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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <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>Directions of Transformational Changes in Motor Transport Enterprises</title>
      <link>https://trid.trb.org/View/2694413</link>
      <description><![CDATA[The efficiency of a significant part of motor transport enterprises is unsatisfactory due to their inability to respond quickly to changes in the external and internal environments. One of the ways to solve this problem is to implement transformational changes across functional, organizational, structural, and managerial domains. These changes are implemented through a set of external and internal measures aimed at developing the enterprise in a dynamic external environment to ensure the efficiency of its operations and the necessary level of competitiveness. A model of transformational changes in motor transport enterprises has been developed. This model and the developed modelling algorithm allow us to identify promising strategies and to form and explore options for implementing transformational changes. To select the optimal transformational change in the work, an objective function that includes a competitiveness indicator (an integrated competitiveness indicator) and economic indicators (profitability index, net present value, and internal rate of return) has been justified. It is proposed to select the optimal option based on the “worst-case method”. Through this approach, the weight coefficients for the objective function criteria have been identified as follows: 0.308 for the integral competitiveness indicator; 0.154 for net present value; 0.462 for the profitability index; and 0.076 for the internal rate of return. Utilizing the developed models and algorithms, strategies have been outlined, and various options for implementing transformational changes have been formulated for the Vinnytsia branch of the private enterprise “Avtotranskom” (Ukraine). Using the set objective function and the “worst-case method”, the optimal transformational change among those developed was determined. By implementing this option, enterprises can operate more efficiently and compete more successfully in the market.]]></description>
      <pubDate>Fri, 29 May 2026 14:09:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694413</guid>
    </item>
    <item>
      <title>Micromobility and Economy</title>
      <link>https://trid.trb.org/View/2580784</link>
      <description><![CDATA[Transportation, which is seen as an important development tool in developed countries, is a field where developments in technology are used intensively. Problems such as energy and climate crises caused by fuel consumption at the global level leads developed countries’ technology and infrastructure investments in transportation towards electric alternatives, specifically for short-distance journeys. Micromobility is a short-range and electricity-oriented transportation adaptation that continues to develop rapidly to keep pace with these problems. It makes an economic contribution by saving costs and reducing travel time. It reduces distance cost by 69% and carbon emissions by 84% compared to the car when used with public transportation. Within the scope of this study, the current situation of micromobility in the cities of Türkiye is explained with basic economic variables and the potential cities where it can be the subject of investment are interpreted with spatial statistical analysis. The findings show that micromobility investments are located in cities which have metropolitan municipality administration also in the southern and western regions. Although not yet statistically significant, it is noteworthy that the results show that the correlation between high micromobility investment—high economic level is most significant in Istanbul, while the correlation between low micromobility investment—low economic level is most significant in the southeast and eastern regions. The emphasis on the fact that micromobility will gain a share of 25% in the mode choice for the future years, especially in developed countries, is a sign that micromobility will be a very important investment tool for the transportation and energy sectors of the national economy.]]></description>
      <pubDate>Thu, 28 May 2026 17:09:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580784</guid>
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    <item>
      <title>Integrated Container Slot Allocation and Automated Stacking Crane Scheduling in Automated Container Terminals with Limited Buffers</title>
      <link>https://trid.trb.org/View/2703736</link>
      <description><![CDATA[This paper investigates the integrated scheduling of automated stacking cranes (ASCs) and container slot allocation in automated container terminals (ACTs) with limited buffer capacity. A hybrid stacking strategy based on time windows is proposed, and a bi-objective mixed-integer programming model is developed, considering automated guided vehicles and truck buffer capacities, ASC safety distances, and handshake area operations. An enhanced non-dominated sorting genetic algorithm II with tabu search (NSGA-II-TS) is designed, with parameters optimized via sensitivity analysis. Experiment results show that comparisons with an exact mixed-integer linear programming solver validate the solution quality of the proposed approach, and that the proposed algorithm significantly outperforms benchmark heuristic methods in generating high-quality Pareto-optimal solutions. Case studies reveal that dynamically adjusting handshake area locations and setting buffer capacity to six units effectively balance container flow and operational costs. The proposed approach is also validated against two alternative scheduling strategies, demonstrating superior effectiveness. This research provides new strategies and a robust method for improving the operational efficiency of ACTs under buffer constraints.]]></description>
