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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Effective Features for Machine Learning-enhanced Aircraft Recovery</title>
      <link>https://trid.trb.org/View/2736887</link>
      <description><![CDATA[Machine learning has demonstrated remarkable potential in tackling airline recovery problems. Most existing studies largely emphasize the construction of frameworks and empirical evaluations across multiple learning models, whereas the role of feature engineering has received comparatively little dedicated investigation. In particular, many features used in the aircraft recovery literature are only weakly coupled with disruption characteristics, which limits their ability to capture the complex interactions between disruptions and recovery decisions and, in turn, constrains predictive performance. In this paper, we adopt a machine learning-based framework to predict key aircraft that are likely to undergo schedule adjustments after recovery, thereby enabling accelerated recovery optimization. Within this framework, we develop two classes of effective features: recovery-specific features that characterize the potential cost savings achievable through aircraft swapping, and disruption-specific features that capture the spatio-temporal proximity between disruptions and candidate aircraft via distance metrics. Together, these features enable more accurate prediction of whether an aircraft will be reassigned in the optimal recovery solution. Experiments on real operational data from five major Chinese airlines show that the proposed features dominate the importance rankings, occupying the top 7 positions, and lead to substantial improvements in recovery performance. Compared with traditional optimization-based approaches, our method achieves comparable solution quality while reducing the end-to-end recovery time by 66% on average.]]></description>
      <pubDate>Wed, 16 Sep 2026 16:15:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2736887</guid>
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    <item>
      <title>Effects of international airline alliances on domestic–international connecting passengers in Japan</title>
      <link>https://trid.trb.org/View/2714220</link>
      <description><![CDATA[This paper estimates the effect of international airline alliances on the volume of passengers connecting from domestic to international flights. Using data on Japanese domestic air services, the analysis focuses on the initial wave of alliance expansion by Japan’s major carriers between 1995 and 2005. The identification strategy compares changes in passenger volumes between airlines that expanded their alliance participation and those that did not, and further contrasts passengers connecting from domestic to international flights (type I) with those traveling solely on domestic flights (type D) on the same domestic segments. The results indicate that alliance expansion significantly increased the number of type I passengers.]]></description>
      <pubDate>Wed, 16 Sep 2026 11:21:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714220</guid>
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    <item>
      <title>Assessing stakeholder impacts of capacity regulations and algorithmic capacity-on-demand mechanisms in European air traffic management: A network-level ECAC operational case study</title>
      <link>https://trid.trb.org/View/2713630</link>
      <description><![CDATA[Regulatory mechanisms in European air traffic management, including Air Traffic Flow Management slot allocation and flow restrictions, are widely used to address sector-level demand-capacity imbalances. Although effective for safety and feasibility, they impose departure delays that propagate through airline rotations, increasing costs, reducing passenger reliability, and disrupting airport operations. Standard Air Traffic Flow and Capacity Management assessments mainly report regulation compliance and aggregate delay, without explicitly assessing network propagation or differentiated stakeholder impacts.This paper compares the regulatory baseline with an algorithmic demand-capacity balancing approach based on early delegation of clusters of aircraft to adjacent sectors. Under congestion, control of eligible aircraft is proactively reassigned to reshape sector occupancy profiles and balance workload across neighboring sectors, without changing traffic demand or declared capacities.A stakeholder-oriented framework evaluates impacts on airlines, passengers, airports, and air navigation service providers, combining monetized indicators with proxy metrics where valuation is not feasible. Results indicate that early delegation substantially reduces the need for sector-level Air Traffic Controller capacity regulations, lowering direct and reactionary delay and associated costs. Reduced delay propagation is associated with more stable schedules and a smoother temporal distribution of demand for airport infrastructure and services.Overall, rigid regulation-driven allocation can create system-level inefficiencies even when safety constraints are satisfied. Adaptive, data-driven balancing mechanisms show potential to improve efficiency and to alter the distribution of congestion-related impacts, informing policy discussions on the evolution of demand-capacity management in European air traffic systems.]]></description>
      <pubDate>Wed, 16 Sep 2026 11:21:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2713630</guid>
    </item>
    <item>
      <title>A dual-processing airline service model: Cognitive analytical judgment of quality vs affective holistic assessment of satisfaction</title>
      <link>https://trid.trb.org/View/2714898</link>
