Pub Date : 2025-12-10DOI: 10.1016/j.jairtraman.2025.102937
Nicolò Avogadro, Chiara Morlotti, Renato Redondi
Demand forecasting is a pivotal aspect of the multifaceted business of airlines and airports, significantly influencing long-term strategic decisions. For airports, accurate traffic forecasts are particularly crucial for aligning infrastructure capacity with future needs, necessitating tailored approaches to capture complex demand dynamics. This paper proposes a novel modeling framework to formulate high-granular itinerary-level demand forecasts, ultimately ensuring robust system-level predictions. The modeling framework leverages a state-of-the-art integrated demand modeling coupled with a customized scenario analysis tool. We demonstrate the validity of the proposed approach in supporting airport strategic planning by reporting the outcomes of its application on the Italian airport system, formulating traffic forecasts up to 2035 and testing predictive ability based on actual traffic data for 2024. We showcase the adaptability of the framework in addressing diverse challenges that decision-makers and policymakers will face in the near future, such as implementing policies to support the aviation industry’s transition to net-zero emissions.
{"title":"Forecasting high-granular air passenger demand flows: An integrated modeling framework applied to the Italian airport system","authors":"Nicolò Avogadro, Chiara Morlotti, Renato Redondi","doi":"10.1016/j.jairtraman.2025.102937","DOIUrl":"10.1016/j.jairtraman.2025.102937","url":null,"abstract":"<div><div>Demand forecasting is a pivotal aspect of the multifaceted business of airlines and airports, significantly influencing long-term strategic decisions. For airports, accurate traffic forecasts are particularly crucial for aligning infrastructure capacity with future needs, necessitating tailored approaches to capture complex demand dynamics. This paper proposes a novel modeling framework to formulate high-granular itinerary-level demand forecasts, ultimately ensuring robust system-level predictions. The modeling framework leverages a state-of-the-art integrated demand modeling coupled with a customized scenario analysis tool. We demonstrate the validity of the proposed approach in supporting airport strategic planning by reporting the outcomes of its application on the Italian airport system, formulating traffic forecasts up to 2035 and testing predictive ability based on actual traffic data for 2024. We showcase the adaptability of the framework in addressing diverse challenges that decision-makers and policymakers will face in the near future, such as implementing policies to support the aviation industry’s transition to net-zero emissions.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102937"},"PeriodicalIF":3.6,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734007","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}
Pub Date : 2025-12-09DOI: 10.1016/j.jairtraman.2025.102954
Ukbe Üsame Uçar
Aircraft emissions during taxi-out operations constitute a significant portion of local air pollution at airports and are rarely modeled in conjunction with operational and meteorological variables. Although numerous studies focus on fuel burn or emission factors based on the ICAO LTO cycle, limited research integrates real-world airport conditions. In this article, CO2, NOx, CO, and HC emissions during the taxi-out phase at Istanbul Airport for the period 2024–2030 were estimated by considering the technical specifications of aircraft, operational delays, and meteorological visibility indices. Detailed analyses were conducted under three categories (Best, Normal, Worst) and 12 scenarios, and the daily intensity of emissions per unit area was evaluated according to the IDLH health risk indicator. In the estimation study, a new hybrid method called the FoREC-HHO algorithm was developed and compared with machine learning, metaheuristic algorithms, and statistical techniques. As a result of the analysis, the FoREC-HHO algorithm showed the highest accuracy rate for all emission types and achieved the lowest MAE values, demonstrating superior prediction performance. According to the analysis findings, in the worst-case scenario, CO2 emissions increased by 80 %, NOx by 76 %, HC by 78 %, and CO by 66 % between 2024 and 2030. In the normal scenario, the emission increases were observed as 57 % for CO2, 52 % for NOx, 53 % for HC, and 46 % for CO. In contrast, under the best-case scenario, these increases were considerably more moderate, measured at 34 % for CO2, 31 % for NOx, 30 % for HC, and 26 % for CO. In addition, by 2030, the risk density for CO2 is projected to reach 2.33 kg/m2/day, while for CO, this value is 0.01293 kg/m2/day. The calculated densities for NOx and HC were determined to be 0.00221 and 0.00030 kg/m2/day, respectively. These values were found to potentially pose high acute toxicity risks for CO, chronic respiratory and nervous system risks for NOx and HC, and climate-related effects and physiological burdens on personnel working in enclosed spaces for CO2. In this study, a comprehensive approach was presented for both temporal and seasonal estimation of emissions associated with the taxi-out process at airports and health-based risk assessment using the newly developed FoREC-HHO algorithm.
