Journal of Air Transport Management最新文献

{"title":"Implementation of Karolinska sleepiness scale to improve pilots awareness and confidence in fatigue reporting","authors":"Patrick Mullan,&nbsp;Viktoriia Ivannikova","doi":"10.1016/j.jairtraman.2026.102982","DOIUrl":"10.1016/j.jairtraman.2026.102982","url":null,"abstract":"<div><div>Fatigue among pilots in short-haul, multi-sector night freight operations remains a critical challenge to aviation safety. Irregular schedules and prolonged exposure to the Window of Circadian Low (WOCL) cause cognitive impairments, slower reaction times, and reduced situational awareness. Despite regulatory frameworks such as Fatigue Risk Management Systems (FRMS), cultural and organisational barriers, including fear of punitive action and lack of standardised tools, continue to limit effective fatigue reporting. This study investigates the use of the Karolinska Sleepiness Scale (KSS) as a subjective fatigue management tool in short-haul night freight operations. A mixed-methods approach was applied, combining a six-week survey with semi-structured interviews. The study provides the first systematic evaluation of the KSS not only as a fatigue measurement instrument but also as a communication tool that bridges the gap between pilot experience and FRMS reporting practices in short-haul night freight operations. Pilots used the KSS during operational duties to assess fatigue levels and evaluate its influence on awareness and reporting practices. Findings indicate that the KSS improves pilots’ ability to recognise and communicate fatigue, supports proactive workload management, and fosters collaboration within crews. However, organisational gaps remain, including the absence of integration into Standard Operating Procedures (SOPs), lack of structured training, and hesitancy among less experienced pilots without formal company endorsement. The study recommends the formal adoption of the KSS into SOPs, supported by recurrent training and feedback mechanisms, together with integration of objective measures such as biometrics. Results highlight the potential of the KSS as a cornerstone of fatigue risk management and emphasise the importance of supportive safety cultures in prioritising pilot well-being as a key component of operational safety.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"134 ","pages":"Article 102982"},"PeriodicalIF":3.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of China’s intercontinental air network affected by the COVID-19 pandemic and geopolitical disruptions","authors":"Weichen Peng ,&nbsp;Weicheng Wang ,&nbsp;Xueyan Bai ,&nbsp;Xiangru Wu","doi":"10.1016/j.jairtraman.2025.102963","DOIUrl":"10.1016/j.jairtraman.2025.102963","url":null,"abstract":"<div><div>This study investigates the heterogeneous responses of Chinese and foreign airlines to the compound disruptions from the COVID-19 pandemic and geopolitical tensions, focusing on the restructuring of China’s international direct air transport network. Utilizing airline-route-level data from 2019 to 2024, the research employs a probit model to analyse route service decisions in the China–North America and China–Europe markets. The empirical findings reveal divergent recovery patterns shaped by distinct underlying drivers. In the China–Europe market, Chinese airlines, benefiting from sustained access to Russian airspace, assumed a dominant role, whereas foreign airlines faced a slower recovery constrained by costly operational detours. In contrast, the recovery in the China–North America market remained suppressed for all carriers due to persistent geopolitical tensions. Strategically, foreign airlines became more likely to serve more competitive routes and to avoid routes already operated by alliance partners, compared to the pre-disruption period. Conversely, Chinese airlines exhibited a greater likelihood of serving less competitive routes and routes already operated by other alliance members. These findings underscore how asymmetric operational constraints and geopolitical factors reshape aviation networks through carrier-specific strategies, offering critical insights for policymakers and managers.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102963"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiency of Peruvian regional airports: Does the PPP framework make a difference?","authors":"Victor Chang ,&nbsp;Beatriz Tovar","doi":"10.1016/j.jairtraman.2026.102972","DOIUrl":"10.1016/j.jairtraman.2026.102972","url":null,"abstract":"<div><div>This paper examines whether Public-Private Partnership (PPP) frameworks have improved the technical efficiency of Peruvian regional airports. Using panel data from 17 airports between 2004 and 2017, we estimate a Latent Class Stochastic Frontier Model (LCSFM) based on an input-oriented Cobb-Douglas distance function, which is explicitly controlling for unobserved technological heterogeneity. Airports are classified into two technological groups, with