Pub Date : 2025-07-10DOI: 10.1016/j.jairtraman.2025.102853
Kiljae K. Lee , Li Zou , Scott Ambrose
This study examines how six service features affect passenger share and airfare in the U.S. domestic market. Applying two-stage least squares and random forest models to 5248 O&D records, we find seat pitch has the strongest impact. The relationship is nonlinear: share rises sharply at 29 inches, then levels off -- suggesting passengers may view 29 inches as a minimum comfort threshold. Wi-Fi impact plateaus: moving from no to paid Wi-Fi boosts share, but making it free adds little, suggesting connectivity is valued more than whether it is free. Live TV is negatively associated with share. USB access and aircraft age show modest positive association with both share and fares, while aircraft size has a strong positive association with share but a slight negative effect on fares. Building on recent empirical studies of service differentiation in aviation, these findings highlight that passenger preferences are evolving by valuing functional and digital connectivity.
{"title":"The influence of seat pitch, wi-fi, and other service features on airfares and passenger share in the U.S. domestic air travel market","authors":"Kiljae K. Lee , Li Zou , Scott Ambrose","doi":"10.1016/j.jairtraman.2025.102853","DOIUrl":"10.1016/j.jairtraman.2025.102853","url":null,"abstract":"<div><div>This study examines how six service features affect passenger share and airfare in the U.S. domestic market. Applying two-stage least squares and random forest models to 5248 O&D records, we find seat pitch has the strongest impact. The relationship is nonlinear: share rises sharply at 29 inches, then levels off -- suggesting passengers may view 29 inches as a minimum comfort threshold. Wi-Fi impact plateaus: moving from no to paid Wi-Fi boosts share, but making it free adds little, suggesting connectivity is valued more than whether it is free. Live TV is negatively associated with share. USB access and aircraft age show modest positive association with both share and fares, while aircraft size has a strong positive association with share but a slight negative effect on fares. Building on recent empirical studies of service differentiation in aviation, these findings highlight that passenger preferences are evolving by valuing functional and digital connectivity.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102853"},"PeriodicalIF":3.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588384","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 : 2025-07-09DOI: 10.1016/j.jairtraman.2025.102852
Yongkang Song , Yanhua Li , Hanchen Ke , Keyan Zhao
Existing studies on airport efficiency predominantly emphasize operational performance, often overlooking airports' social responsibilities as public infrastructure. This study adopts a socioeconomic impact analysis perspective to evaluate the subsidy efficiency of 56 small and medium-sized airports in China from 2015 to 2019, offering insights to improve the interaction between airport operations and socioeconomic development. The study consists of two main components. Firstly, Network Data Envelopment Analysis (NDEA) decomposes the subsidy process into two sub-processes: stimulating air transport volume and enhancing socioeconomic development, enabling a detailed efficiency assessment. Secondly, a panel data regression model is utilized to analyze the key factors influencing subsidy efficiency. The efficiency assessment highlights that the weak correlation between airport operations and regional economic development is the primary barrier to improving subsidy efficiency. Additionally, the results reveal significant geographic disparities, with airports in eastern regions exhibiting higher subsidy efficiency than those in the west. The panel regression analysis identifies several factors with substantial positive effects on subsidy efficiency, including the number of airlines and connected destinations, the city's population size, and highway passenger traffic. To the best of our knowledge, this study is among the first to evaluate airport subsidy efficiency, specifically focusing on social economic outcomes, particularly for small and medium-sized airports. By extending the scope of existing research on airport efficiency evaluation, this study contributes to a deeper understanding of the role of subsidies in supporting smaller airports and their relationship with social development.