      <description><![CDATA[This paper deals with the assessment of airline services from the passengers' point of view. The novelty of the study is linked to an implemented dual-processing model, consisting in capturing two different types of information from airline users: a cognitive analytical judgement of service quality and an affective holistic assessment of satisfaction with the service, whereas the concepts of service quality and satisfaction have been generally considered as the same in the literature. An additional novelty is the usage of two different scales for collecting judgements of service quality and satisfaction rates. The final aim of the paper is investigating the relationship between airline service quality, air passengers' satisfaction and their loyalty. Due to the complexity of this relationship and the variety of the aspects characterizing airline services, the approach adopted in this work is based on the collection of data concerning the several factors characterizing airline services, the overall service quality and satisfaction, and the intentions of the passengers to use the service again or recommend it to others. The collected data are analysed through a Covariance-Based Structural Equation Modelling (CB-SEM) approach, which is suitable for analysing a complex phenomenon characterized by unobservable factors. In addition, a Structural Equation Modelling-Multiple Indicators Multiple Causes (SEM-MIMIC) structure including the effects of passengers' characteristics is proposed to investigate also the heterogeneity of passengers’ perceptions. The work is supported by a case study represented by air passengers living in a region of the southern Italy. The main finding of the study suggests that satisfaction and service quality are two different concepts, and investigating them separately is more appropriate than considering them as the same concepts.]]></description>
      <pubDate>Tue, 01 Sep 2026 14:02:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714898</guid>
    </item>
    <item>
      <title>Mitigating the Financial Impact of Carbon Risk in Airlines: The Role of Management Practices</title>
      <link>https://trid.trb.org/View/2743231</link>
      <description><![CDATA[This study examines the financial impact of carbon risk on airlines and the moderating role of management practices across different business models. Using unbalanced panel data from 53 publicly listed airlines, the results show that higher carbon risk significantly reduces profitability. The moderating effects vary by airline business models. Board skill sets mitigate the negative impact in low-cost carriers, while board size plays a positive role in full-service carriers. In airline-within-airline groups, efficient governance and strong financial management, particularly investment and market capitalisation, help reduce carbon-related financial pressure. The findings highlight the importance of aligning board governance and financial strategies with business models to improve airline financial resilience during the green transition.]]></description>
      <pubDate>Tue, 01 Sep 2026 14:02:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2743231</guid>
    </item>
    <item>
      <title>Flight Frequency, Schedule Differentiation, and Route Revenue: Evidence for Competition and Scheduling Policy</title>
      <link>https://trid.trb.org/View/2752704</link>
      <description><![CDATA[This study examines the joint effects of flight frequency and schedule differentiation on passenger number, airfare, and revenue in the Australian domestic airline market. It distinguishes between two dimensions of scheduling strategies: between-carrier schedule differentiation and within-carrier schedule dispersion. The monthly panel dataset employed comprises 349 carrier-route-specific cross-sectional units, covering 102 oligopolistic domestic routes (51 airport pairs) in Australia for the 2015M1∼2025M6 period (excluding the COVID period 2020M1∼2021M10). The results show that flight frequency has a consistently positive and significant effect on passenger number and revenue. Between-carrier schedule differentiation is found to increase carrier-route-specific passenger demand and support higher airfare, suggesting that temporal differentiation across competitors reduces direct competition and enhances pricing power. In contrast, more clustered within-carrier scheduling increases passenger attraction by improving service convenience, although its effect on airfare is generally insignificant. To summarise, the empirical findings indicate that a strategy combining higher frequency, greater differentiation relative to competitors, and more concentrated within-carrier scheduling is most conducive to route revenue generation.]]></description>
      <pubDate>Tue, 01 Sep 2026 14:02:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2752704</guid>
    </item>
    <item>
      <title>The cost implications of upgauging in the U.S. airline industry</title>
      <link>https://trid.trb.org/View/2711667</link>
      <description><![CDATA[The cost impact of upgauging is often attributed to economies of density, yet production theory emphasizes that cost savings depend on how intensively available capacity is utilized. This implies a potentially nonlinear relationship between aircraft seat capacity and short-run variable costs. Accordingly, a critical question arises for the airline industry: is there still room for further upgauging, or have airlines already reached the limit of its cost-saving potential? Using an unbalanced panel of U.S. airlines from 2000 to 2024, we estimate translog variable cost functions by business model to examine the cost implications of upgauging, measured by seats per departure. The results provide evidence consistent with a U-shaped relationship between upgauging and variable costs: moderate increases in seat capacity are associated with lower variable costs, while further increases eventually correspond to higher costs, potentially reflecting operational frictions and utilization constraints. In addition, the results provide strong evidence that low-cost carriers operate below cost-minimizing aircraft size, while the evidence for full-service airlines is less conclusive, suggesting potential scope for further upgauging. Robustness checks across pre- and post-crisis subsamples yield qualitatively similar patterns. Collectively, these findings challenge the view that the benefits of upgauging have been fully realized.]]></description>
      <pubDate>Mon, 31 Aug 2026 10:31:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711667</guid>
    </item>
    <item>