concessionaire status (AdP) serving as a separating variable. Results reveal that airports managed under PPP schemes achieve higher efficiency levels and are more likely to operate with superior technology, with both groups exhibiting increasing returns to scale. Evidence of technological progress, biased towards operational expenditures, suggests that efficiency gains have been driven by labour innovations, outsourcing, and digitalization. These findings highlight the positive role of PPPs in fostering operational improvements and underline the risks of ignoring heterogeneity in regulatory benchmarking. We argue that incorporating heterogeneity-adjusted models into regulatory frameworks could strengthen incentive-based policies, guide infrastructure investments more effectively, and support sustainable development of regional air transport networks.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102972"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Award travel in U.S. domestic markets: An analysis of free ticket redemptions","authors":"Kurt Fuellhart ,&nbsp;Will Livsey ,&nbsp;Yi Gao","doi":"10.1016/j.jairtraman.2026.102979","DOIUrl":"10.1016/j.jairtraman.2026.102979","url":null,"abstract":"<div><div>Frequent flyer programs (FFPs) are central to airline strategy, yet little empirical work examines the routes on which free award tickets are redeemed. Using U.S. Department of Transportation Airline Origin and Destination Survey (DB1B) data accessed through Cirium's Diio Mi, this study analyzes general levels of free award travel in the U.S. domestic market from 2000 to 2025. Next, it provides a detailed cross-sectional assessment of free domestic award travel in 2024. Longitudinal results show redemption levels shifting at key industry moments but diverging sharply by carrier over time. Cross-sectional OLS analysis confirms that carrier identity is the strongest predictor of domestic free ticket redemptions, with Southwest exhibiting the highest levels, United the lowest, and Delta rising steadily. Routes with heavy imbalances in passenger origin have significantly higher award shares than those with more balanced routes. Seasonality, market competition, and carrier yield add nuance to the analysis. Our results show that award travel exhibits clear, measurable patterns within domestic markets, with implications for revenue management, competition, and regulatory oversight.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102979"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the classification and optimization strategies of civil aviation customer service based on BERTopic and the Kano model","authors":"Heyong Wang,&nbsp;Yuanhao Chen","doi":"10.1016/j.jairtraman.2025.102959","DOIUrl":"10.1016/j.jairtraman.2025.102959","url":null,"abstract":"<div><div>This study presents an innovative data-driven framework for optimizing airline customer service by integrating BERTopic topic modeling, SnowNLP sentiment analysis, and the Kano model. Unlike traditional approaches relying on surveys or subjective judgment, this method analyzes real customer service dialogues to extract 15 key service topics, assess satisfaction and attention scores, and categorize them into basic, expected, attractive, and indifferent needs. Findings show that Children's Ticket Inquiries, Pet Transportation, Baggage Regulations, and Seat Selection fall under basic needs, requiring prioritized investment to prevent dissatisfaction. Flight Rescheduling, Membership Verification, and Medical Refunds are expected needs that demand targeted improvements to enhance satisfaction. Promotional Inquiries and Expedited Services are attractive needs where innovative enhancements can create surprise and delight. Indifferent needs such as Standard Refunds, Meal Services, and Lost Item Handling require only baseline quality maintenance. Guided by the principle of demand-oriented resource allocation, the study proposes tailored optimization strategies for each category. This framework reveals latent customer priorities and transforms unstructured dialogue data into actionable insights, offering both theoretical contributions and practical implications for improving service quality and competitive positioning in the civil aviation sector.