The airline industry has long faced high financial distress and frequent bankruptcies, with traditional bankruptcy prediction models struggling to provide timely and industry-specific early warning signals. Existing financial models, such as the Altman Z-score and its adaptations, have been widely applied but often fail to capture the unique financial structures and risk factors of airlines. This study introduces a novel two-dimensional financial distress indicator explicitly designed for the airline industry.The proposed model hypothesis-tests and visualizes an airline’s bankruptcy risk using two key financial parameters: the operational ratio (OPR)—calculated as operating expenses divided by operating revenues—and the equity-to-debt ratio (E/D). These metrics are plotted on a two-dimensional graph to illustrate the financial position of airlines over time. To quantify bankruptcy risk, the model integrates the Pilarski bankruptcy score, a logit-based probability model tailored to the airline sector.A dataset of 52 airlines covering the period 2015–2019 is analyzed to evaluate the effectiveness of the model. The results highlight distinct financial patterns: airlines with lower operational ratios and higher equity-to-debt ratios tend to exhibit greater financial stability, whereas highly leveraged carriers with poor operational efficiency show a significantly higher probability of bankruptcy. The model successfully differentiates between financially robust and distressed airlines, demonstrating a clear visual representation of financial trajectories.Comparative analysis across U.S. and European airlines reveals key industry trends. U.S. low-cost carriers (LCCs) tend to maintain stronger financial positions, while European carriers display a wider variation in financial health. Airlines such as Delta and British Airways emerge as strong performers, whereas carriers with excessive leverage, such as American Airlines, show elevated financial risk for the period studied.Unlike traditional bankruptcy models, which often provide only static, one-year-ahead reliable predictions, this approach allows for dynamic time-path analysis. By tracking an airline’s financial evolution, managers can take proactive corrective actions to improve financial performance. This model also facilitates competitive benchmarking, enabling industry stakeholders to assess an airline’s position relative to its peers.Overall, the proposed two-dimensional financial distress indicator provides a practical, visual, and industry-specific tool for assessing airline financial health. It enhances traditional bankruptcy models by incorporating a clear temporal dimension, allowing for improved decision-making and risk management by the airlines and bankers.

Freighter aircraft play a critical role in shaping the spatial organisation of global air cargo flows, yet existing research offers limited insight into their network structure and temporal behaviour. Prior studies rely heavily on annual snapshots, regional analyses, or integrator-focused data, leaving the dynamics of general cargo carriers largely unexplored. This paper addresses these gaps by constructing the Worldwide Freighter Network (WFN), a unique global dataset covering 327 consecutive weeks (2018-2024) and including both scheduled and charter operations for 24 major freighter airlines. Using a temporally granular network framework, we examine how freighter connectivity patterns persist, reconfigure, and concentrate across space over time. We analyse the evolution of freighter networks at both global and airline levels, providing the first temporally granular, airline-specific analysis of global freighter network dynamics. The results reveal a persistent shift toward greater spatial concentration and gateway dominance after the COVID-19 shock, indicating a structural reorganisation of the global air cargo system rather than a temporary disruption. Beyond this system-wide transition, airline-level analysis reveals substantial heterogeneity in network design, routing logic, and temporal stability, underscoring that global connectivity patterns obscure diverse carrier-specific strategies. Overall, the findings highlight the importance of spatio-temporal resolution for interpreting the spatial structure, resilience, and evolution of global freight transport networks as well as for individual airlines.