      <pubDate>Sat, 16 May 2026 12:15:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703736</guid>
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    <item>
      <title>Resilience and efficiency of global container ports: A DEA–Malmquist analysis based on physical infrastructure and strategic typologies</title>
      <link>https://trid.trb.org/View/2658012</link>
      <description><![CDATA[Container port efficiency is vital for sustaining global trade, especially amid disruptions such as the COVID-19 pandemic, which exposed systemic weaknesses such as port congestion and schedule delays. However, limited research has systematically evaluated port performance dynamics across systemic shocks, especially from a resilience and investment-alignment perspective. In this study, a Malmquist data envelopment analysis (DEA) framework is applied to examine the efficiency and productivity trends of major container ports from 2018 to 2022. The proposed model addresses cross-port differences and data constraints by focusing on key physical infrastructure inputs—gantry cranes, port area, and quay length—and container throughput as output. The results show that ports such as Singapore and Shanghai consistently achieve high efficiency, whereas other ports lag behind. Productivity gains mainly reflect technological change (TC), not technical efficiency change (TEC), exposing a gap with the scale efficiency change (SEC) needed to realize investments. A strategic matrix classifies ports by overall performance and progress, identifying resilient and advancing ports such as Ningbo-Zhoushan and Qingdao. These insights help policymakers and port managers align investment with long-term resilience goals and respond more effectively to future disruptions.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658012</guid>
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    <item>
      <title>Transportation Efficiency in Latvia in the Context of Economic Productivity and Environmental Sustainability</title>
      <link>https://trid.trb.org/View/2579700</link>
      <description><![CDATA[This study analyzes the transportation efficiency in Latvia within the broader context of economic productivity and environmental sustainability. The study aims also to explore how transportation efficiency is influenced by Latvia's unique spatial distribution of population density, in particular, the pronounced concentration of residents in the capital / its surroundings and the sparse population (rural areas – almost uninhabitable) of territories near the borders with neighboring countries (including EU). The object of this study is the territories of Latvian municipalities (36 counties and 7 cities of national significance that are not part of the counties), the empirical base is territorial statistics and data from the State Treasury of Latvia for 2022–2023. Quantitative research methods: correlation analysis using the Pearson coefficient, two-stage hierarchical cluster analysis. The results of the study indicate significant differences between the central (within a radius of approximately 100 km from Riga) and remote territories of the country. Centered municipalities benefit from better transport infrastructure, higher economic productivity and comparatively low per capita greenhouse gas emissions, but face problems associated with concentrated emissions per unit area. In contrast, Latvia’s remote municipalities demonstrate lower economic productivity, relatively high per capita greenhouse gas emissions and poor transport infrastructure, leading to economic isolation and environmental inefficiency. The study emphasizes the need for tailored strategies to enhance transportation efficiency in Latvia: optimizing networks and promoting sustainable transport in centered regions, and investing in infrastructure and innovative mobility solutions in remote areas.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579700</guid>
    </item>
    <item>
      <title>Circular supply chain with product-service systems: a case of recycled products</title>
      <link>https://trid.trb.org/View/2651884</link>
      <description><![CDATA[Circular supply chain management has encountered a critical challenge in promoting recycled products to the market and maintaining product competitiveness. Integrating the product-service system in the circular supply chain is expected to deliver better business performance. This study explores the supply chain mechanism based on a product-service system of recycled products. The qualitative technique has been deployed to collect data on the key personnel involved product-service system in the circular supply chain. Thirteen key informants are participated and interviewed separately. The data have been analysed, and results show that the marketability of recycled products, digital platform, customer services, supplier readiness and product return flow is the critical success of the product-service system in a circular supply chain. In addition, the manufacturing supply chain must pay attention to the network distribution, risk management and mitigation strategy.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2651884</guid>