      <title>Enhancing customer loyalty in the airline industry: the role of E-CRM and customer experience at Middle East Airlines</title>
      <link>https://trid.trb.org/View/2703986</link>
      <description><![CDATA[Developing customer loyalty in the highly competitive airline industry today depends more on providing exceptional, personalised customer experiences than merely offering efficiency and affordability. This research examines the impact of electronic customer relationship management (E-CRM) on customer loyalty, with customer experience playing a role as a mediator, in the context of Middle East Airlines (MEA). Information gathered from 351 passengers underwent analysis with the use of SPSS. Findings show that customer loyalty is significantly affected by E-CRM dimensions like security, problem-solving, and customer orientation, while technology by itself does not have a significant impact. The results emphasise the importance of customer experience in linking E-CRM strategies and loyalty. This research contributes to the growing body of knowledge on digital transformation in the airline industry and offers actionable insights for enhancing customer retention strategies through robust E-CRM systems. The information is especially important for airlines operating in culturally diverse and highly competitive markets.]]></description>
      <pubDate>Thu, 27 Aug 2026 16:32:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703986</guid>
    </item>
    <item>
      <title>The Treasury’s Assistance to the Airline Industry and National Security Businesses During the COVID-19 Pandemic</title>
      <link>https://trid.trb.org/View/2742794</link>
      <description><![CDATA[During the COVID-19 pandemic, which began in early 2020 in the United States, lawmakers enacted legislation to stabilize the airline industry in response to a sharp and widespread decline in air travel. That legislation, known as the Coronavirus Aid, Relief, and Economic Security (CARES) Act, authorized the Treasury to provide broad-based assistance through two programs: grants to support payrolls (the Payroll Support Program) and a credit program to support air carriers, related businesses, and businesses critical to national security (the Section 4003 Loan Program). (The CARES Act also provided other assistance to various entities unrelated to the airlines or national security businesses.) The Treasury was given discretion in setting compensation for the government, which was subsidizing those grants and loans. In this report, the Congressional Budget Office examines the assistance provided to the airlines and other businesses through those programs.]]></description>
      <pubDate>Mon, 24 Aug 2026 08:44:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742794</guid>
    </item>
    <item>
      <title>Analyzing network connectivity of four major airport groups in China through relative entropy theory</title>
      <link>https://trid.trb.org/View/2694577</link>
      <description><![CDATA[The rapid growth in air transport demand has spurred the development of Multi-Airport Systems (MAS) worldwide. China has adopted a distinct model known as Airport Groups (AGs). Unlike single metropolitan-focused MAS, AGs operate on a broader regional scale, emphasizing inter-regional connectivity and economic integration. This study integrates network topology with Relative Entropy (RE) theory to propose a comprehensive Network Connectivity Index (NCI) for quantifying the effects of airport disruptions on the airline and passenger connectivity of China's four major AGs. By constructing a two-layer China's airport network model comprising an AG network (23 AG member airports, 156 routes) and an external airport network (234 non-AG, airports 2276 routes), we examined connectivity patterns across AG to AG, AG to AG-network and AG to external-airport-network. Then, the connectivity effects of AGs under different network structures were analyzed by NCI model. Results reveal significant heterogeneity in connectivity structures, functional roles of core and auxiliary airports, and the dominant influence of passenger flow on network connectivity. The proposed NCI integrates flight and passenger flow data with traditional metrics by capturing the impact of dynamic disruptions and distribution shifts. Compared to centrality metrics based solely on topological characteristics, the NCI more effectively identifies airports critical to AG connectivity. These results underscore the importance of NCI in comprehensively considering the impact of airlines and passengers within connectivity analysis.]]></description>
      <pubDate>Mon, 10 Aug 2026 16:51:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694577</guid>
    </item>
    <item>
      <title>Employer attractiveness in air transport industry: Insights from fuzzy AHP</title>
      <link>https://trid.trb.org/View/2692414</link>
      <description><![CDATA[This study aims to present a framework for air transport companies to manage their employer brands more successfully and effectively in the competition for potential employees. Focusing on the emerging air transport industry in Türkiye, the study uses a fuzzy Analytical Hierarchy Process approach to determine the relative importance of key factors influencing employer attractiveness, which contribute to a company's attractiveness as an employer. It then assesses the attractiveness of air transport companies across six different categories using these weighted factors. First-time job seekers as potential employees of the air transport companies were carefully selected as participants based on their impending graduation and their familiarity with each air transport company included in the study. The two most effective factors among the five factors -Interest Value, Social Value, Economic Value, Development Value, and Application Value-were determined to be Development Value and Economic Value. The proposed framework provides an important managerial tool for air transport companies. Air transport companies can use this tool to develop strategies for increasing employer attractiveness by considering the importance first-time job seekers assign to the factors in the decision model and how those factors influence overall employer attractiveness.]]></description>
