Impact of COVID-19 on air transport passenger markets: Examining evidence from the Chinese market

AI-supported estimation of safety critical wind shear-induced aircraft go-around events utilizing pilot reports

The occurrence of wind shear and severe thunderstorms during the final approach phase contributes to nearly half of all aviation accidents. Pilots usually employ the go-around procedure in order to lower the likelihood of an unsafe landing. However, multiple factors influence the go-arounds induced by wind shear. In order to predict the wind shear-induced go-around, this study utilized a cutting-edge AI-based Combined Kernel and Tree Boosting (KTBoost) framework with various data augmentation strategies. First, the KTBoost model was trained, tested, and compared to other Machine Learning models using the data extracted from Hong Kong International Airport (HKIA)-based Pilot Reports for the years 2017-2021. The performance evaluation revealed that the KTBoost model with Synthetic Minority Oversampling Technique - Edited Nearest Neighbor (SMOTE-ENN)- augmented data demonstrated superior performance as measured by the F1-Score (94.37%) and G-Mean (94.87%). Subsequently, the SHapley Additive exPlanations (SHAP) approach was employed to elucidate the interpretation of the KTBoost model using data that had been treated with the SMOTE-ENN technique. According to the findings, flight type, wind shear magnitude, and approach runway contributed the most to the wind shear-induced go-around. Compared to international flights, Hong Kong-based airlines endured the highest number of wind shear-induced go-arounds. Shear due to the tailwind contributed more to the go-around than the headwinds. The runways with the most wind shear-induced Go-arounds were 07C and 07R.

Risk perceptions of COVID-19, vocational identity, and employment aspirations of Chinese aviation students: a structural equation modeling approach

BACKGROUND

The COVID-19 pandemic has wreaked havoc on the aviation and education sectors in China. This study examined the relationships between risk perceptions of the pandemic, vocational identity, and employment aspirations of Chinese aviation students.

METHODS

The study used a convenience sampling approach to collect data (n = 276 respondents) from August 2 to 8, 2022. An online survey was sent via WeChat and QQ to Chinese students majoring in aviation service management who were under lockdown at six Chinese schools.

RESULTS

In spite of the strong support for the stringent COVID policies and full awareness of infection risk and protective measures, respondents were worried about the current unstable situation and felt fear for its severity and long-lasting symptoms. The casual path from career commitment to employment aspiration was supported, but high risk perceptions of the pandemic failed to have any psychological effect on the two constructs of vocational identity and employment aspirations.

CONCLUSIONS

The findings not only demonstrate the power of career commitment on employment aspirations but also reveal that a relatively high self-assessment of career proficiency may not necessarily lead to a clear career aspiration, possibly due to poor risk communication and insufficient career planning guidance. Thus, Chinese aviation students should improve their career proficiency and commitment, broaden their career options and adaptability, and have a clear career plan, in order to be well prepared for the fierce job market that will face the next wave of the ongoing pandemic.

Systematic review of passenger demand forecasting in aviation industry

Forecasting aviation demand is a significant challenge in the airline industry. The design of commercial aviation networks heavily relies on reliable travel demand predictions. It enables the aviation industry to plan ahead of time, evaluate whether an existing strategy needs to be revised, and prepare for new demands and challenges. This study examines recently published aviation demand studies and evaluates them in terms of the various forecasting techniques used, as well as the advantages and disadvantages of each. This study investigates numerous forecasting techniques for passenger demand, emphasizing the multiple factors that influence aviation demand. It examined the benefits and drawbacks of various models ranging from econometric to statistical, machine learning to deep neural networks, and the most recent hybrid models. This paper discusses multiple application areas where passenger demand forecasting is used effectively. In addition to the benefits, the challenges and potential future scope of passenger demand forecasting were discussed. This study will be helpful to future aviation researchers while also inspiring young researchers to pursue careers in this industry.

