Journal of Air Transport Management最新文献

{"title":"Advances of operations research in air transportation in the intelligence age","authors":"Xin Wen,&nbsp;Tsan-Ming Choi,&nbsp;Hoi-Lam Ma,&nbsp;Xuting Sun","doi":"10.1016/j.jairtraman.2024.102691","DOIUrl":"10.1016/j.jairtraman.2024.102691","url":null,"abstract":"<div><div>The constant growth in the demand of air cargo and air passenger nowadays has imposed many new challenges to the operations and management in the aviation industry. Both the academia and the industry have devoted great efforts to coducting extensive research and developed many new operations research (OR) techniques to address complex aviation management issues. In response to the expansion of aviation networks and the growth of flight frequencies, researchers have attempted to combine emerging technologies, such as artificial intelligence (AI), with OR techniques to achieve better results. This paper reviews the literature of advanced OR in air transportation, introduces and summarises the papers featured in this special issue, identifies the research development trends, and provides future research directions for aviation management. The reviewed studies are divided into three areas: airline operations, aviation data analysis and decision-making, and aviation sustainable development. Airline operations research focuses on four aspects of airline scheduling, including flight scheduling, fleet assignment, aircraft maintenance routing, and crew scheduling. Aviation data analytics and decision-making research focuses on operational safety and efficiency, profitability, delays, and disruption management. Finally, aviation sustainable development focuses on the aspects of subsidy policies, environmental protection, and the application of emerging technologies in supporting the long-term development of the aviation industry. By reviewing and analyzing the related studies, we propose a list of future research directions.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"122 ","pages":"Article 102691"},"PeriodicalIF":3.9,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757546","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}

{"title":"Exploring prediction accuracy for optimal taxi times in airport operations using various machine learning models","authors":"Simon Okwir ,&nbsp;Kaveh Amouzgar ,&nbsp;Amos HC. Ng","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 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 &amp; runaway allocation.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"122 ","pages":"Article 102684"},"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}

{"title":"Curved flight procedure construction with site-specific statistical meteorological data: A Swedish example","authors":"Xin Zhao ,&nbsp;Ulrika Ziverts ,&nbsp;Henrik Ekstrand ,&nbsp;Maria Ullvetter ,&nbsp;Peter Lukic ,&nbsp;Anette Näs ,&nbsp;Esbjörn Olsson ,&nbsp;Martin Ridal ,&nbsp;Åke Johansson ,&nbsp;Martin Wall ,&nbsp;Olivier Petit ,&nbsp;Tomas Grönstedt","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":"121 ","pages":"Article 102694"},"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}

{"title":"Global air freight flow data for aviation policy modelling","authors":"Lynnette Dray ,&nbsp;Joanna Kuleszo ,&nbsp;Roger Teoh ,&nbsp;Marc Stettler ,&nbsp;James Stewart ,&nbsp;Andreas Schäfer","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":"121 ","pages":""},"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}

{"title":"Understanding military pilots’ fuel-saving intentions for supporting logistics missions","authors":"Ioan Gaitan ,&nbsp;Gawon Yun ,&nbsp;Harry Joo ,&nbsp;Sunil Hwang","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":"121 ","pages":"Article 102689"},"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}

{"title":"Evaluating the impact of multiple uncertainty shocks on China's airline stocks volatility: A novel joint quantile perspective","authors":"Xin Li ,&nbsp;Chi Wei Su","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":"121 ","pages":"Article 102688"},"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}

{"title":"Dynamic airspace sectorization with machine learning enhanced workload prediction and clustering","authors":"Qihang Xu,&nbsp;Yutian Pang,&nbsp;Yongming Liu","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":"121 ","pages":"Article 102683"},"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}

{"title":"Do healthy and environmentally sustainable inflight foods matter to international flight passengers? Frequent vs. occasional flyers","authors":"Eunmin (Min) Hwang ,&nbsp;Yen-Soon Kim ,&nbsp;Seyhmus Baloglu ,&nbsp;Carola Raab","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":"121 ","pages":"Article 102687"},"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}

{"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":"Arlley Pereira de Araujo ,&nbsp;Maria Rosa Borges","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":"121 ","pages":"Article 102682"},"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}

{"title":"Quantifying civilian aircraft vulnerability: A data-driven approach in geo-political conflict zones for improved risk assessment of aircraft shot-down","authors":"Stanislav Bukhman,&nbsp;Mario P. Brito,&nbsp;Ming-Chien Sung","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":"121 ","pages":"Article 102674"},"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}