{"title":"Estimation of key pollutant emission during the taxi-out phase using a novel hybrid forecasting algorithm(FoREC-HHO): Application to Istanbul Airport","authors":"Ukbe Üsame Uçar","doi":"10.1016/j.jairtraman.2025.102954","DOIUrl":"10.1016/j.jairtraman.2025.102954","url":null,"abstract":"<div><div>Aircraft emissions during taxi-out operations constitute a significant portion of local air pollution at airports and are rarely modeled in conjunction with operational and meteorological variables. Although numerous studies focus on fuel burn or emission factors based on the ICAO LTO cycle, limited research integrates real-world airport conditions. In this article, CO<sub>2</sub>, NO<sub>x</sub>, CO, and HC emissions during the taxi-out phase at Istanbul Airport for the period 2024–2030 were estimated by considering the technical specifications of aircraft, operational delays, and meteorological visibility indices. Detailed analyses were conducted under three categories (Best, Normal, Worst) and 12 scenarios, and the daily intensity of emissions per unit area was evaluated according to the IDLH health risk indicator. In the estimation study, a new hybrid method called the FoREC-HHO algorithm was developed and compared with machine learning, metaheuristic algorithms, and statistical techniques. As a result of the analysis, the FoREC-HHO algorithm showed the highest accuracy rate for all emission types and achieved the lowest MAE values, demonstrating superior prediction performance. According to the analysis findings, in the worst-case scenario, CO<sub>2</sub> emissions increased by 80 %, NO<sub>x</sub> by 76 %, HC by 78 %, and CO by 66 % between 2024 and 2030. In the normal scenario, the emission increases were observed as 57 % for CO<sub>2</sub>, 52 % for NO<sub>x</sub>, 53 % for HC, and 46 % for CO. In contrast, under the best-case scenario, these increases were considerably more moderate, measured at 34 % for CO<sub>2</sub>, 31 % for NO<sub>x</sub>, 30 % for HC, and 26 % for CO. In addition, by 2030, the risk density for CO<sub>2</sub> is projected to reach 2.33 kg/m<sup>2</sup>/day, while for CO, this value is 0.01293 kg/m<sup>2</sup>/day. The calculated densities for NO<sub>x</sub> and HC were determined to be 0.00221 and 0.00030 kg/m<sup>2</sup>/day, respectively. These values were found to potentially pose high acute toxicity risks for CO, chronic respiratory and nervous system risks for NO<sub>x</sub> and HC, and climate-related effects and physiological burdens on personnel working in enclosed spaces for CO<sub>2</sub>. In this study, a comprehensive approach was presented for both temporal and seasonal estimation of emissions associated with the taxi-out process at airports and health-based risk assessment using the newly developed FoREC-HHO algorithm.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102954"},"PeriodicalIF":3.6,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733853","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}
Pub Date : 2025-12-05DOI: 10.1016/j.jairtraman.2025.102949
Fabian Kianpour
{"title":"Service innovations in airlines: A frontline employee perspective","authors":"Fabian Kianpour","doi":"10.1016/j.jairtraman.2025.102949","DOIUrl":"10.1016/j.jairtraman.2025.102949","url":null,"abstract":"","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102949"},"PeriodicalIF":3.6,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682224","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}
Pub Date : 2025-12-05DOI: 10.1016/j.jairtraman.2025.102927
Xiaoyao Zhao, Xuting Sun
In aviation operations, the airline and maintenance service provider (MSP) have a close collaborative relationship, and their operational decisions often influence each other. However, in practical operational environments, flight delays negatively affect both stakeholders involved in this decision-making system, which reduces the robustness of the tactical decisions and overall system performance at the operational level. To address this issue, we propose a novel bilevel optimization framework that explicitly models the interaction between maintenance resource allocation and aircraft routing with the consideration of primary delay and delay propagation. To tackle the intrinsic complexity of this NP-hard problem, we design an accelerated bilevel solution approach that integrates customized heuristics for practical scalability. By enabling iterative coordination between the MSP and the airline, our approach allows both parties to optimize their tactical decisions in response to operational disruptions, thereby systematically enhancing the robustness of both aircraft maintenance and routing decisions. Extensive experiments on real-world datasets validate the effectiveness and robustness of the proposed framework. Based on seven weekly scenarios, the results show that the proposed bilevel model achieves reduction on the number of flight cancellations and yields notable day-of-operation savings. Comparative results verify that this collaborative decision-making mechanism yields lower operational costs for the airline and improved service efficiency for the MSP, consistently outperforming several baseline models which neglect delay propagation or collaborative mechanisms. These findings demonstrate the potential of our framework as well as solution approach as an intelligent decision support tool for addressing delay-induced disruptions in aircraft maintenance routing. Some actionable insights suach as proactive and flexiable maintenance operations via re-routing are obtained as well.
