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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>How to promote sustainable aviation fuel: Is flexibility beneficial to quota policies?</title>
      <link>https://trid.trb.org/View/2673134</link>
      <description><![CDATA[As sectoral emissions rebound post-COVID, decarbonizing aviation has become a pressing priority, and sustainable aviation fuel (SAF) is widely regarded as the most practical short- to medium-term option. To accelerate deployment, many jurisdictions have adopted SAF blending quotas, while some policies now allow flexible quotas by averaging SAF usage across multiple airports rather than meeting the quota at each airport individually. This paper evaluates the operational and network performance implications of such flexibility in a multi-airport, multi-airline setting. Using an analytical game-theoretic model that captures airline competition, economies of scale in SAF production, logistics, transportation costs, and airport-specific SAF co-benefits, the study finds that flexibility enhances network efficiency by lowering SAF costs, increasing total traffic, and facilitating SAF uptake. However, these gains are not uniform across the network: airports and airlines near SAF production facilities benefit the most, while remote or smaller airports may face declining traffic, especially under weak scale economies or strong local SAF incentives. Extensions with asymmetric market and plant locations reveal that mismatches between SAF production sites and demand centers can amplify disparities; in some cases, small airports located near these facilities act primarily as “quota-fulfillment tools” yet still see diminished activity. Furthermore, the Book-and-Claim mechanism maximizes system-wide efficiency by decoupling logistics, but concentrates co-benefits at the hub, depriving remote airports of local incentives. Overall, while flexibility supports cost-effective SAF adoption, it also risks aggravating regional inequalities, which highlights the need for targeted support and coordinated policy design to ensure a balanced and equitable transition.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673134</guid>
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    <item>
      <title>Public transport subsidies and the marginal cost of public funds: An interpretative review</title>
      <link>https://trid.trb.org/View/2665779</link>
      <description><![CDATA[This paper examines the rationale for public transport subsidies when revenues are raised through distortionary taxation, captured by the Marginal Cost of Public Funds (MCF). While first-best arguments such as scale economies and the Mohring effect justify subsidies, their relevance in second-best settings depends on the fiscal cost of raising funds. We compare general and partial equilibrium approaches, highlighting their advantages and limitations in incorporating key efficiency arguments, externalities, and labor market effects. Building on this, we develop a unified analytical framework that derives second-best pricing rules for public transport and assesses the welfare implications of subsidies under different conditions of scale economies, congestion, and labor taxation. Our framework clarifies when subsidies increase welfare and when the fiscal cost of financing them outweighs efficiency gains, providing both theoretical insights and policy-relevant guidance.]]></description>
      <pubDate>Tue, 26 May 2026 09:40:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665779</guid>
    </item>
    <item>
      <title>Multi-period hub-and-spoke network design considering flow-dependent economies of scale</title>
      <link>https://trid.trb.org/View/2649627</link>
      <description><![CDATA[This study explores a novel and generalized uncapacitated hub location problem (HLP) by integrating time-dependent decisions and flow-dependent economies of scale into the design of multi-allocation hub-and-spoke networks. Substantial investment and long-term strategic planning are required to construct such networks, during which market share often fluctuates significantly out of external factors like global economic dynamics and government policies. Flexible decision-making still lacks sufficient theoretical guidance despite its recognized importance in the timely deployment of hubs and the effective adjustment of transportation routes. Instead of a one-time implementation, this study investigates a budget-constrained phased network design that incorporates flow-dependent economies of scale to improve economic efficiency. This model captures the cost-sharing effects on inter-hub arcs as flow demand fluctuates across time periods. A mixed-integer linear programming model with a piecewise-linear concave cost function is formulated for the problem, posing a computational difficulty. To solve this challenging model, a specialized Benders decomposition algorithm is developed, which incorporates the Benders multi-cuts technique, the idea of approximate Pareto-optimal cuts, and a rolling horizon heuristic strategy. Through extensive numerical experiments, the proposed algorithm outperforms benchmark approaches. Findings include: (1) the impacts of budget and economies of scale are more significant in longer planning horizons but gradually diminish; (2) the flow-dependent approach enables more effective route consolidation and greater cost savings through economies of scale, an advantage that becomes more apparent over time.]]></description>
      <pubDate>Thu, 19 Feb 2026 10:53:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2649627</guid>
    </item>
    <item>
      <title>A hybrid cost model for light and heavy metro services</title>
      <link>https://trid.trb.org/View/2608034</link>
