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    <title>Transport Research International Documentation (TRID)</title>
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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>Heterogeneous labour, city size and transportation in agglomeration equilibrium</title>
      <link>https://trid.trb.org/View/2703726</link>
      <description><![CDATA[This paper analyses the theoretical mechanism of skill heterogeneity across city size and transportation under the ‘new’ new economic geography (NNEG) framework. We make a heterogeneous selection model from the NNEG framework and a heterogeneous assumption for skilled workers with continuous density function ∫ˢₛ ƒ(s)ds in which both iceberg-type transport costs and the value of spatial interactions between workers from across-cities are taken into account in a spatial economy. Our framework shows that the presence of transportation and city size creates a mechanism which always promotes spatial sorting for heterogeneous workers according to skills’ spatial distribution. Agglomeration equilibrium in large cities is the unique equilibrium and it is stable when the cost of trade and the value of spatial interactions between workers exist across-cities. It is obvious that tougher competition in larger cities requires more high-skilled workers, thus becoming more attractive to skilled job seekers.]]></description>
      <pubDate>Thu, 27 Aug 2026 16:32:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703726</guid>
    </item>
    <item>
      <title>An adjustable pricing scheme for public charging stations: Balancing drivers' range anxiety and operational efficiency</title>
      <link>https://trid.trb.org/View/2725126</link>
      <description><![CDATA[With the increasing penetration of electric vehicles, the shortage of public charging piles impacts the charging experience of electric vehicle drivers, exacerbating their range anxiety. In particular, low charging power at a high state of charge (SOC) reduces the service efficiency of public charging facilities, leads to long access time for drivers waiting for charging, and restrains the profit of a public charging operator. To address this challenge, we develop a market equilibrium model and introduce an adjustable pricing scheme in which the price per unit amount of charging (i.e., unit price) changes linearly with the SOC to affect drivers' charging decisions (i.e., whether to charge and when to stop charging) and improve social welfare, which includes drivers' utility from charging and the operator’s profit. We further formulate three optimization scenarios (i.e., social welfare maximization, profit maximization, and second best), and deduce the properties of the optimal solutions. We theoretically prove that the welfare-oriented operator should adopt a zero unit price at the minimum SOC and gradually raise the unit price as the current SOC increases. Moreover, whether in pursuit of maximum profit or maximum social welfare, the operator should avoid the 'inefficient charging' behavior of drivers (i.e., persisting in charging at a high SOC), even with low potential demand or sufficient charging piles. We also compare the proposed adjustable pricing scheme with traditional static pricing strategies, proving that the adjustable pricing scheme is superior in improving social welfare. We further conduct numerical experiments to verify the above analytical findings. The proposed adjustable pricing scheme is demonstrated to be able to allow the public charging operator to achieve a higher welfare or profit. Its practical feasibility and policy implications are discussed. The proposed model is also extended to account for heterogeneous VOT and EV charging specifications, quadratic pricing, and pricing linearly dependent on charging power. The numerical results of the extended models show that the welfare-oriented operator still sets a high unit price at high SOC levels to deter drivers from inefficient charging.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2725126</guid>
    </item>
    <item>
      <title>The time slot allocation problem in liberalised passenger railway markets: a multi-objective approach</title>
      <link>https://trid.trb.org/View/2643265</link>
      <description><![CDATA[The liberalisation of the European passenger railway markets recently promoted by the entry into force of the 4th railway package states a new scenario where different Railway Undertakings compete with each other in a bidding process for time slots. The infrastructure resources are provided by the Infrastructure Manager, who analyses and assesses the bids received, allocating the resources to each Railway Undertaking. Time slot allocation is a fact that drastically influences the market equilibrium. In this paper, we address the time slot allocation problem within the context of a liberalised passenger railway market as a multi-objective model. The Infrastructure Manager is tasked with selecting a point from the Pareto front as the solution to the time slot allocation problem. We propose two criteria for making this selection: the first one allocates time slots to each company according to a set of priorities, while the second one introduces a criterion of fairness in the treatment of companies to incentive competition. The assessment of the impact of these rules on market equilibrium has been conducted on a liberalised high-speed corridor within the Spanish railway network.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643265</guid>
