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The impact of the COVID-19 pandemic is unprecedented in airline history, with irregular flight bans, the inability for accurate demand estimation, several turns in the epidemiological evolution, and a wide range of downstream effects on all aviation stakeholders. While most airlines have increasingly entered a recovery stage, compared to the utmost disruption around April 2020, the airline business is far from back-to-normality. Throughout the past two years, recurrent statements have been made regarding the existence of so-called ghost flights, where airlines operate nearly empty aircraft on markets with insufficient demand, partially with the aim to avoid losing precious airport slots. This study investigates the extent of such abnormal market service during the COVID-19 pandemic through an explorative, data-driven analysis, based on actual load factor data of European airlines for the years 2017 to 2021. We break down the observed deviations by airlines, markets, and airports. We find that low-cost carriers are most-likely to have performed abnormal flights during the pandemic; and that abnormal flights have mostly occurred on frequently-served markets. In addition, we show that airline responses, in terms of departure and yield changes, are largely heterogeneous across the 24 airlines in this study. Our study is the first one to shed light on the important issue of load factor deviations, and we hope that our findings can contribute to a better understanding of the existence of abnormal flights during the pandemic, as well as deriving appropriate policies for dealing with the ubiquitous threat and impact of ghost flights in the future. • Ghost flights were ubiquitous threats during the COVID-19 pandemic. • Abnormal market service of European airlines for the years 2017 to 2021 is investigated. • Low-cost carriers are most-likely to have performed abnormal flights during the pandemic. • Such abnormal flights have mostly occurred on frequently-served markets. • Towards the end of 2021, the effect of abnormal flights has almost vanished. [ABSTRACT FROM AUTHOR]

Depopulated regions face declines in traffic demand for airline service. The airline network in Hokkaido, Japan, plays an important role in the regional economy, healthcare, and sightseeing. Toward maintaining this airline network, the "bundled privatization" of airports has been discussed. Under such a system, several airports are privatized as a package for management by a single company. This study proposes a model for analyzing the behaviors of airport operators, airline companies, and passengers when bundled privatization is introduced to an airline network. Under bundled privatization, an airport management company can determine the landing fees of all airports such as to maximize the profits of all its airports, while an airline company can determine its service frequencies and aircraft sizes such as to maximize its profit. As a result of these two profit-maximization behaviors, an equilibrium state is obtained. The proposed model is applied to the airline network in Hokkaido, and the results of numerical calculations are discussed. • We discussed the impact of the bundled airport privatization on the airline network. • We modeled the behaviors of users, airport managers, and airline companies. • The airport managers decide the landing fees of their airports under the bundled privatization. • The airline companies decide the service frequencies and aircraft sizes. • The numerical calculation is performed in the airline network of Hokkaido as an example. [ABSTRACT FROM AUTHOR]

Following several decades of growth, COVID-19 has confronted the aviation industry with an unprecedented drop in demand. As airports are forced to focus on business continuity and crisis recovery, the question arises as to whether they should re-evaluate growth projects. In the short term, whilst the industry focuses on traffic recovery, most airports will be required to pause or reconsider longer-term growth projects involving major new infrastructure. The authors find that opportunities can still exist for airports to proceed with capacity growth projects — even considering the current crisis. Their comparatively low complexity, cost and lead times make capacity interventions involving process and technology enhancements viable alternatives or precursors to physical infrastructure interventions. By referring to a redefined purpose and integrated growth definition, the authors also identify opportunities for airports to continue investing in organisational growth, revenue growth and sustainable growth. This opinion piece further explores critical growth enablers, including customer centricity, change management and collaborative value creation. As airports continue to invest in these growth projects, the industry builds the resilience to overcome this latest crisis, and to thrive in future ones. This paper discusses opportunities for airports to continue investing in capacity growth, albeit with increased focus on targeted process and technology interventions. [ABSTRACT FROM AUTHOR]