      <description><![CDATA[We develop a hybrid cost model to estimate the standard cost of light metro (LM) and heavy metro (HM) services, incorporating key technological factors such as degree of automation, wheel technology, and peak hourly capacity. The analysis draws on economic and transport data covering the entire universe of metro revenue kilometers operated in Italian cities in 2017. Our results show that cost structures vary substantially with the underlying technology. HM services are more capital-intensive due to higher train depreciation and associated capital costs compared to LM services. As a result, while HM services exhibit higher costs per kilometer, they are more cost-efficient on a per seat-km basis due to greater capacity. This implies that significant investments in high-capacity metro systems are economically justified only when demand levels are sufficiently high. A sensitivity analysis shows that standard unit costs decrease with improvements in train and driver productivity, and that gains in infrastructure maintenance efficiency have a stronger impact than those in train maintenance. Also scale economies play a role, as unit costs decline with increasing service size. Additionally, extending station opening hours results in higher costs that local authorities may choose to bear to enhance service quality. These findings can inform the definition of maximum economic compensation (i.e., the auction base) in competitive tendering procedures, or serve as a benchmark in negotiations with local monopolistic operators.]]></description>
      <pubDate>Mon, 29 Dec 2025 09:33:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2608034</guid>
    </item>
    <item>
      <title>Response Strategies for Demand Surges in Last-Mile Logistics: Managing Delivery Efficiency in Volatile Environments</title>
      <link>https://trid.trb.org/View/2539826</link>
      <description><![CDATA[Last-mile logistics firms are facing increasingly volatile environments in which they must constantly cope with demand fluctuations. This study provides insights into how last-mile logistics firms can effectively respond to sudden demand surges caused by unexpected events. Based on the literature review and practitioner interviews, the authors identify six popular last-mile logistics response strategies and compare their effectiveness. The authors first develop a theoretical framework that can assess the effectiveness of multiple response strategies systematically by utilizing a well-known transport economics theory, economies of scale. They then conduct a series of simulation experiments to (1) empirically evaluate the performance of the six strategies using their framework and (2) examine if the best-performing strategy(s) differs from one operating condition to another using the contingency theory perspective. Results suggest that many popular strategies used in practice are “non-viable” ones that can result in diseconomies of scale and reduce firms' competitiveness. Results also suggest that the set of “best” and “viable” strategies that can bring competitive advantages to firms varies from one firm to another depending on the firm's operating conditions.]]></description>
      <pubDate>Thu, 05 Jun 2025 13:59:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2539826</guid>
    </item>
    <item>
      <title>Economies of scale vs. service quality and environmental concerns: an application to integrated sea-land shipping systems with carbon tax policy insights</title>
      <link>https://trid.trb.org/View/2543182</link>
      <description><![CDATA[This paper explores the trade-offs among various objectives in determining optimal interport connections and the modal mix for inland transportation. The study is based on precise data on specific export and import ports, the American Northeastern rail network, vessel types, mode-specific costs, transit times, and CO₂ equivalent (CO₂e) emissions. The authors employ integer linear programming to address a multimodal, multi-objective, and multi-period transportation problem concerning unidirectional flows, from Western Europe to customers along the Ontario-Quebec trade corridor. The authors’ findings suggest that reducing land-based transportation costs outweighs the benefits of achieving economies of scale at sea. The results emphasize the importance of the geographic proximity of import ports to customers in the hinterland, in terms of determining optimal traffic flows, making the nearest import port to customers the most effective in traffic capture. This observation aligns with arguments in the literature on the limited effectiveness of large vessels due to factors beyond vessel size—such as port capacity and cargo handling efficiency among other logistical considerations. The authors tested the practicality of this approach through sensitivity analyses, considering scenarios such as a carbon tax regime and increased rail capacities.]]></description>
      <pubDate>Wed, 21 May 2025 09:52:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2543182</guid>
    </item>
    <item>
      <title>Market power of railway operators under different vertical structures</title>
      <link>https://trid.trb.org/View/2533821</link>
      <description><![CDATA[This paper theoretically and quantitatively investigates the effects of structural reforms – separation between infrastructure operations and train operations and the introduction of competition – on the degree of market power downstream, as measured by the Lerner index, by explicitly considering economies of scale at the infrastructure level and regulated access fees. We find that vertical separation reduces the degree of market power when there is a monopoly downstream. Besides, under vertical separation, the Lerner index under duopoly downstream exceeds that under monopoly when economies of scale are large enough. This follows from incomplete pass-through of access fees to prices. The authors' quantitative analysis indicates that, compared to separation, the Lerner index is higher and consumer surplus and social welfare are also higher in the case of a vertically integrated monopoly. With competition downstream, an integrated structure yields decreases in the integrated operator’s degree of market power and modest gains in terms of consumer surplus and social welfare for low degrees of product differentiation compared to separation. Larger economies of scale result in lower rail prices and access fees, which enhance consumer surplus and industry profits although the Lerner indices go up.]]></description>
