Journal of Air Transport Management最新文献

A privacy-preserving federated learning approach for airline upgrade optimization 优化航空公司升舱的隐私保护联合学习方法

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-10-24 DOI: 10.1016/j.jairtraman.2024.102693

Purpose

A key issue of making upgrade decisions is to match the most relevant upgrade offers to the right customers at the right time. To optimize upgrade strategies and profitability, companies seek to break “data silos” between themselves and other business partners for a more holistic view of customers' consumption experiences. However, multi-source data fusion may lead to potential privacy leakage. To overcome these two challenges in data silos and privacy protection, this study introduced a privacy-preserving federated learning (FL) approach and explained the process of using FL in modeling airline passengers’ willingness to pay for upgrade offers.

Design/methodology/approach

Federated learning is a new confidential computing technique that allows companies to train a model cooperatively by exchanging model parameters instead of the actual raw data, which might include customers' privacy sensitive information. Using a case study of a Chinese airline company, this study demonstrated how FL-based upgrade models using multi-source data can be developed to improve the accuracy of predicting customers' willingness to pay for upgrades while preserving customers’ personal data privacy.

Findings

Comparing with traditional unilateral model using single-source data, the federated logistic regression and SecureBoost models demonstrate better model performance. This indicates that the proposed FL approach can enhance the accuracy of modeling airline passengers' willingness to pay for upgrade offers while preserving passengers’ data privacy. The findings also show that the FL-based models generally took longer running time than the traditional unilateral model due to the design of FL approach in ensuring data privacy.

Originality

This study contributes to the literature of upgrade optimization by introducing the new FL approach for developing machining learning models to predict customers’ reaction to upgrade offers. Although we focus on the airline industry in our case study, the proposed FL approach can be applied to other industries with a similar issue of upgrade optimization such as hotels or cruise lines, and car rental.

目的升级决策的一个关键问题是在正确的时间向正确的客户提供最相关的升级服务。为了优化升级策略和盈利能力，企业寻求打破自身与其他业务合作伙伴之间的 "数据孤岛"，以更全面地了解客户的消费体验。然而，多源数据融合可能会导致潜在的隐私泄露。为了克服数据孤岛和隐私保护这两大挑战，本研究引入了一种保护隐私的联合学习（FL）方法，并解释了使用联合学习对航空公司乘客的升级优惠支付意愿进行建模的过程。设计/方法/途径联合学习是一种新的保密计算技术，它允许公司通过交换模型参数而不是实际原始数据（可能包括客户的隐私敏感信息）来合作训练模型。本研究以中国某航空公司为案例，展示了如何利用多源数据开发基于联合学习的升舱模型，以提高预测客户升舱付费意愿的准确性，同时保护客户的个人数据隐私。这表明，所提出的 FL 方法可以在保护乘客数据隐私的同时，提高航空公司乘客为升舱优惠付费意愿建模的准确性。研究结果还表明，由于 FL 方法在确保数据隐私方面的设计，基于 FL 的模型通常比传统的单边模型需要更长的运行时间。本研究通过引入新的 FL 方法来开发加工学习模型，以预测客户对升舱优惠的反应，为升舱优化方面的文献做出了贡献。虽然我们的案例研究侧重于航空业，但所提出的 FL 方法也可应用于其他具有类似升级优化问题的行业，如酒店、邮轮公司和汽车租赁业。

{"title":"A privacy-preserving federated learning approach for airline upgrade optimization","authors":"","doi":"10.1016/j.jairtraman.2024.102693","DOIUrl":"10.1016/j.jairtraman.2024.102693","url":null,"abstract":"<div><h3>Purpose</h3><div>A key issue of making upgrade decisions is to match the most relevant upgrade offers to the right customers at the right time. To optimize upgrade strategies and profitability, companies seek to break “data silos” between themselves and other business partners for a more holistic view of customers' consumption experiences. However, multi-source data fusion may lead to potential privacy leakage. To overcome these two challenges in data silos and privacy protection, this study introduced a privacy-preserving federated learning (FL) approach and explained the process of using FL in modeling airline passengers’ willingness to pay for upgrade offers.</div></div><div><h3>Design/methodology/approach</h3><div>Federated learning is a new confidential computing technique that allows companies to train a model cooperatively by exchanging model parameters instead of the actual raw data, which might include customers' privacy sensitive information. Using a case study of a Chinese airline company, this study demonstrated how FL-based upgrade models using multi-source data can be developed to improve the accuracy of predicting customers' willingness to pay for upgrades while preserving customers’ personal data privacy.</div></div><div><h3>Findings</h3><div>Comparing with traditional unilateral model using single-source data, the federated logistic regression and SecureBoost models demonstrate better model performance. This indicates that the proposed FL approach can enhance the accuracy of modeling airline passengers' willingness to pay for upgrade offers while preserving passengers’ data privacy. The findings also show that the FL-based models generally took longer running time than the traditional unilateral model due to the design of FL approach in ensuring data privacy.</div></div><div><h3>Originality</h3><div>This study contributes to the literature of upgrade optimization by introducing the new FL approach for developing machining learning models to predict customers’ reaction to upgrade offers. Although we focus on the airline industry in our case study, the proposed FL approach can be applied to other industries with a similar issue of upgrade optimization such as hotels or cruise lines, and car rental.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530726","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}