Community detection in a complex network is an ongoing field. While the air transport network has gradually formed as a complex system, the topological and geographical characteristics of airline networks have become crucial in understanding the network dynamics and airports' roles. This research tackles the highly interconnected parts in weighted codeshare networks. A dataset comprising ten major international airlines is selected to conduct a comparative analysis. The result confirms that the clique percolation method can be used in conjunction with other metrics to shed light on air transport network topology, recognizing patterns of inter- and intra-community connections. Moreover, the topological detection results are interpreted and explained from a transport geographical perspective, with the physical airline network structure. As complex as it may seem, the airline network tends to be a relatively small system with only a few high-order communities, which can be characterized by geographical constraints. This research also contributes to the literature by capturing new insights regarding the topological patterns of the air transport industry. Particularly, it reveals the wide hub-shifting phenomenon and the possibility of airlines with different business models sharing an identical topology profile. [ABSTRACT FROM AUTHOR]

In the real word, the decision maker may want to use revenue and cost eficiency analysis for existing units compared to virtual units, traditional DEA models can no longer be used and FDH models must be used to evaluate the efficiency of decision-making units. In this paper, we develop the revenue and cost efficiency models based on the FDH model and obtain the efficiency scores based on pair wise comparisons. In the following, we will develop the proposed models for the two-stage network structure and obtain the desired scores of inputs and outputs by considering the input and output prices. An algorithm for measuring the revenue and cost efficiency is presented based on the ratio of inputs and outputs. Finally, we use the proposed algorithm to evaluate the efficiency of 13 airports in Iran with a two-stage network structure without considering the constraint of convexity and present the results of the research. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused by SARS-CoV-2 dominated the year 2020 and has an unprecedented impact on global air transport. This paper tries to make an overall review on the interaction of air transport and the COVID-19 pandemic. Although the confirmed cases were first reported in China, the origin of the pandemic remains uncertain. China was the first country to control the COVID-19 pandemic, and domestic air traffic recovers at a fast pace. Compared to 2019 level, world scheduled capacity, passengers carried, and revenues for 2020 were reduced by 50%, 60%, and $371 billion, respectively. Compared with domestic passenger traffic, international passenger traffic reduces more seats, passengers, and revenues. Because air transport contributes to economic growth, many countries or regions provide aviation bailout. The US provides most direct aid, while China mostly provides policy measures. In the post-COVID-19 period, IATA suggests that accepting vaccinated passengers is the best practice to reopen borders. Air cargo will play an important role in the distribution of COVID-19 vaccines. Meanwhile, air transport should be more digitalized, sustainable, and responsible in the future. [ABSTRACT FROM AUTHOR]

Dynamic pricing is a modern tool of railways, airline and bus transportation companies that aims at the revenue increase due to timely passenger demand accounting and successive adjusting ticket prices. From the passengers' side, it is therefore useful in these dynamic settings to decide when it is better to buy the desired ticket in order to save money. It brings one to the problem of forecasting ticket dynamic prices. This problem is usually solved by using historical price data and the chosen train/airplane/bus departure features (e.g. the number of days before the departure and the departure week day) as predictor variables. The purpose of our study is to investigate whether search engine query open data can improve the ticket price forecast quality for statistical and artificial neural network-based models. Our experiments with the Spanish Renfe Railways dataset and certain train ticket-related search engine query data from Google Trends show that this is indeed so for railway ticket dynamic prices. [ABSTRACT FROM AUTHOR]