{"title":"Study on the subsidy efficiency of small and medium-sized airports in China based on social economic impact","authors":"Yongkang Song , Yanhua Li , Hanchen Ke , Keyan Zhao","doi":"10.1016/j.jairtraman.2025.102852","DOIUrl":"10.1016/j.jairtraman.2025.102852","url":null,"abstract":"<div><div>Existing studies on airport efficiency predominantly emphasize operational performance, often overlooking airports' social responsibilities as public infrastructure. This study adopts a socioeconomic impact analysis perspective to evaluate the subsidy efficiency of 56 small and medium-sized airports in China from 2015 to 2019, offering insights to improve the interaction between airport operations and socioeconomic development. The study consists of two main components. Firstly, Network Data Envelopment Analysis (NDEA) decomposes the subsidy process into two sub-processes: stimulating air transport volume and enhancing socioeconomic development, enabling a detailed efficiency assessment. Secondly, a panel data regression model is utilized to analyze the key factors influencing subsidy efficiency. The efficiency assessment highlights that the weak correlation between airport operations and regional economic development is the primary barrier to improving subsidy efficiency. Additionally, the results reveal significant geographic disparities, with airports in eastern regions exhibiting higher subsidy efficiency than those in the west. The panel regression analysis identifies several factors with substantial positive effects on subsidy efficiency, including the number of airlines and connected destinations, the city's population size, and highway passenger traffic. To the best of our knowledge, this study is among the first to evaluate airport subsidy efficiency, specifically focusing on social economic outcomes, particularly for small and medium-sized airports. By extending the scope of existing research on airport efficiency evaluation, this study contributes to a deeper understanding of the role of subsidies in supporting smaller airports and their relationship with social development.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102852"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579293","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 : 2025-07-09DOI: 10.1016/j.jairtraman.2025.102857
Wenchao Wang, Jian He, Jingjing Wang
The insufficient hazard management capacity of general aviation enterprises has led to frequent safety incidents and placed the industry in a persistent safety dilemma. Enhancing hazard identification and control is therefore critical to improving the current unstable safety situation. This paper proposes an evidence-based analytical approach to systematically examine hazard causation in general aviation, integrating factors across human, technical, environmental, and managerial domains. Drawing on accident chain theory, a risk coefficient-based optimization model is developed, and an evidence-based hazard tracing method is constructed within the EBAS-HO framework, which builds upon and improves the HOP-HFACS model. Grey Relational Analysis and structural entropy theory are employed to assess hazard interactions and system structure. Results. The analysis of 43 accident cases identifies six key hazard factors: safety production cost, human error, occupational factors, emergency preparedness, technical safety measures, and environmental conditions. In addition, violations behavior serves as a critical mediating factor linking other variables to accident occurrence. Comparative model evaluation demonstrates that the proposed EBAS-HO framework outperforms traditional HFACS in terms of accuracy, structure, and predictive capability. Compared to conventional hazard identification approaches, the integration of evidence-based tracing and control enhances the visibility and traceability of system hazards, enabling more targeted safety interventions. This approach substantially improves hazard governance and safety management capacity in the general aviation sector.
{"title":"Evidence-based analysis on the hazard causation of general aviation in China","authors":"Wenchao Wang, Jian He, Jingjing Wang","doi":"10.1016/j.jairtraman.2025.102857","DOIUrl":"10.1016/j.jairtraman.2025.102857","url":null,"abstract":"<div><div>The insufficient hazard management capacity of general aviation enterprises has led to frequent safety incidents and placed the industry in a persistent safety dilemma. Enhancing hazard identification and control is therefore critical to improving the current unstable safety situation. This paper proposes an evidence-based analytical approach to systematically examine hazard causation in general aviation, integrating factors across human, technical, environmental, and managerial domains. Drawing on accident chain theory, a risk coefficient-based optimization model is developed, and an evidence-based hazard tracing method is constructed within the EBAS-HO framework, which builds upon and improves the HOP-HFACS model. Grey Relational Analysis and structural entropy theory are employed to assess hazard interactions and system structure. Results. The analysis of 43 accident cases identifies