引用次数: 0

Exploring prediction accuracy for optimal taxi times in airport operations using various machine learning models 利用各种机器学习模型探索机场运营中最佳滑行时间的预测精度

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-10-23 DOI: 10.1016/j.jairtraman.2024.102684

Understanding delay conditions and making accurate predictions are essential for optimizing turnaround and taxi times, which in turn reduces fuel consumption and lowers CO₂ emissions in airport operations. However, while existing research has explored the impact of various prediction models on airport operations, it often overlooks the performance of Collaborative Decision Making (CDM) variables when discussing delay conditions. The implementation of CDM at major European airports has led to a milestone-based approach within airport operations, particularly in the turnaround operations, segmenting these operations with unique features. The purpose of this paper is to systematically investigate the efficacy of various machine learning techniques, such as linear regression, regression trees, random forests, elastic nets, and multi-layer perceptrons (MLP), in accurately predicting delay categories within the CDM framework. For this purpose, we analyzed CDM operational data from Madrid Airport, with at least 166,185 flight observations. Our findings illustrate a training methodology on how different models vary in prediction accuracy when applied to CDM operational data. We applied the SHAP (SHapley Additive exPlanations) method for feature importance analysis of all our independent variables to interpret the output of our machine learning models. Our results indicate that linear regression and elastic nets are the most effective machine learning models for achieving high prediction accuracy within the CDM framework. To test their robustness, we extended the analysis with predictions for better schedule times for taxi times on arrival and depature for selected runways using a different dataset. Our results contribute by showcasing a training methodology, highlighting how elastic net model as the best-performing model can be adopted for turnaround operations. In conclusion, we discuss the implications of our results for runway demand policies and use of airport resources such as gate & runaway allocation.

了解延误情况并做出准确预测对于优化周转和滑行时间至关重要，而优化周转和滑行时间又能减少机场运营中的燃油消耗和二氧化碳排放。然而，虽然现有研究已经探讨了各种预测模型对机场运营的影响，但在讨论延误情况时往往忽略了协同决策（CDM）变量的性能。欧洲主要机场实施 CDM 后，在机场运营中采用了基于里程碑的方法，特别是在周转运营中，将这些运营划分为具有独特功能的部分。本文旨在系统地研究各种机器学习技术（如线性回归、回归树、随机森林、弹性网和多层感知器（MLP））在 CDM 框架内准确预测延误类别的功效。为此，我们分析了马德里机场的 CDM 运行数据，其中至少包含 166,185 次航班观测。我们的研究结果说明了在 CDM 运行数据中应用不同模型时预测准确性差异的训练方法。我们采用 SHAP（SHapley Additive exPlanations）方法对所有自变量进行特征重要性分析，以解释机器学习模型的输出结果。我们的结果表明，线性回归和弹性网是在 CDM 框架内实现高预测精度的最有效机器学习模型。为了测试它们的稳健性，我们使用不同的数据集扩展了分析，对选定跑道的滑行到达时间和滑行结束时间进行了更好的预测。我们的结果展示了一种训练方法，突出了如何将弹性网模型作为表现最佳的模型用于周转运行。最后，我们讨论了我们的结果对跑道需求政策和机场资源（如登机口&）使用的影响；失控分配。

{"title":"Exploring prediction accuracy for optimal taxi times in airport operations using various machine learning models","authors":"","doi":"10.1016/j.jairtraman.2024.102684","DOIUrl":"10.1016/j.jairtraman.2024.102684","url":null,"abstract":"<div><div>Understanding delay conditions and making accurate predictions are essential for optimizing turnaround and taxi times, which in turn reduces fuel consumption and lowers CO<sub>2</sub> emissions in airport operations. However, while existing research has explored the impact of various prediction models on airport operations, it often overlooks the performance of Collaborative Decision Making (CDM) variables when discussing delay conditions. The implementation of CDM at major European airports has led to a milestone-based approach within airport operations, particularly in the turnaround operations, segmenting these operations with unique features. The purpose of this paper is to systematically investigate the efficacy of various machine learning techniques, such as linear regression, regression trees, random forests, elastic nets, and multi-layer perceptrons (MLP), in accurately predicting delay categories within the CDM framework. For this purpose, we analyzed CDM operational data from Madrid Airport, with at least 166,185 flight observations. Our findings illustrate a training methodology on how different models vary in prediction accuracy when applied to CDM operational data. We applied the SHAP (SHapley Additive exPlanations) method for feature importance analysis of all our independent variables to interpret the output of our machine learning models. Our results indicate that linear regression and elastic nets are the most effective machine learning models for achieving high prediction accuracy within the CDM framework. To test their robustness, we extended the analysis with predictions for better schedule times for taxi times on arrival and depature for selected runways using a different dataset. Our results contribute by showcasing a training methodology, highlighting how elastic net model as the best-performing model can be adopted for turnaround operations. In conclusion, we discuss the implications of our results for runway demand policies and use of airport resources such as gate & runaway allocation.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530727","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}

引用次数: 0

Curved flight procedure construction with site-specific statistical meteorological data: A Swedish example 利用特定地点的统计气象数据构建曲线飞行程序：瑞典范例

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-10-18 DOI: 10.1016/j.jairtraman.2024.102694

