originated at Wuhan, China, has spread to more than 158 countries of the world infecting more than 47 crores of the population as per World Health Organisation data. Since most of the countries had their primary infection through people from pandemic areas, many countries have stopped flight operations and closed their borders. Moreover the pandemic brought trade and business of the affected countries into halt and they also restricted the movement of people in all respects. The flight cancellations caused huge loss to the airline industry. Likewise, many sectors of the society were affected with the prolonged country-wide lockdown, global economic downturn and associated disruption of demand and supply chains. Apart from being a global health concern, COVID-19 is having major consequences on the world economy, and experts have predicted that COVID- 19 will lower global gross domestic product growth by one-half a percentage point for 2020. Furthermore, the economy is likely to face a protracted period of slowdown. The Indian economy also witnessed an unprecedented shock due to the outbreak of the Covid-19 pandemic. The economic impact is determined by the length of the lockdown and how the situation unfolds after it is lifted. It is important to have a coherent interference of the global researchers to understand and limit the economic fallout. In this context, this study aims to discuss the potential impacts of the pandemic over economy of Kerala, by assessing the GDP data for the last 10 years from 2011to 2020.

Resilient airline scheduling to minimize delay risks

Airlines tend to design their flights schedules with the primary concern of the minimization of operational costs. However, the recently emerging idea of resilient scheduling defined as staying operational in case of unexpected disruptions and adaptability should be of great importance for airlines as well due to the high opportunity costs caused by the flight cancellations and passenger inconvenience caused by delays in the schedule. In this study, we integrate resilient airline schedule design, aircraft routing and fleet assignment problems with uncertain non-cruise times and controllable cruise times. We follow a data-driven method to estimate flight delay probabilities to calculate the airport congestion coefficients required for the probability distributions of non-cruise time random variables. We formulate the problem as a bi-criteria nonlinear mixed integer mathematical model with chance constraints. The nonlinearity caused by the fuel consumption and CO2 emission function associated with the controllable cruise times in our first objective is handled by second order conic inequalities. We minimize the total absolute deviation of the aircraft path variability’s from the average in our second objective to generate balanced schedules in terms of resilience. We compare the recovery performances of our proposed schedules to the minimum cost schedules by a scenario-based posterior analysis.

Problems of hotel business functioning during the martial law

The hotel business is one of the main components of the tourism industry of Ukraine. In the long run, the hotel industry should become a leading factor in intensifying tourism, integrating the state into the world structures of international cooperation, and increasing the importance of national culture. The impact of force majeure on the hospitality industry has become one of the main problems over the last few years. Thus, initially the devastating impact on the hotel business was caused by the effects of the global pandemic, and since February 24, 2022 - the military aggression of the Russian Federation has dealt a terrible blow to the lives of Ukrainians in general and business structures in particular. Closed state borders, danger, rocket fire, cancellation of flights, restrictions on movement within Ukraine between regions and isolation of the country from foreign tourists have caused great damage to the domestic tourism industry, including the hotel business. This led to the choice of the direction of this study and confirms its relevance. The factors influencing the efficiency of the tourism business, which intensified during the war, are systematized. Selected factors are divided into several spheres of influence – financial, legal, customs, logistical, resources, information. Using the methods of correlation and regression analysis, these factors are ranked in order of importance. Given the significant reduction in tourist services during the war, it is advisable to implement a set of measures to increase efficiency by reducing the bureaucracy of permitting procedures and the introduction of anti-crisis measures in the hotel business. An improved management system of the hotel enterprise in the post-war period is proposed. The scientific novelty of this study is to develop and justify ways to mitigate the crisis caused by the military aggression of the Russian Federation against Ukraine. Thus as a direction of the further researches it is expedient to specify necessity of development of directions of adaptation of the world experience of struggle against the crisis phenomena in the hotel industry to the national environment.

U.S. network and low-cost carriers' performance in response to COVID-19: Strictness of government policies and passengers' panic

Coronavirus outbreak has been highly disruptive for aviation sector. There is strong correlation between COVID-19 related news, volatility in transportation, low confidence in travel safety, and uncertainty in this era. In this research, we study and distinguish the COVID-19's impact on U.S. airlines' performance. The network and low-cost carriers responded differently to it in terms of capacity reduction, market share reduction, scheduled flights reduction, flight cancellations, and service quality in the year 2020. We illustrate low-cost carrier had higher efficiency compared to network ones during pandemic by applying Network Data Envelopment Analysis. Furthermore, the effects of two key factors that emerge from COVID-19, the government's stringency actions and passengers' panic, on U.S. airlines efficiency are studied. Our analysis demonstrate that the negative effect is more significant for passengers' panic than it is for governments' stringency measures. In addition, we show that passengers' panic has more impact on the efficiency of network carriers compared to low-cost carrier.

