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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>Profitability determinants of logistics firms: a comparative analysis of Croatia and Slovenia</title>
      <link>https://trid.trb.org/View/2701332</link>
      <description><![CDATA[This paper examines the profitability factors of logistics firms in Croatia and Slovenia, small open economies that rely on logistics infrastructure and operations to leverage their geographical advantages and maximise their potential to develop into regional logistics hubs and clusters. The analysis is based on a sample of 3,680 logistics firms in the Republic of Croatia and 5,730 in the Republic of Slovenia. The data for the analysis are sourced from the Orbis - Bureau van Dijk database and cover the period from 2007 to 2022. The study applies dynamic panel data analysis using the Arellano-Bond GMM estimator. The results show that a firm’s past profitability and net asset turnover have significant positive effects on the profitability of logistics firms, demonstrating the dynamic behaviour of logistics firm profitability. The findings indicate that the logistics market is dynamic and that industry specifics have a significant impact on profitability. Despite the increasing importance of logistics firms in national economies, research on logistics is rarely conducted from the perspective of logistics firm profitability. This study examines the determinants of logistics firm profitability and incorporates industry specifics into the analysis, which are important but often neglected in research of this type. The added value of this study also lies in the application of a dynamic model to examine the dynamic nature of firm profitability, which is rare but highly relevant.]]></description>
      <pubDate>Wed, 23 Sep 2026 15:14:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701332</guid>
    </item>
    <item>
      <title>Beggar or enrich-thy-neighbor? Impact of platform cross-border acquisition</title>
      <link>https://trid.trb.org/View/2742980</link>
      <description><![CDATA[E-commerce platforms have increasingly pursued cross-border acquisitions in recent years, targeting either foreign online platforms or foreign brick-and-mortar retailers. Motivated by this practice, this paper investigates how the choice of acquisition target reshapes global supply chain dynamics. We develop a game-theoretic model that captures the data-driven network effect associated with acquiring foreign platforms and the in-store service investment and resulting showrooming effect from acquiring foreign retailers. Several findings emerge. First, both acquisition strategies are double-edged swords for the upstream manufacturer. Acquiring a foreign retailer raises the manufacturer’s profit but heightens its exposure to tariff increases, whereas acquiring a foreign platform may reduce its profit but mitigates the adverse effects of tariff increases. Second, the two strategies generate contrasting channel spillovers. Acquiring a foreign platform constitutes a “beggar-thy-neighbor” strategy that benefits acquisition-related channels at the expense of non-acquired channels, whereas acquiring a foreign retailer may serve as an “enrich-thy-neighbor” strategy. Third, provided that the acquisition price is appropriate, either strategy can improve social welfare in both the domestic and foreign countries. Finally, although a stronger showrooming effect may seem to favor the foreign platform, it does not necessarily do so. These findings offer managers a framework for evaluating cross-border acquisition targets and provide policymakers with a welfare-based lens for assessing and regulating such acquisitions.]]></description>
      <pubDate>Tue, 01 Sep 2026 14:02:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742980</guid>
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    <item>
      <title>Optimization of Cross-Administrative Waterborne Tourism Transportation Network and Profit Allocation under an Alliance Framework</title>
      <link>https://trid.trb.org/View/2704153</link>
      <description><![CDATA[Water area resources typically span multiple administrative regions. To avoid administrative barrier hampering economies of scale in water tourism transportation and offer better tourism transportation services, a business model for operating the resources of water tourism and water transportation in entire water area based on alliances is proposed. According to waterside accessibility of tourism resources, a cross-administrative water transportation network is established, and a bi-level model is built to determine the optimal ship ticket price and passenger flows on shipping routes with objective to maximize alliance’s profit. Based on resource endowments of each region and its shipping companies, a ship assignment model for tourism shipping routes is developed to determine routes’ capacities and the capacities being placed by each member. By inverse optimization, a revenue distribution model considering tourism resources is established to find a suitable resource compensation price to ensure Pareto equilibrium, so as to stabilize the alliance. The results of the case study show that the revenue of tourism shipping companies under the alliance increases by 26.88% compared with that of independent operation, and the mode share of waterway transportation of scenic tourism increases to 87.3%.]]></description>
      <pubDate>Mon, 03 Aug 2026 09:10:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2704153</guid>
    </item>
    <item>
      <title>Competition and Anomalies Redux: Evidence from U.S. Auto Dealers</title>
      <link>https://trid.trb.org/View/2728012</link>