{"title":"Data-driven collaborative optimization between the airline and maintenance service provider: A Bi-level acceleration framework","authors":"Xiaoyao Zhao, Xuting Sun","doi":"10.1016/j.jairtraman.2025.102927","DOIUrl":"10.1016/j.jairtraman.2025.102927","url":null,"abstract":"<div><div>In aviation operations, the airline and maintenance service provider (MSP) have a close collaborative relationship, and their operational decisions often influence each other. However, in practical operational environments, flight delays negatively affect both stakeholders involved in this decision-making system, which reduces the robustness of the tactical decisions and overall system performance at the operational level. To address this issue, we propose a novel bilevel optimization framework that explicitly models the interaction between maintenance resource allocation and aircraft routing with the consideration of primary delay and delay propagation. To tackle the intrinsic complexity of this NP-hard problem, we design an accelerated bilevel solution approach that integrates customized heuristics for practical scalability. By enabling iterative coordination between the MSP and the airline, our approach allows both parties to optimize their tactical decisions in response to operational disruptions, thereby systematically enhancing the robustness of both aircraft maintenance and routing decisions. Extensive experiments on real-world datasets validate the effectiveness and robustness of the proposed framework. Based on seven weekly scenarios, the results show that the proposed bilevel model achieves reduction on the number of flight cancellations and yields notable day-of-operation savings. Comparative results verify that this collaborative decision-making mechanism yields lower operational costs for the airline and improved service efficiency for the MSP, consistently outperforming several baseline models which neglect delay propagation or collaborative mechanisms. These findings demonstrate the potential of our framework as well as solution approach as an intelligent decision support tool for addressing delay-induced disruptions in aircraft maintenance routing. Some actionable insights suach as proactive and flexiable maintenance operations via re-routing are obtained as well.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102927"},"PeriodicalIF":3.6,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682225","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}
Pub Date : 2025-12-04DOI: 10.1016/j.jairtraman.2025.102953
Tianyu Zhao, Jose Escribano, Arnab Majumdar, Washington Yotto Ochieng
This paper presents a robust algorithm for three-dimensional dynamic airspace sectorization, introducing for the first time multilayer traffic networks in the study field. Distinct from widely used meta-heuristic algorithms, this approach delivers consistent results for the same traffic scenario, avoiding the instability of stochastic search techniques. This approach uses a graph-based model, taking the air traffic network as input, based on which we calculate traffic complexity. To quantify the complexity assigned to the network, we employ two parameters: one derives from the traffic scenarios based on flight vectors, and the other from the network topology. Using this complexity-weighted network as input, a multi-layer spectral clustering algorithm is applied to generate the desired number of communities. To achieve an ideal sector structure, we introduce a boundary refinement framework to produce smooth and tightly connected three-dimensional sectors. The performance of the proposed algorithm is validated using three Key Performance Indicators (KPIs): workload, sector flight time, and dynamic density, demonstrating its capability to generate more load-balanced sector configurations compared to both the current UK operational sectors and the widely used Voronoi diagram-based methods. The performance of the algorithm is evaluated through eight experiments under both peak and off-peak traffic conditions, including four-hour short-term and four six-hour long-term scenarios, with the number of target sectors kept consistent with the operational configuration. The reduced standard deviations and coefficients of variation of the KPIs indicate that the proposed sectorization achieves a more balanced distribution of traffic loads across sectors. This research provides Air Navigation Service Providers (ANSPs) with an automatic tool for three-dimensional airspace sectorization, enabling more balanced workload distribution while adapting to evolving air traffic flow patterns.