      <pubDate>Tue, 13 May 2025 17:11:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2533821</guid>
    </item>
    <item>
      <title>Does antitrust immunity matter for complementary shipping alliances? Competition and welfare analysis</title>
      <link>https://trid.trb.org/View/2537072</link>
      <description><![CDATA[Shipping alliances are granted antitrust immunity (ATI) as a cooperative strategy for market development. However, the European Commission has ruled that these alliances no longer benefit from ATI treatment within the European Union (EU), raising concerns among governments about the implications for alliances and their associated ATI privileges. The authors analyze the alliance strategies of shipping companies, shippers’ consumer surplus, and governments’ social welfare in local and intermodal markets, focusing on service differentiation and economies of scale. They examine equilibrium decisions within three typical structures—no alliance, single alliance, and double alliance. Results show that shipping alliances significantly influence strategic decisions by lowering freight rates through the internalization of negative externalities from independent pricing. For both alliances and independents, moderate-scale economies and service differentiation reduce freight rates while increasing demand. Shipping companies form alliances to enhance competitiveness when these factors are significant, producing higher consumer surplus and social welfare. However, in markets with low service differentiation and scale economies, new alliances can undermine the benefits of both pre-existing alliances and independents. In such cases, social welfare is higher without alliances, and canceling alliance agreements may be a better market decision.]]></description>
      <pubDate>Mon, 28 Apr 2025 08:50:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2537072</guid>
    </item>
    <item>
      <title>Scaling laws of dynamic high-capacity ride-sharing</title>
      <link>https://trid.trb.org/View/2522376</link>
      <description><![CDATA[This study discovers a few scaling laws that can effectively capture the key performance of dynamic high-capacity ride-sharing through extensive experiments based on real-world mobility data from ten cities. These scaling laws are concise and contain only one dimensionless variable named system load that reflects the relative magnitude of demand versus supply. The scaling laws can accurately measure how key performance metrics such as passenger service rate and vehicle occupancy rate change with the system load. The scaling laws strongly agree with experimental results, with the values of 𝑅² exceeding 0.95 under all scenarios. In addition, the scaling laws can accurately reproduce experimental results of dynamic high-capacity ride-sharing involving different road networks, supply–demand patterns, vehicle capacities, and matching algorithms, indicating these scaling laws could be general and applied to other cities. These scaling laws provide a reference for transportation network companies and governments to efficiently manage dynamic ride-sharing services. For example, according to these scaling laws, when the demand is relatively high, e.g., system load equals 3, ride-sharing services with a capacity of 2 passengers can only accommodate 50% of demand. In comparison, high-capacity ride-sharing services with a capacity of 4 passengers can satisfy 72% of demand. The findings provide insight into the expected performance of ride-sharing, informing decisions about how to operate a fleet to improve transportation efficiency.]]></description>
      <pubDate>Tue, 22 Apr 2025 15:51:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2522376</guid>
    </item>
    <item>
      <title>The hierarchical multimodal hub location problem for cross-border logistics networks considering multiple capacity levels, congestion and economies of scale</title>
      <link>https://trid.trb.org/View/2517267</link>
      <description><![CDATA[The continuous growth of international container trade calls for logistics networks that seamlessly connect cross-border, domestic, and local transport services. In the design of these networks with various hubs and modes of transport, the consideration of both economies of scale for multimodal transport and congestion is essential since they can significantly impact the location of the hubs and their size. Thereby, in this paper, the authors study these features within a multimodal hub location problem for international trade that considers a hierarchy in the network structure. They develop a mixed-integer linear programming formulation, minimizing infrastructural, operational, and congestion costs. A hybrid adaptive variable neighborhood search algorithm with tailored operators and speed-up strategies is proposed to solve large-scale instances. Numerical experiments are conducted for China’s New Western Land-Sea Corridor case and provide new managerial insights for designing hierarchical, multi-modal, cross-border logistics networks.]]></description>
      <pubDate>Wed, 19 Mar 2025 16:58:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2517267</guid>
    </item>
    <item>
      <title>What do walking and e-hailing bring to scale economies in on-demand mobility?</title>
      <link>https://trid.trb.org/View/2499554</link>
