Pub Date : 2025-04-16DOI: 10.1016/j.jairtraman.2025.102787
Dimitrios Ziakkas, Hans C. Natakusuma
The research paper explores the potential benefits of integrating electric Vertical TakeOff and Landing (eVTOL) aircraft into emergency medical services (EMS) in the ASEAN-5 countries (Indonesia, Malaysia, the Philippines, Thailand, and Singapore). The study addresses significant urban traffic congestion, which hinders efficient emergency response, and evaluates how eVTOL EMS can mitigate these issues. The methodology employs a mixed-method approach over six months, combining qualitative case studies and quantitative surveys to assess public perception, operational challenges, and the effectiveness of eVTOL EMS. Key findings indicate high public support for eVTOL EMS, primarily due to anticipated faster response times and reduced traffic delays. However, challenges such as regulatory differences, infrastructure limitations, and workforce constraints must be addressed to implement eVTOL EMS successfully. The paper concludes that while eVTOL EMS shows promise, further research and strategic planning are essential to optimize its integration into the ASEAN region's urban emergency services and a proposed structure for future ICAO annexes.
{"title":"Advanced Air Mobility(AAM)and emergency services: The Association of Southeast Asian Nations(ASEAN)Case study","authors":"Dimitrios Ziakkas, Hans C. Natakusuma","doi":"10.1016/j.jairtraman.2025.102787","DOIUrl":"10.1016/j.jairtraman.2025.102787","url":null,"abstract":"<div><div>The research paper explores the potential benefits of integrating electric Vertical TakeOff and Landing (eVTOL) aircraft into emergency medical services (EMS) in the ASEAN-5 countries (Indonesia, Malaysia, the Philippines, Thailand, and Singapore). The study addresses significant urban traffic congestion, which hinders efficient emergency response, and evaluates how eVTOL EMS can mitigate these issues. The methodology employs a mixed-method approach over six months, combining qualitative case studies and quantitative surveys to assess public perception, operational challenges, and the effectiveness of eVTOL EMS. Key findings indicate high public support for eVTOL EMS, primarily due to anticipated faster response times and reduced traffic delays. However, challenges such as regulatory differences, infrastructure limitations, and workforce constraints must be addressed to implement eVTOL EMS successfully. The paper concludes that while eVTOL EMS shows promise, further research and strategic planning are essential to optimize its integration into the ASEAN region's urban emergency services and a proposed structure for future ICAO annexes.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102787"},"PeriodicalIF":3.9,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832558","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}
This paper empirically investigates the factors that impact airline performance and the effects of airline performance on domestic tourism demand considering the impact of the COVID-19 pandemic. Firstly, the Tobit model is employed to study the significant factors and underlying mechanisms that affect flight cancellation rate. Secondly, the panel vector autoregressive model (PVAR) is applied to quantitatively measure the degree and duration of the impact of COVID-19 on flight frequency and passenger numbers. Finally, the possible impact of airline performance (flight frequency) on tourism demand during the COVID-19 pandemic is further discussed. The results suggest that travel bans, the number of confirmed cases in destination, route diversity, and share of low-cost carriers’ seats are the main reasons for the rise in flight cancellation rate, while high load factors reduce flight cancellations. Meanwhile, the negative impacts of new COVID-19 cases on both flight frequency and tourism demand gradually attenuated to stability over the study period with a lag effect. In addition, as the impact of the pandemic and travel policies gradually diminishes, airline operation recovers faster and earlier than tourism demand, indicating the airline industry may play a key role in the revival of tourism. The findings contribute to the relevant debates on the ‘air access–tourism’ relationship by taking major emergencies as a quasi-natural experiment.