This paper presents a study of using site-specific statistical meteorological data in the construction of curved flight procedures to explore its potential in reducing the environmental impact of air traffic near the airports. In the study, the statistical meteorological data which covers a 10-year period of time, from 2009 to 2018, have been collected for the air space centred two major Swedish airports, Arlanda at Stockholm (ESSA) and Landvetter at Göteborg (ESGG). Two procedure design practices, one is an area navigation (RNAV) standard instrument departure (SID) procedure from runway 08 of Arlanda airport and another is a required navigation performance authorization required (RNP AR) approach procedure heading to the runway 03 at Landvetter airport, have been performed and analyzed. Applying the 95th percentile wind speed from statistical meteorological data, instead of the ICAO standardized tailwind component (TWC), offers varying benefits depending on the specific case. For the RNAV SID procedure from ESSA, the part of the designed departure path which is outside of the regulated noise dispersion area is significantly reduced. Whilst for the RNP AR approach procedure to ESGG, the smaller turning radius resulted from the lower TWC which is calculated from the local meteorological data makes it possible to avoid flying over an inhabited area. Besides the notable potential of noise impact reduction, flight distance shortening of 3.7 NM (RNAV SID ESSA case) and 1 NM (RNP AR ESGG case) compared to the same procedures designed on ICAO standard TWC have been observed. In general, the presented results are positive in supporting the use of local meteorological data in planning curved flight procedures during departures and approaches. A validation performed using an A320 full flight simulator has confirmed the operability of the ESGG RNP AR procedure from the design practice. In the full flight simulator, even with the 100th percentile wind condition from the collected statistical meteorological data, the designed RNP AR approach procedure can be operable considering RNP 0.3 corridor while a 30° bank angle is required for approximately 20 s during the turn.

本文介绍了一项关于在构建曲线飞行程序时使用特定地点统计气象数据的研究，以探索其在减少机场附近空中交通对环境影响方面的潜力。在这项研究中，收集了以瑞典两大机场（斯德哥尔摩的阿兰达机场（ESSA）和哥德堡的兰德维特机场（ESGG））为中心的空域的气象统计数据，时间跨度为 10 年（2009 年至 2018 年）。对两种程序设计实践进行了分析，一种是从阿兰达机场08号跑道出发的区域导航（RNAV）标准仪表起飞（SID）程序，另一种是前往兰德维特机场03号跑道的必要导航性能授权（RNP AR）进近程序。根据具体情况，采用统计气象数据中的第 95 百分位数风速而非国际民航组织标准化尾风分量（TWC）可带来不同的益处。就 ESSA 的 RNAV SID 程序而言，设计的离港路径中位于受管制的噪声扩散区域之外的部分明显减少。而对于飞往 ESGG 的 RNP AR 进近程序，由于根据当地气象数据计算的 TWC 较低，因此转弯半径较小，可以避免飞越居民区。与根据国际民航组织标准 TWC 设计的相同程序相比，除了显著降低噪声影响的潜力外，还观察到飞行距离缩短了 3.7 NM（RNAV SID ESSA 案例）和 1 NM（RNP AR ESGG 案例）。总体而言，所提供的结果对在离港和进港过程中使用当地气象数据规划曲线飞行程序具有积极意义。使用 A320 全飞行模拟器进行的验证证实了 ESGG RNP AR 程序在设计实践中的可操作性。在全飞行模拟器中，即使在收集到的统计气象数据的第100百分位风况下，所设计的RNP AR进近程序在考虑到RNP 0.3走廊的情况下也是可操作的，而在转弯过程中需要约20秒的30°倾角。

{"title":"Curved flight procedure construction with site-specific statistical meteorological data: A Swedish example","authors":"","doi":"10.1016/j.jairtraman.2024.102694","DOIUrl":"10.1016/j.jairtraman.2024.102694","url":null,"abstract":"<div><div>This paper presents a study of using site-specific statistical meteorological data in the construction of curved flight procedures to explore its potential in reducing the environmental impact of air traffic near the airports. In the study, the statistical meteorological data which covers a 10-year period of time, from 2009 to 2018, have been collected for the air space centred two major Swedish airports, Arlanda at Stockholm (ESSA) and Landvetter at Göteborg (ESGG). Two procedure design practices, one is an area navigation (RNAV) standard instrument departure (SID) procedure from runway 08 of Arlanda airport and another is a required navigation performance authorization required (RNP AR) approach procedure heading to the runway 03 at Landvetter airport, have been performed and analyzed. Applying the 95th percentile wind speed from statistical meteorological data, instead of the ICAO standardized tailwind component (TWC), offers varying benefits depending on the specific case. For the RNAV SID procedure from ESSA, the part of the designed departure path which is outside of the regulated noise dispersion area is significantly reduced. Whilst for the RNP AR approach procedure to ESGG, the smaller turning radius resulted from the lower TWC which is calculated from the local meteorological data makes it possible to avoid flying over an inhabited area. Besides the notable potential of noise impact reduction, flight distance shortening of 3.7 NM (RNAV SID ESSA case) and 1 NM (RNP AR ESGG case) compared to the same procedures designed on ICAO standard TWC have been observed. In general, the presented results are positive in supporting the use of local meteorological data in planning curved flight procedures during departures and approaches. A validation performed using an A320 full flight simulator has confirmed the operability of the ESGG RNP AR procedure from the design practice. In the full flight simulator, even with the 100th percentile wind condition from the collected statistical meteorological data, the designed RNP AR approach procedure can be operable considering RNP 0.3 corridor while a 30° bank angle is required for approximately 20 s during the turn.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530241","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}

