Journal of Air Transport Management最新文献_第3页

The impacts of airport economic zones on local urban development in China 中国空港经济区对地方城市发展的影响

IF 3.6 2区工程技术

Journal of Air Transport Management Pub Date : 2025-08-05 DOI: 10.1016/j.jairtraman.2025.102875

Jianhua Pi , Xingjian Liu , Will W. Qiang , Chris Webster

{"title":"The impacts of airport economic zones on local urban development in China","authors":"Jianhua Pi , Xingjian Liu , Will W. Qiang , Chris Webster","doi":"10.1016/j.jairtraman.2025.102875","DOIUrl":"10.1016/j.jairtraman.2025.102875","url":null,"abstract":"<div><div>China's implementation of Airport Economic Zones (AEZs) seeks to capitalize on aviation infrastructure for local development. While existing studies have assessed airport-related urban development in China, the specific impacts of AEZ policies on local economies remain underexamined. To this end, our study evaluates the impacts of AEZs on local economies, utilizing a panel dataset of 62 prefecture-level cities in China spanning 2000–2019. We employ a heterogeneous timing difference-in-differences method to assess localized economic impacts of AEZs, considering three specific treatment timings. The results show that AEZs have positive but limited impacts on localized economic growth, particularly evident in increased economic activities around airports. Local economic impacts of more recently announced national airport economic demonstration zones are insignificant in the analysis. Meanwhile, the establishment of other kinds of development zones around airports fosters nearby economic activity and employment in airport-related sectors, oftentimes with higher levels of statistical significance. These findings add empirical evidence for airport region development's impact on economy and underscore the importance of institutional support for maximizing AEZs' contributions to urban development.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102875"},"PeriodicalIF":3.6,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771884","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}

引用次数: 0

Data-driven governing equation identification of near terminal air traffic flow dynamics 数据驱动的近航站楼空中交通流动力学控制方程辨识

IF 3.6 2区工程技术

Journal of Air Transport Management Pub Date : 2025-08-05 DOI: 10.1016/j.jairtraman.2025.102871

Qihang Xu, Yutian Pang, Zhiming Zhang, Yongming Liu

{"title":"Data-driven governing equation identification of near terminal air traffic flow dynamics","authors":"Qihang Xu, Yutian Pang, Zhiming Zhang, Yongming Liu","doi":"10.1016/j.jairtraman.2025.102871","DOIUrl":"10.1016/j.jairtraman.2025.102871","url":null,"abstract":"<div><div>Efficient air traffic management (ATM) relies on accurately understanding and predicting air traffic patterns and delays. While deep learning methods have shown promise in prediction tasks, they often lack interpretability and require large volumes of data. This paper presents a novel, data-driven framework to model and predict near-terminal traffic flow and flight delays by identifying the underlying partial differential equations (PDEs) that govern air traffic dynamics. Our approach leverages aircraft trajectory patterns and density distributions to estimate probability density functions (PDFs) of travel times. Using sparse regression for system identification, we learn the governing equations that capture the temporal evolution of density and travel time distributions. These equations are then embedded into a Physics-Informed Neural Network (PINN) for integrated prediction. Experiments with real-world data validate the framework’s effectiveness in accurately identifying governing PDEs and forecasting flight delays. By combining physical modeling with deep learning, the proposed method improves both the interpretability and generalizability of AI applications in ATM, offering practical value in enhancing airport efficiency and operational decision-making.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102871"},"PeriodicalIF":3.6,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779335","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}

引用次数: 0

Flight schedules under partnership: The effects of capacity purchase agreements on airline schedule buffers 伙伴关系下的航班计划：运力购买协议对航空公司计划缓冲的影响

IF 3.6 2区工程技术

Journal of Air Transport Management Pub Date : 2025-08-05 DOI: 10.1016/j.jairtraman.2025.102876

Jules Yimga

引用次数: 0

Passenger perceptions of Artificial Intelligence in airline operations: Implications for air transport management 乘客对航空公司运营中人工智能的看法：对航空运输管理的影响

IF 3.6 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-31 DOI: 10.1016/j.jairtraman.2025.102874