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102959"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting transition towards sustainable air transport systems: A hybrid decision support system for effective national-level performance evaluation","authors":"Karahan Kara ,&nbsp;Galip Cihan Yalçın ,&nbsp;Emre Kadir Özekenci ,&nbsp;Günal Bilek ,&nbsp;Vladimir Simic ,&nbsp;Çağatay Tunçsiper ,&nbsp;Dragan Pamucar","doi":"10.1016/j.jairtraman.2025.102964","DOIUrl":"10.1016/j.jairtraman.2025.102964","url":null,"abstract":"<div><div>Air transport plays a pivotal role in enhancing economic development by supporting trade, tourism, and regional competitiveness. The growing environmental concerns and social expectations have necessitated the transition towards sustainable air transport systems. Sustainable air transport refers to aviation activities that balance environmental, economic, and social objectives, aiming to minimize carbon emissions, promote renewable energy usage, and enhance socio-economic welfare. In this study, a novel multi-criteria decision-making (MCDM)-based decision support system (DSS) is proposed to evaluate the sustainable air transport performance of the European countries. The main objective of this research is to develop a comprehensive and integrative framework for measuring and ranking the sustainable air transport performance of nations. A hybrid method, termed fractional fuzzy–ranking comparison-response to criteria weighting (RANCOM)–response to criteria weighting (RECA)–ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS), is introduced. DSS consists of five main stages: expert-based subjective weighting using fractional fuzzy RANCOM, objective weighting via RECA, aggregation of weights, and final performance ranking through the RATGOS method. The results indicate that Germany ranks highest, while Cyprus has the lowest sustainable air transport performance among the evaluated countries. The criterion \"commercial aircraft fleet by age of aircraft\" is determined to have the highest importance among the sustainable air transport performance indicators. The study provides a comprehensive, replicable framework for policymakers and stakeholders aiming to monitor and improve sustainable aviation systems. It contributes to the literature by addressing the gap in national-level sustainable air transport performance evaluation.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102964"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An improved optimization algorithm for solving arrival aircraft scheduling problem in the Terminal Maneuvering Area","authors":"Ying Huo ,&nbsp;Daniel Delahaye ,&nbsp;Huijuan Yang ,&nbsp;Maolin Wang","doi":"10.1016/j.jairtraman.2025.102961","DOIUrl":"10.1016/j.jairtraman.2025.102961","url":null,"abstract":"<div><div>The Terminal Maneuvering Area (TMA) is one of the most complex and congested airspace segments, where tools like the Arrival Manager (AMAN) are used to manage inbound traffic and provide accurate, efficient scheduling for each flight. The associated optimization problem is NP-hard, requiring advanced algorithms to meet performance demands in both computational time and solution quality. Heuristic algorithms, such as Simulated Annealing (SA), are known for their ability to provide fast, near-optimal solutions in large and complex state spaces. In our previous work, simulation-based optimization using SA was employed, where information of all flights was integrated into each simulation, resulting in a computationally intensive evaluation process. In this study, we propose a more efficient method by leveraging the inherent safety dependencies between neighboring flights in the operation.By focusing on the performance of individual flights and their immediate impact on adjacent flights, the optimization process becomes more targeted, eliminating the need to integrate all flight data at once. This improves both efficiency and flexibility. To demonstrate the advantages of a selective structure in Simulated Annealing, we introduce Selective Simulated Annealing (SSA) and compare it to the Standard Simulated Annealing algorithm (OSA), highlighting their distinct features. A case study at Paris-Charles de Gaulle (CDG) Airport is used to analyze the performance of both algorithms. Key parameter adjustments are examined to gain insights into their optimization behaviors. The comparison reveals that SSA significantly outperforms OSA, delivering faster computation and reducing delays by 50%.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102961"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond route-specific forecasting: An empirical test of two cross-series transfer learning strategies for airline demand with short-data constraints","authors":"Kiljae K. Lee,&nbsp;Ahmed F. Abdelghany","doi":"10.1016/j.jairtraman.2026.102981","DOIUrl":"10.1016/j.jairtraman.2026.102981","url":null,"abstract":"<div><div>Airline demand forecasting frequently faces a “short-data” problem, where individual routes have limited historical records due to new route launches, seasonal suspensions, or external shocks such as COVID-19. While this constraint impedes the performance of forecasting models trained on single-series data, the presence of numerous parallel routes—a typical characteristic of airline networks—presents a “short-but-wide” data structure, offering a clear opportunity for cross-series transfer learning.</div><div>To exploit this opportunity, we propose and empirically validate two competing strategies: a feature-rich Fine-Tuned Global Forecasting Model (FT-GFM) and an adaptation-focused Adapted Model-Agnostic Meta-Learning (Adapted-MAML).