引用次数: 0

Global air freight flow data for aviation policy modelling 用于航空政策建模的全球航空货运流量数据

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-10-17 DOI: 10.1016/j.jairtraman.2024.102692

Models of air freight are often constrained by a lack of available data. This study brings together different sources of air freight supply and demand data to address this gap. To study air freight operations, we combine schedules, flight tracking data and country-level databases of passenger and freight movements to produce estimates of global flight segment-level capacity and load factors in freighter aircraft and passenger holds for 2019–2021. To study true origin-ultimate destination air freight demand, a freight mode choice model by commodity group is developed for 2019 to fill gaps in mode information in international and national trade datasets, and estimates are made for 2019 and 2021. Initial comparisons of supply and demand data demonstrate that air freight journeys differ significantly from passenger journeys, typically including more flight legs (roughly, around 2, compared to 1.2 for passengers) and greater leg distances (2.2–2.5 times average passenger distance), with significant asymmetry in commodity flows and operations to and from individual countries and regions. These differences persist in 2021, despite COVID-19 induced shifts towards carrying more air freight in freighter aircraft. This research forms a first step towards making available an integrated database of estimated global air freight flows by commodity.

航空货运模型往往受制于可用数据的缺乏。本研究汇集了不同来源的航空货运供需数据，以弥补这一不足。为了研究航空货运业务，我们将航班时刻表、航班跟踪数据和国家级客货运数据库结合起来，得出了 2019-2021 年全球航班分段运力、货机载运率和客舱载运率的估计值。为了研究真正的始发地-最终目的地航空货运需求，我们开发了 2019 年按商品类别划分的货运模式选择模型，以填补国际和国家贸易数据集中模式信息的空白，并对 2019 年和 2021 年进行了估算。供需数据的初步比较表明，航空货运旅程与客运旅程有很大不同，通常包括更多的飞行航段（大致为 2 段左右，而客运为 1.2 段）和更长的航段距离（平均客运距离的 2.2-2.5 倍），进出各个国家和地区的商品流量和业务量存在很大的不对称性。尽管 COVID-19 引发了更多货运飞机的空运转变，但这些差异在 2021 年依然存在。这项研究迈出了第一步，为按商品估算的全球航空货运流量提供了一个综合数据库。

{"title":"Global air freight flow data for aviation policy modelling","authors":"","doi":"10.1016/j.jairtraman.2024.102692","DOIUrl":"10.1016/j.jairtraman.2024.102692","url":null,"abstract":"<div><div>Models of air freight are often constrained by a lack of available data. This study brings together different sources of air freight supply and demand data to address this gap. To study air freight operations, we combine schedules, flight tracking data and country-level databases of passenger and freight movements to produce estimates of global flight segment-level capacity and load factors in freighter aircraft and passenger holds for 2019–2021. To study true origin-ultimate destination air freight demand, a freight mode choice model by commodity group is developed for 2019 to fill gaps in mode information in international and national trade datasets, and estimates are made for 2019 and 2021. Initial comparisons of supply and demand data demonstrate that air freight journeys differ significantly from passenger journeys, typically including more flight legs (roughly, around 2, compared to 1.2 for passengers) and greater leg distances (2.2–2.5 times average passenger distance), with significant asymmetry in commodity flows and operations to and from individual countries and regions. These differences persist in 2021, despite COVID-19 induced shifts towards carrying more air freight in freighter aircraft. This research forms a first step towards making available an integrated database of estimated global air freight flows by commodity.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442733","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}

引用次数: 0

Understanding military pilots’ fuel-saving intentions for supporting logistics missions 了解军事飞行员支持后勤任务的节油意图

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-10-04 DOI: 10.1016/j.jairtraman.2024.102689

Military pilots can play important roles in saving aviation fuel by operating aircraft in an environmentally sustainable manner. Based on the theory of planned behavior (TPB), this study investigates the factors associated with cargo pilots’ fuel-saving intentions during logistics missions. We collected 108 survey responses, including 62 from the United States Air Force (USAF) and 46 from the Republic of Korea Air Force (ROKAF). Confirmatory factor analysis (CFA) and structural equation modeling (SEM) using the survey data show partial support for the relationships between three antecedents (attitude, subjective norms, and perceived behavioral control) and behavioral intention. Contrary to existing studies involving TPB, which are mostly about personal choices with some degree of freedom, the results suggest that the impact of subjective norms is greater than that of attitude in this study context, which can be explained by the rigid military culture and strict air traffic control including specific routes, altitudes, and speeds mandated by Air Combat Command. The theoretical and practical contributions of this study provide insights into how subjective norms influence intentions across different contexts, extending the applicability of TPB to industries with rigid organizational cultures and tight operational controls, such as the airline industry.