    </item>
    <item>
      <title>Application of an AI-Based Hybrid Model for LNG Spot Freight Rate Prediction</title>
      <link>https://trid.trb.org/View/2669607</link>
      <description><![CDATA[In response to the increasing volatility of liquefied natural gas (LNG) spot freight rates, this study applies deep learning models to improve forecasting accuracy. The performance of standalone models—Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN)—is compared with that of hybrid models. The results show that the LSTM+CNN model achieved the highest prediction accuracy, reaching approximately 88% for short-term forecasts. While the standalone CNN model performed poorly in both short- and long-term predictions, its combination with LSTM significantly improved prediction accuracy. This improvement is attributed to CNN’s ability to extract local patterns and LSTM’s strength in capturing long-term dependencies, demonstrating a complementary effect. Furthermore, incorporating the attention mechanism (ATT), which has proven effective in previous studies, enhanced predictive performance, particularly in long-term forecasting. The LSTM+ATT model showed strong results due to the attention mechanism’s capability to assign greater weight to important time steps and reduce information loss over longer sequences.]]></description>
      <pubDate>Mon, 20 Apr 2026 11:14:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669607</guid>
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    <item>
      <title>Intelligent Arctic shipping route planning with dual objectives of economy and carbon emission reduction using deep reinforcement learning</title>
      <link>https://trid.trb.org/View/2685334</link>
      <description><![CDATA[The rapid opening of Arctic Sea routes driven by climate change presents significant strategic opportunities for global shipping while intensifying the trade-off between economic efficiency and environmental sustainability. Existing route-planning approaches face challenges in dynamically balancing this conflict under complex and variable ice conditions. This study proposes an intelligent Arctic route-planning framework based on Deep Q-Network (DQN) reinforcement learning. A key contribution is the development of a reward function incorporating dynamic carbon emission and time penalties, calibrated through an ice-resistance model to capture increased fuel consumption in thicker ice conditions, thereby enabling simultaneous optimization of navigational efficiency and emission reduction objectives. The framework is validated using both simulated environments and real Arctic sea-ice data from August 2025. By adjusting a single trade-off parameter, a spectrum of optimized routing strategies can be generated. In a realistic 78 × 34 ice-grid environment, compared with the cost-priority strategy, the balanced strategy increases voyage distance by 4.94% and travel time by 3.79%, while reducing carbon emissions by 1.53%; compared with the emission-priority strategy, it shortens voyage distance by 4.41% and travel time by 8.44%, with only a 1.29% increase in carbon emissions. In a constrained 8 × 8 grid environment, all strategies converge to the same optimal path due to structural limitations. This study provides a data-driven approach for quantitatively characterizing and balancing the economic–environmental trade-off in the Arctic route planning, offering practical decision support for low-carbon navigation and the sustainable transition of maritime transport.]]></description>
      <pubDate>Fri, 27 Mar 2026 10:14:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685334</guid>
    </item>
    <item>
      <title>Container terminal efficiency under external shocks: A hybrid DEA-Regression analysis of Dar es Salaam port (2019–2023)</title>
      <link>https://trid.trb.org/View/2646867</link>
      <description><![CDATA[Purpose. This paper evaluates the technical Efficiency of Dar es Salaam Port’s container terminal operations over the period 2019–2023, explicitly accounting for the influence of macroeconomic conditions and the COVID-19 pandemic on performance metrics. The study addresses a critical gap in port efficiency research by disentangling internal operational capability from external contextual factors in a developing-economy maritime gateway serving landlocked East and Central African countries. Methodology. A two-stage hybrid analytical framework integrates input-oriented Data Envelopment Analysis (DEA) with Contextual Value Added (CVA) regression. DEA efficiency scores are computed using a three-year rolling window approach with inputs (quay length, gantry cranes, terminal area) and outputs (container throughput, vessel calls). Second-stage ordinary least squares regression isolates the effects of GDP, trade volume, and pandemic disruption on measured efficiency. Quantitative findings are triangulated with qualitative stakeholder surveys (n=45) and semi-structured interviews to capture operational perceptions and institutional constraints. Results. DEA analysis reveals temporal efficiency variation