    </item>
    <item>
      <title>High-speed rail and the spatial economy</title>
      <link>https://trid.trb.org/View/2652546</link>
      <description><![CDATA[High-speed rail (HSR) is expanding rapidly worldwide. This review identifies three defining features of HSR: its strong appeal to high-value business travelers, the presence of long-haul economies whereby costs per kilometer decline with distance, and its capacity to enable intercity commuting between cities. These characteristics lead to non-trivial implications for the spatial economy. While HSR infrastructure is costly, travel-time savings and induced economic spatial reallocation can be substantial. We review both cost–benefit analyzes and empirical evidence, and argue that general equilibrium effects are central to understanding the full economic impact of HSR.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652546</guid>
    </item>
    <item>
      <title>Who benefits from autonomous vehicles? Distributional and general-equilibrium effects in a monocentric city with heterogeneous households and tax interactions</title>
      <link>https://trid.trb.org/View/2647914</link>
      <description><![CDATA[I study the welfare and distributional effects of autonomous vehicles (AVs) using a monocentric city model with heterogeneous households and endogenous labor supply. The formulation captures the fact that AVs allow performing activities while commuting. Numerical results show that AVs increase aggregate welfare, but low-skilled households can experience losses if they are initially located further from the CBD and only high-skilled households can afford an AV. This is due to high-skilled households moving to the periphery, causing an increase in housing prices for the low-skilled, among others general-equilibrium effects. Using the revenues from a distance-based road pricing to finance a labor tax cut for the low-skilled results in gains for both skill types, but reaches only 15% of the welfare increase obtained from using the revenues to finance a general labor tax cut. This latter recycling scheme almost doubles the welfare gains from the introduction of AVs, but amplifies its uneven effects.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647914</guid>
    </item>
    <item>
      <title>A Literature Review and Methodological Recommendations to Measure the Economic Impact of Air Transport</title>
      <link>https://trid.trb.org/View/2666100</link>
      <description><![CDATA[This paper reviews 96 studies on the economic impact of air transport, focusing on four key methodologies: input-output analysis, cost-benefit analysis (CBA), computable general equilibrium (CGE) models, and econometric techniques. Our findings show that input-output analysis and CGE models are best suited for studying the broad economic effects of air transport on the entire economy. Input-output analysis reveals that air transport creates jobs and economic value, with a stronger backward linkage—its effect on upstream industries—than a forward linkage. It also plays a key role in tourism, logistics, and freight. CBA and econometric methods are more effective for analyzing localized effects. The CBA literature indicates that airport expansion projects significantly increase social welfare. CGE models show that subsidies and taxes on air transport can benefit the economy by boosting government revenues, and that capacity expansions help both core and peripheral regions. Econometric studies confirm a positive link between air transport and various economic indicators, including GDP, employment, trade, and foreign direct investment. The methodologies themselves have advanced to overcome certain limitations. Input-output analysis has been extended with multi-period and multi-region models. CBA now uses alternative discounting techniques. CGE models have become more sophisticated with spatial and dynamic applications, and some even integrate air transport networks and game theory. Econometric techniques have adopted more robust models like heterogeneous time series cross section Granger causality, difference-in-difference, propensity score matching, seemingly unrelated regression and spatial econometrics to better address endogeneity. These advanced methods can provide a more robust approach for future research.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666100</guid>
    </item>
    <item>
      <title>Assessing the benefits of collaborative ridesharing across transportation network companies</title>
      <link>https://trid.trb.org/View/2633658</link>