军事飞行员可以通过以环境可持续的方式操作飞机，在节约航空燃料方面发挥重要作用。本研究以计划行为理论（TPB）为基础，探讨了货运飞行员在执行后勤任务时节油意愿的相关因素。我们收集了 108 份调查问卷，其中 62 份来自美国空军（USAF），46 份来自大韩民国空军（ROKAF）。使用调查数据进行的确认因素分析（CFA）和结构方程建模（SEM）显示，三个前因因素（态度、主观规范和感知行为控制）与行为意向之间的关系得到了部分支持。与涉及 TPB 的现有研究（这些研究大多涉及具有一定自由度的个人选择）相反，研究结果表明，在本研究背景下，主观规范的影响大于态度的影响，这可以用僵化的军事文化和严格的空中交通管制（包括空中作战司令部规定的特定航线、高度和速度）来解释。本研究在理论和实践方面的贡献在于，它深入揭示了主观规范如何影响不同情境下的意向，并将主观规范理论的适用范围扩展到了航空业等组织文化僵化、运营控制严格的行业。

{"title":"Understanding military pilots’ fuel-saving intentions for supporting logistics missions","authors":"","doi":"10.1016/j.jairtraman.2024.102689","DOIUrl":"10.1016/j.jairtraman.2024.102689","url":null,"abstract":"<div><div>Military pilots can play important roles in saving aviation fuel by operating aircraft in an environmentally sustainable manner. Based on the theory of planned behavior (TPB), this study investigates the factors associated with cargo pilots’ fuel-saving intentions during logistics missions. We collected 108 survey responses, including 62 from the United States Air Force (USAF) and 46 from the Republic of Korea Air Force (ROKAF). Confirmatory factor analysis (CFA) and structural equation modeling (SEM) using the survey data show partial support for the relationships between three antecedents (attitude, subjective norms, and perceived behavioral control) and behavioral intention. Contrary to existing studies involving TPB, which are mostly about personal choices with some degree of freedom, the results suggest that the impact of subjective norms is greater than that of attitude in this study context, which can be explained by the rigid military culture and strict air traffic control including specific routes, altitudes, and speeds mandated by Air Combat Command. The theoretical and practical contributions of this study provide insights into how subjective norms influence intentions across different contexts, extending the applicability of TPB to industries with rigid organizational cultures and tight operational controls, such as the airline industry.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417345","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

Evaluating the impact of multiple uncertainty shocks on China's airline stocks volatility: A novel joint quantile perspective 评估多重不确定性冲击对中国航空股波动性的影响：新颖的联合量化视角

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-10-01 DOI: 10.1016/j.jairtraman.2024.102688

This study proposes a new joint quantile impulse response function (jQIRF) and applies that function to investigate the impact of multiple uncertainty shocks on the volatility of China's airline industry. The jQIRF not only allows one to examine the joint impact of multiple factors on the target variable; the impact of these factors on specific quantiles or states of the target variable can also be examined. The empirical results show that, compared to traditional IRF, the proposed jQIRF successfully reveals the positive impact of multiple uncertainties on the volatility of the airline industry and obtains a narrower confidence interval for IRF. The jQIRF also successfully corrects the overestimation bias caused by simple aggregation in generalized IRF. In addition, empirical results at different quantiles show the existence of a “leverage effect” in the impact of uncertainty on airline volatility. This means that, in more volatile market environments, the positive joint impact of uncertainties is stronger. However, research that has focused on individual airline stocks indicates that the airlines appear to be capable of implementing measures to stabilize stock volatility, thereby mitigating the negative impact of uncertainties on the airline industry. Overall, the proposed jQIRF and empirical conclusions in this paper help to more accurately assess the impact of multiple factors on the airline industry from a joint perspective. This ability is beneficial for both policymakers and investors.

本研究提出了一种新的联合量子脉冲响应函数（jQIRF），并应用该函数研究了多种不确定性冲击对中国航空业波动性的影响。jQIRF 不仅可以考察多种因素对目标变量的共同影响，还可以考察这些因素对目标变量特定量级或状态的影响。实证结果表明，与传统的 IRF 相比，所提出的 jQIRF 成功地揭示了多种不确定性因素对航空业波动性的积极影响，并为 IRF 取得了更窄的置信区间。jQIRF 还成功地纠正了广义 IRF 中简单聚合造成的高估偏差。此外，不同数量级的实证结果表明，不确定性对航空公司波动性的影响存在 "杠杆效应"。这意味着，在波动性更大的市场环境中，不确定性的正向联合影响更强。然而，针对航空公司个股的研究表明，航空公司似乎有能力采取措施稳定股票波动，从而减轻不确定性对航空业的负面影响。总体而言，本文提出的 jQIRF 和实证结论有助于从联合视角更准确地评估多种因素对航空业的影响。这种能力对政策制定者和投资者都是有益的。

{"title":"Evaluating the impact of multiple uncertainty shocks on China's airline stocks volatility: A novel joint quantile perspective","authors":"","doi":"10.1016/j.jairtraman.2024.102688","DOIUrl":"10.1016/j.jairtraman.2024.102688","url":null,"abstract":"<div><div>This study proposes a new joint quantile impulse response function (jQIRF) and applies that function to investigate the impact of multiple uncertainty shocks on the volatility of China's airline industry. The jQIRF not only allows one to examine the joint impact of multiple factors on the target variable; the impact of these factors on specific quantiles or states of the target variable can also be examined. The empirical results show that, compared to traditional IRF, the proposed jQIRF successfully reveals the positive impact of multiple uncertainties on the volatility of the airline industry and obtains a narrower confidence interval for IRF. The jQIRF also successfully corrects the overestimation bias caused by simple aggregation in generalized IRF. In addition, empirical results at different quantiles show the existence of a “leverage effect” in the impact of uncertainty on airline volatility. This means that, in more volatile market environments, the positive joint impact of uncertainties is stronger. However, research that has focused on individual airline stocks indicates that the airlines appear to be capable of implementing measures to stabilize stock volatility, thereby mitigating the negative impact of uncertainties on the airline industry. Overall, the proposed jQIRF and empirical conclusions in this paper help to more accurately assess the impact of multiple factors on the airline industry from a joint perspective. This ability is beneficial for both policymakers and investors.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142356967","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