ranging from 0.838 (2019) to 0.966 (2021), with post-pandemic decline to 0.890 (2023). CVA regression identifies a statistically significant negative relationship between trade volume and efficiency (ß = -1.76×10⁻⁵, p = 0.03), indicating binding infrastructure constraints. The COVID-19 dummy exhibits a paradoxical positive coefficient (ß = +0.090, p = 0.02), reflecting efficiency gains under suppressed demand rather than genuine productivity enhancement. Theoretical contribution. This study advances port efficiency assessment by demonstrating that unadjusted frontier methods can mask capacity deficits when external demand fluctuates. The hybrid DEA-CVA framework enables evidence-based attribution of efficiency sources, enhancing policy relevance. Practical implications. Findings underscore the urgent need for infrastructure expansion and procedural digitalization to accommodate regional trade growth under the African Continental Free Trade Area.]]></description>
      <pubDate>Wed, 25 Mar 2026 16:41:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646867</guid>
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      <title>A study on the efficiency and influencing factors of China’s four-stage ports using DEA and Tobit two-stage models</title>
      <link>https://trid.trb.org/View/2675860</link>
      <description><![CDATA[Chinese ports reached their fourth stage of development in 2013. Based on this context, this study analyzes the efficiency of four-stage ports using time series data on 16 major coastal ports in China from 2010 to 2019, covering the latter half of stage three into stage four. Using Data Envelope Analysis (DEA)-Window and Tobit models, the results indicate that although most ports maintained high efficiency, issues such as inefficient resource use, over-expansion, and a lack of strategic planning were identified. Particularly, based on the average efficiency scores, ports in the central region exhibited relatively lower efficiency levels compared to those on the north and south coasts. Factors such as local population size, industrial productivity, and economic level positively influenced efficiency. In addition, our results showed a negative correlation between port efficiency and loans from financial institutions, suggesting financial support may not always positively contribute to port development. Based on these findings, we propose policy recommendations for the Chinese government, port management authorities, operators, and the international port industry.]]></description>
      <pubDate>Wed, 25 Mar 2026 11:44:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2675860</guid>
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    <item>
      <title>Statistical analysis of vehicle usage intensity in a transport company</title>
      <link>https://trid.trb.org/View/2666015</link>
      <description><![CDATA[The article presents the application of selected statistical analyses to monitor the degree of efficiency of the use of a fleet of vehicles in a transport company. The main objective of the work was to present selected statistical tests for a given number of vehicles. 179 vehicles of various types and brands in use. Three groups of vehicles were distinguished in the analysis in terms of the load capacity of the cargo space: small cars, delivery vans and trucks. One of the factors differentiating vehicles within the distinguished groups was their mileage at the beginning of the observation period. Data on the vehicle usage intensity during one year of operation were analyzed. The single-factor statistical analyses used are of a preliminary nature, being an introduction to the issues of multifactor analysis. On the other hand, single-factor analyses can be used in the issues of classification of a heterogeneous the fleet of vehicles in road transport companies. The presented procedure showed the possibility of adapting statistical analyses to the management and forecasting of vehicle use in a transport company from the B2B and B2C sectors.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666015</guid>
    </item>
    <item>
      <title>Does economic regulation improve efficiency? The case of airports</title>
      <link>https://trid.trb.org/View/2673080</link>
      <description><![CDATA[Over the past 30 years, regulatory reforms have been introduced to enhance airport efficiency compared to traditional rate-of-return regulation. But have these reforms succeeded? We survey research on the impact of airport regulatory frameworks on technical, cost and allocative efficiency, addressing methodological challenges and identifying gaps for future study. We find that approaches such as total factor productivity, stochastic frontier analysis and data envelopment analysis are useful for assessing the effects of regulation, but many studies miss salient inputs and outputs, particularly in measuring capital. In second stage analyses, governance related variables, such as ownership structure, competition and regulatory design, are often overlooked. Most studies conclude that regulation improves airport efficiency, with dual-till price-caps and light-handed regulation being the more effective. However, light-handed regulation fails to reduce aeronautical charges and there is no consensus on which regulatory model achieves lower charges. Finally, allocative efficiency through peak pricing and slot trading remains unexplored.]]></description>
