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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>
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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>Shipping-Freight Forecasting with Multi-Domain Features: Role of News Sentiment</title>
      <link>https://trid.trb.org/View/2711987</link>
      <description><![CDATA[The shipping market is complex and nonlinear, which makes freight-rate forecasting highly challenging. This study proposes an STE-Informer model that integrates a multisource feature set. First, we collect 120,000 shipping-news articles from several major industry websites and use the FinBERT model to extract sentiment features, capturing market-sentiment fluctuations. Second, we apply technical analysis to construct a set of technical indicators, exploring the intrinsic information embedded in freight indices. Third, we incorporate economic features to reflect the impact of global economic conditions and external shocks on the shipping market. Finally, we integrate sentiment, technical, and economic features into a multidimensional feature matrix and employ the Informer deep neural network for freight-index forecasting. The results show three key findings: (1) short-term sentiment provides the best predictive performance, improving accuracy by 10%–70% compared with medium- and long-term sentiment; (2) the multisource feature set reduces mean squared error by 76.9%, 83.1%, 88.2%, and 92.5% across four shipping markets, respectively, relative to the no-feature baseline Informer(N); (3) the proposed STE-Informer model achieves the best overall performance in shipping-index prediction, ranking first in forecasting the Baltic Dry Index and Baltic Dirty Tanker Index.]]></description>
      <pubDate>Tue, 09 Jun 2026 10:54:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711987</guid>
    </item>
    <item>
      <title>Driving through the Gig Economy in Latin America: Uber Drivers Views on Needs, Risks and Opportunities</title>
      <link>https://trid.trb.org/View/2663588</link>
      <description><![CDATA[The Uber-IPSOS 2024 study provides the most comprehensive assessment to date of Uber drivers in Latin America, capturing insights from more than 13,000 respondents across the region. It reveals that ride-hailing platforms have become an important occupational alternative and a key source of flexible income for a diverse and increasingly educated workforce. Drivers are predominantly male, middle-aged, and often use the platform part-time to supplement other income sources. Most consider themselves as independent workers and prioritize autonomy and flexibility over traditional employment arrangements. Despite its role as a financial buffer, platform work does not shield drivers from broader economic vulnerabilities. Like the general population, the majority report being in debt and using their Uber earnings to meet essential household needs, underscoring the importance of this occupational alternative for their financial security. Social protection coverage remains limited and fragmented, with low participation in health insurance and pension systems. While many drivers express interest in saving for retirement, few have access to structured, portable mechanisms that facilitate long-term financial planning. The findings highlight the need for policies centered on individuals rather than employment status, capable of combining flexibility with protection. Expanding access to financial tools, portable benefit schemes, and voluntary savings mechanisms can strengthen workers’ resilience without undermining the appeal of flexible work. The evidence collected in this and other IDB surveys suggest the need to update the regulation and avoid the trade-offs of the current binary regulation. Ideally, a “third way” to facilitate the use of platforms and improve the coverage of those who choose it as an alternative to complement their income.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:13:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663588</guid>
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    <item>
      <title>Climate change: trends and their effect on seaport activity and infrastructure: insights from major ports of India</title>
      <link>https://trid.trb.org/View/2666407</link>
      <description><![CDATA[Seaborne transport plays a crucial role in local, national, and global economies, helping to shift manufacturing from regional to global levels. However, international trade is susceptible to the impacts of changing climate patterns. This paper examines how climate disruptions affect India’s international trade by analysing the seaport traffic of eight major Indian ports from 1982 to 2021. To that effect, using Principal Component Analysis, we create a climate index consisting of wind speed, temperature, relative humidity, and precipitation variables and we show that the index variables significantly impact port activities. Additionally, our analysis also accounts for variables such road and railway infrastructure, since this directly affects cargo flows, port traffic and regional incomes. Moreover, in the context of our analysis, we consider that robust road and rail infrastructure improves resilience against extreme weather events by ensuring better connectivity, quicker recovery, and sustained economic stability. We employ several econometric techniques, and diagnostic checks to draw empirical inferences. Moreover, the analysis distinguishes between east and west coast ports of India, given their markedly different climatic and economic conditions. India’s position as a climate change hotspot heightens the vulnerability of its ports. The methods and findings discussed here provide steps for policymakers to prioritise training, revise insurance policies, upgrade infrastructure, promote stakeholder collaboration, and adopt green solutions to mitigate climate impact.we]]></description>