{"title":"Impacts of the COVID-19 pandemic on airline performance and tourism demand: Evidence from a quasi-natural experiment in Southwest China","authors":"Chuntao Wu , Hongmeng Yan , Wenjing Xue , Yonglei Jiang","doi":"10.1016/j.jairtraman.2025.102797","DOIUrl":"10.1016/j.jairtraman.2025.102797","url":null,"abstract":"<div><div>This paper empirically investigates the factors that impact airline performance and the effects of airline performance on domestic tourism demand considering the impact of the COVID-19 pandemic. Firstly, the Tobit model is employed to study the significant factors and underlying mechanisms that affect flight cancellation rate. Secondly, the panel vector autoregressive model (PVAR) is applied to quantitatively measure the degree and duration of the impact of COVID-19 on flight frequency and passenger numbers. Finally, the possible impact of airline performance (flight frequency) on tourism demand during the COVID-19 pandemic is further discussed. The results suggest that travel bans, the number of confirmed cases in destination, route diversity, and share of low-cost carriers’ seats are the main reasons for the rise in flight cancellation rate, while high load factors reduce flight cancellations. Meanwhile, the negative impacts of new COVID-19 cases on both flight frequency and tourism demand gradually attenuated to stability over the study period with a lag effect. In addition, as the impact of the pandemic and travel policies gradually diminishes, airline operation recovers faster and earlier than tourism demand, indicating the airline industry may play a key role in the revival of tourism. The findings contribute to the relevant debates on the ‘air access–tourism’ relationship by taking major emergencies as a quasi-natural experiment.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102797"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817249","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}
We propose a framework for identifying alternative airports and analyzing backup characteristics in weighted air transport networks. We compare our method with an unweighted network method to clarify its usefulness. The proposed framework enables a quantitative assessment of the impact of one airport’s closure on the entire air transport network. Specifically, we construct and analyze a directed and weighted network based on the backup characteristics of airports handling diverted traffic for a given airport closure. We apply the proposed framework to the Japanese domestic air transport network on a monthly basis from 2012 to 2021. Our results reveal heterogeneous and unidirectional alternative relations among airports, which cannot be identified by the existing method for unweighted networks. Further, our investigation reveals that the evolution of backup traffic loads of the Japanese domestic air transport can be classified into three periods according to the characteristics of major alternative airports.
{"title":"Identifying alternative airports in weighted air transport networks","authors":"Woratat Leelaworaset, Kashin Sugishita, Shinya Hanaoka","doi":"10.1016/j.jairtraman.2025.102792","DOIUrl":"10.1016/j.jairtraman.2025.102792","url":null,"abstract":"<div><div>We propose a framework for identifying alternative airports and analyzing backup characteristics in weighted air transport networks. We compare our method with an unweighted network method to clarify its usefulness. The proposed framework enables a quantitative assessment of the impact of one airport’s closure on the entire air transport network. Specifically, we construct and analyze a directed and weighted network based on the backup characteristics of airports handling diverted traffic for a given airport closure. We apply the proposed framework to the Japanese domestic air transport network on a monthly basis from 2012 to 2021. Our results reveal heterogeneous and unidirectional alternative relations among airports, which cannot be identified by the existing method for unweighted networks. Further, our investigation reveals that the evolution of backup traffic loads of the Japanese domestic air transport can be classified into three periods according to the characteristics of major alternative airports.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102792"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820527","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 : 2025-04-11DOI: 10.1016/j.jairtraman.2025.102793
Bo Sun , Zehui Xu , Ming Wei , Xin Wang
This study elaborated a tripartite evolutionary game model of civil aviation, high-speed rail (HSR), and passengers in an air-rail intermodal transport system (ARITS). It is used to find the optimal interaction between civil aviation, HSR, and passengers on non-direct journeys, as expressed in payoffs of the three players and decision-making behaviors in game. Payoff matrices of three game players were created considering travel time, fare, and mileage cost. The replicated dynamic equations were then derived to analyze the stability of the evolutionary model and the dynamic behavior of each game player under the initial status. Finally, a case of five transport corridors in China was conducted to assess the effects of such key factors as discounted fares, travel time, and mileage costs on the evolutionary trend and final strategy. The results strongly indicated that each game player would tend to choose the strategy with the highest payoff, in which civil aviation and HSR were ultimately inclined to a cooperative strategy while passengers eventually preferred to support the construction of ARITS. Besides, the variation of each game player's factors affected the trend of the tripartite evolutionary game. Still, only the discount on fares may change the final strategies of three game players, in which civil aviation would be more likely to change into a competitive strategy due to individual interests.