      <pubDate>Fri, 20 Mar 2026 08:38:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673080</guid>
    </item>
    <item>
      <title>Static and dynamic scheduling of flex-route transit services using constraint programming</title>
      <link>https://trid.trb.org/View/2670108</link>
      <description><![CDATA[Flex-route transit (FRT) has emerged as a promising solution for low-density areas, but its operational scheduling, particularly in real-time, presents significant challenges. This paper develops a novel scheduling system to generate optimal and efficient schedules for both static (pre-planned) and dynamic (real-time) FRT operations. The system utilizes a two-stage algorithm based on Constraint Programming (CP). In the first stage, a Constrained-Insertion heuristic generates an initial feasible schedule. In the second stage, this solution is systematically improved using a CP-based local search procedure that explores various neighborhoods to find an optimal schedule while satisfying all operational constraints. The algorithm’s effectiveness is validated through a series of numerical experiments. This network was designed with realistic operational parameters, including a 10 km route, varying demand rates, and systematically adjusted slack times and schedule adherence constraints to test the model under diverse conditions. Results demonstrate the proposed mechanism’s ability to generate high-quality schedules in a timely manner. The two-stage algorithm significantly outperforms a conventional insertion algorithm, especially under tight constraints. For instance, relaxing the on-time arrival constraint at intermediate stops by just one minute increased the percentage of served static requests from 86% to 91.5%. Furthermore, the system effectively utilizes available slack time, enhancing service capacity for both static and dynamic requests. The findings show that introducing small, controlled schedule flexibility at intermediate stops can substantially improve FRT service efficiency and passenger accommodation. This suggests that less rigid schedules, when managed by an intelligent optimization system, can make FRT more reliable and cost-effective services.]]></description>
      <pubDate>Wed, 18 Mar 2026 09:00:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670108</guid>
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    <item>
      <title>Partial factor productivity and its determinants for Chinese railway</title>
      <link>https://trid.trb.org/View/2648591</link>
      <description><![CDATA[Given that Chinese central and local governments determine the railway network exogenously, it’s crucial to measure partial factor productivity (PFP) in addition to total factor productivity (TFP) and identify its determinants. This study uses panel data from 18 railway bureaus in China from 2009 to 2020, employing a three-stage DEA-Malmquist index and Tobit model to measure the partial factor productivity of the railway system and its determinants from static and dynamic perspectives across national, regional, and bureau levels. The findings show that fixed production factors have limited impact on the efficiency of the railway industry, particularly in the northeastern and eastern regions of China. Additionally, the efficiency of China’s railway system shows significant regional heterogeneity, with the DEA-effective regions mainly concentrated in the central and eastern regions. Furthermore, external environmental factors play a role in optimizing railway transport efficiency, with varying degrees of influence across different regions. Changes in industrial structure, increased R&D investment, and the expansion of per capita highway mileage all contribute to improving railway transport efficiency. Conversely, road density and per capita GDP have a negative impact on railway efficiency, the influence of these determinants varies across different regions.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2648591</guid>
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    <item>
      <title>Re-Examining the Sources of Inefficiency in Hub's European Ports</title>
      <link>https://trid.trb.org/View/2665628</link>
      <description><![CDATA[European ports now face the challenge of handling significant international traffic. Ports need to improve their operating efficiency because of their limited logistics capacity. We employ a non-parametric approach by using the Generalised Method of Moments (GMM), based on data envelopment analysis, to evaluate and compare the performance of European ports. Data from 30 European HUB ports from 2005 to 2019 are included in our study. According to the findings, port development is essential to the prosperity of European ports because it boosts economic growth, particularly in those without container traffic, and it has a significant impact on the major economic sectors by influencing them to address port inefficiencies. By concentrating on fixing inefficiencies, ports with little container traffic can nevertheless be very important. Despite their low direct throughput, these ports can boost economic activity in other sectors with effective administration and expansion. © 2025, Faculty of Maritime Studies. All rights reserved.]]></description>
      <pubDate>Thu, 19 Feb 2026 13:21:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665628</guid>
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