      <description><![CDATA[We examine a choice between bonus contracts offered to dealers of a U.S. auto manufacturer. In our data, dealers select the non-profit-maximizing option in 20 percent of observations, costing the mistaken dealers $18,453 per year on average. We examine how the propensity to make this mistake varies with competition, identified both cross-sectionally and within dealers over time. Both analyses show that greater competition substantially lowers the rate of mistakes. However, even in the most competitive markets, consequential mistakes persist. Our results suggest that competition disciplines mainly through within-dealer changes in behavior rather than entry and exit.]]></description>
      <pubDate>Thu, 23 Jul 2026 16:13:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2728012</guid>
    </item>
    <item>
      <title>Day-to-day dynamics in two-sided ridesourcing markets</title>
      <link>https://trid.trb.org/View/2643218</link>
      <description><![CDATA[To understand why ridesourcing markets may be prone to evolve towards potentially socially undesirable equilibrium states, we conceptualize the network effects present in ridesourcing provision. In addition, we propose an agent-based model that allows simulating the effect of market conditions and platform strategies on system performance, accounting for such network effects. This day-to-day model captures sequential decentralized processes characterizing both sides of the two-sided ridesourcing market, i.e. information diffusion, platform registration, platform participation, and learning based on experience. We apply the model on a case representing Amsterdam, the Netherlands. Our simulation results suggest that a profit-maximizing ridesourcing platform may trade-off market transaction volume for higher earnings on successful transactions, a strategy that is harmful to the interests of travellers and drivers, and possibly of (very) limited benefit to the platform. Moreover, we find that ridesourcing operations may be viable even when potential supply and demand in an area are limited.]]></description>
      <pubDate>Wed, 25 Mar 2026 15:50:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643218</guid>
    </item>
    <item>
      <title>Vertical and horizontal fairness concerns in the ride-hailing platform with solo and carpool ride services</title>
      <link>https://trid.trb.org/View/2594370</link>
      <description><![CDATA[With the rapid growth of ride-hailing platforms, drivers have raised concerns about the platform’s commission rate and their compensation not aligning with their service efforts. In this paper, we investigate the impact of drivers’ fairness concerns on operational decisions within ride-hailing services. Specifically, we focus on two types of fairness issues: vertical fairness, which concerns the profit gap between the driver and the platform, and horizontal fairness, which concerns the profit disparity between the solo ride driver and the carpool ride driver. To examine the impact of fairness concerns, we analyze four scenarios: (1) when neither fairness concern is considered (NN), (2) when only the vertical fairness concern is considered (NV), (3) when only the horizontal fairness concern is considered (HN), and (4) when both fairness concerns are considered (HV). Each of these scenarios is modeled as a Stackelberg game, where we examine the interactions between the platform and drivers under different fairness conditions. Our analysis reveals that Vertical fairness effect, arising from the vertical fairness concern, reduces the ride-hailing platform’s profit. In contrast, Horizontal fairness effect, stemming from the horizontal fairness concern, increases the platform’s profit. Additionally, we find that the vertical fairness effect is greater than the horizontal fairness effect when the solo ride service price is sufficiently low, the customer’s inconvenience cost for taking a carpool service is low, or the commission rate between the platform and drivers is high enough. Based on these insights, we provide managerial implications for ride-hailing platform operators on how to optimize platform operations when drivers’ fairness concerns are taken into account.]]></description>
      <pubDate>Wed, 11 Mar 2026 14:44:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2594370</guid>
    </item>
    <item>
      <title>Operational modes and market structures selection in the on-demand ride-hailing platform considering matching-induced utility uncertainty</title>
      <link>https://trid.trb.org/View/2659487</link>
      <description><![CDATA[In on-demand ride-hailing platforms, participants face matching-induced utility uncertainty, a distinct phenomenon where participants cannot predict whether they will be successfully matched with counterparts. This uncertainty creates gaps between participants’ expected and realized utility, thus significantly influencing how platforms should optimize their pricing strategies to shape participants’ choices and market outcomes. To address this challenge, this paper constructs a theoretical framework of an on-demand platform ecosystem consisting of a ride-hailing platform (RP) and its upstream contract manufacturer (CM). We investigate how both parties strategically make pricing decisions to influence market structure formation and determine the optimal operational mode selection between business-to-customer (B2C) and peer-to-peer (P2P). Our comprehensive analysis reveals several key insights: 1) Regarding market structure formation, high service investment consistently leads to balanced structures across various commission rates in both operational modes. However, as service investment declines, the two modes diverge significantly: P2P mode invariably tends towards buyer markets regardless of commission rates, while B2C mode results in buyer markets only when commission rates exceed certain thresholds 2) When the platform supply chain achieves market balance, the CM exhibits a quality-profit inflection phenomenon, benefiting from increased service investment only when it surpasses a critical threshold. Below this threshold, profits paradoxically decrease as service investment improves due to intensified pricing competition at lower quality levels. 