{"title":"A study on the strategic behavior of players participating in air-rail intermodal transportation based on evolutionary games","authors":"Bo Sun , Zehui Xu , Ming Wei , Xin Wang","doi":"10.1016/j.jairtraman.2025.102793","DOIUrl":"10.1016/j.jairtraman.2025.102793","url":null,"abstract":"<div><div>This study elaborated a tripartite evolutionary game model of civil aviation, high-speed rail (HSR), and passengers in an air-rail intermodal transport system (ARITS). It is used to find the optimal interaction between civil aviation, HSR, and passengers on non-direct journeys, as expressed in payoffs of the three players and decision-making behaviors in game. Payoff matrices of three game players were created considering travel time, fare, and mileage cost. The replicated dynamic equations were then derived to analyze the stability of the evolutionary model and the dynamic behavior of each game player under the initial status. Finally, a case of five transport corridors in China was conducted to assess the effects of such key factors as discounted fares, travel time, and mileage costs on the evolutionary trend and final strategy. The results strongly indicated that each game player would tend to choose the strategy with the highest payoff, in which civil aviation and HSR were ultimately inclined to a cooperative strategy while passengers eventually preferred to support the construction of ARITS. Besides, the variation of each game player's factors affected the trend of the tripartite evolutionary game. Still, only the discount on fares may change the final strategies of three game players, in which civil aviation would be more likely to change into a competitive strategy due to individual interests.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102793"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817163","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 : 2025-04-11DOI: 10.1016/j.jairtraman.2025.102794
Sebastian Wandelt, Shuang Wang, Xinyue Chen, Changhong Zheng, Shuming Chang, Xiaoqian Sun
Air transportation and its subsystems constitute complex systems with various interactions between its components. This leads to an ubiquitous presence of networks in many aspects of the industry, be it in the context of connectivity, efficiency, or resilience. This study presents a comprehensive survey of existing literature about networks and their usage in air transportation, highlighting the critical role that network structures play for the industry. Our review encompasses various types and dimensions of air transport-related networks. The application areas in our review cover, among others, connectivity/efficiency analysis, resilience, delay propagation, disease spreading, strategic airline planning, as well as operational airline scheduling. For each subject, we highlight advancements in network modeling and simulation techniques, alongside pointers into empirical studies that provide insights into the real-world application of network theories in air transport. By synthesizing findings from diverse research streams and publication venues, our review aims to identify existing overlaps/potential synergies and also reports on emerging trends, gaps, and future research directions.
{"title":"Network structures in air transportation: A comprehensive review of applications and challenges","authors":"Sebastian Wandelt, Shuang Wang, Xinyue Chen, Changhong Zheng, Shuming Chang, Xiaoqian Sun","doi":"10.1016/j.jairtraman.2025.102794","DOIUrl":"10.1016/j.jairtraman.2025.102794","url":null,"abstract":"<div><div>Air transportation and its subsystems constitute complex systems with various interactions between its components. This leads to an ubiquitous presence of networks in many aspects of the industry, be it in the context of connectivity, efficiency, or resilience. This study presents a comprehensive survey of existing literature about networks and their usage in air transportation, highlighting the critical role that network structures play for the industry. Our review encompasses various types and dimensions of air transport-related networks. The application areas in our review cover, among others, connectivity/efficiency analysis, resilience, delay propagation, disease spreading, strategic airline planning, as well as operational airline scheduling. For each subject, we highlight advancements in network modeling and simulation techniques, alongside pointers into empirical studies that provide insights into the real-world application of network theories in air transport. By synthesizing findings from diverse research streams and publication venues, our review aims to identify existing overlaps/potential synergies and also reports on emerging trends, gaps, and future research directions.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102794"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817250","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 : 2025-04-11DOI: 10.1016/j.jairtraman.2025.102780
Mohammad Sadrani , Filippos Adamidis , Laurie A. Garrow , Constantinos Antoniou
Urban Air Mobility (UAM) is a transport system enabling the movement of people and goods within urban areas using electric vertical take-off and landing (eVTOL) aircraft. Nonetheless, this concept remains an emerging technology with various challenges that can hinder its implementation. This research introduces a Multi-Criteria Decision-Making (MCDM) framework to prioritize barriers to UAM implementation in Germany and the USA. We identify 26 barriers across technological, economic, social, environmental, and operational aspects through a comprehensive literature review and expert interviews. Using the Fuzzy Best-Worst Method (FBWM), we determine the weight of each barrier based on input from industry and academic experts in Germany and the USA. Our findings reveal that economic aspects pose the greatest challenge in Germany, followed by social, operational, technological, and environmental aspects. In the USA, operational aspects are the most significant, followed by technological, economic, social, and environmental aspects. The operational aspect shows the largest difference between the two countries, while the environmental aspect shows the least. Globally, the top three barriers in Germany are price affordability, investment uncertainty, and user acceptance concerns. In the USA, the top three barriers are airspace utilization challenges, remote/autonomous operations, and system safety and cybersecurity issues, which rank tenth, twelfth, and sixteenth, respectively, in Germany. We also discuss the potential implications of our findings, offering strategies to effectively address high-priority barriers.