      <pubDate>Tue, 26 May 2026 09:40:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666407</guid>
    </item>
    <item>
      <title>Determinants of Perceived Service Quality in Urban Public Transport in Emerging Economies</title>
      <link>https://trid.trb.org/View/2694407</link>
      <description><![CDATA[This article examines the main factors influencing user satisfaction with urban public transport, based on the case of the ALSA network in Greater Agadir (Morocco). A questionnaire survey conducted among 205 users was analyzed using a two-step statistical approach: Principal Component Analysis (PCA) was first employed to identify the dimensions of perceived service quality, followed by multiple linear regression to assess their impact on overall satisfaction. The results highlight three major determinants: service reliability, travel time, and cost. These findings emphasize the importance of improving service regularity and adapting fare policies in order to enhance equity and the overall quality of urban transport. The study therefore provides an empirical framework that can support decision-making and may be applicable to other emerging urban contexts.]]></description>
      <pubDate>Wed, 13 May 2026 17:01:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694407</guid>
    </item>
    <item>
      <title>Surface Parking Lots in Downtown Areas and the Role of Regulatory Delay in Optimal Dynamic Land Use*</title>
      <link>https://trid.trb.org/View/2659429</link>
      <description><![CDATA[In this paper, we explore the implication for urban form, urban structure and optimal land use policy of vacant land used for downtown surface parking lots in urban areas. We develop a dynamic, spatial general equilibrium urban model to show cases where vacant land can be optimal and suboptimal depending upon its temporary use, economic and regulatory conditions as well as externalities. We show in numerical simulations how the structure of the urban economy responds to different policies and consider their implications for different types of cities. These results have important implications for cities concerned about the impacts of vacant land and in particular of surface parking lots in downtown areas.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659429</guid>
    </item>
    <item>
      <title>The Distributional Consequences of Tax Pass-Through: The Case of Germany’s Fuel Tax Discount</title>
      <link>https://trid.trb.org/View/2640930</link>
      <description><![CDATA[Exploiting exogenous variation in retail fuel prices from a temporary fuel tax discount in Germany, we explore the distributional consequences emerging from differential pass-through rates over space and time. We draw on daily gasoline prices of virtually all gas stations in Germany and neighboring France, with France serving as a control site, and estimate an event study model covering the full period of the discount from June to August 2022. We find average pass-through rates on the order of 96% for diesel and 82% for petrol, but with substantial variability by regional income and station density. Our results additionally reveal heterogeneity over time: The magnitude of the pass-through rate dissipates sharply for both fuel types over the three months in which the discount was in effect, dropping to 46% for diesel and 74% for petrol by the final month, a pattern consistent with retailer responses to short-term changes in consumer attention. Taken together, our results indicate that average pass-through estimates may obscure spatial and temporal heterogeneity that bears upon the assessment of distributional effects: A back-of-the-envelope calculation indicates that 62% of the discount’s financial relief accrues to households with above-median incomes.]]></description>
      <pubDate>Tue, 17 Mar 2026 09:47:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640930</guid>
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    <item>
      <title>The volatility in shipping market: Relationship between container freight rates and inflation</title>
      <link>https://trid.trb.org/View/2630680</link>
      <description><![CDATA[The COVID-19 pandemic has triggered pronounced fluctuations in the shipping market, complicating decisions on freight rate setting, capacity allocation, and investment planning. Understanding how inflation influences container shipping is therefore essential for shipping companies seeking to anticipate market changes more accurately. This study examines the nonlinear relationship between container freight rates and inflation, focusing on the China–Europe route and the China–North America West Coast route. To ensure robust results, the analysis incorporates three control variables: port congestion index, container trade index, and container fleet growth. The findings reveal an inverted N-shaped relationship between inflation and freight rates, with two inflection points demarcating shifts in the direction of the effect: inflation exerts a positive influence within the range between the two points but a negative influence outside it. The inflection points observed in this study are higher for the United States compared to Europe, likely due to differences in economic performance and monetary policy. These results highlight the need for shipping companies to adapt their operational and pricing strategies based on the specific economic conditions of the regions in which they operate.]]></description>
      <pubDate>Mon, 02 Mar 2026 08:56:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630680</guid>
    </item>
    <item>
      <title>Impact of the Ripple Effect on the Resilience of Multimodal Container Port Operations: A System Dynamics Simulation Approach</title>
      <link>https://trid.trb.org/View/2657953</link>
