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    <title>Transport Research International Documentation (TRID)</title>
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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>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Research trends in airport management literature: a bibliometric analysis</title>
      <link>https://trid.trb.org/View/2664086</link>
      <description><![CDATA[The air transport industry is undergoing a significant transformation, ranging from operational processes to digitalization, driven by increasing global mobility. This transformation has evolved airport management from a mere infrastructure service into a complex, data-driven, multi-stakeholder, and technology-oriented discipline. The aim of this study is to examine 7,542 academic publications on “air traffic management,” “airport operations,” “airport performance,” and “airport planning” indexed in the Scopus database between 1928 and 2025 using bibliometric analysis methods. Analyses conducted using VOSviewer software revealed that the literature is predominantly concentrated in Engineering (37.1%) and Computer Science (18.1%). The research findings indicate that while airport management literature historically developed around the USA and NASA, there has been a significant increase in publication volume from Chinese institutions (e.g., Nanjing University of Aeronautics and Astronautics) in recent years. Thematic analyses demonstrate a shift in the field from conventional topics such as “safety” and “air traffic control” towards autonomous and predictive systems involving “machine learning,” “trajectory prediction,” and “artificial intelligence”. Consequently, this study predicts that future research in airport management will be shaped around digitalization and artificial intelligence, offering a strategic roadmap for researchers regarding interdisciplinary collaborations.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:34:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664086</guid>
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    <item>
      <title>Optimization of Air Navigation Spare Parts Supply Chain</title>
      <link>https://trid.trb.org/View/2693092</link>
      <description><![CDATA[Ensuring spare parts availability in air navigation systems is essential for operational continuity in aviation infrastructure. However, existing supply chain models often fail to jointly consider procurement decisions, transportation mode selection, inventory strategies, and risk factors, particularly in high-reliability sectors such as aviation. This study addresses this gap by developing a Mixed Integer Linear Programming (MILP) framework that integrates these components into a unified decision-making model aimed at minimizing total operational costs while maintaining high service levels. The model is tested on a real-world case study derived from Hamad International Airport operations, focusing on four critical radar components across a five-week planning horizon. The results demonstrate that a dual sourcing strategy and prioritizing maritime transport led to a significant reduction in logistics costs while ensuring full demand fulfillment. Strategic use of safety stock and vendor diversification contributed to both cost efficiency and operational reliability. These findings underscore the value of integrating risk-aware logistics and multi-modal transport planning in spare parts supply chains for critical infrastructure systems.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2693092</guid>
    </item>
    <item>
      <title>Airline schedule padding as a competitive strategy</title>
      <link>https://trid.trb.org/View/2647712</link>
      <description><![CDATA[This paper examines schedule padding as a strategic response to competitors' scheduling behavior in the U.S. domestic airline market. Using quarterly panel data at the airline–airport-pair level for 2023 and instrumental-variable estimation, we find strong evidence of strategic complementarity: 1-min increase in competitors’ padding induces nearly a 1-min increase by the focal carrier. This imitation persists across multiple benchmark definitions and market hauls, though the intensity is slightly weaker in highly competitive markets. The results suggest that the U.S. Department of Transportation on-time performance metrics may unintentionally promote a padding “arms race,” lengthening schedules, with implications for competition policy, scheduling efficiency, and consumer welfare.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647712</guid>
    </item>
    <item>
      <title>Mapping SDG Interlinkages in Airport Sustainability Strategies: A Co-occurrence, Clustering, and Network Perspective</title>
      <link>https://trid.trb.org/View/2649779</link>
      <description><![CDATA[Although airports increasingly reference the Sustainable Development Goals (SDGs), how these goals interact within airport sustainability strategies remains insufficiently explored. This study addresses this gap by systematically analyzing SDG interlinkages in the sustainability disclosures of 150 of the world’s busiest airports, representing over 60% of global passenger traffic. Using a structured three-phase analytical framework comprising co-occurrence analysis, hierarchical clustering, and network analysis, the study identifies dominant priorities and structural misalignments in current strategies. Airports most frequently align with SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure), and SDG 11 (Sustainable Cities and Communities), reflecting a prevailing emphasis on economic and urban development. Co-occurrence analysis confirms these patterns but also reveals significant trade-offs, particularly between SDG 8 and SDG 13 (Climate Action), highlighting persistent tensions between growth objectives and environmental responsibility. Hierarchical clustering isolates SDG 8 in a standalone group, illustrating the sector’s ongoing “growth versus sustainability” paradox. Network analysis identifies SDG 7 (Affordable and Clean Energy) and SDG 4 (Quality Education) as bridging goals capable of connecting fragmented sustainability domains. The findings support targeted interventions such as sustainability-linked finance, emissions-based investment, and unified reporting, to help airports transform sustainability from a compliance obligation into a driver of value creation.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2649779</guid>