{"title":"Challenges in urban air mobility implementation: A comparative analysis of barriers in Germany and the United States","authors":"Mohammad Sadrani , Filippos Adamidis , Laurie A. Garrow , Constantinos Antoniou","doi":"10.1016/j.jairtraman.2025.102780","DOIUrl":"10.1016/j.jairtraman.2025.102780","url":null,"abstract":"<div><div>Urban Air Mobility (UAM) is a transport system enabling the movement of people and goods within urban areas using electric vertical take-off and landing (eVTOL) aircraft. Nonetheless, this concept remains an emerging technology with various challenges that can hinder its implementation. This research introduces a Multi-Criteria Decision-Making (MCDM) framework to prioritize barriers to UAM implementation in Germany and the USA. We identify 26 barriers across technological, economic, social, environmental, and operational aspects through a comprehensive literature review and expert interviews. Using the Fuzzy Best-Worst Method (FBWM), we determine the weight of each barrier based on input from industry and academic experts in Germany and the USA. Our findings reveal that economic aspects pose the greatest challenge in Germany, followed by social, operational, technological, and environmental aspects. In the USA, operational aspects are the most significant, followed by technological, economic, social, and environmental aspects. The operational aspect shows the largest difference between the two countries, while the environmental aspect shows the least. Globally, the top three barriers in Germany are price affordability, investment uncertainty, and user acceptance concerns. In the USA, the top three barriers are airspace utilization challenges, remote/autonomous operations, and system safety and cybersecurity issues, which rank tenth, twelfth, and sixteenth, respectively, in Germany. We also discuss the potential implications of our findings, offering strategies to effectively address high-priority barriers.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102780"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816818","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 : 2025-04-11DOI: 10.1016/j.jairtraman.2025.102788
Maarten Beltman , Marta Ribeiro , Jasper de Wilde , Junzi Sun
Punctuality is a key performance indicator for any airline, especially hub-and-spoke airlines, given their focus on short passenger connections. Flights that are delayed at departure need to compensate for lost time whilst airborne. Because fuelling takes place well before scheduled departure, predicted departure delays determine the planned fuel amounts for en-route speed optimization. To prevent unnecessary fuel burn, airlines benefit from highly accurate departure delay predictions. This study aims to extend previous work on airline departure delay forecasting to a dynamic and probabilistic domain, whilst incorporating novel day-of-operations airline information to further minimize prediction errors. Random Forest, CatBoost, and Deep Neural Network models are proposed for a case study on departure flights of a major hub-and-spoke airline from its hub airport between 1 January 2020 and 1 August 2023. The Random Forest model is selected for its probabilistic performance and high accuracy in predicting delays between 5 and 25 min, for which en-route speed optimization has the largest effect. At the 90 min prediction horizon, the model reaches a Mean Absolute Error of 8.46 min and a Root Mean Square Error of 11.91 min. For 76% of flights, the actual delay is within the predicted probability distribution range. Finally, this study puts a strong emphasis on explainability. Flight dispatchers are therefore provided with the main factors impacting the prediction, explaining the context of the flight. The versatility of the model is demonstrated in two shadow runs within the procedures of an international airline, where delays caused by familiar and unfamiliar factors were successfully predicted.