six key hazard factors: safety production cost, human error, occupational factors, emergency preparedness, technical safety measures, and environmental conditions. In addition, violations behavior serves as a critical mediating factor linking other variables to accident occurrence. Comparative model evaluation demonstrates that the proposed EBAS-HO framework outperforms traditional HFACS in terms of accuracy, structure, and predictive capability. Compared to conventional hazard identification approaches, the integration of evidence-based tracing and control enhances the visibility and traceability of system hazards, enabling more targeted safety interventions. This approach substantially improves hazard governance and safety management capacity in the general aviation sector.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102857"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579291","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 : 2025-07-08DOI: 10.1016/j.jairtraman.2025.102851
Mustansir Farooq, M. Manoj, K. Ramachandra Rao
<div><div>Connected air itineraries are an integral part of air travel. There is a mixed perception among passengers regarding connections at an intermediate airport as they present a range of difficulties, such as the chances of missing a flight, and loosing or delaying of checked-in baggage. In addition, operational issues (long inter-terminal transfers, inadequate availability of intra-airport shuttle services, delays in baggage check-in, etc.) at the airports also cause inconvenience to passengers using connected itineraries. One of the critical backend procedures to provide uninterrupted and efficient air travel for passengers is the provision of minimum connection time (MCT) at an airport for an itinerary with a connection, which is vital for flight operations. There have been discussions on the amount of time spent for a connection, and the conventional belief that passengers favour short connection times is widespread among air travellers. This study aims to analyse this hypothesis for domestic air itineraries by using a revealed preference data collected in India. A multinomial logit (MNL) specification with correction for price endogeneity is adopted to model airline itinerary choice of passengers. A recursive method in MNL is used to dynamically create the utility function to handle large and varying alternatives. For alternative choice set generation, actual (real) alternatives available to passengers are used in the MNL model. A piecewise linear specification is used to address the non-linearity of the connection time for direct itineraries (includes a stop, with no plane change) and connected itineraries (includes a stop, with a plane change). Results reveal that there is a positive influence of connection time on utilities up to 120 min for connected itineraries. The connection time duration of 90–120 min for connected itineraries is found to provide maximum utility to flyers, balancing the need for sufficient time to navigate transitions such as security checks and gate changes, while minimizing the inconvenience of extended waiting periods. For direct itineraries a connection time beyond 35 min is found to reduce the utility substantially on direct itineraries. To understand the economic significance of the connection time, the willingness to pay estimates are evaluated and validated by estimating confidence intervals using Monte Carlo simulations using a truncated normal distribution. Findings reveal that flyers are willing to pay INR 14 (USD 0.16) per minute up to 90 min and INR 30 (USD 0.36) per minute for reductions beyond 120 min for connected itineraries. In contrast, for direct itineraries, passengers are willing to pay INR 2.8 (USD 0.03) per minute for layovers up to 35 min and INR 66 (USD 0.77) per minute for reductions beyond 35 min. This paper provides insights regarding the willingness to pay for each additional minute on a connection, thereby can help carriers to schedule their connections and provide adequate connec
{"title":"Effects of connection time on connected itineraries in Indian domestic aviation market","authors":"Mustansir Farooq, M. Manoj, K. Ramachandra Rao","doi":"10.1016/j.jairtraman.2025.102851","DOIUrl":"10.1016/j.jairtraman.2025.102851","url":null,"abstract":"<div><div>Connected air itineraries are an integral part of air travel. There is a mixed perception among passengers regarding connections at an intermediate airport as they present a range of difficulties, such as the chances of missing a flight, and loosing or delaying of checked-in baggage. In addition, operational issues (long inter-terminal transfers, inadequate availability of intra-airport shuttle services, delays in baggage check-in, etc.) at the airports also cause inconvenience to passengers using connected itineraries. One of the critical backend procedures to provide uninterrupted and efficient air travel for passengers is the provision of minimum connection time (MCT) at an airport for an itinerary with a connection, which is vital for flight operations. There have been discussions on the amount of time spent for a connection, and the conventional belief that passengers favour