• The first implicit measure for traffic climate was developed. • Both implicit and explicit measures were used to examine the relationships. • People hold different implicit and explicit attitudes towards traffic climate. • Implicit measure of functionality was related to positive driver behaviors variance in lane positioning. Traffic climate is about the road users' attitudes towards traffic context and it is assumed that perceived traffic climate might influence drivers' behaviors. In the literature, traffic climate was measured only by using self-report questionnaires. People might give biased responses to self-report measures due to social desirability. The aim of the current study was to develop the first implicit measure for traffic climate. In addition, both implicit and explicit attitudes towards traffic climate and their relationships with self-reported driver behaviors and outcomes of simulated driving were investigated in a young Turkish driver sample. According to the results, implicit measure of functionality was positively related to positive driver behaviors and negatively related to variance in lane positioning. Based on the findings, it can be suggested that drivers might have different implicit and explicit attitudes towards traffic climate. Additionally, it might be suggested that young drivers might need more experience to form stable attitudes towards traffic context. Interventions to change people's attitudes towards traffic climate to improve road traffic safety might be more effective if stated differences are taken into consideration. [ABSTRACT FROM AUTHOR]

The objective of this contribution is the application of a new methodology for assessing connectivity in passenger transport regarding selected tariff points accessibility in the context of developing the selected region. From the passenger's point of view, it is necessary to specially assess the accessibility of lines within transportation, between the selected destinations using passenger air transport. The length of the travel time, the number of necessary transfers and the number of travel opportunities affects the possibilities of transport between place A and B. The connections and lines are thus influenced by many factors. This is the basic point to consider when designing a set of evaluation criteria for assessing the connectivity and in carrying out a case study for a specific region. In this paper, Václav Havel Airport in Prague (Czech Republic) with selected air transport connections were evaluated according to the proposed methodology. [ABSTRACT FROM AUTHOR]

This article presents a response from the author to comments made on his paper "The Rise and Demise of PATCO." According to the author, the thesis of his article is that the strike was the result of the organization's plan to privatize its relations with the U.S. Federal Aviation Administration (FAA). FAA is the public sector employer of the Professional Air Traffic Controllers Organization. Other contributing factors were the weak response of the federal government and the failure of PATCO leadership to understand the changing political and economic environment of 1981.

The article mentions Washington National Airport and Dulles International Airport with a focus on solving the problems of safety and traffic flow at major airports in the United States. Solutions to airport congestion include expanding peak-load capacity by building more airports, improving air traffic control by implementing the National Airspace System, and allocating landing and flight space by fiat rationing. The locational dimension of traffic patterns, passengers' preferences, role of ticket prices in relation to airport use, effect of price differentials on distribution of demand, recommendations of the Federal Aviation Administration (FAA), and the FAA Bureau of National Capitol Airports are mentioned.

The transportation sector accounts for 61.5% of global oil consumption and is responsible for 29% of the world's total energy demand. Passenger transportation utilizes around 50%–60% of the energy used for transportation-related activities. Accurate prediction of future transportation energy consumption is essential for governments to make well-informed decisions regarding transportation infrastructure development and utilization, which supports the United Nations' Sustainable Development Goals (SDGs) and advances the shift to a net-zero carbon economy. With the expected increase in population, vehicles, and economic growth, it is essential to predict the energy demand to ensure sustainable urban transportation. This is crucial not only for economic prosperity but also for promoting human health and mitigating carbon emissions. Therefore, transportation energy demand prediction plays a vital role in designing sustainable future urban transportation and making informed energy investment and policy decisions. This study proposes a novel methodology and investigates for the application of machine learning stacking ensemble method with hyperparameter tuning and multicollinearity removal to predict transportation energy demand in Turkey based on historic data from 1975–2019. The dataset includes GDP, year, vehicle miles traveled, population, oil price, passenger miles traveled, and ton-miles traveled as features. A performance evaluation and comparison of 19 machine learning algorithms is first carried out to find the best candidate for the stacking ensemble models, including eXtreme Gradient Boosting algorithm. This performance comparison uses all features and also only two of them during the training phase, and it takes into consideration a 4-fold cross-validation. A combination of permutation importance and hierarchical clustering algorithm on the Spearman rank-order correlations is used for dimensionality reduction of the dataset. Extra Tree Regressor and ADABoost Regressor, which are both placed in the second level of the suggested models, are two meta-regressors that are proposed for stacking ensembles because they perform better compared to single machine learning algorithm. In total, eight stacking ensemble models – four for each of the meta-regressors – were developed and investigated considering all features and only two of them separately. Six metrics – R-squared, MSE, MAE, RMSE, RMSLE, and MAPE – are used to assess all models. The Extra Trees Regressor can be used as a meta-regressor in the best proposed stacking ensemble model to predict the energy demand for transportation. This model achieves an R-squared value of approximately 0.99 when all the features are taken into consideration. When only two features from the dataset are considered the same stacking ensemble model can achieve an accuracy of 0.98. These findings have the potential to contribute to the development of more accurate models and results, which can, in turn, lead to improved strategies for managing future transportation energy demand. Additionally, this research can support the advancement of alternative technologies that promote sustainable urban development, ultimately helping to move towards a net-zero carbon economy. • Novel methodology for predicting transportation energy using stacking ensemble. • Evaluation of 19 ML algorithms and development of 8 stacking ensemble models. • Vehicle-Km and Oil-Price significantly impact energy predictions. • Hierarchical clustering and permutation importance for multicollinearity removal. [ABSTRACT FROM AUTHOR]