Dynamic airspace sectorization with machine learning enhanced workload prediction and clustering 利用机器学习增强工作量预测和聚类进行动态空域分区

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-09-28 DOI: 10.1016/j.jairtraman.2024.102683

Addressing the complexities of modern Air Traffic Management (ATM), this paper introduces a novel framework for dynamic airspace sectorization, tailored to enhance efficiency and safety in congested airspaces. Central to this framework is the WP-ConvLSTM model, an innovative deep learning approach equipped with attention mechanisms. This model excels in accurately predicting workload dynamics, a critical factor in managing air traffic flow. To implement sectorization, we adopt a constrained K-means clustering technique for spatial division, followed by a refinement process involving Support Vector Machine (SVM) algorithms for precise boundary generation. Further optimization of sector boundaries is achieved through an evolutionary algorithm, ensuring both flexibility and stability in airspace divisions. Our methodology was thoroughly evaluated using real-world data from one of the busiest airspaces, demonstrating significant improvements in workload prediction accuracy and airspace sector management. The findings highlight the model’s robustness in practical scenarios, offering a scalable solution for ATM challenges. We conclude with a recognition of the study’s limitations and propose avenues for future research to build upon our findings, particularly in enhancing real-time data integration and adapting to evolving air traffic patterns.

针对现代空中交通管理（ATM）的复杂性，本文介绍了一种新颖的动态空域分区框架，旨在提高拥挤空域的效率和安全性。该框架的核心是 WP-ConvLSTM 模型，这是一种配备注意力机制的创新型深度学习方法。该模型擅长准确预测工作量动态，这是管理空中交通流量的关键因素。为实现扇区划分，我们采用受限 K-means 聚类技术进行空间划分，然后通过支持向量机（SVM）算法进行细化，以精确生成边界。通过进化算法进一步优化扇区边界，确保空域划分的灵活性和稳定性。我们使用来自最繁忙空域之一的真实数据对我们的方法进行了全面评估，结果表明在工作量预测准确性和空域扇区管理方面都有显著改善。研究结果凸显了模型在实际场景中的稳健性，为应对 ATM 挑战提供了可扩展的解决方案。最后，我们认识到了研究的局限性，并提出了未来的研究方向，尤其是在加强实时数据整合和适应不断变化的空中交通模式方面，以我们的研究成果为基础。

{"title":"Dynamic airspace sectorization with machine learning enhanced workload prediction and clustering","authors":"","doi":"10.1016/j.jairtraman.2024.102683","DOIUrl":"10.1016/j.jairtraman.2024.102683","url":null,"abstract":"<div><div>Addressing the complexities of modern Air Traffic Management (ATM), this paper introduces a novel framework for dynamic airspace sectorization, tailored to enhance efficiency and safety in congested airspaces. Central to this framework is the WP-ConvLSTM model, an innovative deep learning approach equipped with attention mechanisms. This model excels in accurately predicting workload dynamics, a critical factor in managing air traffic flow. To implement sectorization, we adopt a constrained K-means clustering technique for spatial division, followed by a refinement process involving Support Vector Machine (SVM) algorithms for precise boundary generation. Further optimization of sector boundaries is achieved through an evolutionary algorithm, ensuring both flexibility and stability in airspace divisions. Our methodology was thoroughly evaluated using real-world data from one of the busiest airspaces, demonstrating significant improvements in workload prediction accuracy and airspace sector management. The findings highlight the model’s robustness in practical scenarios, offering a scalable solution for ATM challenges. We conclude with a recognition of the study’s limitations and propose avenues for future research to build upon our findings, particularly in enhancing real-time data integration and adapting to evolving air traffic patterns.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142356968","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

Do healthy and environmentally sustainable inflight foods matter to international flight passengers? Frequent vs. occasional flyers 对国际航班乘客来说，健康和环境可持续的机上食品重要吗？经常乘坐飞机的乘客与偶尔乘坐飞机的乘客

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-09-27 DOI: 10.1016/j.jairtraman.2024.102687

Airlines continuously seek strategic ways to impress their passengers and build memorable experiences. Inflight food services as an imperative interaction, the research included healthy and environmentally sustainable attributes (e.g., production method, product origin), reflecting the emphasis on longevity/well-being and sustainability to design optimal inflight food bundles as well as the brand and taste attributes. This exploratory research investigated differences in inflight food preferences between frequent and occasional flyers. A total of 16 full-profile pairwise comparison questions of mixed levels for five attributes were given to the sample of international flight passengers (n = 490). The participants were asked to rate inflight food bundles using a 9-point Likert scale. The results indicate that healthy and environmentally sustainable inflight foods will be preferred over brand-named or tasty foods when served onboard. There were notable differences in inflight food preferences between occasional and frequent flyers. While both flyers preferred low-calorie and tasty foods made with nationally sourced ingredients, frequent flyers highly preferred branded foods made with organically grown ingredients. In contrast, occasional flyers desired generic branded foods made with conventionally grown ingredients. The study findings are discussed further to help airline marketers build a desirable inflight food bundle.