</div><div>Our analysis uses 28 months of data for 1203 origin–destination pairs arriving at three major U.S. hubs (ATL, DFW, DEN). The feature-rich FT-GFM improved accuracy substantially, reducing SMAPE by an average of 28.45% and outperforming local models on 86.74% of routes. The data-efficient Adapted-MAML achieved even greater gains, reducing SMAPE by 45.88% and outperforming local models on 93.81% of routes, despite using only historical passenger volumes.</div><div>The results validate both strategies as effective solutions and show that, in data-constrained environments, Adapted-MAML's meta-learned initialization yields superior route-level forecasting accuracy compared with FT-GFM's feature-driven approach. These findings provide actionable guidance for airlines on selecting appropriate cross-series transfer learning strategies to mitigate the short-data problem and enhance operational resilience under uncertainty.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102981"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-series risk forecasting of airport conflict hotspot with SA-GRU","authors":"Wen Tian ,&nbsp;Yuchen Li ,&nbsp;Xuefang Zhou ,&nbsp;Jinghui Sun ,&nbsp;Xv Shi","doi":"10.1016/j.jairtraman.2026.102977","DOIUrl":"10.1016/j.jairtraman.2026.102977","url":null,"abstract":"<div><div>Airport surface operations increasingly confront collision risks from intricate layouts, vehicle-aircraft interactions, and dense mixed traffic flows. This study develops a predictive framework for conflict hotspot identification by integrating topological, network vulnerability, and traffic complexity metrics into a composite risk evaluation system. A hybrid method combining composite weighting and improved TOPSIS first identifies latent hotspots through node-level risk assessments. Temporal risk patterns are then extracted via principal component analysis of hotspot features, with future risk trajectories predicted using a GRU network enhanced by self-attention mechanisms. Validated through Shenzhen Bao'an International Airport simulations, the proposed SA-GRU model reduces RMSE by 9.14–11.55 % against benchmark models (HA/ARIMA/SVR/LSTM/GRU). Analysis reveals significant spatiotemporal variations in hotspot risks, where daily trends show similar risk fluctuation patterns across zones but differ substantially in intensity. High-risk areas dynamically shift across operational phases, emphasizing the necessity of time-sensitive predictions. The framework enables proactive identification of critical conflict zones through predictive risk monitoring, demonstrating practical potential for optimizing airport surface management. By translating multidimensional operational data into actionable safety insights, this methodology supports intelligent decision-making for collision prevention and resource allocation in complex aviation environments, while remaining adaptable to diverse airport configurations.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102977"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-stage stochastic optimization approach for mega-airport departure metering under data-driven taxi-time uncertainty predictions","authors":"Jiawei Kang,&nbsp;Jie Bao,&nbsp;Junfeng Zhang,&nbsp;Xiaowei Tang,&nbsp;Jiaqi Han,&nbsp;Jiaman He","doi":"10.1016/j.jairtraman.2026.102973","DOIUrl":"10.1016/j.jairtraman.2026.102973","url":null,"abstract":"<div><div>Over the past decade, mega-airports have experienced a surge in air traffic demand, physical expansion, and increased complexity in apron layouts, leading to a high level of aircraft taxi-time uncertainty and shifting the airport surface management from integrated tower control to dedicated apron control. In this study, a two-stage stochastic optimization framework is developed for mega-airport departure metering (DM), which specializes apron-centric and tower-centric optimization in different stages. Moreover, a data-driven Mixture Density Network (MDN) is built to predict the aircraft taxi-time distribution and characterize the uncertainty levels. A large-scale trajectory dataset is collected from a representative mega-airport in China to illustrate the procedure. The results indicate that the developed two-stage stochastic optimization framework distinguishes tower control and apron control in the DM process, improving the overall flexibility of airport airside operations. The data-driven neural network could better predict the taxi-time uncertainty levels through multimodal probability distributions especially at mega-airport with volatile traffic situations. Furthermore, compared with state-of-the-art DM methods, the two-stage stochastic optimization framework could achieve more robust performance of airport departure management and better trade-off between gate-holding and runway throughput.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"133 ","pages":"Article 102973"},"PeriodicalIF":3.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}