    </item>
    <item>
      <title>A Group Decision-Making Based Spherical Fuzzy MCDM Approach for Smart Airports</title>
      <link>https://trid.trb.org/View/2648627</link>
      <description><![CDATA[Recent technological developments have changed the business landscape in the aviation industry. The widespread use of advanced digital technologies has transformed customers’ and passengers’ behaviors and expectations, as well as the future trajectory of the industry. The aviation ecosystem is characterized by its complexity, comprising numerous components, players, and systems. Within this framework, airports hold significant importance as they function as critical junctions for all components, stakeholders, and participants involved in the industry. The smart airport concept has become a buzzword with the integration of digital technologies into airports to offer innovative solutions and seamless passenger experiences. At this point, it is critical to understand the characteristics of a smart airport. However, transitioning to a smart airport is a strategic decision-making process that requires considering multiple criteria. Therefore, this study aims to identify and analyze the characteristics of smart airports to inform future strategies and roadmaps for decision-making. It emphasizes the importance of technology selection and investment planning through a group decision-making (GDM) approach. The study systematically collects characteristics through a comprehensive literature review and the insights of three decision-makers (DMs) who possess expertise in the industry. To evaluate the suitability, accuracy, and validity of these characteristics, the research utilizes the Spherical Fuzzy Analytic Hierarchy Process (SF AHP) methodology within the context of an airport in Turkey. The study findings indicate that technology infrastructure plays a crucial role in smart airports. Additionally, cybersecurity, interactivity, human-machine collaboration, connectivity, and technology strategy should be prioritized within the smart airport ecosystem.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2648627</guid>
    </item>
    <item>
      <title>Environmental and welfare effects of airline fuel tankering strategy</title>
      <link>https://trid.trb.org/View/2583125</link>
      <description><![CDATA[Fuel tankering refers to loading an aircraft with extra fuel—beyond immediate flight needs—to avoid costly refueling at the destination, taking advantage of inter-airport fuel price differences. This study constructs a game-theoretic model to examine strategic adoption patterns of fuel tankering under competitive market conditions and investigate the associated environmental and welfare effects. We find that, first, the fuel price difference alone does not necessarily induce fuel tankering adoption; rather, the extra fuel consumption and strategic interaction between airlines are also essential factors in the airlines’ decision. Second, a prisoner’s dilemma may emerge where airlines use fuel tankering in equilibrium to save costs, but they end up with lower profits compared to the case where no one adopts the fuel tankering strategy. Third, the use of fuel tankering always results in higher equilibrium consumer surplus, but at the cost of an adverse environmental effect. It may also lead to reduced social welfare. In addition, welfare analysis shows the airlines’ inefficient bias toward fuel tankering. Finally, policy implications are discussed.]]></description>
      <pubDate>Thu, 23 Oct 2025 09:24:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2583125</guid>
    </item>
    <item>
      <title>The impacts of airline corporate social responsibility in the air transport industry</title>
      <link>https://trid.trb.org/View/2566090</link>
      <description><![CDATA[This paper investigates the implications of airline corporate social responsibility (CSR) uptake in the air transport industry. Then, the authors extend the analysis considering the impact of parallel airline alliances on CSR of airlines. The results suggest that airports play a crucial role in shaping the CSR practices of airlines and that this impact should be viewed in the context of a network in the downstream market. When an airline adopts CSR, it can lead to an increase in social welfare and consumer surplus if the degree of substitutability of services provided by the airline and its parallel alliance is high enough.]]></description>
      <pubDate>Thu, 21 Aug 2025 09:19:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2566090</guid>
    </item>
    <item>
      <title>Airport Energy Resilience Decision Support Tools



</title>
      <link>https://trid.trb.org/View/2588334</link>
      <description><![CDATA[Airports across the United States are facing rapidly evolving and increasingly complex energy demands while facing significant challenges in managing their existing energy systems. Additionally, most existing airport energy planning tools and methods lack granularity, forecasting capability, scenario modeling, and resilience-focused performance metrics needed to guide strategic decision-making. 