short connection times is widespread among air travellers. This study aims to analyse this hypothesis for domestic air itineraries by using a revealed preference data collected in India. A multinomial logit (MNL) specification with correction for price endogeneity is adopted to model airline itinerary choice of passengers. A recursive method in MNL is used to dynamically create the utility function to handle large and varying alternatives. For alternative choice set generation, actual (real) alternatives available to passengers are used in the MNL model. A piecewise linear specification is used to address the non-linearity of the connection time for direct itineraries (includes a stop, with no plane change) and connected itineraries (includes a stop, with a plane change). Results reveal that there is a positive influence of connection time on utilities up to 120 min for connected itineraries. The connection time duration of 90–120 min for connected itineraries is found to provide maximum utility to flyers, balancing the need for sufficient time to navigate transitions such as security checks and gate changes, while minimizing the inconvenience of extended waiting periods. For direct itineraries a connection time beyond 35 min is found to reduce the utility substantially on direct itineraries. To understand the economic significance of the connection time, the willingness to pay estimates are evaluated and validated by estimating confidence intervals using Monte Carlo simulations using a truncated normal distribution. Findings reveal that flyers are willing to pay INR 14 (USD 0.16) per minute up to 90 min and INR 30 (USD 0.36) per minute for reductions beyond 120 min for connected itineraries. In contrast, for direct itineraries, passengers are willing to pay INR 2.8 (USD 0.03) per minute for layovers up to 35 min and INR 66 (USD 0.77) per minute for reductions beyond 35 min. This paper provides insights regarding the willingness to pay for each additional minute on a connection, thereby can help carriers to schedule their connections and provide adequate connec","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102851"},"PeriodicalIF":3.9,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579290","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 : 2025-07-07DOI: 10.1016/j.jairtraman.2025.102856
Jungho Baek , Soojoong Nam
This article investigates how fluctuations in oil prices influence air travel demand in Korea and Japan, considering short- and long-term impacts. Using both ARDL and NARDL models, the study reveals that oil prices significantly influence air travel demand, with asymmetrical impacts more pronounced in Korea than in Japan. While both countries show short-term sensitivity to oil prices, Korea also experiences long-term effects. Economic growth and exchange rates are also critical factors affecting air travel demand. These findings suggest tailored policy approaches for Korea and Japan to enhance the resilience of their aviation sectors in response to oil price changes.
{"title":"Do oil price fluctuations influence air travel Demand? Symmetric and asymmetric insights from Korea and Japan","authors":"Jungho Baek , Soojoong Nam","doi":"10.1016/j.jairtraman.2025.102856","DOIUrl":"10.1016/j.jairtraman.2025.102856","url":null,"abstract":"<div><div>This article investigates how fluctuations in oil prices influence air travel demand in Korea and Japan, considering short- and long-term impacts. Using both ARDL and NARDL models, the study reveals that oil prices significantly influence air travel demand, with asymmetrical impacts more pronounced in Korea than in Japan. While both countries show short-term sensitivity to oil prices, Korea also experiences long-term effects. Economic growth and exchange rates are also critical factors affecting air travel demand. These findings suggest tailored policy approaches for Korea and Japan to enhance the resilience of their aviation sectors in response to oil price changes.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102856"},"PeriodicalIF":3.9,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570333","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 : 2025-07-04DOI: 10.1016/j.jairtraman.2025.102844
Haonan Lin, Jian Luo, Guofang Nan
Air cargo subsidy policies are being implemented in several Chinese provinces to promote industrial development and stimulate regional economic growth. This study explores the impact of government quantity subsidies to the airline or shippers on the air cargo market. We consider the impact of these subsidy policies from the perspectives of all-cargo airline and economies of scale. Our findings show that the subsidy provided to the airline or shippers have similar effects on air cargo quantity, airline’s profits, and social welfare. However, these subsidies influence airline’s pricing decisions differently due to different payment streams. Thus, if the government focuses on air cargo volume or airline’s profit, both the airline and shipper can benefit from the subsidy policy, although social welfare may be compromised. This analysis provides managerial insights for the government to formulate air cargo policies accordingly.