{"title":"Robust 3D dynamic airspace sectorization: A multilayer graph-based approach","authors":"Tianyu Zhao, Jose Escribano, Arnab Majumdar, Washington Yotto Ochieng","doi":"10.1016/j.jairtraman.2025.102953","DOIUrl":"10.1016/j.jairtraman.2025.102953","url":null,"abstract":"<div><div>This paper presents a robust algorithm for three-dimensional dynamic airspace sectorization, introducing for the first time multilayer traffic networks in the study field. Distinct from widely used meta-heuristic algorithms, this approach delivers consistent results for the same traffic scenario, avoiding the instability of stochastic search techniques. This approach uses a graph-based model, taking the air traffic network as input, based on which we calculate traffic complexity. To quantify the complexity assigned to the network, we employ two parameters: one derives from the traffic scenarios based on flight vectors, and the other from the network topology. Using this complexity-weighted network as input, a multi-layer spectral clustering algorithm is applied to generate the desired number of communities. To achieve an ideal sector structure, we introduce a boundary refinement framework to produce smooth and tightly connected three-dimensional sectors. The performance of the proposed algorithm is validated using three Key Performance Indicators (KPIs): workload, sector flight time, and dynamic density, demonstrating its capability to generate more load-balanced sector configurations compared to both the current UK operational sectors and the widely used Voronoi diagram-based methods. The performance of the algorithm is evaluated through eight experiments under both peak and off-peak traffic conditions, including four-hour short-term and four six-hour long-term scenarios, with the number of target sectors kept consistent with the operational configuration. The reduced standard deviations and coefficients of variation of the KPIs indicate that the proposed sectorization achieves a more balanced distribution of traffic loads across sectors. This research provides Air Navigation Service Providers (ANSPs) with an automatic tool for three-dimensional airspace sectorization, enabling more balanced workload distribution while adapting to evolving air traffic flow patterns.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102953"},"PeriodicalIF":3.6,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682223","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}
Pub Date : 2025-12-03DOI: 10.1016/j.jairtraman.2025.102936
Georg Hirte , Johannes Jaekel , Hans-Martin Niemeier
The paper examines the horizontal efficiency of aircraft approaches in the lower airspace. We propose two measures for horizontal efficiency and study the determinants, notably air traffic control's choice variables, of both efficiency metrics using robust (MM) and Tobit regression analyses. Our metrics indicate an average deviation from the optimum efficiency of 21.6 % and 19.6 %, respectively. We calculate that these inefficiencies generate approximately 165,088 tons of CO2 emissions and fuel costs of around € 23.8 million per annum. Improving the efficiency of approaches is thus a means to reduce aviation's externalities and lower its negative impact on the climate and noise. The metrics are significantly affected by the volume of flights, aircraft weight, weather threats, and the decision variables of air traffic control, which are runway change, runway choice and route choice. This is evidence that air traffic control can contribute to horizontal efficiency and reduce externalities.