To address these challenges, airports need practical, data-informed tools capable of quantifying resilience across multiple energy systems, forecasting capacity needs under a variety of transition and disruption scenarios, and identifying energy-related pinch points that may affect operations, maintenance, and capital development. Building upon the foundational concepts outlined in ACRP Research Report 260: Airport Energy Resiliency Roadmap, this project aims to advance the industry from conceptual guidance to operational tools and measurable performance metrics. Research is needed to identify the critical variables and factors that influence airport energy resilience and to develop practical tools that provide structured, repeatable methodologies for assessing existing and future energy resilience and support data-driven decision-making.

The objective of this research is to develop decision support tool(s) for U.S. airports of various sizes that can help quantify airport energy resilience spanning across airport asset categories (e.g., equipment, subsystems, buildings, campus) and functional areas (e.g., operations, maintenance, capital planning), focusing on existing and new actions of which the airport has direct influence or control, and a guide for applying the tool(s).]]></description>
      <pubDate>Tue, 12 Aug 2025 10:11:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2588334</guid>
    </item>
    <item>
      <title>Identifying potential routes and airports in Brazil: An integration of the route selection and fleet assignment problems</title>
      <link>https://trid.trb.org/View/2522612</link>
      <description><![CDATA[The strategic planning of airline networks is critical for maximizing profitability and operational efficiency. Among the key challenges faced by airlines is the Route Selection Problem (RSP)—determining which routes to operate based on demand, economic conditions, and infrastructure—and the Fleet Assignment Problem (FAP)—optimally assigning aircraft to routes to minimize costs. While these problems are typically addressed separately, their integration can yield more robust and profitable solutions. This study presents a novel mathematical model that integrates RSP and FAP using Mixed Integer Linear Programming (MILP) to optimize network profitability and fleet utilization. The model was validated through a case study of a fictional regional airline in Southeast Brazil, analyzing 41 potential locations. The results identified 28 profitable routes, including 11 destinations currently without regular flights and one without an airport. By optimizing fleet allocation and route selection, the model provides a data-driven framework for airlines, policymakers, and investors to enhance network efficiency and identify underserved markets. This study demonstrates that an integrated approach to route selection and fleet assignment can significantly improve decision-making in the airline industry, offering a scalable methodology for network expansion and strategic investment.]]></description>
      <pubDate>Thu, 10 Apr 2025 09:23:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2522612</guid>
    </item>
    <item>
      <title>Incorporating Shock Events into Aviation Demand Forecasting and Airport Planning</title>
      <link>https://trid.trb.org/View/2484659</link>
      <description><![CDATA[This report presents a methodology to help airport operators identify relevant shock events, understand their potential impact on airport business, and develop strategies to better withstand and respond to them. The research team drew on experiences from the COVID-19 pandemic and other shock events within both the airport industry and other sectors to develop a five-step, systematic methodology to address shock events in airport forecasting, management, and planning. The report will be of interest to airports of all sizes and the planners and consultants who support them.]]></description>
      <pubDate>Sun, 05 Jan 2025 17:07:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2484659</guid>
    </item>
    <item>
      <title>Airport Cooperative Research Program (ACRP) 2024 Annual Report</title>
      <link>https://trid.trb.org/View/2485308</link>
      <description><![CDATA[The Airport Cooperative Research Program (ACRP) is an applied research program managed by the Transportation Research Board of the National Academies of Sciences, Engineering, and Medicine, and sponsored by the Federal Aviation Administration. Together with public- and private-sector industry experts, ACRP produces research solutions that cover a diverse set of topics: safety, policy and planning, airport design, construction, legal issues, operations and maintenance, human resources, sustainability, administration, among others. ACRP addresses and helps solve the airport industry’s most pressing issues. This 2024 annual report contains the following: Introduction; Meet the ACRP Staff; Innovations; Research and Publications; Strategic Planning; Communication and Collaboration; Digital Engagement; Appendix A - Publications of the Airport Cooperative Research Program; and Appendix B - Summary of Project Status Through December 31, 2024.]]></description>
      <pubDate>Sun, 05 Jan 2025 17:07:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2485308</guid>
    </item>
    <item>
      <title>Factors affecting efficient cargo logistics management at Murtala Muhammed International Airport, Lagos, Nigeria</title>
      <link>https://trid.trb.org/View/2471350</link>