Evaluating the Impact of the Pandemic Crisis on the Aviation Industry

This paper investigates the intellectual structure of the literature addressing "epidemic/pandemic" and "aviation industry" through a bibliometric approach to the literature from 1991 to 2021. The final count of 856 publications was collected from Web of Science and analyzed by CiteSpace (version 5.8.R1) and VOS Viewer. Visualization tools are used to perform the co-citation, co-occurrence, and thematic-based cluster analysis. The results highlight the most prominent nodes (articles, authors, journals, countries, and institutions) within the literature on "epidemic/pandemic" and "aviation industry." Furthermore, this study conceptualizes and compares the growth of literature before theCOVID-19 pandemic and during the COVID-19 ("hotspot") era. The conclusion is that the aviation industry is an engine for global economics on the road to recovery from COVID-19, in which soft (human) resources can play an integral part.

The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China

This paper applies a three-step framework to quantify COVID-19's impacts on China's domestic and international air travel demand and to evaluate how the impacts evolve from January 2020 to January 2022. Time series techniques and combination forecasting are tested to identify the best-performing model to generate baseline forecasts, with which actual demands are compared to assess the impact of COVID-19. The results demonstrate that during the period under study, China's domestic aviation sector experienced two V-shape recoveries, while its international counterpart was devastated and showed no sign of revival. It suggests that to mitigate the impact of COVID-19, containing virus spread and removing mobility controls are essential; and when travel restrictions are lifted or loosened, governments play important roles in accelerating the rate of demand recovery.

COVID-19 pandemic and air transportation: Summary of Recent Research, Policy Consideration and Future Research Directions

The COVID-19 pandemic can be considered an unparalleled disruption to the aviation industry in the last century. Starting with an at-that-time inconceivable reduction in the number of flights from March 2020 to May 2020, the aviation industry has been trying to navigate through and out of the crisis. This process is accompanied with a significant number of scientific studies, reporting on the direct and indirect impact of the COVID-19 pandemic on aviation and vice versa. This paper reviews the impacts in context of the recent literature. We have collected nearly 200 well-published papers on the subject in the years 2021/2022 and dissected them into a framework of eight categories, built around: airlines, airports, passengers, workforce, markets, contagion, sustainability, and economics. We highlight the essence of findings in the literature and derive a set of future research directions and policy considerations which we deem important on the way towards pandemic-resilient aviation.

The Effects of Diminished Tourism Arrivals and Expenditures Caused by Terrorism and Political Unrest on the Kenyan Economy

The economic development of many countries globally relies heavily on tourism arrivals and spending. Terrorist attacks, political unrest, and other external shocks create disruptions and imbalances that lead to tourism crises with devastating effects on a country’s economy. The paper quantitatively examines the wider economic impacts and welfare effects of a continued decrease in tourism revenues caused by terrorism and political instability on the Kenyan economy. We use a dynamic Computable General Equilibrium model which we calibrate to a 2003 Social Accounting Matrix for Kanya. Our results reveal that a decrease in tourism spending causes a contraction of the economy in the short-term and long-term. Tourism contraction leads to decreased output, prices and wages in urban households, whereas the rural households notice an increase in welfare in the short and medium-term and a decrease in the long-term. Diversification of the tourism product, better branding, crisis management preparations and emphasis on domestic tourism that is less affected by disruption are ways to safeguard tourism in Kenya and beyond.

Health risks of airplane boarding methods with apron buses when some passengers disregard safe social distancing

Many airlines instituted social distancing practices to keep passengers safe during the pandemic. The practices include keeping the middle seats empty, reducing the number of passengers taking an apron bus from the terminal to the airplane, and prescribing that passengers maintain 1 m social distance of separation from other passengers in the aisle while advancing to their seats. However, not all passengers comply with a prescribed 1 m aisle social distance. Through agent-based simulations of passenger boarding when apron buses are used, we examine boarding policies adapted for the pandemic when the level of passenger compliance varies. To compare policies, we consider the duration of time that passengers are too close to other passengers while walking or standing in the aisle. We consider other health metrics from previous research and the time to complete boarding of the airplane. We find that the WilMA–Spread and Reverse-pyramid–Spread boarding methods provide favorable outcomes. Airlines should use WilMA–Spread if their primary concern is the risk to passengers while walking down the aisle and Reverse-pyramid–Spread if they want faster times to complete boarding of the airplane and reduced risk to aisle seat passengers from later boarding passengers. The level of the passengers’ non-compliance with the prescribed aisle social distance can impact a health metric by up to 6.75%—depending on the boarding method and metric. However, non-compliance reduces the time to complete boarding of the airplane by up to 38.8% even though it increases the average time an individual passenger spends boarding.