{"title":"Horizontal approach flight efficiency and emissions at the lower airspace","authors":"Georg Hirte , Johannes Jaekel , Hans-Martin Niemeier","doi":"10.1016/j.jairtraman.2025.102936","DOIUrl":"10.1016/j.jairtraman.2025.102936","url":null,"abstract":"<div><div>The paper examines the horizontal efficiency of aircraft approaches in the lower airspace. We propose two measures for horizontal efficiency and study the determinants, notably air traffic control's choice variables, of both efficiency metrics using robust (MM) and Tobit regression analyses. Our metrics indicate an average deviation from the optimum efficiency of 21.6 % and 19.6 %, respectively. We calculate that these inefficiencies generate approximately 165,088 tons of CO2 emissions and fuel costs of around € 23.8 million per annum. Improving the efficiency of approaches is thus a means to reduce aviation's externalities and lower its negative impact on the climate and noise. The metrics are significantly affected by the volume of flights, aircraft weight, weather threats, and the decision variables of air traffic control, which are runway change, runway choice and route choice. This is evidence that air traffic control can contribute to horizontal efficiency and reduce externalities.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102936"},"PeriodicalIF":3.6,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682222","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}
Pub Date : 2025-12-03DOI: 10.1016/j.jairtraman.2025.102948
Zheng Xu , Jun Hua , Guangquan Lu , Nan Zheng
The integration of electric vertical take-off and landing (eVTOL) vehicles into existing transportation systems represents a paradigm shift toward advanced low-altitude transportation (ALT), yet user acceptance remains a critical barrier to successful implementation. Traditional acceptance studies rely predominantly on questionnaire-based methodologies that capture hypothetical preferences rather than experiential responses, creating significant gaps in understanding real-world adoption patterns. This study addresses these limitations through a novel virtual reality (VR) simulation platform that enables multi-perspective evaluation of ALT acceptance across three distinct stakeholder roles: ALT passengers, conventional vehicle drivers, and pedestrians. Through systematic experimentation involving 2430 test scenarios across three realistic urban environments (straight roadway, freeway merging, and complex urban driving), this research establishes comprehensive relationships between technical performance optimization and human acceptance patterns. The results demonstrate that ALT implementation yields substantial performance benefits, including 37–45% reductions in travel times and 41–80% decreases in safety-critical events across different scenarios. However, behavioral analysis reveals a critical disconnect between objective performance improvements and subjective acceptance levels. Real-time intervention measurements show that user acceptance declines significantly with increasing ALT penetration rates, from 89% acceptance at 5% penetration to 59% at 20% penetration, with over 80% of the 745 recorded interventions occurring at implementation rates exceeding 15%. Within our experimental scenarios, we observed convergence of technical performance and operational comfort indicators around 15% penetration. These simulation-based findings provide preliminary evidence that integrates technical performance optimization with human factors analysis for ALT systems. The results offer initial insights for policymakers designing pilot programs and for industry stakeholders planning sustainable urban air mobility deployment.