      <description><![CDATA[By allowing two or more passengers to dynamically share parts of their trips in a single vehicle, ridesharing can lead to significant vehicle mileage traveled (VMT) savings, but its potential is often limited by market fragmentation, due to the co-existence of multiple Transportation Network Companies (TNCs). Although a collaborative ridesharing market that allows sharing across TNCs can produce additional VMT savings, to what extent such benefits vary based on market characteristics and behaviors of individual TNCs remains insufficiently understood. This study presents a framework to assess the maximum potential benefits of collaborative ridesharing and the contrasting equilibrium benefits resulting from varying strategic behaviors of TNCs. Specifically, we adopt a multi-TNC shareability network approach to estimate the maximum benefits under various market conditions, assuming that all TNCs are fully collaborative. In reality, TNCs’ willingness to collaborate is primarily motivated by their own profit gains, and thus we further propose a game-theoretic model to capture the collaboration dynamics among TNCs as a Nash game, allowing us to estimate the equilibrium benefits of collaborative ridesharing and evaluate the effectiveness of various profit-sharing schemes. Using the real-world TNC market in Manhattan, New York City as a case study, we find that a fully collaborative ridesharing market can generate additional VMT savings of up to 10.3 % over the existing fragmented market, and this upper bound is jointly determined by demand density, market division, competition intensity, and trip length. The Nash game results also reveal that the TNCs’ willingness to collaborate largely depends on the profit-sharing scheme; the Shapley value scheme tends to favor smaller, higher-priced TNCs, while the Equal Profit Method benefits dominant TNCs and more effectively facilitates collaboration among TNCs with greater pricing disparities. The proposed framework provides valuable insights for market regulators and business alliances, enabling them to evaluate collaboration outcomes and design appropriate profit-sharing schemes to promote and sustain collaborative ridesharing.]]></description>
      <pubDate>Tue, 10 Mar 2026 09:56:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633658</guid>
    </item>
    <item>
      <title>To park or to share your autonomous vehicle?</title>
      <link>https://trid.trb.org/View/2599027</link>
      <description><![CDATA[With the ability to drive autonomously during trips and park themselves, autonomous vehicles (AVs) are anticipated to revolutionize future mobility. How AVs interact with people and transform travel behavior patterns (mobility paradigm shift) is expected to be a “game changer”. This paper investigates an innovative future mobility paradigm where private-AV owners can share their vehicles on a mobility service platform when not in use. We develop tractable models to characterize the travel, parking, and vehicle-sharing choices of AV users, optimize operation strategies of the mobility service platform considering AV sharing, and evaluate their system-wide impacts. In particular, given the operation strategies of the mobility service platform, we formulate the system equilibrium that includes the AV owners’ choice equilibrium and the mobility service market equilibrium. We consider two different business formats for platform operator (namely reselling and commissioning) and three types of AV owners (risk-neutral, risk-averse or risk-seeking). Subject to the system equilibrium, we examine the pricing and fleet sizing strategies of the platform to achieve either profit-maximization or social welfare-maximization. Our analysis explores the impacts of introducing the AV sharing scheme on AV owners, mobility service operator and users, and social welfare. It shows that introducing the AV sharing scheme has the potential to create a win-win-win outcome for AV owners, mobility service operator, and users, with an overall improvement in social welfare. Moreover, both a social welfare-maximizing operator and a profit-maximizing operator may achieve a win-win-win outcome under certain conditions. With risk-averse AV owners, the reselling format proves to be superior to the commissioning format; with risk-seeking AV owners, the commissioning format will outperform the reselling format; while with risk-neutral AV owners, both formats can yield identical platform profit and social welfare. Numerical examples are presented to illustrate the analytical results and provide a deeper understanding of the potential implications of AV sharing.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599027</guid>
    </item>
    <item>
      <title>Integrated operation of ride-hailing and shared micromobility services in multimodal transportation networks with public transit: The unintended consequences of regulations</title>
      <link>https://trid.trb.org/View/2599158</link>