This paper presents a constrained calibration framework that reconstructs itinerary-level air cargo flows by disaggregating Origin-Destination (OD) demand across feasible road-air routing options under behavioral and operational assumptions. The model integrates observed leg-level payloads with detailed supply attributes, such as airline network structure, flight schedules, aircraft capacities, and first- and last-mile road-feeder services, to capture hub roles, carrier strategies, transshipment constraints, and catchment area effects. For each OD pair, we generate choice sets of feasible itineraries subject to transfer rules, hub sequencing, airport geography, and journey-time bounds. Itinerary attractiveness is determined by a constant-elasticity term that combines generalized time and schedule depth, and flows are assigned using an attractiveness-based allocation, while ensuring routing feasibility and capacity limits are enforced. Calibration is posed as a scalarized dual-objective non-linear optimization that balances accuracy in observed leg loads (via absolute deviation penalties) against over-allocation of capacity (via hinge penalties), yielding capacity-consistent reconstructions at the network scale. Applied to a large real-world schedule and capacity snapshot, the framework reproduces realistic leg loads and itinerary patterns, delivering interpretable insights, including load factors, hub throughput, transit-time distributions, indirect routing, catchment areas, and network imbalances. In practice, the model functions as a demand-to-itinerary disaggregation layer that (i) can feed downstream optimization, emissions inventories, and policy analysis, or (ii) can be embedded within a joint network-design loop in which capacity, timing, and disaggregation co-evolve. Validation against publicly available leg-level data and robustness analyses support the approach. In the absence of itinerary-level ground truth, results are interpreted as model-implied, feasibility-consistent reconstructions for decision support and scenario testing (e.g., capacity shocks or schedule changes).

Although airports increasingly reference the Sustainable Development Goals (SDGs), how these goals interact within airport sustainability strategies remains insufficiently explored. This study addresses this gap by systematically analyzing SDG interlinkages in the sustainability disclosures of 150 of the world’s busiest airports, representing over 60% of global passenger traffic. Using a structured three-phase analytical framework comprising co-occurrence analysis, hierarchical clustering, and network analysis, the study identifies dominant priorities and structural misalignments in current strategies. Airports most frequently align with SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure), and SDG 11 (Sustainable Cities and Communities), reflecting a prevailing emphasis on economic and urban development. Co-occurrence analysis confirms these patterns but also reveals significant trade-offs, particularly between SDG 8 and SDG 13 (Climate Action), highlighting persistent tensions between growth objectives and environmental responsibility. Hierarchical clustering isolates SDG 8 in a standalone group, illustrating the sector’s ongoing “growth versus sustainability” paradox. Network analysis identifies SDG 7 (Affordable and Clean Energy) and SDG 4 (Quality Education) as bridging goals capable of connecting fragmented sustainability domains. The findings support targeted interventions such as sustainability-linked finance, emissions-based investment, and unified reporting, to help airports transform sustainability from a compliance obligation into a driver of value creation.

The aviation industry has undergone significant transformation due to the adoption of self-service technology (SST), which aims to enhance operational efficiency and passenger experience. This study aims to understand the key factors contributing to the successful adoption and usage of self-service check-in kiosks. We examine how flow experience and user acceptance are influenced by perceived performance expectancy, effort expectancy, social influence, and facilitating conditions within the context of Soekarno-Hatta Airport. The study employs an electronic questionnaire and partial least square structural equation modelling (PLS-SEM) to analyze the data. The results indicate that social influence and facilitating conditions significantly enhance flow experience, which positively influences passengers’ intention to continue to use SST. These findings contribute to the theoretical expansion of the unified theory of acceptance and use of technology (UTAUT) model by integrating the concept of flow experience and providing practical insights for enhancing passenger engagement and satisfaction through SST in airports.

This study analyses and compares the economic impact of Belgium's five commercial airports on their region and country. The airports represent different types, including Belgium's main airport, Brussels Airport and four regional airports: a low-cost regional airport (Brussels South Charleroi Airport), a specialised cargo regional airport (Lie`ge Airport), and two small regional airports (Antwerp Airport and Ostend-Bruges Airport). The economic impact is measured through input-output analysis, which assesses added value and employment on a direct, indirect, and induced level. To improve accuracy, we employ a bottom-up approach that links company-level employment and added value data to the input-output framework via NACE classifications. Additionally, a Monte Carlo sensitivity analysis is introduced to strengthen the robustness of our findings. Our results demonstrate significant differences in the airports' economic contributions based on airport size and operational focus, with Lie`ge Airport's cargo specialisation generating a particularly strong regional impact. These findings lead to a broader discussion on airport subsidies based on the economic impact. Beyond the Belgian context, our bottom-up approach provides a replicable framework for more precise airport impact assessments.