3) The RP selects the P2P mode exclusively when both service investment and commission rates are simultaneously high, otherwise strategically shifting to the B2C mode to access multiple revenue streams and reduce dependence on commission income alone. 4) The analysis extends to incorporate participant risk preferences and endogenous service investment decisions, which not only validates the core findings but also reveals how behavioral factors and strategic quality investments interact to shape market structures.]]></description>
      <pubDate>Fri, 27 Feb 2026 17:10:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659487</guid>
    </item>
    <item>
      <title>Algorithmic pricing in supply chains: implications for product quality, pricing, and profits</title>
      <link>https://trid.trb.org/View/2652535</link>
      <description><![CDATA[The rapid adoption of algorithmic pricing by retailers, enabled by big data analytics, is reshaping decisions in supply chains and affecting consumer surplus. We develop a game-theoretic model to examine how a retailer’s operation under an algorithmic-pricing regime, compared with a uniform-pricing regime, influences the manufacturer’s product quality and wholesale pricing decisions, as well as profits and consumer surplus. We uncover three key findings. First, algorithmic pricing affects product quality through two opposing effects: the demand segmentation effect, which encourages quality improvement by better matching products to heterogeneous consumers, and the profit compression effect, which discourages quality investment when the consumer distribution is highly skewed. Second, algorithmic pricing generates asymmetric profit impacts for supply chain members. While the retailer benefits more directly from pricing precision, both firms can benefit, particularly under a balanced mix of consumer types, through increased market coverage and reduced channel conflict. Third, when algorithmic reliability is high and consumer heterogeneity is moderate, algorithmic pricing can improve consumer surplus by aligning prices with willingness-to-pay and incentivizing higher quality. As reliability improves and the consumer distribution becomes more balanced, the system can achieve a tripartite win–win that benefits the manufacturer, the retailer, and consumers. These findings highlight the dual, condition-dependent role of algorithmic pricing as both a coordination tool and a quality-enhancement mechanism in supply chains. They also offer managerial implications for the strategic deployment of algorithmic pricing tools and inform policy debates on regulating algorithm-driven markets.]]></description>
      <pubDate>Thu, 29 Jan 2026 17:01:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652535</guid>
    </item>
    <item>
      <title>Offline operations strategies of bike-sharing platforms: pure profit or beyond profit?</title>
      <link>https://trid.trb.org/View/2647539</link>
      <description><![CDATA[Bike-sharing platforms can adopt two different offline operations strategies, i.e., independent operations (Strategy I), where each platform independently manages its offline operations, and outsourcing (Strategy O), where one platform outsources its offline operations to another competing platform. With the rise of the “beyond profit” management doctrine, many bike-sharing platforms have begun to pursue dual purposes, i.e., both profits and consumer surpluses, instead of the single purpose, i.e., “pure profit”. Given these facts, this work examines the equilibrium offline operations strategies of two bike-sharing platforms in a duopoly market based on the Hotelling framework and analyzes the platform profits and consumer surplus when the platforms pursue a single purpose or dual purposes. Several important results are obtained. When the platforms engage in intensive competition, the equilibrium operations strategy of the two platforms is Strategy O, and pursuing dual purposes can harm their respective profits. Under weak platform competition, both the investment synergy effect and the investment efficiency of offline operations can significantly affect the platform equilibrium offline operations strategies, and the platforms can obtain higher profits when pursuing dual purposes than pursuing a single purpose if they give low attention weightings to consumer surplus. Additionally, consumer surplus can always be higher when the platforms pursue dual purposes than when pursuing a single purpose, but Pareto improvement may be achieved by the platforms and consumers regardless of the platform competition intensity and the adoption of Strategy I or O.]]></description>
      <pubDate>Thu, 29 Jan 2026 17:01:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647539</guid>
    </item>
    <item>
      <title>A mathematical model to maximize the grain transport planning profit</title>
      <link>https://trid.trb.org/View/2641115</link>