      <description><![CDATA[This paper investigates the integrated operation of ride-hailing and shared micromobility services provided by transportation network companies (TNCs) such as Uber, Lyft, and Didi, and examines the policy implications of prevalent TNC regulations under complex multimodal interactions. We consider a TNC platform that simultaneously coordinates a fleet of for-hire vehicles and deploys micromobility infrastructures to offer both ride-hailing and shared micromobility services, in conjunction with a public transit agency operating in the same transportation network. To capture the key elements of such a multimodal system, we develop a market equilibrium model that incorporates ride-hailing waiting times, micromobility access and egress times, the spatial distribution of micromobility infrastructure, passenger demand, platform pricing and fleet sizing, vehicle repositioning, and traffic congestion. The platform’s decision-making problem is formulated as a non-convex program, and a tailored solution method is proposed to efficiently compute the solution through problem reformulation and dimensionality reduction. Using the developed model, we analyze the implications of two prevalent TNC regulations: (a) a congestion charge on ride-hailing services aimed at mitigating traffic congestion; and (b) a vehicle density floor for shared micromobility services to promote spatial equity. Our results reveal several unintended consequences of these regulations due to the interplay between ride-hailing, shared micromobility, and public transit in a multimodal transportation network. Interestingly, we find that how the congestion charge on ride-hailing trips influences public transit ridership crucially depends on micromobility’s role as a feeder mode: when micromobility serves as a significant transit feeder, the congestion charge increases transit ridership; otherwise, the congestion charge on ride-hailing services could inadvertently reduce transit ridership. Furthermore, we find that imposing a vehicle density floor for micromobility services, while improving the spatial equity of micromobility, may inadvertently reduce the equity of ride-hailing services, ultimately widening the overall equity gap across the multimodal transportation network. These unintended consequences are observed only when all three modes-ride-hailing, shared micromobility, and public transit-are jointly modeled, underscoring the critical importance of accounting for multimodal interactions in the design and evaluation of TNC regulations.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599158</guid>
    </item>
    <item>
      <title>Mean reversion and long memory dynamics in the Shanghai Containerized Freight Index</title>
      <link>https://trid.trb.org/View/2595148</link>
      <description><![CDATA[This paper deals with the investigation of the long memory properties of the Shanghai Containerized Freight Index for the time period from 16 October 2009 to 18 October 2024. Using fractional integration methods, we want to determine if shocks in the series have transitory or permanent effects. The results indicate that the series are very persistent when using the whole sample size with an order of integration above 1. However, if we separate three different subsamples, corresponding to the pre-Covid, Covid and post-Covid periods, we observe reversion to the mean in the pre-Covid period; however, during the Covid, there is a substantial increase in the value of d and turns decreasing after the pandemic.]]></description>
      <pubDate>Thu, 20 Nov 2025 17:06:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2595148</guid>
    </item>
    <item>
      <title>Beyond lotka-volterra: A game-theoretic exploration of two-dimensional airline competition</title>
      <link>https://trid.trb.org/View/2588425</link>
      <description><![CDATA[Korea’s airline industry has undergone a transformative period marked by the strategic acquisition of Asiana Airlines (AAR) by Korean Air Lines (KAL). This acquisition is an important moment for the Korean airline industry, as KAL, a full-service carrier (FSC) strengthens its position while facing competition from low-cost carriers (LCCs). The competition between FSCs and LCCs in Korea has shifted due to the coronavirus pandemic, new regulations, and market changes. This study presents a two-stage Lotka–Volterra model integrated with game theory to analyze the competitive dynamics between FSCs and LCCs in Korea. Specifically, this study examines airline competition before and after COVID-19 to reflect evolving market dynamics, in which each carrier’s market share is influenced by the others’ strategies. Incorporating game theory makes it possible to evaluate carrier interactions and analyze the effects of competition and cooperation strategies on market equilibrium. The model uncovers shifts in competitive behavior and market dynamics, highlighting the pandemic’s influence on airline competition. Although LCCs and FSCs adopted different strategies, the industry’s unstable recovery highlights ongoing restructuring and sustainability challenges. The findings of this study provide managerial insights into airline competition and strategic approaches for navigating external shocks.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2588425</guid>