{"title":"The effects of different subsidy policy modes on China’s air cargo market: The all-cargo airline and scale economies perspective","authors":"Haonan Lin, Jian Luo, Guofang Nan","doi":"10.1016/j.jairtraman.2025.102844","DOIUrl":"10.1016/j.jairtraman.2025.102844","url":null,"abstract":"<div><div>Air cargo subsidy policies are being implemented in several Chinese provinces to promote industrial development and stimulate regional economic growth. This study explores the impact of government quantity subsidies to the airline or shippers on the air cargo market. We consider the impact of these subsidy policies from the perspectives of all-cargo airline and economies of scale. Our findings show that the subsidy provided to the airline or shippers have similar effects on air cargo quantity, airline’s profits, and social welfare. However, these subsidies influence airline’s pricing decisions differently due to different payment streams. Thus, if the government focuses on air cargo volume or airline’s profit, both the airline and shipper can benefit from the subsidy policy, although social welfare may be compromised. This analysis provides managerial insights for the government to formulate air cargo policies accordingly.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102844"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563860","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 : 2025-07-04DOI: 10.1016/j.jairtraman.2025.102846
João Basilio Tarelho Szenczuk , Rogéria de A. Gomes , Jorge M.R. Silva
This study employs a statistical modeling approach to commercial aviation fuel consumption and flight time to assess air traffic management (ATM) performance. The study investigates the operational factors that impact ATM efficiency, exploring airport-specific performance. Using datasets from Automatic Dependent Surveillance - Broadcast (ADS-B) surveillance systems, the Brazilian air transport statistical database, and meteorological data, the research develops linear regression models to quantify the effects of traffic intensity, weather conditions, and airspace structure on fuel consumption and flight time. The data covers the Brazilian domestic market from 2018 to 2022, totaling more than 1.3 million flights analyzed. The findings suggest differences in the impacts of traffic intensity and adverse weather conditions among the busiest airports in Brazil. Some airports had better efficiency levels for the same traffic intensity level, while the airspace structure’s impact was somewhat more similar in all major airports. At SBGR, for example, the busiest airport in Brazil, the traffic intensity during arrivals caused about 74 kilograms of extra fuel per flight, while the airspace structure was associated with about 160 kilograms of extra fuel per flight. This research offers insights into quantifying potential savings from ATM improvements by providing a data-driven approach.
{"title":"Estimating the impacts of traffic intensity, weather conditions, and airspace structure on fuel consumption and flight time of Brazilian commercial aviation","authors":"João Basilio Tarelho Szenczuk , Rogéria de A. Gomes , Jorge M.R. Silva","doi":"10.1016/j.jairtraman.2025.102846","DOIUrl":"10.1016/j.jairtraman.2025.102846","url":null,"abstract":"<div><div>This study employs a statistical modeling approach to commercial aviation fuel consumption and flight time to assess air traffic management (ATM) performance. The study investigates the operational factors that impact ATM efficiency, exploring airport-specific performance. Using datasets from Automatic Dependent Surveillance - Broadcast (ADS-B) surveillance systems, the Brazilian air transport statistical database, and meteorological data, the research develops linear regression models to quantify the effects of traffic intensity, weather conditions, and airspace structure on fuel consumption and flight time. The data covers the Brazilian domestic market from 2018 to 2022, totaling more than 1.3 million flights analyzed. The findings suggest differences in the impacts of traffic intensity and adverse weather conditions among the busiest airports in Brazil. Some airports had better efficiency levels for the same traffic intensity level, while the airspace structure’s impact was somewhat more similar in all major airports. At SBGR, for example, the busiest airport in Brazil, the traffic intensity during arrivals caused about 74 kilograms of extra fuel per flight, while the airspace structure was associated with about 160 kilograms of extra fuel per flight. This research offers insights into quantifying potential savings from ATM improvements by providing a data-driven approach.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102846"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549560","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 : 2025-07-02DOI: 10.1016/j.jairtraman.2025.102848
Yueer Zhou , Wenliang Ma , Yuchao Xu , Xiangru Wu , Linbo Li
Network structure is a crucial strategic factor influencing airline revenue. A hub-and-spoke network can reduce airline costs due to economies of scale; however, it may lead to passenger leakage when alternative transportation modes are available. On the other hand, a point-to-point network offers greater convenience for passengers but is generally less profitable for airlines. This paper develops an optimization algorithm (Self-Regulated Ant Colony Optimization) to design a hybrid airline network that can simultaneously optimize route design and frequency setting. Then, applying a case study of the airline network of China Southern Airlines, we find that the designed hybrid network generates better financial performance, manifesting as higher revenue and larger load factors compared to the original network. At the same time, the airlines' operating time is significantly reduced. The results also indicate that, following network optimization, airlines tend to use smaller aircraft. Finally, we identify the characteristics of the suspended and newly generated routes after optimization. This paper has important policy implications for airline operations and network design.