Accounting for 50 % of European airports and 30 % of European traffic, regional airports are vital to the aviation sector. However, their diverse characteristics and operational challenges complicate the development of effective business and management strategies. Given the increasing financial and environmental pressures on regional airports, the aim of this paper is to understand the differences between well-performing and underperforming types of regional airports in order to effectively tailor regional airport business and management strategies. This study applies latent profile cluster analysis to categorise regional airports in Western Europe based on operational characteristics, financial performance, environmental initiatives, and external factors such as geographical context, competitive dynamics, and ownership structure. The analysis identified four distinct categories, including (1) leading regional airports that serve over five million passengers and excel in financial performance, diversified airline partnerships, and sustainability commitment; (2) small regional airports that handle fewer than three million passengers and typically rely on public funding to maintain services. They are further divided into remote/rural and non-remote subcategories; (3) challenged low-cost regional airports, marked by a high share of low-cost carrier movements, that face intense competition and financial instability; and (4) specialised cargo airports that focus primarily on freight operations but face unique operational challenges. The clusters offer practical implications for stakeholders regarding opportunities and challenges faced by different regional airport types. For instance, airport operators can use the clusters as a basis to benchmark performance and tailor strategies concerning, e.g., cost optimisation and airline partnerships. Policymakers could consider targeted public support for remote/rural small regional airports and further investigate the relationship between ownership structures and financial efficiency.

This study represents the first in-depth analysis of the global airport industry's compliance with the Sustainable Development Goals (SDGs), assessing the SDG alignment of the world's 150 busiest airports across 48 countries, which collectively account for approximately 60% of global air traffic in 2019. We discovered a 42% overall alignment with the SDGs, illustrating the aviation sector's relatively slow incorporation of green technologies and sustainable practices, especially when contrasted with industries such as Oil and Gas (O&G), and banking. Notably, a subset of 23% of airports demonstrates high alignment, characterized by implementing targeted SDG actions and establishing comprehensive monitoring and evaluation frameworks, indicating a significant, albeit challenging, shift toward sustainability. Our analysis also pinpoints that airports in Europe and those handling larger passenger volumes exhibit more substantial alignment, attributing this to the influence of Europe's stringent sustainability regulations and the prioritization of passenger-focused operations on enhancing SDG commitments. Conversely, an airport's alignment with the SDGs is not significantly predicted by its host country's national SDG scores, suggesting that regional sustainability pressures exert a more direct influence on airport practices than national achievements. These findings lead to recommendations for standardizing SDG reporting and developing specific metrics for tracking progress at airports, alongside advocating for governmental and international entities to establish regulatory frameworks, financial incentives, and certification programs to enhance global aviation sustainability.

This paper aims to identify gaps in the literature and present a future research agenda for investigations on regional airports. The research topics appearing from the systematic literature review are linked to the roles that regional airports have held and currently hold. In this way, challenges and research gaps that deserve extra attention are identified. Moreover, the paper deals with one of the most pressing research gaps, the definition of a regional airport. The literature and accompanying industry review reveal a diverse use of the term regional airport, and ACI Europe (2017) and the European Parliament (2021) even indicate that there is currently no definition for a regional airport in Europe. To address future research and challenges of regional airports in a more unified and structured manner, a proposal is made to capture the term ’regional airport’ based on objective criteria. With the dual outcome of possibilities for future research and a proposal for a common use of a definition of regional airports, we aim at a more coordinated and impactful progress in research concerning regional airports.

This paper studies the connectivity of European airports and their impact on regional development, measured by employment. It uses flight schedule data for 207 NUTS-2 regions from 2012 to 2019 in a network analysis. Statistical analysis shows that the degree grew steadily, while the shortest and quickest path connectivity decreased significantly in 2019. Moreover, the panel data analyses indicate that degree consistently positively impacts employment, whereas the significance of the shortest and quickest path's impact is less consistent, indicating that focusing on increasing a region's number of distinct edges might be most effective in stimulating regional development.