{"title":"Dynamically forecasting airline departure delay probability distributions for individual flights using supervised learning","authors":"Maarten Beltman , Marta Ribeiro , Jasper de Wilde , Junzi Sun","doi":"10.1016/j.jairtraman.2025.102788","DOIUrl":"10.1016/j.jairtraman.2025.102788","url":null,"abstract":"<div><div>Punctuality is a key performance indicator for any airline, especially hub-and-spoke airlines, given their focus on short passenger connections. Flights that are delayed at departure need to compensate for lost time whilst airborne. Because fuelling takes place well before scheduled departure, predicted departure delays determine the planned fuel amounts for en-route speed optimization. To prevent unnecessary fuel burn, airlines benefit from highly accurate departure delay predictions. This study aims to extend previous work on airline departure delay forecasting to a dynamic and probabilistic domain, whilst incorporating novel day-of-operations airline information to further minimize prediction errors. Random Forest, CatBoost, and Deep Neural Network models are proposed for a case study on departure flights of a major hub-and-spoke airline from its hub airport between 1 January 2020 and 1 August 2023. The Random Forest model is selected for its probabilistic performance and high accuracy in predicting delays between 5 and 25 min, for which en-route speed optimization has the largest effect. At the 90 min prediction horizon, the model reaches a Mean Absolute Error of 8.46 min and a Root Mean Square Error of 11.91 min. For 76% of flights, the actual delay is within the predicted probability distribution range. Finally, this study puts a strong emphasis on explainability. Flight dispatchers are therefore provided with the main factors impacting the prediction, explaining the context of the flight. The versatility of the model is demonstrated in two shadow runs within the procedures of an international airline, where delays caused by familiar and unfamiliar factors were successfully predicted.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102788"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820526","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 : 2025-04-08DOI: 10.1016/j.jairtraman.2025.102790
Fanrong Sun , Di Shen , Dikai Yang , Meize Dai
To establish an impartial air safety evaluation system, this study translated qualitative air safety assessment into quantitative probability estimation using machine learning and historical data. A quantitative ATC safety assessment framework was formulated based on the SHEL model, complemented by a cloud model for safety evaluation drawing on fuzzy and uncertainty theories. A copula function analyzed correlations among cloud model indices, refined the model, and the entropy weight method determined membership weights. Ordered logistic regression categorized ATC safety levels, while genetic algorithms extracted factors' attributes and principal component analysis reduced model complexity. Ultimately, a semi-supervised learning-based collaborative ATC safety evaluation system was developed, enhancing the cloud model's generalizability and precision. Cross-validation and multifaceted verification confirmed the system's objectivity and reliability.
{"title":"Research on safety assessment of air traffic control in small and medium airports based on machine learning","authors":"Fanrong Sun , Di Shen , Dikai Yang , Meize Dai","doi":"10.1016/j.jairtraman.2025.102790","DOIUrl":"10.1016/j.jairtraman.2025.102790","url":null,"abstract":"<div><div>To establish an impartial air safety evaluation system, this study translated qualitative air safety assessment into quantitative probability estimation using machine learning and historical data. A quantitative ATC safety assessment framework was formulated based on the SHEL model, complemented by a cloud model for safety evaluation drawing on fuzzy and uncertainty theories. A copula function analyzed correlations among cloud model indices, refined the model, and the entropy weight method determined membership weights. Ordered logistic regression categorized ATC safety levels, while genetic algorithms extracted factors' attributes and principal component analysis reduced model complexity. Ultimately, a semi-supervised learning-based collaborative ATC safety evaluation system was developed, enhancing the cloud model's generalizability and precision. Cross-validation and multifaceted verification confirmed the system's objectivity and reliability.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102790"},"PeriodicalIF":3.9,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792490","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 : 2025-04-05DOI: 10.1016/j.jairtraman.2025.102800
Shuai Yue , Weijun Liao , Qing Ji , Chunan Wang
Using daily flight data and annual financial indicators, this paper investigates the effect of carriers’ financial performance, measured by profitability, growth, and operational capacity, on aviation carbon emissions. The findings reveal that while increased profitability does not immediately reduce total emissions, it can slow the rate of carbon growth. In terms of carbon efficiency, growth capacity enhances emission efficiency, whereas a decline in operational capacity significantly degrades it. Additionally, carriers with different service patterns, geographic locations, and market conditions exhibit varying sensitivities to financial performance. Notably, full-service carriers in the Americas and developed markets produce higher emissions in response to the same improvements in profitability or growth.