{"title":"The impact of network optimization on airline financial performance: Evidence from China domestic routes","authors":"Yueer Zhou , Wenliang Ma , Yuchao Xu , Xiangru Wu , Linbo Li","doi":"10.1016/j.jairtraman.2025.102848","DOIUrl":"10.1016/j.jairtraman.2025.102848","url":null,"abstract":"<div><div>Network structure is a crucial strategic factor influencing airline revenue. A hub-and-spoke network can reduce airline costs due to economies of scale; however, it may lead to passenger leakage when alternative transportation modes are available. On the other hand, a point-to-point network offers greater convenience for passengers but is generally less profitable for airlines. This paper develops an optimization algorithm (Self-Regulated Ant Colony Optimization) to design a hybrid airline network that can simultaneously optimize route design and frequency setting. Then, applying a case study of the airline network of China Southern Airlines, we find that the designed hybrid network generates better financial performance, manifesting as higher revenue and larger load factors compared to the original network. At the same time, the airlines' operating time is significantly reduced. The results also indicate that, following network optimization, airlines tend to use smaller aircraft. Finally, we identify the characteristics of the suspended and newly generated routes after optimization. This paper has important policy implications for airline operations and network design.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102848"},"PeriodicalIF":3.9,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534217","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 : 2025-06-30DOI: 10.1016/j.jairtraman.2025.102849
Manel Ouni , Rafaa Mraihi
The inclusive growth paradigm has gained significant attention, with several organizations emphasizing its importance. However, while the concept of inclusive growth remains a topic of ongoing debate, the specific role of air transportation in promoting inclusive growth remains underexplored, particularly in its capacity to enhance accessibility, promote regional development, and integrate marginalized areas into national and global economies. This study investigates the relationship between air transportation and inclusive growth in Tunisia using annual data from 1965 to 2021. This study utilized the Autoregressive Distributed Lag (ARDL) model to analyze both short- and long-term relationships between the variables. At the same time, the wavelet coherence approach is used to examine how these relationships evolve over time and across different frequencies. The results from the ARDL model indicate that air transport, foreign direct investment, and social globalization are key determinants of inclusive growth in Tunisia. Moreover, the wavelet coherence analysis reveals that these factors positively influence inclusive growth, while the wavelet causality identifies a bidirectional causality between inclusive growth and the regressors, with variations in the timing and frequency of causality. This study contributes to the growing literature on transport infrastructure and inclusive growth by providing robust methodological insights and practical policy recommendations. These findings show the critical role of air transportation as a catalyst for sustainable and inclusive growth, emphasizing the importance of targeted investments and strategic policy interventions in Tunisia.
{"title":"Air transportation and inclusive growth in Tunisia: Evidence from Autoregressive Distributed Lag and wavelet coherence approach","authors":"Manel Ouni , Rafaa Mraihi","doi":"10.1016/j.jairtraman.2025.102849","DOIUrl":"10.1016/j.jairtraman.2025.102849","url":null,"abstract":"<div><div>The inclusive growth paradigm has gained significant attention, with several organizations emphasizing its importance. However, while the concept of inclusive growth remains a topic of ongoing debate, the specific role of air transportation in promoting inclusive growth remains underexplored, particularly in its capacity to enhance accessibility, promote regional development, and integrate marginalized areas into national and global economies. This study investigates the relationship between air transportation and inclusive growth in Tunisia using annual data from 1965 to 2021. This study utilized the Autoregressive Distributed Lag (ARDL) model to analyze both short- and long-term relationships between the variables. At the same time, the wavelet coherence approach is used to examine how these relationships evolve over time and across different frequencies. The results from the ARDL model indicate that air transport, foreign direct investment, and social globalization are key determinants of inclusive growth in Tunisia. Moreover, the wavelet coherence analysis reveals that these factors positively influence inclusive growth, while the wavelet causality identifies a bidirectional causality between inclusive growth and the regressors, with variations in the timing and frequency of causality. This study contributes to the growing literature on transport infrastructure and inclusive growth by providing robust methodological insights and practical policy recommendations. These findings show the critical role of air transportation as a catalyst for sustainable and inclusive growth, emphasizing the importance of targeted investments and strategic policy interventions in Tunisia.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102849"},"PeriodicalIF":3.9,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514265","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 : 2025-06-29DOI: 10.1016/j.jairtraman.2025.102843