      <description><![CDATA[Cargo logistics management at most commercial airports is crucial to a nation’s economy and serves as a revenue source for airlines and other stakeholders. To maximise the importance of cargo operations at airports, there is a need to successfully manage cargo distribution efficiently to reduce delivery time and costs. However, achieving efficient air cargo logistics management is often challenging due to several factors limiting cargo processing. This paper examines the factors affecting cargo logistics management at airports in Nigeria. The study followed the quantitative research method and surveyed various stakeholders by random sampling at the Murtala Mohammed International Airport, Lagos through a well-designed research questionnaire. Data collected were analysed using exploratory and confirmatory factor analysis. Exploratory Factor Analysis (EFA) identified bureaucracy, equipment and facilities, traffic flow, and malpractices as the significant factors affecting the logistics of cargo distribution at the airport. Confirmatory Factor Analysis (CFA) validated the statistical significance of bureaucracy, equipment and facilities, traffic flow, and malpractices as critical factors affecting the logistics of cargo distribution at the airport. It was found that bureaucracy negatively affects equipment and facilities, while malpractices negatively affect traffic flow and equipment and facilities. The findings highlight the need to incorporate real-time automation of cargo processing with equipment provision to enhance airports' capacity for efficient cargo logistics management in Nigeria. In practice, the finding implies that airport stakeholders need to improve their efficiency by eliminating bureaucratic bottlenecks to cargo distribution. The finding also highlights research need to examine the level at which bureaucracy and malpractices impact cargo supply chains at airports. The study impacts the air cargo logistics industry with strategic options for improving airport cargo operations.]]></description>
      <pubDate>Thu, 26 Dec 2024 16:14:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2471350</guid>
    </item>
    <item>
      <title>ACRP Insight Event: Exploring the Impact of Artificial Intelligence on the Airport Industry



</title>
      <link>https://trid.trb.org/View/2413898</link>
      <description><![CDATA[Artificial intelligence (AI) technology and applications are growing exponentially across all industries. For airports, use of AI can result in improved operational efficiencies, more accurate traffic forecasting, and improved system diagnostics. While there is much interest in the possible applications of AI at airports, both the supporting technologies and possible applications are still at a nascent stage. There is much to be learned about the benefits, risks, and limitations—particularly in the areas of cyber and operational security, fact validation, legal issues, and public safety.

The objective of this project is to conduct an in-person ACRP Insight Event (see Special Note A) for airport-industry practitioners, relevant stakeholders, and subject matter experts (SMEs) to discuss the key factors related to the benefits, risks, and transformational aspects of AI technology for airports.]]></description>
      <pubDate>Mon, 05 Aug 2024 19:19:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2413898</guid>
    </item>
    <item>
      <title>Optimization of Airline Support Facility Space at Non-Major Airports of India Using Goal Programming</title>
      <link>https://trid.trb.org/View/2369426</link>
      <description><![CDATA[A forecast by the India Brand Equation suggests that the Maintenance, Repair, and Overhaul (MRO) industry will burgeon to US$ 2.4 billion by 2028. This anticipated expansion necessitates the strategic allocation of airport land for essential airline support facilities, which is pivotal in augmenting non-aeronautical revenue. In this study, land allotment practices at twenty-three Indian airports were evaluated against proposed optimization strategies for fuel stations, ground servicing equipment (GSE), hangars, and porta-cabins. Goal Programming was employed to minimize discrepancies in achieving land use and revenue benchmarks. The optimization, considering various constraints, revealed a potential 77% enhancement in area utilization and a 95% increase in revenue. Additionally, a model was formulated to determine the optimal allocation for commercial outlets, utilizing hypothetical data. The findings advocate for land resource optimization at non-major airports, where traditional traffic-based revenue is limited. This paper presents a roadmap for airport operators and policymakers, ensuring efficient resource management amid the aviation sector’s growth.]]></description>
      <pubDate>Thu, 16 May 2024 16:35:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2369426</guid>
    </item>
    <item>
      <title>Priority Issues</title>
      <link>https://trid.trb.org/View/2379647</link>
      <description><![CDATA[In the administration of the Airport Cooperative Research Program, there are times when issues arise that require immediate attention and cannot wait for the typical ACRP research processes.  In response, ACRP has created this Priority Issues Sub-program with a panel to review and select time-sensitive projects--either as Quick Response Projects, designed to provide the industry with targeted, practical research results within a year's time, or as First Look Projects, to address issues for which the airport industry needs a basic understanding of potential implications before more thorough research can be done.]]></description>
      <pubDate>Tue, 14 May 2024 15:31:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2379647</guid>
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