This study aimed to provide a multiangled comparison of the impact of real and virtual setups on the behaviour and perception of electric scooter (e-scooter) riding to examine the external validity of the virtual environments in the micro-mobility context. For this purpose, a within-subject design experiment was conducted to collect data on the behaviour of e-scooter riders. Furthermore, self-reported

This paper presents an approach to use GPS-based travel behavior surveys to determine who is being served well and who is being served poorly by the transport system. We draw on the extensive literature on travel behavior, which has shown that people’s travel behavior is at least in part shaped by the travel barriers they experience. Starting from this basic insight, we define 17 parameters that may

In this study, the transportation network design problem (NDP) is investigated by integrating geometric and topological indices—continuity, regularity, betweenness centrality, and closeness centrality—alongside the traditional total travel time minimization objective. Each index is individually optimized within a bi-level optimization framework, enabling a comprehensive assessment of its impact on

Out-of-school time (OST) activities are essential for students’ educational achievement and workforce development. However, economically disadvantaged youth have far less OST access compared to their wealthier counterparts. In sprawling, low-density metropolitan areas, a lack of reliable and cost-effective transportation services constitutes a considerable barrier to OST participation for youth from

As a newly emerging mode of shared micro-mobility, the e-bike sharing system (EBSS) is increasingly establishing more stations to meet rising user demand. Due to the vast number of stations and the limited space available on urban streets, the operation of the EBSS largely relies on the platform’s battery swapping. This paper, for the first time, models the EBSS battery swapping problem as a variant

The Russia-Ukraine conflict and international sanctions against Russia have destabilized European segments of Sino-Russian trade corridors, necessitating a shift toward alternative routes. In order to improve the reliability of Sino-Russian trade transportation, a bi-level network optimization model is constructed with considering the geopolitical risks and seasonal Arctic shipping route, where the

Precise and dependable identification of traffic states is crucial for optimizing traffic system, which forms the foundation for mitigating congestion and enhancing the overall efficiency and stability of traffic operations. Existing research has mainly adopted methods such as signal processing methods and traffic fundamental diagrams, but each has its own shortcomings. Therefore, this study introduces

We propose a nonparametric mixed logit model that is estimated using market-level choice share data. The model treats each market as an agent and represents taste heterogeneity through market-specific parameters by solving a multiagent inverse utility maximization problem, addressing the limitations of existing market-level choice models with parametric estimation. A simulation study is conducted to

Mixed transportation of passengers and freights is an effective strategy for reducing environmental pollution and improving the service level of railway systems. This study addresses the problem of robust train composition and carriage arrangement for the mixed transportation of passengers and freights in a high-speed railway (HSR) network. Specifically, a network-based robust optimization (RO) model

Hemodialysis centers use session-based scheduling to provide regular treatments for chronic hemodialysis patients. Optimizing the use of hemodialysis machines is crucial to managing daily patient loads, which requires the timely initiation of parallel sessions. Many centers offer transportation (shuttle) services to ensure punctual patient arrivals. However, post-disaster scenarios pose significant

This paper studies the relative performance of congestion pricing versus tradable permits for a congested bi-modal transport system with traffic externalities, that affect passengers only, and societal externalities that go beyond the passengers. The point in this case is infection risks, as in the pandemic. We study this relative performance for the case where there are uncertainties on both traffic

The COVID-19 pandemic has heightened the need to better understand travellers’ preferences for reduced crowding in public transport. Using panel data from repeated choice experiments with a large sample of Norwegian metro and train users during and after the pandemic, we investigate how the marginal valuation of travel time varies depending on crowding levels and passengers’ positions when sitting

The autonomous truck platoon control using multi-agent reinforcement learning (MARL) presents a few challenges, including social dilemmas, restricted perception information, and rigid formation structures. To overcome these challenges, this study proposes a novel collaborative decision-making approach, termed autonomous truck driving collaborative decision-making (ATDrive), which is based on QMIX,

Berth allocation and scheduling at marine container terminals holds critical significance for optimizing port operations and ensuring efficient maritime logistics, yet it is exceptionally challenging due to its operational complexity and practical constraints. This study presents a mixed-integer linear programming model for the dynamic discrete berth allocation and scheduling problem with the objective

Enhancing transportation network redundancy is an effective approach to proactively improving network resilience and mitigating the consequences of potential disruptions. This research addresses a route diversity redundancy-oriented strategic transportation network planning problem that involves the integration of two typical means: (1) constructing new infrastructure (e.g., road segments and bridges)

Autonomous vehicles (AVs) may exacerbate traffic congestion due to zero-occupant cruise to avoid parking and save parking fees. Congestion pricing strategies are considered as important solutions to reduce traffic congestion. However, there is still insufficient research on the congestion pricing strategy on zero-occupancy AVs, which we refer to as the cruise pricing strategy. Therefore, this paper