      <description><![CDATA[Current assessments of port resilience primarily focus on the risks affecting its operations, often neglecting the ripple effects across different subsystems within a port. In multimodal container ports, these sub-systems include liner shipping, feeder shipping, railways, and trucking. Moreover, prevailing research predominantly addresses port resilience from a macro perspective without detailing micro-level operational concerns. This article proposes a new integrated methodology that not only considers but also quantifies the ripple effects across different multimodal sub-systems and their impact on overall port resilience. It employs real operational and accident data to assess the resilience of a multimodal container port under different disruption scenarios, hence providing valuable insights into preventing systemic failures through targeted interventions at the subsystem level. The proposed methodology comprises three principal components: a system dynamics (SD) simulation that integrates variables and factors affecting port resilience, a resilience analysis model that converts system performance into a resilience metric based on three fundamental criteria, and a comprehensive port system resilience assessment utilizing Evidential Reasoning (ER). Each step, from the detailed simulation model reflecting micro-level mechanisms to aggregating information across subsystems, builds toward determining the port's overall resilience. Multiple disruptive scenarios are designed and derived from historical failures and field investigations to validate the effectiveness of the proposed methodology. The results demonstrate that the proposed approach effectively assesses port performance under disruptions, identifies critical subsystems, and supports timely recovery strategies. Applicable to other port systems, this approach offers essential insights for improving long-term resilience in container port operations.]]></description>
      <pubDate>Wed, 18 Feb 2026 11:59:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2657953</guid>
    </item>
    <item>
      <title>Distribution of humanitarian aid considering accessibility limitations due to transitory road disruptions</title>
      <link>https://trid.trb.org/View/2594498</link>
      <description><![CDATA[This paper presents a humanitarian aid distribution framework designed to address accessibility limitations caused by temporary road disruptions. The proposed mathematical programming model minimizes total arrival time at delivery points while considering route continuity, vehicle scheduling, fleet capacity, and road repair progress. Validation was performed using a real-world case study, and scenario analyses were conducted to assess the impact of variations in fleet availability, road damage ratios, and repair times on total arrival time. The results revealed that synchronizing the departure and arrival times of vehicles at each destination node based on the progress of road repairs can minimize the time required for aid vehicles to reach the destination nodes, offering practical applications for improving logistical processes. This approach contributed to understanding the impact of road disruptions and the progress of road restoration activities on the configuration of humanitarian aid distribution routes and the overall operation time. As an additional contribution, a methodological approach was considered for establishing the arrival and departure times of a limited number of vehicles to demand points, taking into account the expected completion times of repair operations on affected roads.]]></description>
      <pubDate>Mon, 13 Oct 2025 13:52:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2594498</guid>
    </item>
    <item>
      <title>Highway Revenues Under Changing Economic Conditions</title>
      <link>https://trid.trb.org/View/2560889</link>
      <description><![CDATA[The three primary sources of revenue for the Texas State Department of Highways and Public Transportation (previously the Texas Highway Department) in the past have been federal funding, license fees, and motor fuels taxes. In 1974, these three sources alone accounted for over 93 percent of all revenues. With rising fuel prices at least two of these primary sources, license fees and fuels taxes, may not continue to increase, and in fact may even decline in the future. Using the results of the analysis contained within the report, future revenues from license fees and fuels taxes are estimated under different scenarios about future incomes and prices.]]></description>
      <pubDate>Mon, 04 Aug 2025 17:46:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2560889</guid>
    </item>
    <item>
      <title>State Revenue Scenarios for Different Economic Conditions and Taxation Policies</title>
      <link>https://trid.trb.org/View/2549154</link>
      <description><![CDATA[Recent changes in basic economic conditions have had a considerable impact on state revenues available to the Texas State Department of Highways and Public Transportation (SDHPT). The historical growth pattern for revenues has been interrupted because of reduced growth in travel and numbers of vehicles. This change in the revenue growth pattern, coupled with large increases in costs, has resulted in a large reduction in the real purchasing power of available revenues. Because of this new revenue and cost situation, it is more difficult to predict future SDHPT revenues for different possible economic conditions and taxation policies. This report presents a method that can be used to project future revenues for different scenarios (forecasts) of economic conditions and different taxation policies. Revenue projections for the different economic conditions considered in this report reveal that there is a wide variation in future revenues, depending upon which scenario is considered. Even in the most optimistic case, however, a considerable increase in taxes would be necessary to prevent real revenues from decreasing substantially, if current trends in highway costs continue in the future.]]></description>
      <pubDate>Mon, 16 Jun 2025 17:15:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2549154</guid>