Joan-Francesc Fondevila-Gascón , Óscar Gutiérrez-Aragón , David Lopez-Lopez , Gonzalo Curiel-Barrios , Júlia Alabart-Algueró

{"title":"Passenger perceptions of Artificial Intelligence in airline operations: Implications for air transport management","authors":"Joan-Francesc Fondevila-Gascón , Óscar Gutiérrez-Aragón , David Lopez-Lopez , Gonzalo Curiel-Barrios , Júlia Alabart-Algueró","doi":"10.1016/j.jairtraman.2025.102874","DOIUrl":"10.1016/j.jairtraman.2025.102874","url":null,"abstract":"<div><div>Artificial Intelligence (AI) is reshaping the aviation industry, driving efficiency, automation, and innovation across multiple operational domains. This study examines commercial airline passengers’ perceptions of AI’s role in addressing key industry challenges, including air traffic management, predictive maintenance, passenger experience, and sustainability. Using a quantitative approach, a survey was conducted among 320 airline passengers in Spain to assess their attitudes toward AI-driven applications in aviation. The findings reveal strong support for AI in optimizing flight operations, reducing delays, and enhancing security procedures. However, significant skepticism remains regarding AI’s autonomy in decision-making, particularly in pilot replacement and automated flight rerouting. Statistical analyses indicate that younger and frequent travelers exhibit higher confidence in AI’s potential, whereas older passengers demonstrate greater reluctance toward AI-driven automation. Additionally, AI is perceived as a crucial enabler of environmental sustainability, with respondents acknowledging its role in reducing fuel consumption and emissions. These insights provide valuable implications for policymakers, airlines, and technology developers seeking to align AI adoption with passenger expectations while ensuring safety, efficiency, and regulatory compliance. The study highlights the need for a balanced approach that integrates AI’s technological advancements with human oversight to foster trust and acceptance in the future of AI-powered aviation.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102874"},"PeriodicalIF":3.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750530","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}

引用次数: 0

Time series prediction of airport operational resilience under severe weather conditions 恶劣天气条件下机场运行弹性的时间序列预测

IF 3.6 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-31 DOI: 10.1016/j.jairtraman.2025.102862

Yuhui Zhang , Lili Liu , Xiong Peng

{"title":"Time series prediction of airport operational resilience under severe weather conditions","authors":"Yuhui Zhang , Lili Liu , Xiong Peng","doi":"10.1016/j.jairtraman.2025.102862","DOIUrl":"10.1016/j.jairtraman.2025.102862","url":null,"abstract":"<div><div>Airport operational resilience is a crucial metric reflecting an airport’s capacity to adapt to external shocks, essential for maintaining safety and operational efficiency. While there has been research on airport resilience under various severe weather conditions, the specific contributing factors and their impacts remain inadequately explored. This study develops a comprehensive index system that integrates airport performance and meteorological data, using a random forest algorithm to quantify the influence of various factors on airport resilience across five types of severe weather. Furthermore, a PatchTST(Patch time series Transformer)-based time series model improved by the Cauchy loss function is proposed to accurately predict airport operational resilience. Focusing on severe weather events during the period from January 2023 to July 2024 at Dallas-Fort Worth International Airport in the United States. To mitigate multicollinearity, variables with high Pearson correlation and variance inflation factor (VIF) values were removed prior to analysis. Feature importance results reveal that hourly flight movements (HFM) consistently hold the highest importance across weather types, while temperature (TEMP), relative humidity (RHUM) and air pressure (PRES) exhibit relatively higher meteorological influence despite limited overall impact. The optimal Cauchy-PatchTST model, with a look-back window of <span><math><mrow><mi>L</mi><mo>=</mo><mn>36</mn></mrow></math></span> and a forecast length of <span><math><mrow><mi>T</mi><mo>=</mo><mn>1</mn></mrow></math></span>, outperforms the traditional PatchTST model with MSE loss, three Transformer-based models and other optimized machine learning algorithms, achieving a 15.49% to 94.10% reduction in MAE on the test set. This study provides critical indicator analysis for airports across various severe weather conditions and offers reliable resilience data to support future operations management.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102862"},"PeriodicalIF":3.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739346","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}