Exploring the co-movements between COVID-19 pandemic and international air traffic: A global perspective based on wavelet analysis

The travel and tourism industry was one of the fastest-growing industries before the onset of the COVID-19 pandemic. However, to avoid COVID-19 spread, the government authorities imposed strict lockdown and international border restrictions except for some emergency international flights that badly hit the travel and tourism industry. The study explores the nexus between international air departures and the COVID-19 pandemic in this strain. We use a novel wavelet coherence approach to dissect the lead and lag relationships between international flight departures and COVID-19 deaths from January 2020 to September 2020 (COVID-19 first wave period). The results reveal that international flights cause the spread of COVID-19 spread during May 2020 to June 2020 worldwide. The overall findings suggest asymmetries between daily international flight departures and COVID-19 deaths globally at different time-frequency periods due to uncertainty surrounding the COVID-19 pandemic. The study will be conducive for the policymakers to control the upsurge of COVID-19 spread worldwide.

The Impact of the COVID-19 Pandemic on China's Airline Industry

Background

The COVID-19 pandemic has posed a great challenge to the development of China's airline industry. Although the existing literature has analyzed the economic impact of the pandemic on the airline industry from different perspectives, it remains to be further studied given the operating characteristics of different types of airlines in China.

Methods

Using a new perspective of heterogeneous airline service models, this study collects high-frequency data on stock prices on six sample airline companies (including both full-service airlines and low-cost airlines) in China over 519 trading days, from August 1, 2019 to September 15, 2021, and identifies structural change points for each company's stock price using the Quandt-Andrews test. The outcome is used to construct an econometric model to quantify the economic impact of the pandemic on different airlines' stock prices under different structural changes.

Results

All results have passed the Quandt-Andrews test. The impact coefficient of full-service airlines is negative, while that of low-cost airlines is positive. Most of them have passed the test at the significance level of 10%.

Conclusions

All Chinese airlines experienced significant sudden changes in stock prices due to the pandemic, but there are sectoral differences in the order of the sudden changes, with full-service airlines experiencing structural changes much earlier than low-cost airlines. In addition, the impact of the pandemic on stock prices varies across airline types, with a negative impact on full-service airlines and a significant positive effect on most low-cost airlines.

Borrowing Power from Potential Entrants and High-Speed Rail: Entry Pattern of China’s Low-Cost Carrier

This paper investigates the impact of market structure and high-speed rail on China’s low-cost carrier Spring Airlines’ entry patterns during the pre-pandemic period. Dividing the air transport system into discrete distance segments (i.e., short-, medium- and long-haul) helps better reveal critical factors that affect the route entry of Spring. Given the existence of market power in China’s airline industry and the capacity constraints at major airports, Spring strives to enter routes that can accommodate more potential entrants without a strong response from incumbents and are connected with more concentrated or lower-capacity airports. The complementary and competition effects of high-speed rail are well-distinguished in different distance ranges.

Recovering from a Major Aviation Disaster: The Airlines’ Family Assistance Centre

An aviation disaster with mass fatalities can overwhelm an organisation and impact the lives of thousands. The response to such crises can determine the future of the organisation and, more importantly, it can have a lasting effect on the victims’ friends and families. This paper identifies and analyses airlines’ legal requirements and duty of care in relation to the operation of a family assistance centre (FAC). The case study of flight MH370 was used, and interviews with key figures in the aviation industry who have experienced disaster first-hand were conducted. The study highlighted that subtle differences in response significantly impact the quality of care provided. The research also outlined the importance of training and preparedness. Choosing the right people to work in the FACs and to care for friends and families is integral. The study concluded that the speed and accuracy of communication with friends and family are critical factors in the success of any response.