航空公司不断寻求给乘客留下深刻印象和难忘体验的战略方法。机上食品服务作为一种必要的互动，研究包括健康和环境可持续属性（如生产方法、产品来源），反映了对长寿/健康和可持续发展的重视，以设计最佳的机上食品组合以及品牌和口味属性。这项探索性研究调查了经常乘坐飞机和偶尔乘坐飞机的乘客对机上食品偏好的差异。研究人员向国际航班乘客样本（n = 490）提供了五种属性的共 16 个全貌成对比较问题。参与者被要求使用 9 点李克特量表对机上食品进行评分。结果表明，与品牌食品或美味食品相比，健康和环境可持续的机上食品更受欢迎。偶尔乘坐飞机的乘客和经常乘坐飞机的乘客对机上食品的偏好存在明显差异。虽然这两种乘客都偏好使用本国食材制作的低热量美味食品，但经常乘坐飞机的乘客更偏好使用有机种植食材制作的品牌食品。与此相反，偶尔乘坐飞机的乘客则更喜欢使用传统原料制作的普通品牌食品。我们将进一步讨论研究结果，以帮助航空公司营销人员建立理想的机上食品组合。

{"title":"Do healthy and environmentally sustainable inflight foods matter to international flight passengers? Frequent vs. occasional flyers","authors":"","doi":"10.1016/j.jairtraman.2024.102687","DOIUrl":"10.1016/j.jairtraman.2024.102687","url":null,"abstract":"<div><div>Airlines continuously seek strategic ways to impress their passengers and build memorable experiences. Inflight food services as an imperative interaction, the research included healthy and environmentally sustainable attributes (e.g., production method, product origin), reflecting the emphasis on longevity/well-being and sustainability to design optimal inflight food bundles as well as the brand and taste attributes. This exploratory research investigated differences in inflight food preferences between frequent and occasional flyers. A total of 16 full-profile pairwise comparison questions of mixed levels for five attributes were given to the sample of international flight passengers (n = 490). The participants were asked to rate inflight food bundles using a 9-point Likert scale. The results indicate that healthy and environmentally sustainable inflight foods will be preferred over brand-named or tasty foods when served onboard. There were notable differences in inflight food preferences between occasional and frequent flyers. While both flyers preferred low-calorie and tasty foods made with nationally sourced ingredients, frequent flyers highly preferred branded foods made with organically grown ingredients. In contrast, occasional flyers desired generic branded foods made with conventionally grown ingredients. The study findings are discussed further to help airline marketers build a desirable inflight food bundle.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327725","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

Analyzing the impacts on passenger yield of incumbent companies after the entry of a new company into the aviation market: The case of Brazil 分析新公司进入航空市场后对现有公司乘客收益率的影响：巴西案例

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-09-24 DOI: 10.1016/j.jairtraman.2024.102682

The public air transport market is generally oligopolistic, meaning that the market strategies of some companies can influence the decisions of rivals and impact consumer prices. This sector has been marked by a large flow of airline entries and exits. Considering this scenario, the objective of this work is to evaluate how the revenue from airline tickets of incumbent companies in the national aviation market in Brazil was impacted after the entry of a new company. A fixed-effects Difference-in-Differences model (DID) using a feasible generalized least squares (FGLS) estimator with panel data is used to assess this impact. To assess the impact of the entrant on yield dispersion, we apply the regression equation to P90 and P10 of the distribution. We also applied the equation, considering the Gini coefficient as the dependent variable. The results showed that the average income of incumbent companies reduced by an estimated magnitude of 5.9% in the period after the new company entered the market. Our findings also indicate an increase in distribution dispersion in the period following market entry, with a more pronounced reduction of 19% in the P10 and 1.5% in the P90. We conclude that the entry of the new company was readily assimilated by the incumbents, so that the competitive effect can explain the identified reduction in average income. The entry of a new competitor was especially beneficial to consumers in the lower tail of the distribution.

公共航空运输市场通常是寡头垄断的，这意味着一些公司的市场策略会影响竞争对手的决策，并影响消费者的价格。该行业的特点是航空公司的大量进入和退出。考虑到这一情况，本研究的目的是评估巴西全国航空市场上现有公司的机票收入在新公司进入后受到的影响。为了评估这种影响，我们采用了固定效应差分模型（DID），使用可行的广义最小二乘法（FGLS）估计器和面板数据。为了评估新进入者对收益率离散度的影响，我们将回归方程应用于分布的 P90 和 P10。我们还将基尼系数视为因变量，应用了该方程。结果显示，在新公司进入市场后的一段时间内，在位公司的平均收入估计减少了 5.9%。我们的研究结果还表明，在新公司进入市场后的一段时间内，分布离散程度有所提高，P10 和 P90 的下降幅度分别为 19% 和 1.5%。我们的结论是，新公司的进入很容易被原有公司所吸收，因此竞争效应可以解释平均收入的减少。新竞争者的加入尤其有利于收入分布尾部较低的消费者。