      <pubDate>Mon, 10 Aug 2026 16:51:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692414</guid>
    </item>
    <item>
      <title>Balancing fuel efficiency and environmental impact: 4D trajectory optimization through Fast Marching Tree for transatlantic flights considering contrails</title>
      <link>https://trid.trb.org/View/2692413</link>
      <description><![CDATA[This paper proposes a method for computing an airliner trajectory in its cruise phase, minimizing environmental impact. In particular, the problem of contrails is addressed. The proposed method is based on an algorithm derived from robotics, the Fast Marching Tree algorithm. After having been tested on Unmanned Aerial Vehicles (UAVs) and on computing trajectories in a wind field for commercial aircraft, it is now adapted to the case of contrails. Several modifications and additions are made to enable it to deal with soft obstacles that evolve over time, as well as the operational constraints associated with the cruise phase. The method is thus able to propose flight level changes in line with operational expectations, adaptable to the strategy of the user (airline for example). Two experiments are proposed on the Paris–Miami and Paris–Denver flights, showing low computation times and satisfactory results. Contrail consideration affects the number of level changes, more specifically, level ups are less frequent and level downs are added compared to usual practice.]]></description>
      <pubDate>Mon, 10 Aug 2026 16:51:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692413</guid>
    </item>
    <item>
      <title>Research on the Operational Efficiency of Airlines Based on the Characteristics of Airport Clusters</title>
      <link>https://trid.trb.org/View/2732257</link>
      <description><![CDATA[The features of airport clusters have a big impact on regional air transport. But problems within these clusters also affect airline operations. This study uses the Data Envelopment Analysis (DEA) model. It selects 16 airlines of different sizes as samples. It also identifies relevant input and output indicators to measure operational efficiency. The results show that the efficiency of large and medium-sized airlines generally went up. Small airlines have shown a slow but steady improvement in efficiency, with significant volatility due to cost and slot constraints. So, the study analyzes pure technical efficiency, scale efficiency, and comprehensive efficiency. It finds out the changing patterns of operational efficiency among airlines of different sizes and the reasons behind them.]]></description>
      <pubDate>Sun, 02 Aug 2026 17:23:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732257</guid>
    </item>
    <item>
      <title>Airline-alliance extensions: Spillovers within networks</title>
      <link>https://trid.trb.org/View/2696181</link>
      <description><![CDATA[This paper explores beneficial network spillovers resulting from airline-alliance extensions like those that occur when a US carrier adds new foreign partners to its existing international alliance. In the model, a US carrier and an existing foreign alliance partner initially cooperate in providing service between an interior US domestic endpoint and a foreign destination via an international US gateway. Then, a second foreign carrier, which previously provided traditional interline service to a different foreign endpoint via the same gateway, also becomes an alliance partner of the US carrier. Since trips to the two foreign destinations from the interior US endpoint share the same domestic route to the gateway, cost complementarity between the two international markets exists under economies of density. As a result, the alliance extension, by reducing the fare and raising traffic to the new foreign endpoint (which flows on the domestic segment), leads to a lower cost for alliance service to the original foreign endpoint, further reducing the fare in this market, which was already low due to the presence of the initial alliance. The paper analyzes this beneficial spillover along with others using a simple model.]]></description>
      <pubDate>Wed, 29 Jul 2026 09:16:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2696181</guid>
    </item>
    <item>
      <title>Financial sustainability in the airline industry: Panel evidence from leading global carriers</title>
      <link>https://trid.trb.org/View/2673121</link>
      <description><![CDATA[This study aims to identify the key financial drivers of profitability-based financial sustainability in the global airline industry by jointly examining Return on Invested Capital (ROIC) and Return on Assets (ROA). Using panel data from 40 of the world's largest airline companies over the 2015–2024 period, the study adopts an integrated framework that captures both capital efficiency and asset-based profitability. The results indicate that operational efficiency, measured by EBITDA Margin, and debt-servicing capacity, proxied by the Interest Coverage Ratio, are the most consistent positive determinants of both ROIC and ROA. In contrast, leverage exerts a persistent negative effect, highlighting the risks associated with excessive debt in a capital-intensive and volatile industry. Liquidity and asset turnover contribute positively to asset-based returns but have limited influence on capital efficiency, while firm size shows a negative association with both profitability measures, suggesting potential diseconomies of scale among the largest carriers. While the study does not introduce new theoretical constructs, its contribution lies in the rigorous empirical application of established financial frameworks by jointly analyzing ROIC and ROA within a unified model. From a policy perspective, the findings support regulatory and strategic initiatives aimed at enhancing industry resilience against fuel price volatility, demand shocks, and macroeconomic uncertainty.]]></description>
      <pubDate>Tue, 28 Jul 2026 11:07:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673121</guid>
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