      <description><![CDATA[The authors developed a mathematical model to maximize grain transport planning profit by allowing an intermodal network structure based on Static Network Design (SND). A graph G (V,A) was structured with producers, ports, warehouses, and transshipment terminals represented by nodes (V) and connections defined by edges (A). Subsequently, a linear programming model spanning multiple periods was formulated to maximize the G (V,A) profit. The authors extend the transport planning approach considering SND-based network structure technical factors such as grain loss during transportation, static warehouses, transshipment terminals capacities, and selling prices. From four instances (AT, A, T, and R) generated to emulate practical soybean transport planning in Brazil, the highest profit was obtained in an instance where different modals and selling prices during the off-season can be selected, the warehouses and transshipment terminals reached the maximum static storage capacity, leading to an increased offer of grains during harvest periods, with reduced selling price, impacting the transport planning profit. In general, this research contributes to developing economic policies for the agricultural production chain in Brazil, where agricultural production represents 20% of the gross domestic product.]]></description>
      <pubDate>Thu, 15 Jan 2026 14:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2641115</guid>
    </item>
    <item>
      <title>How Ancillary Fees Drive Revenue Surplus of U.S. Airlines</title>
      <link>https://trid.trb.org/View/2619208</link>
      <description><![CDATA[After decades of deregulation, the U.S. Department of Transportation (DOT) has begun re-regulating the airline industry through new rules on family seating, refund requirements, and ancillary fee transparency. While economists often caution against market intervention, the rapid expansion of ancillary fees raises questions about whether such oversight is warranted. In this study, revenue surplus is defined as the markup of price over marginal cost, capturing the degree to which airlines generate revenue beyond the level justified by cost efficiency.This paper examines how ancillary revenues affect airlines’ revenue surplus and reshape competitive dynamics across business models. Using panel data on U.S. airlines from 2000 to 2019, we find that ancillary revenues significantly enhance overall revenue surplus, with ultra–low-cost carriers (ULCCs) outperforming both low-cost (LCCs) and full-service airlines (FSAs) despite offering lower base fares. These results indicate that ancillary fees are not simply cost-recovery mechanisms but serve as a strategic profit lever—one that alters pricing structures and market competition in the post-deregulation era.]]></description>
      <pubDate>Mon, 29 Dec 2025 09:34:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2619208</guid>
    </item>
    <item>
      <title>The impact of sustainable aviation fuel quota mandates on the optimal on-airport fuel facility ownership</title>
      <link>https://trid.trb.org/View/2601322</link>
      <description><![CDATA[Sustainable Aviation Fuel (SAF) is a cornerstone of aviation decarbonization in the short-to-medium term, prompting governments to adopt policies like SAF quota mandates. However, the aviation fuel supply chain—particularly the role of fuel suppliers and the ownership of on-airport fuel facilities—remains understudied. This paper develops a theoretical model to analyze how SAF quota mandates influence the optimal ownership structure of on-airport fuel facilities, comparing three observed arrangements: third-party, airport-owned, and airline-owned. Our findings reveal that airport or airline ownership increases traffic volumes and profits for off-airport suppliers, airports, and airlines compared to third-party ownership. Notably, while third-party ownership maximizes social welfare under low SAF quotas and small market sizes, higher quotas favor airport or airline ownership, suggesting a potential need for ownership transitions as SAF mandates escalate. Furthermore, with intensified airline competition, the choice between airport and airline ownership hinges on market size and the SAF quota level. Extending the analysis to test several real-world constraints reveals crucial sensitivities. For instance, finite SAF production capacity imposes a fundamental trade-off, rendering ambitious mandates incompatible with large-scale aviation activity. Furthermore, a more competitive upstream fuel market raises the market-size threshold at which integration becomes socially optimal. Finally, alternative stakeholder objectives can introduce significant market instability; a welfare-maximizing airport, for example, can create an equilibrium that is vulnerable to exploitation by a profit-maximizing supplier.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2601322</guid>
    </item>
    <item>
      <title>Toward mobility incentive: Integrating green service and carbon inclusion scheme into the ride-hailing market</title>
      <link>https://trid.trb.org/View/2604747</link>
      <description><![CDATA[Increasing individual responsibility for reducing emissions is a potentially effective way to address mobility sustainability issues. In recent years, the carbon inclusion scheme has been widely implemented to incentivize individual low-carbon travel behaviors. Motivated by the practice, this paper examines the ride-hailing market that integrates the green service with the carbon inclusion scheme to comprehend how the government-led carbon inclusion scheme affects the operation of the ride-hailing market and the prospects of reducing carbon emissions and promoting electrification. We propose two product strategies for the ride-hailing platform: (a) One-product strategy with mixed service provided by electric vehicles (EVs) and fuel vehicles (FVs); and (b) Differentiated-product strategy with green service provided by EVs and basic service provided by FVs. We also consider the significant differences in adopting electric buses in different countries/regions when discussing