This paper estimates and analyses the air cargo demand and supply imbalances between large geographical regions based on newly collected demand and supply data. Due to the need for more data for academics and the industry, and the lesser research interest compared to its passenger counterpart, limited empirical research on air cargo market dynamics has been conducted. Live flight and aircraft data were collected for five consecutive years to reconstruct the air cargo network and capacity. Air cargo sales tonnes data were collected and introduced as these data eliminate double counting of transfer route volumes. Both datasets were used and compared to analyse the air cargo trade imbalances. The major findings indicate an imbalance in demand on most of the 110 studied region pair combinations. The supply data indicate a high imbalance for freighter capacity, a relatively smaller imbalance for integrator capacity and a limited imbalance for the wide-body belly capacity. The data indicate that the Middle East, Northeast Asia, Russia, Central Asia, and Central America regions are all transfer or in-transit regions where a large amount of cargo passes through. However, limited cargo volumes originate or find their final destination here. Although the general assumption indicates that air cargo supply follows air cargo demand, imbalances between demand and supply in opposing directions were found for several region pairs. To the best of our knowledge, this paper is one of the first academic sources to introduce data analysis based on sales tonnes. This research assists academics and the industry in getting a better understanding of the current air cargo market dynamics. It also provides a base to enhance future air cargo market research, analysis and forecasting.

This paper proposes a holistic definition of airport sustainability comprising social, economic, operational, and environmental dimensions. Methodologically, a composite indicator approach is applied to build the Airport Sustainability Evaluation Index (ASEI), which aims to benchmark airports' sustainability performance across the four dimensions. To justify the issue of subjectivity in composite indicator building, two different methods are used in each of the normalization, weighting, and aggregation processes. Consequently, this forms eight composite indicator building schemes. Then, a variance-based sensitivity analysis, average shift in ranking (ASR), and Cronbach's alpha test are performed to examine the sensitivity and reliability among the eight schemes. Schiphol airport is selected as a demonstration to validate the ASEI with its data from 2012 to 2021 as inputs. The results reveal a significant consensus among the eight schemes in identifying the outstanding and bottom performers across the analyzed period. Additionally, weighting is found to be the most influential composite indicator building process. Further, the scheme with the most significant contribution to the result reliability found in this paper is re-scaling as the normalization method, Benefit-of-the-doubt (BoD) as the weighting method, and Non-compensatory multi-criteria approach (NCMC) as the aggregation method.

Objectives. General aviation (GA) safety has become a key issue worldwide and pilot errors have grown to be the primary cause of GA accidents. However, fewer empirical studies have examined the contribution of management and organizational factors for these unsafe acts. Flawed decisions at the organizational level have played key roles in the performance of pilots. This study provides an in-depth understanding of the management and organizational factors involved in GA accident reports. Methods. A total of 109 GA accidents in China between 1996 and 2021 were analysed. Among these reports, pilot-related accidents were analysed using the human factors analysis and classification system (HFACS) framework. Results. The significant effects of managerial and organizational factors and the failure pathways on GA accidents have been identified. Furthermore, unlike traditional HFACS-based analyses, the statistically significant relationships between failures at the organizational level and the sub-standard acts of the pilots in GA accidents were revealed. Conclusions. Such findings support that the GA accident prevention strategy that attempts to reduce the number of unsafe acts of pilots should be directed to the crucial causal categories at HFACS organizational levels: resource management, organizational process, failure to correct a known problem, inadequate supervision and supervisory violations.

The air transport industry is a competitive and volatile market, creating a challenging operating environment for both airports and airlines. While airline market structures are rapidly changing, airports are in a continuous need to improve their technical efficiency. Therefore, in this paper, we examine the effect of airline dominance on airport technical efficiency. Previous research is contributed by examining this effect on a balanced panel dataset of medium-sized European airports while considering the effect of the macro-environment, ownership, belonging to an airport group, and the network structure of the dominant carrier (LCC or FSC). Results demonstrate a significant positive relationship between airline dominance and the airport's technical efficiency. The paper has an important policy implication as it highlights the importance of taking into account efficiency effects at airports when evaluating airline consolidation cases.