Chuhao Deng, Hong-Cheol Choi, Hyunsang Park, Inseok Hwang
Research in developing data-driven models for Air Traffic Management (ATM) has gained tremendous interest in recent years. However, data-driven models are known to have long training time and require large datasets to achieve good performance, and the majority of proposed data-driven models ignores ATM system’s multi-agent characteristic. To fill the research gaps, this paper proposes a Multi-Agent Bidirectional Encoder Representations from Transformers (MA-BERT) model, which fully considers the multi-agent characteristic of the ATM system and outputs results based on all agents in the airspace. Additionally, compared to most data-driven models that are designed for a single application, the proposed MA-BERT’s encoder architecture enables it to be pre-trained through a self-supervised method and fine-tuned for a variety of data-driven ATM applications, saving a substantial amount of training time and data usage. The proposed MA-BERT is tested and compared with other widely used models using the Automatic Dependent Surveillance-Broadcast (ADS-B) data recorded in three airports in South Korea in 2019. The results show that MA-BERT can achieve much better performance than the comparison models, and by pre-training MA-BERT on a large dataset from a major airport and then fine-tuning it to other airports and applications, a significant amount of the training time can be saved. For newly adopted procedures and constructed airports where no historical data is available, the results show that the pre-trained MA-BERT can achieve high performance by updating regularly with small amount of data.
近年来，空中交通管理（ATM）数据驱动模型的研究引起了人们极大的兴趣。然而，众所周知，数据驱动模型的训练时间长，需要大量的数据集才能达到良好的性能，并且大多数提出的数据驱动模型都忽略了ATM系统的多智能体特性。为了填补研究空白，本文提出了一种多智能体双向编码器表示（Multi-Agent Bidirectional Encoder Representations from Transformers, MA-BERT）模型，该模型充分考虑了ATM系统的多智能体特性，并基于空域中所有智能体输出结果。此外，与大多数为单一应用设计的数据驱动模型相比，所提出的MA-BERT编码器架构使其能够通过自监督方法进行预训练，并针对各种数据驱动的ATM应用进行微调，从而节省了大量的训练时间和数据使用。利用2019年在韩国三个机场记录的自动相关监视广播（ADS-B）数据，对拟议的MA-BERT进行了测试，并与其他广泛使用的模型进行了比较。结果表明，与比较模型相比，MA-BERT可以获得更好的性能，并且通过在主要机场的大型数据集上预训练MA-BERT，然后对其进行微调，可以节省大量的训练时间。对于新采用的程序和没有历史数据的新建机场，结果表明，预训练的MA-BERT可以通过少量数据定期更新来获得高性能。
{"title":"Multi-agent learning for data-driven air traffic management applications","authors":"Chuhao Deng, Hong-Cheol Choi, Hyunsang Park, Inseok Hwang","doi":"10.1016/j.jairtraman.2025.102843","DOIUrl":"10.1016/j.jairtraman.2025.102843","url":null,"abstract":"<div><div>Research in developing data-driven models for Air Traffic Management (ATM) has gained tremendous interest in recent years. However, data-driven models are known to have long training time and require large datasets to achieve good performance, and the majority of proposed data-driven models ignores ATM system’s multi-agent characteristic. To fill the research gaps, this paper proposes a Multi-Agent Bidirectional Encoder Representations from Transformers (MA-BERT) model, which fully considers the multi-agent characteristic of the ATM system and outputs results based on all agents in the airspace. Additionally, compared to most data-driven models that are designed for a single application, the proposed MA-BERT’s encoder architecture enables it to be pre-trained through a self-supervised method and fine-tuned for a variety of data-driven ATM applications, saving a substantial amount of training time and data usage. The proposed MA-BERT is tested and compared with other widely used models using the Automatic Dependent Surveillance-Broadcast (ADS-B) data recorded in three airports in South Korea in 2019. The results show that MA-BERT can achieve much better performance than the comparison models, and by pre-training MA-BERT on a large dataset from a major airport and then fine-tuning it to other airports and applications, a significant amount of the training time can be saved. For newly adopted procedures and constructed airports where no historical data is available, the results show that the pre-trained MA-BERT can achieve high performance by updating regularly with small amount of data.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102843"},"PeriodicalIF":3.9,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144510993","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号