引用次数: 0

Profit Efficiency: Insight into airline business models and strategic choices 利润效率：洞察航空公司的商业模式和战略选择

IF 3.9 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-22 DOI: 10.1016/j.jairtraman.2025.102863

Fecri Karanki , Roger Schaufele

{"title":"Profit Efficiency: Insight into airline business models and strategic choices","authors":"Fecri Karanki , Roger Schaufele","doi":"10.1016/j.jairtraman.2025.102863","DOIUrl":"10.1016/j.jairtraman.2025.102863","url":null,"abstract":"<div><div>Following a challenging start to the 21st century, airlines rebounded to achieve record profits in the aftermath of the Great Recession (2007–2009). While profitability refers to the absolute financial gains of a firm, profit efficiency is a measure of how effectively a firm converts its resources into maximum potential profit, given its operating environment and input prices. These distinct economic concepts raise key questions about airline strategies: Can airlines maximize their profits? Which business models achieve higher profit efficiency? What factors influence their profit efficiency? This study addresses these questions using a stochastic profit efficiency model based on data from U.S. airlines spanning from 2009 to 2019. Our findings reveal that the U.S. airline industry exhibits an average profit efficiency of 93.2 %. Low-Cost Carriers (LCCs) have a higher mean efficiency score of 98.7 % while Full-Service Airlines (FSAs) follow them with 95.3 %. Ultra-Low-Cost Carriers (ULCCs) have the lowest profit efficiency at 86.1 %. Finally, LCCs have demonstrated more stable profit efficiency over the years. In addition, ancillary revenues positively impact the profit efficiency, indicating higher markup resulting from add-on pricing. The strategies implemented after the Great Recession—such as capacity discipline and mergers—have significantly increased profit efficiency while the airport network expansion result in lower profit inefficiency. Overall, this study highlights the extent of profit efficiency for the U.S. airline industry and identifies the key factors influencing it.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102863"},"PeriodicalIF":3.9,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679478","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}

引用次数: 0

Route expansion trends, performances and driving factors of Chinese low-cost carriers 中国低成本航空公司航线扩张趋势、表现及驱动因素

IF 3.9 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-21 DOI: 10.1016/j.jairtraman.2025.102861

Chuntao Wu, Xiaohe He, Wenjing Xue

引用次数: 0

Multi-agent task allocation and path planning for autonomous ground support equipment 自主地面保障设备多智能体任务分配与路径规划

IF 3.9 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-18 DOI: 10.1016/j.jairtraman.2025.102855

Manouk van der Zwan , Gülçin Ermiş, Alexei Sharpanskykh

{"title":"Multi-agent task allocation and path planning for autonomous ground support equipment","authors":"Manouk van der Zwan , Gülçin Ermiş, Alexei Sharpanskykh","doi":"10.1016/j.jairtraman.2025.102855","DOIUrl":"10.1016/j.jairtraman.2025.102855","url":null,"abstract":"<div><div>We aim to contribute to the automation of ground handling tasks using autonomous ground support equipment (GSE) at airports. Automation of airside operations has recently become critical for the airports to achieve higher levels of safety and efficiency under growing traffic demand and requires solving a complex scheduling and path planning problem. To address this problem, we present a multi-agent task allocation and path planning model for handling airside operations on the apron. In the problem, the ground handling tasks are to be allocated to the equipment, the trips of vehicles should be scheduled within specific time windows considering the flight schedules, and the collisions of vehicles on the apron and service roads should be avoided. We present a centralized multi-agent task allocation and routing model which aims to optimize the allocation and routing of various types of ground handling tasks over a heterogeneous set of GSE vehicles. We convert the allocation and routing problem into vehicle routing problem with time windows, pick-ups, deliveries and solve the problem using a warm start mixed integer linear programming (MILP) model. We also introduce a nonlinear objective function which converts the MILP model into a mixed integer nonlinear programming (MINLP) model, to minimize the time service locations at the stands are occupied. Then, we solve the corresponding path finding problem to find collision free paths for the GSE, by the multi-agent path finding model. The proposed model outperforms the decentralized approach in previous research regarding the allocation rate of assigning tasks to vehicles and the performance indicators of finding conflict free paths, and in CPU time. The mean deviations from shortest paths were considerably small in path planning which means that the solution quality was high. Furthermore, the CPU time of allocating tasks has been reduced by 48% compared to the CPU time of decentralized allocation.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102855"},"PeriodicalIF":3.9,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655329","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}