Understanding customer behaviour is critical to retaining loyal customers and attracting new ones when considering an airline brand. Most airlines have frequent-flyer programs (FFPs) meant to entice passengers' decisions regarding airline brand choice. However, the determinants of the attitudes toward FFPs and their effect on airline brand choice are not well documented. This study examined the influence of airline brand awareness and perceived quality on travellers' attitudes towards frequent-flyer programs and airline brand choice. Furthermore, the study investigated whether the attitudes towards FFPs indirectly (moderates) influence the causal relationship between airline brand awareness and brand perceived quality on airline brand choice. Social Exchange Theory (SET) guided the study. An explanatory research design was adopted. Primary data was sourced through the deployment of a structured online survey. Confirmatory factor analysis, composite reliability, and Cronbach alpha coefficients were assessed to determine discriminant validity and reliability of the measurement instrument. Afterwards, Pearson's correlation, simple linear, and multiple hierarchical (step-wise) regression models are estimated to test the conceptualised model using SPSS 27 software. The findings indicate that airline brand awareness and perceived quality influence travellers' attitudes towards FFPs and airline brand choice. Moreover, attitudes towards FFPs positively influence airline brand choice. Additionally, attitudes towards FFPs have a conditional (moderating) effect on the relationship between airline brand awareness and airline brand choice and between airline brand perceived quality and airline choice. The results indicate that high attitudes toward airline FFPs equate to higher airline brand choice despite low airline awareness or even when the airline's quality perception is evaluated as inferior. The findings of the study have significant theoretical and managerial implications.

Addressing a significant gap in the literature, this study commences with a dual focus: assessing sustainability evaluations, both within the airport sector and across a broader range of industries. Through a comprehensive review of 33 academic articles specific to airport sustainability, we delve into a detailed analysis of 16 papers that implement specific methodologies for assessing airport sustainability performance. These methodologies are compartmentalized into three primary categories: Data Envelopment Analysis (DEA) and its extensions, Hybrid Multiple-Criteria Decision Making (MCDM), and composite index-based assessments. A meta-review extending beyond the airport sector uncovers common issues across industries, including the absence of universally adaptable sustainability frameworks and an overemphasis on assessment, overshadowing the essential role of sustainability accounting. Our findings underscore the need for a paradigm shift from pure evaluation towards a holistic approach to sustainability modeling. With systems thinking at its core, this approach allows a better grasp of the complex interactions and feedback loops within sustainability systems and provides a strategy to tackle inherent trade-offs and compensatory effects. By exposing gaps in current practices, this study paves the way for future research, particularly the integration of systems thinking with MCDM, promising to enrich sustainability evaluation and management methodologies, ultimately facilitating more sustainable airport operations.

Since 1987 different countries have commercialized or privatized their national air navigation service provider. The Single European Sky Initiative initiates further market liberalization and structural reforms. This chapter discusses the impact of the commercialization wave on the different stakeholders. The main finding is that commercialization and privatization are insufficient yet often necessary to achieve economic welfare gains. Implementing a proper regulatory framework, however, remains vital.

This chapter analyses the studies of the National Bank. Case studies such as this provide insight into how countries apply methodologies to measure economic impact of aviation and hence might be used as inputs for similar studies in other countries. The multiplier for value added equals 1.81, implying that 1 of value added generated directly by companies operating in air transport or airport activities generates 1.81 via the intersectoral links between these companies and companies upstream and downstream in the air transport value chain. Therefore, in order to put the studies by the NBB in perspective, this section will focus on analysing the noise impact of the largest airport in Belgium, Brussels Airport. Total value added by air transport and airport activities in Belgium amounted to more than 6 billion in 2015, growing at an annual average rate of 7.5 per cent between 2013 and 2015.

This paper proposes a business model typology based on factor analysis of mixed data sourced from the 2016 Air Traffic Management Cost Effectiveness (ACE) benchmarking report, European air navigation service provider (ANSP) websites and annual reports. It provides ANSP management insight into the key strategic business model decisions to be made, their resulting models as well as how these business model decisions contribute to ATM/CNS profits. The findings suggest that ANSPs can benefit from increasing both their level of corporatisation as level of outsourcing. The paper can be used by ANSP managers to position themselves within the European air navigation services (ANS) landscape and as a discussion starter for future business model developments; or by ANS customers to better understand the strategic objectives of the ANSPs.

This paper assesses the existence of economies of scale and cost complementarities in the European air navigation services (ANS) industry to provide policymakers and air navigation service providers (ANSPs) insight into the economic viability of possible industry-led consolidation and unbundling opportunities. While previous studies using parametric methods made abstraction of the multi-product nature of the ANS industry, this paper tries to fill that gap by estimating a stochastic multi-product translog cost frontier. The existence of economies of density and scale is evaluated from the estimated cost frontier at the sample means as well as for individual ANSPs in the panel. The results suggest that during the period from 2006 to 2016 the European ANS industry faced economies of density and produced at constant economies of scale in the sample means. However, cost complementarities do not seem to be present.