    </item>
    <item>
      <title>Tax progressivity and mobility costs</title>
      <link>https://trid.trb.org/View/2572006</link>
      <description><![CDATA[This paper examines how mobility costs influence the effectiveness and desirability of tax progressivity using a general equilibrium spatial model. A key feature of the model is that workers’ idiosyncratic productivity depends on location. The interaction of amenities, idiosyncratic shocks and moving costs implies that progressive taxation distorts location choices by reducing incentives for agents to relocate to their most productive areas. Using a quantitative framework, I find that the negative effect of tax progressivity on output is weakest when mobility costs are either relatively low or high. The optimal degree of tax progressivity balances the costs of spatial tax distortions against the benefits of enhanced insurance, leading to relatively high optimal progressivity at both extremes of mobility costs.]]></description>
      <pubDate>Thu, 28 Aug 2025 17:15:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572006</guid>
    </item>
    <item>
      <title>Attribute Production and Biased Technical Change in Automobiles</title>
      <link>https://trid.trb.org/View/2571870</link>
      <description><![CDATA[Cars have gotten bigger and faster yet more fuel efficient in recent decades. Why? The authors estimate an equilibrium model of car attribute production using U.S. household microdata for 1995–2017 and structurally decompose attribute trends into underlying mechanisms. The authors find that technical change led to gains in all attributes. Rising gas prices boosted efficiency but were offset by surging demand for size and acceleration. Efficiency standards were largely ineffective. The authors show that using technology alone to meet tighter standards quadruples compliance costs, while half the efficiency gain from a fuel-saving technology subsidy is reallocated to other attributes in equilibrium.]]></description>
      <pubDate>Mon, 21 Jul 2025 08:53:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571870</guid>
    </item>
    <item>
      <title>Market size and fare-free public transit in theory</title>
      <link>https://trid.trb.org/View/2567204</link>
      <description><![CDATA[Studies of fare-free public transit claim it is most convenient in small communities, because their transit systems tend to have lower farebox recovery ratios and more available capacity. This paper offers a rationale for these tendencies by working through a static model of a bus route with boarding/alighting delays, crowding and elastic demand that scales with a “market size” parameter. Due to externalities passengers impose, ridership arises as an equilibrium outcome given a certain market size and the agency’s choice of fare and fleet size. When the fare and fleet size are chosen to satisfy the First- and Second-Order Conditions for maximizing social surplus, the farebox recovery ratio, number of passengers on each bus and the rate passengers board each bus are all smaller in smaller markets. An extension explores capacity choice.]]></description>
      <pubDate>Fri, 11 Jul 2025 14:28:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2567204</guid>
    </item>
    <item>
      <title>On the inefficiencies in the multi-platform e-hailing market with impatient customers</title>
      <link>https://trid.trb.org/View/2567481</link>
      <description><![CDATA[In a competitive e-hailing market, each participating platform can only utilize a portion of the total demand (passengers) and supply (drivers). This fragmentation may lead to market inefficiencies. In this paper, the authors introduce an equilibrium model of the multi-platform e-hailing market considering exogenous passenger demand and vehicle supply, and addressing two types of passenger cancellation behaviors. A queueing model with reneging is incorporated to allow passenger cancellations during matching due to impatience. A utility choice model is incorporated to allow passenger cancellations if they are dissatisfied with the service being provided. The authors use the model to quantify the effects of fragmentation, examining varying combinations of demand and supply levels, illustrating different market conditions. The authors investigate multiple scenarios, which include up to 10 symmetrical platforms and asymmetrical duopolies. Additionally, the authors construct and compare the supply curves of a symmetrical duopoly and an equivalent monopoly. It can be shown that the duopoly will be in the Wild Goose Chase (WGC) state for a broader range of market conditions compared to the monopoly, which gives rise to inefficiencies in a fragmented market.]]></description>
      <pubDate>Fri, 11 Jul 2025 14:28:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2567481</guid>
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