{"title":"The effect of financial performance on aviation carbon emissions","authors":"Shuai Yue , Weijun Liao , Qing Ji , Chunan Wang","doi":"10.1016/j.jairtraman.2025.102800","DOIUrl":"10.1016/j.jairtraman.2025.102800","url":null,"abstract":"<div><div>Using daily flight data and annual financial indicators, this paper investigates the effect of carriers’ financial performance, measured by profitability, growth, and operational capacity, on aviation carbon emissions. The findings reveal that while increased profitability does not immediately reduce total emissions, it can slow the rate of carbon growth. In terms of carbon efficiency, growth capacity enhances emission efficiency, whereas a decline in operational capacity significantly degrades it. Additionally, carriers with different service patterns, geographic locations, and market conditions exhibit varying sensitivities to financial performance. Notably, full-service carriers in the Americas and developed markets produce higher emissions in response to the same improvements in profitability or growth.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"126 ","pages":"Article 102800"},"PeriodicalIF":3.9,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783168","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 : 2025-04-05DOI: 10.1016/j.jairtraman.2025.102789
Sara Varenna, Haonan Li, Marta Ribeiro, Bruno F. Santos
The complexity of airline operations requires operations planning to be divided into multiple problems solved sequentially by the respective departments. This is particularly the case for (1) network planning and (2) maintenance planning. Despite the close interaction of these two departments, airlines typically evaluate plans from both domains separately. However, an integrated perspective is necessary to develop robust plans and effective recovery policies in this intrinsically uncertain environment. This paper presents a new modular, stochastic, discrete event simulation model of airline operations named ANEMOS (Airline Network and Maintenance Operations Simulation). ANEMOS contains both network and maintenance dynamics, allowing the evaluation of plans, policies, and scenarios from both domains. The model is validated using data from a major European airline. We show that the simulated results closely resemble the airline’s historical operational performance. ANEMOS is tested with a use-case investigating the effects of adding a second reserve aircraft to a fleet of fifty wide-body aircraft. The results show that the second reserve is capable of reducing cancellations by 55%. However, such does not cover the lost revenue associated with keeping an aircraft non-operational for a part of the time.
{"title":"Stochastic discrete event simulation of airline network and maintenance operations","authors":"Sara Varenna, Haonan Li, Marta Ribeiro, Bruno F. Santos","doi":"10.1016/j.jairtraman.2025.102789","DOIUrl":"10.1016/j.jairtraman.2025.102789","url":null,"abstract":"<div><div>The complexity of airline operations requires operations planning to be divided into multiple problems solved sequentially by the respective departments. This is particularly the case for (1) network planning and (2) maintenance planning. Despite the close interaction of these two departments, airlines typically evaluate plans from both domains separately. However, an integrated perspective is necessary to develop robust plans and effective recovery policies in this intrinsically uncertain environment. This paper presents a new modular, stochastic, discrete event simulation model of airline operations named ANEMOS (Airline Network and Maintenance Operations Simulation). ANEMOS contains both network and maintenance dynamics, allowing the evaluation of plans, policies, and scenarios from both domains. The model is validated using data from a major European airline. We show that the simulated results closely resemble the airline’s historical operational performance. ANEMOS is tested with a use-case investigating the effects of adding a second reserve aircraft to a fleet of fifty wide-body aircraft. The results show that the second reserve is capable of reducing cancellations by 55%. However, such does not cover the lost revenue associated with keeping an aircraft non-operational for a part of the time.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"125 ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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