{"title":"Multi-perspective evaluation of human factors in advanced low-altitude transportation adoption: a virtual reality simulation study","authors":"Zheng Xu , Jun Hua , Guangquan Lu , Nan Zheng","doi":"10.1016/j.jairtraman.2025.102948","DOIUrl":"10.1016/j.jairtraman.2025.102948","url":null,"abstract":"<div><div>The integration of electric vertical take-off and landing (eVTOL) vehicles into existing transportation systems represents a paradigm shift toward advanced low-altitude transportation (ALT), yet user acceptance remains a critical barrier to successful implementation. Traditional acceptance studies rely predominantly on questionnaire-based methodologies that capture hypothetical preferences rather than experiential responses, creating significant gaps in understanding real-world adoption patterns. This study addresses these limitations through a novel virtual reality (VR) simulation platform that enables multi-perspective evaluation of ALT acceptance across three distinct stakeholder roles: ALT passengers, conventional vehicle drivers, and pedestrians. Through systematic experimentation involving 2430 test scenarios across three realistic urban environments (straight roadway, freeway merging, and complex urban driving), this research establishes comprehensive relationships between technical performance optimization and human acceptance patterns. The results demonstrate that ALT implementation yields substantial performance benefits, including 37–45% reductions in travel times and 41–80% decreases in safety-critical events across different scenarios. However, behavioral analysis reveals a critical disconnect between objective performance improvements and subjective acceptance levels. Real-time intervention measurements show that user acceptance declines significantly with increasing ALT penetration rates, from 89% acceptance at 5% penetration to 59% at 20% penetration, with over 80% of the 745 recorded interventions occurring at implementation rates exceeding 15%. Within our experimental scenarios, we observed convergence of technical performance and operational comfort indicators around 15% penetration. These simulation-based findings provide preliminary evidence that integrates technical performance optimization with human factors analysis for ALT systems. The results offer initial insights for policymakers designing pilot programs and for industry stakeholders planning sustainable urban air mobility deployment.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102948"},"PeriodicalIF":3.6,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682221","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}
Pub Date : 2025-12-02DOI: 10.1016/j.jairtraman.2025.102935
Darin Lee, Erin Secatore, Ethan Singer, Eric Amel
This paper compares U.S. airline business models in the deregulation era and provides a data-driven analysis that comprehensively describes the market outcomes following U.S. airline industry consolidation in the 21st century. We detail how these market outcomes following consolidation have impacted consumers. Specifically, we find that: (1) notwithstanding industry consolidation, air travel is extremely accessible, with more choice in domestic and international air travel than two decades ago; (2) as of 2024, U.S. airfares are at or near all-time inflation-adjusted lows; and (3) airlines’ profitability in the post-consolidation era, while modest compared with other large companies, has enabled significant reinvestment in products and service to make travel more convenient, comfortable, and reliable.
{"title":"Business model evolution and consolidation of the U.S. airline industry: Market outcomes in the 21st century","authors":"Darin Lee, Erin Secatore, Ethan Singer, Eric Amel","doi":"10.1016/j.jairtraman.2025.102935","DOIUrl":"10.1016/j.jairtraman.2025.102935","url":null,"abstract":"<div><div>This paper compares U.S. airline business models in the deregulation era and provides a data-driven analysis that comprehensively describes the market outcomes following U.S. airline industry consolidation in the 21st century. We detail how these market outcomes following consolidation have impacted consumers. Specifically, we find that: (1) notwithstanding industry consolidation, air travel is extremely accessible, with more choice in domestic and international air travel than two decades ago; (2) as of 2024, U.S. airfares are at or near all-time inflation-adjusted lows; and (3) airlines’ profitability in the post-consolidation era, while modest compared with other large companies, has enabled significant reinvestment in products and service to make travel more convenient, comfortable, and reliable.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102935"},"PeriodicalIF":3.6,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682226","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}
Pub Date : 2025-12-02DOI: 10.1016/j.jairtraman.2025.102950
Eeshan Bhaduri , Charisma F. Choudhury
Urban air mobility (UAM) is increasingly being recognised as a promising response to the challenges of rapid urban expansion and its negative externalities. While technological advancements in vertical take-off and landing (VTOL) aircraft have accelerated development in this space, the widespread adoption of UAM services hinges on societal acceptance driven by public perceptions. Understanding these perceptions, especially their variation across regions and over time, is critical for developing policies to maximise their adoption rate. This study leverages a large-scale and long-term Twitter dataset to discern the spatio-temporal evolution of public perceptions towards UAM. To this end, we employed a combination of machine learning (ML) and a large language model (LLM) for performing sentiment classification. Subsequently, sentiment polarities are integrated with time series analysis, indicating the prevalence of positive perception for most of the last decade, while detecting the effect of various real-world events. In terms of spatial K-means clustering results, it reveals four clusters of countries with distinct characteristics. For example, people in countries like the USA and Australia are observed to be highly opinionated towards UAM, while public discourse in Germany and India is more neutral. Finally, dynamic topic modelling coupled with an LLM-based representation uncovers underlying themes of public discourse. Topic model findings underline three major global themes: (1) industry innovation and testing, (2) unmanned aviation systems, and (3) mobility benefits. Furthermore, we identified in some cases that local themes driven by specific incidents have a more substantial effect in shaping the preferences than the generic global ones. The paper hence contributes to the literature by providing the first global-level dynamic spatio-temporal assessment of future UAM services. The insights are expected to offer valuable policy guidance for policymakers, regulators, and industry stakeholders aiming to improve the public acceptance of UAM technologies and consequently the uptake.