    </item>
    <item>
      <title>The role of economic size in the interaction between international trade, international tourist arrivals, and transport modes: Empirical evidence in Vietnam</title>
      <link>https://trid.trb.org/View/2519546</link>
      <description><![CDATA[This study examines the role of economic size in the interaction between international trade, international tourist arrivals, and transport modes using the SARIMAX-(E)GARCH model. Using quarterly data for the period 2000–2023 in Vietnam shows that GDP is an important factor explaining the volatility of international trade, international tourist arrivals, and the majority of transport modes in Vietnam. International trade drives the majority of freight transport modes, but it is also positively impacted by sea and air transport. International tourist arrivals is a factor that promotes international trade and has a two-way relationship with passenger transport modes. The growth of international tourist arrivals also contributes to the development of air, road, and rail transport, and vice versa. Meanwhile, its relationship with passenger transport by sea and inland waterways has had the opposite trend. The interaction also shows the tendency for products to be complementary or substitutes between modes of transport. The outbreak of the COVID-19 pandemic has negatively affected international tourist arrivals and most modes of passenger transport, but it has had little impact on international freight and trade. These findings show the different roles of factors and are the basis for forecasting and setting out policies for the development of trade, tourism, and transport.]]></description>
      <pubDate>Mon, 31 Mar 2025 16:15:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2519546</guid>
    </item>
    <item>
      <title>Decision Support Systems for Transport Planning and the Management of Tenders: The Case Study of Lombardy</title>
      <link>https://trid.trb.org/View/2263924</link>
      <description><![CDATA[In Lombardy in the last ten years, public subsidies to bus companies have increased, while the market share and quality of public transport have declined. Lombardy Region initiated a reform of public local transport to improve the effectiveness of the public transport through competition and economic incentives. The reform calls for tenders for a network divided into areas. In this paper a methodology developed to support the grantor both in the choice of the areas and the management of the tenders is described.]]></description>
      <pubDate>Tue, 28 Jan 2025 14:52:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2263924</guid>
    </item>
    <item>
      <title>A data-driven approach to analyse the co-evolution of urban systems through a resilience lens: A Helsinki case study</title>
      <link>https://trid.trb.org/View/2459198</link>
      <description><![CDATA[Urban areas are dynamic systems, in which different infrastructural, social and economic subsystems continuously co-evolve. As such, disruptions in one system can propagate to another. However, open challenges remain in (i) assessing the long-term implications of change for resilience and (ii) understanding how resilience propagates throughout urban systems over time. Despite the increasing reliance on data in smart cities, few studies empirically investigate long-term urban co-evolution using data-driven methods, leading to a gap in urban resilience assessments. This paper presents an approach that combines Getis-ord Gi* statistical and correlation analyses to investigate how cities recover from crises and adapt by analysing how the spatial patterns of urban characteristics and their relationships changed over time. The authors illustrate their approach through a study on Helsinki’s road infrastructure, socioeconomic system and built-up area from 1991 to 2016, a period marked by a major socioeconomic crisis. By analysing this case study, the authors provide insights into the co-evolution over more than two decades, thereby addressing the lack of longitudinal studies on urban resilience.]]></description>
      <pubDate>Mon, 16 Dec 2024 11:59:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2459198</guid>
    </item>
    <item>
      <title>Unveiling the causal effects of China’s minimum living standard guarantee on household transportation expenditures: A causal forest analysis</title>
      <link>https://trid.trb.org/View/2440454</link>
      <description><![CDATA[The authors investigate the causal effects of China’s Minimum Living Standard Guarantee (MLSG, also called Dibao) subsidy on household transportation expenditures. Utilizing data from the Chinese Social Survey, they employ a combination of the propensity score matching (PSM), causal forest (CF) and marginal treatment effect model (MTE) methodologies to rigorously estimate the subsidy’s effects. The PSM allows us to mitigate selection bias by matching MLSG recipients with comparable non-recipients. While the causal forest captures the heterogeneity of treatment effects across various household profiles. The result of MTE indicate that observable and essential heterogeneity are present to influence the effect of their subsidies, which present the consistent with PSM and CF. The causal mediation analysis indicates the mediating mechanism that MLSG impacts on household transportation expenditures, while also revealing significant variations among different regions. The study not only refines their understanding of the MLSG’s effects on household spending but also offers novel insights into applicational advancements by incorporating machine-learning techniques for policy evaluation. These results have important implications for policy formulation and refinement, particularly in the urban-rural differences.]]></description>
      <pubDate>Tue, 22 Oct 2024 09:07:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2440454</guid>
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