Estimating CO2 emissions from emergency-supply transport: The case of COVID-19 vaccine global air transport

The environmental cost of disaster-related emergency supplies is significant. However, little research has been conducted on the estimation of emergency-supply transportation-related carbon emissions. This study created an "emergency supply emission estimation methodology" (ESEEM). The CO₂ emissions from the global air dispatch of COVID-19 vaccines were estimated using two hypothetical scenarios of one dose per capita and additional doses secured. The robustness of the model was tested with the Monte Carlo Simulation method (MCM) based one-sample t-test. The model was validated using the "Expression of Uncertainty in Measurement (GUM)" and GUM's MCM approaches. The results showed that to dispatch at least one dose of the COVID-19 vaccine to 7.8 billion people, nearly 8000 Boeing 747 flights will be needed, releasing approximately 8.1 ± 0.30 metric kilotons (kt) of CO₂. As countries secure additional doses, these figures will increase to 14,912 flights and about 15 ± 0.48 kt of CO₂. According to the variance-based sensitivity analysis, the total number of doses (population), technology, and wealth play a significant role in determining CO₂ emissions across nations. Thus, wealthy nations' long-term population reduction efforts, technological advancements, and mitigation efforts can benefit the environment as a whole and the CO₂ burdens associated with current COVID-19 and any future disasters' emergency-supply transportation.

Benchmarking the recovery of air travel demands for US airports during the COVID-19 Pandemic

The aviation industry has gone through numerous ups and downs in the past decades. Despite the devastating damage caused by the COVID-19 Pandemic, the aviation industry worldwide still manages to bounce back from the abyss of Q2, 2020, though the speed of recovery is less than satisfactory for most regions. Being aware of the existing literature on air travel demands published since March 2020, this study aims to provide US Primary Hub airports with benchmarks that can help airports predict the recovery of air travel demand during the COVID-19 Pandemic. This study uses the passenger numbers going through airport security checkpoints as the input data and the k-shape clustering algorithm to group airports by their travel demand recovery patterns. The clustering analysis results are presented in a circular dendrogram so that any of the 118 subject airports can quickly locate their benchmarking airports. In this process, the geographic location and hub category of an airport are found to play important roles in determining how local outbound traffic recovers during the Pandemic. We also test if state political preference in the 2020 Presidential Election affects local airport traffic but cannot find any convincing results. The method used by this study can be fed with up-to-date data to produce more timely and reliable results to guide airports and other stakeholders through the recovery journey.

COVID-19 Pandemic—Financial Consequences for Polish Airports—Selected Aspects

The COVID-19 pandemic has reduced the mobility of urban residents on an international level. Tourist air traffic was suspended as one of many activities. As a result, the aviation industry has suffered losses at various levels. In addition to carriers, airports are also suffering due to the effects of the pandemic. Their income comes mainly from charges for take-offs and landings of airplanes, passenger charges, and commercial and restaurant activity. In this paper, the authors attempt to estimate the level of losses incurred by six Polish airports in relation to passenger charges. Based on the data for the years 2015–2019, the forecasts of passenger flows for the year 2020 were estimated using the seasonality indicator method, the method of one-name period trends, and models of linear trends with seasonality. Research has shown that the total losses of the examined airports for the year 2020 amounted to approximately 290 million EUR, and these are losses resulting only from the lack of fees charged for servicing passengers at the airports.

Post-COVID-19 Scenarios of Global Airline Traffic until 2040 That Reflect Airport Capacity Constraints and Mitigation Strategies

Although there has been an unprecedented decline in traffic volume due to the COVID-19 crisis, robust growth in global demand for air transport services in the past means that air traffic is expected to recover in the long term. While capacity constraints are currently not a major topic at airports due to the extremely low levels of traffic, there is growing evidence to suggest that important nodes of the worldwide airport network will struggle to deal with capacity constraints after the recovery. The objectives of this research were therefore as follows: to elaborate long-term global passenger and flight volume scenarios in a post-COVID-19 world; to conduct an empirical and model-based analysis of the impact of limited airport capacity on the future development of air traffic in these scenarios; and to derive general strategies for mitigating capacity constraints at certain international airports. Thus, the main aim of this paper is to present a model-based scenario analysis of the long-term impact of the COVID-19 crisis on the capacity situation for airports. Our results indicate that once the pandemic is over, the capacity crunch will remain on the airports’ agenda for some time.