Supply chain management (SCM) is progressing towards a more interconnected and digitized future; blockchain stands out as a key enabler for the next supply chain (SC) excellence generation. In recent years, SC industries have gradually transformed towards the next industrial revolution, and new supply chain and logistics (SCL) challenges have emerged. Rapid technological advancements have been helping

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. We analyze the alliance strategies of shipping companies

The rapid rise and wide penetration of environmental, social and governance (ESG) practices have promoted the green transformation of supply chains (SC) and provided opportunities for building sustainable SC. Corporate environmental governance is a vital ESG component that requires leveraging the synergy between enterprises in SC. This study constructs a panel dataset of listed corporates and their

Using electric micromobility vehicles, shared electric micromobility systems provide an environmental mode of short-distance travel within a city. Given the inescapable costs of vehicles and batteries, and the necessity for the system operator to manage the state-of-charge of vehicles through battery swapping to effectively meet uncertain demands, it is pivotal to accurately determine the initial allocation

This paper examines the optimal design of dynamic pricing strategies for a coupled ride-hailing market with the coexistence of ridesharing and non-ridesharing services. Riders may switch between ridesharing and non-ridesharing alternatives to maximize individual utility, which results in demand diversion. Due to the imbalance between demand and supply, riders may become impatient towards long waiting

Investigating and simulating the impact of floods on crowd dynamics at evacuation bottlenecks is essential, given the increment of the intensity of these disasters due to climate change. Previous studies have primarily focused on flood risk assessment for crowd evacuation during flooding. The complex interactions between pedestrians and water flow near evacuation bottlenecks have been rarely investigated

The mass rapid transit (MRT) systems play a pivotal role in urban mobility services but are frequently susceptible to various disruptions. Bus bridging service is a widely-applied substitute transit service in response to MRT disruptions, which requires a significant number of buses to transport stranded MRT passengers. In practical applications, these buses may be dispatched from the nearby bus lines

Under dynamic traffic demand conditions, two issues must be addressed when perimeter control is implemented for congested areas of a road network. The first is to avoid intersection spillback at the boundaries and expansion of the congestion, and the second is to improve the output traffic efficiency of the congested areas to quickly relieve traffic congestion. To address these two issues and solve

The concurrent availability of shared bikes (DBS) and emerging shared e-bikes (EBS) systems offers new opportunities for sustainable urban mobility, particularly in enhancing first/last-mile connectivity with metro systems. However, a significant gap exists in understanding user choice behavior between DBS and EBS for metro connectivity. As shared micromobility options, DBS and EBS exhibit more competitive

Quality in public transport is a widely discussed topic from both the user's and operator's perspective. With respect to the passenger’s standpoint, the aim of this research was to ascertain whether (and in what way) the traveler’s “quality perception” of high-standard stations could be differently affected by his/her individual attitudes/perceptions, such as to influence mobility choices. To this

Knowledge and expertise are critical to the proper functioning of supply chains. However, scholars have only stated the need for knowledge and information sharing and overlooked how it conceptually develops in organizations. This research provides an in-depth look at the source of knowledge through the lens of four decades of Transactive Memory Systems (TMS) research. Through netnographic research

This paper investigates solution methods for train eco-driving problems that include the classic single-train eco-driving problem, the single-train eco-driving problem with intermediate time-window constraints, and the eco-driving problem for a fleet of trains under the green-wave policy. The latter two problems are particularly relevant in modern, busy railway networks. We start from proposing a relaxed

In a macroscopic assignment model, traffic flows are distributed onto the network by means of a network loading model. The network loading propagates flows along links via a link model and through junctions or intersections via a node model. Most of the travel time delays are caused by queues forming at junctions or intersections, especially in urban networks. Therefore, the efficiency and accuracy

We initiate the study of dynamic traffic assignment for electrical vehicles addressing the specific challenges such as range limitations and the possibility of battery recharge at predefined charging locations. As our main result, we establish the existence of energy-feasible dynamic equilibria within networks using the deterministic queuing model of Vickrey for the flow dynamics on edges.

The bottleneck model has dominated the field on dynamic congestion, as it is tractable and has closed-form solutions. But it has rather specific outcomes that do not occur in most other dynamic models or under static congestion. In the bottleneck model, pricing can remove all travel delays while keeping the generalized price unchanged, making pricing much more beneficial than in other models. Thus

Hospitals are now the fifth-largest source of global greenhouse gas (GHG) emissions. Despite this significant impact, the critical goal of achieving carbon neutrality is often overlooked in optimization studies on healthcare operations management. To address this gap, this paper proposes a novel multi-objective decision-making framework for private hospitals that balances patient health, environmental