      <description><![CDATA[This study investigates the impact of walking and e-hailing on the scale economies of on-demand mobility services. An analytical framework is developed to i) explicitly characterize the physical interactions between passengers and vehicles in the matching and pickup processes, and ii) derive the closed-form degree of scale economies (DSE) to quantify scale economies. The general model is then specified for conventional street-hailing and e-hailing, with and without walking before pickup and after dropoff. The authors show that, under a system-optimum fleet size, the market always exhibits economies of scale regardless of the matching mechanism and the walking behaviors, though the scale effect diminishes as passenger demand increases. Yet, street-hailing and e-hailing show different scale economies in their matching process. While street-hailing matching shows a constant DSE of two, e-hailing matching is more sensitive to demand and its DSE diminishes to one when passenger competition emerges. Walking, on the other hand, has mixed effects on the scale economies: while the reduced pickup and in-vehicle times bring a positive scale effect, the extra walking time and possible concentration of vacant vehicles and waiting passengers on streets negatively affect scale economies. All these analytical results are validated through agent-based simulations on Manhattan with real-life demand patterns.]]></description>
      <pubDate>Fri, 21 Feb 2025 17:08:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2499554</guid>
    </item>
    <item>
      <title>Incorporating Economies of Scale in Top-Down Pavement Management Systems</title>
      <link>https://trid.trb.org/View/2434046</link>
      <description><![CDATA[Top-down maintenance, rehabilitation, and reconstruction (MR&R) policies typically are modeled using Markov decision processes (MDPs). Within this framework, the total agency costs are assumed to increase linearly with the number of MR&R activities undertaken. However, there is empirical evidence to suggest that economies of scale (EoS) are present when agencies implement MR&R actions. EoS in infrastructure management refer to marginal savings in unit costs gained by increasing the scale of similar activities. This paper introduces EoS within a well-established system-level, top-down MR&R optimization framework for pavement management. In particular, given the concave nature of the proposed EoS-based objective function, two solution frameworks were implemented: a piecewise linear (PWL) approximation technique, and a branch-and-bound–based sigmoidal programming algorithm. Using a synthetic case study, the solution quality and computational efficiencies of the EoS-based problem formulations were compared with those of the fixed-unit-cost model. The resulting changes to the state–action distributions induced by the economies of scale are highlighted and discussed.]]></description>
      <pubDate>Mon, 28 Oct 2024 12:29:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2434046</guid>
    </item>
    <item>
      <title>Scale and Scope Economies Based on Net Characteristic of Railway Transportation and Its Application</title>
      <link>https://trid.trb.org/View/2283077</link>
      <description><![CDATA[The supply and cost function based on operating network of single and return rail transportation has been developed in the paper with a model to measure the degree of scale economies and scope economies in the network. After its application in a local rail company, it is determined that deregulation over railway can enhance its market power and compete with the truck transportation to some extent. The freight rate is the primary factor to determine the selection of mode.]]></description>
      <pubDate>Thu, 17 Oct 2024 09:15:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2283077</guid>
    </item>
    <item>
      <title>365-day sectional work zone schedule optimization for road networks considering economies of scale and user cost</title>
      <link>https://trid.trb.org/View/2408287</link>
      <description><![CDATA[This study proposes a methodology for deriving the optimal work zone schedule for the annual routine maintenance planning in an infrastructure asset management system considering the (i) economies of scale in work zone costs due to work zone synchronization and (ii) user costs across the road network with traffic assignments. A key aspect of the proposed methodology is the ability to derive in detail optimal work zone schedules of realistic-scale road networks in 100 m sections for 365 days, which is beneficial in practice. To this end, an optimization model of the work zone schedule is newly formulated as a mixed-integer programming (MIP) problem, and a novel bilevel solution method for the model utilizing the conventional solver Gurobi Optimizer with MIP algorithms such as root relaxation, dual simplex, barrier methods, and cutting planes is proposed. In application examples, the proposed methodology is applied to two real-world road networks, which confirms that the optimal work zone schedule can be obtained in 313.7 s for a network with 2640, 100 m, sections and in 168,180 s (46 h and 43 min) for a network with 5038, 100 m, sections.]]></description>
      <pubDate>Fri, 09 Aug 2024 17:18:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2408287</guid>
    </item>
    <item>
      <title>Research on Flow Distribution Optimization of Capacitated Logistics Network Based on Concave Cost</title>
      <link>https://trid.trb.org/View/2282454</link>
      <description><![CDATA[Due to strong economies of scale encountered in logistics industry, logistics costs are always nonlinearly correlated with the amount of flow and should be modeled as concave cost functions. Capacity of paths and nodes in logistics network is an important factor which will restrict the flow to pass through them, and then influence whole flow distribution. This paper studies the optimization problem of flow distribution for a capacitated logistics network based on concave costs, and its objective is to minimize the total logistics costs of the network. The authors propose an algorithm based on spanning tree-based genetic algorithm (GA) to address the problem. The effectiveness of this algorithm is fully demonstrated by an example.]]></description>
      <pubDate>Thu, 11 Jul 2024 13:52:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2282454</guid>
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