the impact of carbon inclusion on the ride-hailing market. Our findings indicate that without government-led carbon inclusion, it is more appropriate for the ride-hailing platform to adopt the one-product strategy. With government-led carbon inclusion, when the electrification rate of external public transportation is not very high, and the carbon incentive is high enough, the platform can improve its profit by adopting the differentiated-product strategy. Considering the platform's profit maximization decisions, our analysis also highlights that when the electrification rate of the external option is low and the carbon incentive is high, the impact of the carbon inclusion scheme on the ride-hailing market is better in all aspects, which is a win-win outcome that the ride-hailing platform, drivers, and the government would all like (if the government wants to see better driver welfare, electrification and carbon reduction in the ride-hailing market). Additionally, increasing the potential number of EVs in the ride-hailing market and the total number of drivers makes sense both for the platform (to gain higher profits) and government (which may be concerned about increasing driver welfare, the electrification rate and total carbon reduction of the ride-hailing market). The gained managerial insights provide decision support for the platform operating differentiated services and the government implementing carbon inclusion schemes.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604747</guid>
    </item>
    <item>
      <title>The multi-commodity flow problem with outsourcing decisions</title>
      <link>https://trid.trb.org/View/2604746</link>
      <description><![CDATA[We introduce a new prize-collecting problem involving the routing of commodities in a network composed of predefined hub and non-hub nodes. In this setting, the service of non-hub nodes is outsourced to third-party carriers. This study is motivated by the growing prevalence of outsourcing practices in real-world transportation systems, where new entrants or local suppliers increasingly take over parts of the transportation chain – enabling higher volumes and broader network coverage. The problem is modeled as a Stackelberg game: a major firm (the leader) chooses a subset of commodities to serve. The leader aims to outsource the first and last legs of the transportation services to smaller carriers (the followers), assigning at most one carrier to each non-hub node. Each carrier seeks to maximize its own profit, which depends on the offers made by the leader. The goal of the leader is to determine the optimal outsourcing fees, along with the allocation of carriers to the non-hub nodes, so that the profit from the routed commodities is maximized. The optimal response of the followers must be taken into account, as the followers may reject assignments that do not align with their profit-maximizing goals. We also consider two alternative settings: one in which outsourcing fees are fixed, and another where carriers accept any offer yielding non-negative profit. We demonstrate that the set of feasible outsourcing fees can be discretized and formulate the problem as single-level mixed-integer (non)linear program. For all problem variants, we prove NP-hardness and conduct a computational study of various single-level MIP reformulations. Our benchmark instances cover various applications in transportation, such as air transportation, postal delivery and freight transportation. We assess the scalability of proposed formulations and analyze the impact of different carrier reservation prices on solution quality. Finally, by comparing the alternative problem settings, we extract valuable managerial insights.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604746</guid>
    </item>
    <item>
      <title>Deep-tier financing under Web3.0: Visibility enhancement in de-core supply chain finance</title>
      <link>https://trid.trb.org/View/2584393</link>
      <description><![CDATA[Web 3.0 technology drives the transformation of supply chain finance (SCF), alleviating the financing challenges faced by small and medium-sized enterprises (SMEs). This paper constructs a three-tier, four-participant SCF model and employs a game-theoretic approach to explore the impact of the de-core trend and visibility enhancement in SCF on supply chain efficiency, disruption risk, and profit. The transition from the traditional model (Model T), the digital model (Model D), to the advanced digital model (Model AD) represents a reduction in system complexity and an improvement in efficiency, reflecting the progressive deepening of supply chain visibility and the de-core trend. Specifically, Model T relies on the credit guarantee of the manufacturer (core enterprise), which causes high financing costs and inefficiency. Although Model D reduces the dependence on the manufacturer, the financing process still has to go through the 1st tier supplier (supplier in the adjacent-tier of the core enterprise), incurring higher risks. Model AD achieves complete information transparency through the digital SCF platform, enabling the 2nd tier supplier (deep-tier supplier far from the core enterprise) to directly obtain loans from the financial institution. This direct lending mechanism simplifies the process, mitigates risks, and increases efficiency and profits. This research underscores the necessity of reducing dependence on core enterprises and proposes a pathway for optimizing SCF, offering a fresh perspective on risk management for both financial institutions and supply chain participants.]]></description>
      <pubDate>Fri, 21 Nov 2025 08:46:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2584393</guid>
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