{"title":"Analyzing the impacts on passenger yield of incumbent companies after the entry of a new company into the aviation market: The case of Brazil","authors":"","doi":"10.1016/j.jairtraman.2024.102682","DOIUrl":"10.1016/j.jairtraman.2024.102682","url":null,"abstract":"<div><div>The public air transport market is generally oligopolistic, meaning that the market strategies of some companies can influence the decisions of rivals and impact consumer prices. This sector has been marked by a large flow of airline entries and exits. Considering this scenario, the objective of this work is to evaluate how the revenue from airline tickets of incumbent companies in the national aviation market in Brazil was impacted after the entry of a new company. A fixed-effects Difference-in-Differences model (DID) using a feasible generalized least squares (FGLS) estimator with panel data is used to assess this impact. To assess the impact of the entrant on yield dispersion, we apply the regression equation to P90 and P10 of the distribution. We also applied the equation, considering the Gini coefficient as the dependent variable. The results showed that the average income of incumbent companies reduced by an estimated magnitude of 5.9% in the period after the new company entered the market. Our findings also indicate an increase in distribution dispersion in the period following market entry, with a more pronounced reduction of 19% in the P10 and 1.5% in the P90. We conclude that the entry of the new company was readily assimilated by the incumbents, so that the competitive effect can explain the identified reduction in average income. The entry of a new competitor was especially beneficial to consumers in the lower tail of the distribution.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0969699724001479/pdfft?md5=6dc6644036a0ca4bdf4a216c37d3e1ef&pid=1-s2.0-S0969699724001479-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314771","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}

引用次数: 0

Quantifying civilian aircraft vulnerability: A data-driven approach in geo-political conflict zones for improved risk assessment of aircraft shot-down 量化民用飞机的脆弱性：在地缘政治冲突地区采用数据驱动方法改进飞机被击落的风险评估

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2024-09-24 DOI: 10.1016/j.jairtraman.2024.102674

Current risk analysis methods for quantifying the risk of the shooting down of commercial aircraft rely on the use of risk matrices and risk categorisation classes. We show that these processes are not effective, subject to bias and not adequate to help aviation companies decide whether to fly to or over conflict areas.

Information concerning terror attacks, wars or conflicts is instantly available through various internet channels, and we argue that this enables more innovative accurate data-driven aircraft shoot down risk assessment. We propose a generalised linear model with logit link to estimate the likelihood of an aircraft being shot down based on technical and geo-political environmental factors. We use our model to estimate the probability of aircraft being shot down in all countries that are currently affected by military conflict. We demonstrate that probability of shooting down civilian aircraft depends on economic indicator such as GDP per capita, type and intensity of the conflict. We validate our model using out-of-sample tests with cross-validation.

The method proposed in this paper uses data available in open sources, it is easy to implement and utilize in aviation company or other industry bodies for prediction of aircraft shooting risks. It significantly improves currently existing methodologies of aircraft shooting risk assessment.

目前量化商用飞机被击落风险的风险分析方法依赖于使用风险矩阵和风险分类等级。我们的研究表明，这些方法并不有效，会产生偏差，不足以帮助航空企业决定是否飞往或飞越冲突地区。有关恐怖袭击、战争或冲突的信息可通过各种互联网渠道即时获取，我们认为这使得以数据为驱动的飞机被击落风险评估更具创新性和准确性。我们提出了一个带有对数链接的广义线性模型，根据技术和地缘政治环境因素估算飞机被击落的可能性。我们使用该模型估算了目前受军事冲突影响的所有国家中飞机被击落的概率。我们证明，民用飞机被击落的概率取决于人均国内生产总值等经济指标、冲突类型和强度。本文提出的方法使用公开来源的数据，易于在航空公司或其他行业机构中实施和使用，可用于预测飞机被击落的风险。它大大改进了现有的飞机射击风险评估方法。

{"title":"Quantifying civilian aircraft vulnerability: A data-driven approach in geo-political conflict zones for improved risk assessment of aircraft shot-down","authors":"","doi":"10.1016/j.jairtraman.2024.102674","DOIUrl":"10.1016/j.jairtraman.2024.102674","url":null,"abstract":"<div><div>Current risk analysis methods for quantifying the risk of the shooting down of commercial aircraft rely on the use of risk matrices and risk categorisation classes. We show that these processes are not effective, subject to bias and not adequate to help aviation companies decide whether to fly to or over conflict areas.</div><div>Information concerning terror attacks, wars or conflicts is instantly available through various internet channels, and we argue that this enables more innovative accurate data-driven aircraft shoot down risk assessment. We propose a generalised linear model with logit link to estimate the likelihood of an aircraft being shot down based on technical and geo-political environmental factors. We use our model to estimate the probability of aircraft being shot down in all countries that are currently affected by military conflict. We demonstrate that probability of shooting down civilian aircraft depends on economic indicator such as GDP per capita, type and intensity of the conflict. We validate our model using out-of-sample tests with cross-validation.</div><div>The method proposed in this paper uses data available in open sources, it is easy to implement and utilize in aviation company or other industry bodies for prediction of aircraft shooting risks. It significantly improves currently existing methodologies of aircraft shooting risk assessment.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S096969972400139X/pdfft?md5=80d2e7b70fd9741ce2e3639bf54219d5&pid=1-s2.0-S096969972400139X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314769","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}

引用次数: 0