PREDICTING FLIGHT DELAYS WITH ERROR CALCULATION USING MACHINE LEARNING

In the aviation industry, flight delays are a serious issue. The expansion of the aviation industry over the previous two decades has resulted in increased air traffic congestion, which has resulted in flight delays. Flight delays result in not only a loss of fortune but also a waste of time, adversely affect the environment. Flight delays also result in considerable financial losses. Commercial flights are operated by airlines. As a result, they make every conceivable effort. By taking basic precautions, you can avoid flight delays and cancellations. In this work, we use machine learning methods like Logistic Regression, Random Forest Regression, Decision Tree Regression, Bayesian Ridge Regression, Gradient Boosting Regression, we can forecast if a specific event will occur, will the flight be delayed or not.

Global impact of COVID-19 on newborn screening programmes.

IntroductionThe global COVID-19 pandemic has presented extraordinary disruption to healthcare services and exposed them to numerous challenges. Newborn screening (NBS) programmes were also affected; however, scarce data exist on the impact of COVID-19 on NBS.MethodsWe conducted an international survey to assess the global impact of COVID-19 on NBS, with the main aim of gathering the experiences of the COVID-19 pandemic from a large and representative number of NBS centres worldwide.ResultsThe results of our study showed that COVID-19 impacted the NBS programmes, at least partially, in 29 out of 38 responding countries. Majority of the screening centres experienced a broad spectrum of difficulties and most were affected more in the second wave of the pandemic. Delays and unreliability with the postal service as well as flight cancellations caused delays in samples arriving to screening centres and with the provision of laboratory equipment and reagents. The availability of laboratory staff was sometimes reduced due to infection, quarantine or reassignment within the healthcare facility. Sample collection at home, second-tier tests and follow-up were also affected. Social restrictions and interruptions in public transport added to these difficulties. Only a limited number of centres managed to retain a fully functioning NBS programme.ConclusionAs the pandemic might continue or could recur in future years, it would be useful to develop guidelines to protect these valuable services.

Analysis of Airport Risk Propagation in Chinese Air Transport Network

In recent years, due to the close coupling between airports, airport risk propagation has become a huge challenge. However, it has not been fully understood on the network level. Airport risk can be transferred through other airports owing to connected resources. In this study, we consider two risk factors including airport delay and saturation and propose a risk coupling model based on a clustering algorithm to fit the index and form risk series. To understand the risk propagation mechanism, we build risk propagation networks based on the Granger Causality test, and we apply complex network theory to analyze the evolution of the risk propagation network. We study the regular pattern of risk propagation from perspectives of time and space. Through network analysis, we find four time stages in the risk propagation process and the participation of airports in risk propagation has a positive correlation with airport sizes. In addition, more large airports tend to prevent risk propagation in unoccupied and normal situations, while small airports perform better than large airports in busy situations. Via the conclusion, our work can assist airlines or air traffic managers in controlling the scale of risk propagation before its key time turning point. By identifying the critical airport level and related factors in risk propagation, they can also reduce single airport risk and risk participation through corresponding risk control measures, finally avoiding the large-scale spread of risk and reducing delay or cancellation of more flights.

Sustainable supply of aviation fuel in Nigeria: the status quo and the challenges

<span>Adequate fuel supply and availability are vital for economic sustainability. Aviation fuel accounts for more than 30% of an airline’s operating expenditure. Jet fuel price is one of the factors that determine airfare and airlines’ profitability. Nigerian airlines run on civil grade jet A-1 fuel, and almost annually, the aviation sector is plagued with jet fuel scarcity and the resulting flight delays, rescheduling, and cancellations. Jet fuel scarcity and the escalating cost are products of multifaceted factors that are related to finance, logistics, management, and policy. This study highlighted the operational specifics of the Nigerian aviation fuel sector; it identified various business opportunities that affect air transportation and discusses the main industry challenges responsible for jet fuel price volatility and scarcity in Nigeria. Instability and shortage of foreign exchange (Forex), non-refining of jet fuel locally, and absolute dependence on jet fuel importation are some of the key causal factors. A total revamp of the aviation infrastructure, a review of the current incident of multiple and exorbitant operating fees, and licensing of private and modular refineries for jet fuel production will help address jet fuel scarcity issues in Nigeria.</span>