The purpose of this study is to contribute to the general understanding of air transport organization and creation of air interactions in view of three issues - distance, integrity and hierarchy. Although these issues are generally known from literature, they were not properly studied in the case of air transport. Therefore, the article brings a new perspective on the issue of air transport evaluation, the delimitation of functional regions based on air transport interactions, and the evaluation of their hierarchical organization. We analyze the database of flights between civil airports in Central Europe. We specify hinterlands of individual airports by using the modified version of Reilly's gravity law. The main results of this study confirmed the dominance of main airports (mainly Frankfurt and Vienna), while confirming a relatively large autonomy of airports localized in the former socialist countries (Warsaw, Prague). [ABSTRACT FROM AUTHOR]

This paper discusses the reasons behind the success of Airbnb and provides a brief analysis of their business model. The possible revenue effect on the hotel industry is discussed as well as some suggested strategic measures that hotels may consider for successfully competing in the rapidly changing market for holding their fair share of accommodation demand. [ABSTRACT FROM AUTHOR]

Airport accessibility is an important criterion for airport competition. The relevance of airport accessibility and airport competition was studied in this paper based on the panel data collected from nine large airports in Jiangsu province, China from 2005 to 2014. The results showed that the cost of expense, time and fatigue for the arrival at the airport are proposed to quantify levels of fastness, economy and amenity for the passengers to arrive at airport. The airport accessibility is significantly affected by airport passenger traffic and airline frequency. The passenger traffic can be increased by 2% with 1% increase of airport accessibility based on the analysis results of the nine large airports in Jiangsu province. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to determine the key factors affecting passengers' domestic airline choice in Turkey. This study utilized the data of a self-administered survey conducted to 2473 passengers in 11 different airports. The data were analyzed using multinomial and mixed logit (ML) models. The analysis results reveal that ML model is useful to explain preference heterogeneity of passengers' airline choice behavior. The estimation results also indicate that several demographic, socio-economic, and travel destination characteristics were found as the significant drivers of passengers' airline choice. The results of this study may be a valuable tool for policy-makers in the airline industry. [ABSTRACT FROM PUBLISHER]

In this article, we examine how European authorities have responded to reported threats to aviation resulting from individual terrorist tactics. We do so by applying the notion of political resilience and drawing on Palonen's “policy, polity, politicking, and politicization” model as well as on Malcolm Anderson's concept of “politics of the latest outrage.” We argue that the European Union response to aviation terrorism has created polity transformation and generated a long list of new policies but has also in the process become politicized and subject of politicking, with some high-profile measures being criticized for having a deleterious impact on passengers' rights. [ABSTRACT FROM PUBLISHER]