引用次数: 0

An investigation of the relationship among weather, low-level wind shear and aircraft go-around at Jeju International Airport in Korea 济州岛国际机场天气、低层风切变与飞机复飞关系的研究

IF 3.9 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-18 DOI: 10.1016/j.jairtraman.2025.102860

Jinho Cho , Yonghwa Lee , Hojong Baik , Janghoon Park

{"title":"An investigation of the relationship among weather, low-level wind shear and aircraft go-around at Jeju International Airport in Korea","authors":"Jinho Cho , Yonghwa Lee , Hojong Baik , Janghoon Park","doi":"10.1016/j.jairtraman.2025.102860","DOIUrl":"10.1016/j.jairtraman.2025.102860","url":null,"abstract":"<div><div>Wind shear (WS) refers to an abrupt change in wind speed and/or direction, whether in a vertical or horizontal direction. In particular, low-level wind shear (hereafter LLWS) is a type of WS that occurs at or below an altitude of approximately 1600 ft (500 m) and thus affects aircraft operations during landing or take-off phases. Jeju International Airport (CJU) is well-known for experiencing frequent LLWS and consequent occurrence of go-around (GA) operations (also referred to as missed approach). LLWS is known to be elusive and thus difficult to predict. Most previous studies are concerned with elucidating LLWS from a meteorological angle, without considering its potential effects on flight operations. In this study, we investigate the weather conditions that lead to LLWS at CJU airport and then seek the linkage between LLWS and go-around operations. General weather information and flight records containing aircraft speed, altitude, and specific weather observations during GA at CJU airport are collected. We empirically categorize five wind patterns that contribute to severe LLWS and necessitate go-around operations. In this paper, we drive a probability table that summarizes the chances of go-around operations according to the wind direction and speed. We also discuss limitations and areas for future research.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"129 ","pages":"Article 102860"},"PeriodicalIF":3.9,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655328","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}

引用次数: 0

Reconsidering airport economic impact assessments: A bottom-up comparative analysis of Belgian airports 重新考虑机场经济影响评估：比利时机场自下而上的比较分析

IF 3.9 2区工程技术

Journal of Air Transport Management Pub Date : 2025-07-17 DOI: 10.1016/j.jairtraman.2025.102854

Jolien Pauwels , Sven Buyle , Wouter Dewulf , Bart Jourquin

{"title":"Reconsidering airport economic impact assessments: A bottom-up comparative analysis of Belgian airports","authors":"Jolien Pauwels , Sven Buyle , Wouter Dewulf , Bart Jourquin","doi":"10.1016/j.jairtraman.2025.102854","DOIUrl":"10.1016/j.jairtraman.2025.102854","url":null,"abstract":"<div><div>This study analyses and compares the economic impact of Belgium's five commercial airports on their region and country. The airports represent different types, including Belgium's main airport, Brussels Airport and four regional airports: a low-cost regional airport (Brussels South Charleroi Airport), a specialised cargo regional airport (Liège Airport), and two small regional airports (Antwerp Airport and Ostend-Bruges Airport). The economic impact is measured through input-output analysis, which assesses added value and employment on a direct, indirect, and induced level. To improve accuracy, we employ a bottom-up approach that links company-level employment and added value data to the input-output framework via NACE classifications. Additionally, a Monte Carlo sensitivity analysis is introduced to strengthen the robustness of our findings.</div><div>Our results demonstrate significant differences in the airports' economic contributions based on airport size and operational focus, with Liège Airport's cargo specialisation generating a particularly strong regional impact. These findings lead to a broader discussion on airport subsidies based on the economic impact. Beyond the Belgian context, our bottom-up approach provides a replicable framework for more precise airport impact assessments.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"128 ","pages":"Article 102854"},"PeriodicalIF":3.9,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144656885","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}

引用次数: 0