{"title":"Shifting skies: A cross-country investigation of evolution of public perception toward urban air mobility through Twitter (X) discourse","authors":"Eeshan Bhaduri , Charisma F. Choudhury","doi":"10.1016/j.jairtraman.2025.102950","DOIUrl":"10.1016/j.jairtraman.2025.102950","url":null,"abstract":"<div><div>Urban air mobility (UAM) is increasingly being recognised as a promising response to the challenges of rapid urban expansion and its negative externalities. While technological advancements in vertical take-off and landing (VTOL) aircraft have accelerated development in this space, the widespread adoption of UAM services hinges on societal acceptance driven by public perceptions. Understanding these perceptions, especially their variation across regions and over time, is critical for developing policies to maximise their adoption rate. This study leverages a large-scale and long-term Twitter dataset to discern the spatio-temporal evolution of public perceptions towards UAM. To this end, we employed a combination of machine learning (ML) and a large language model (LLM) for performing sentiment classification. Subsequently, sentiment polarities are integrated with time series analysis, indicating the prevalence of positive perception for most of the last decade, while detecting the effect of various real-world events. In terms of spatial K-means clustering results, it reveals four clusters of countries with distinct characteristics. For example, people in countries like the USA and Australia are observed to be highly opinionated towards UAM, while public discourse in Germany and India is more neutral. Finally, dynamic topic modelling coupled with an LLM-based representation uncovers underlying themes of public discourse. Topic model findings underline three major global themes: (1) industry innovation and testing, (2) unmanned aviation systems, and (3) mobility benefits. Furthermore, we identified in some cases that local themes driven by specific incidents have a more substantial effect in shaping the preferences than the generic global ones. The paper hence contributes to the literature by providing the first global-level dynamic spatio-temporal assessment of future UAM services. The insights are expected to offer valuable policy guidance for policymakers, regulators, and industry stakeholders aiming to improve the public acceptance of UAM technologies and consequently the uptake.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102950"},"PeriodicalIF":3.6,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682227","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}
Pub Date : 2025-11-29DOI: 10.1016/j.jairtraman.2025.102938
Gradiyan Budi Pratama , Carlo Caponecchia
Studies in the aviation industry have suggested that differences in national culture profiles may be related to different incident rates across countries and regions. Developing a better understanding of the role of national culture in aviation incidents has therefore been recognised as an important part of continuous improvement. This study aims to examine perceptions on the contribution of national culture factors to aviation incidents, identify examples of national culture-related behaviours that should be anticipated in the aviation safety context, and explore the potential benefits of identifying national culture factors in aviation incidents. Interviews with 16 experienced aviation incident investigators from Indonesia and Australia were conducted. All subject matter experts interviewed in this study confirmed that aviation safety is potentially influenced by national culture factors. These factors were reported to be more apparent when comparing behaviours between the cultures of "Eastern" and "Western" countries. Several examples relevant to national culture were identified by interviewees, such as the cultural elements of steep hierarchies, collectivism, and risk-taking tendencies. Subject matter experts suggested that a more structured identification of national culture factors as part of aviation incident investigations could deliver advantages for the continuous improvement of the aviation system. The identified potential benefits of national culture identification included increased awareness among flight operators, the improvement of standard procedures, and the development of training programs & regulations to counter the potential negative effects of culture in specific countries.
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