Although there is ample empirical evidence that congestion charges can effectively reduce traffic congestion and its detrimental effects, this instrument has only been implemented in a handful European cities. On the basis of a randomized information experiment that was embedded in a survey...

Predicting freeway traffic states is, so far, based on predicting speeds or traffic volumes with various methodological approaches ranging from statistical modeling to deep learning. Traffic on freeways, however, follows specific patterns in space-time, such as stop-and-go waves or mega jams....

This study studies nudging information as a strategy that can complement or substitute externality pricing, by influencing commuter behavior through awareness of the health and environmental impacts of their choices. We develop a bi-modal model with road and metro commuters, with bottleneck...

Background: This paper introduces an enhanced multi-period p-mobile hub location model that accounts for critical factors such as service time, flow processing delays, and congestion impacts at capacity-constrained hubs. As (urban) transportation networks evolve, mobile hubs play an increasingly...

The power exchange and the real-time markets used by the system operator differ in how system constraints are managed. This can result in regulatory arbitrage, which can increase consumer costs, increase the risk of power outages and distort investment incentives. This paper uses a...

This paper uses principal component analysis (PCA) to identify bottlenecks to effective public investment management in LIDCs. The paper describes the current state of affairs regarding public investment and public investment management in LIDCs, drawing on the results of IMF Public Investment...

In early 2024, the European Commission proposed a 90% emissions reduction target for the year 2040 in reference to the year 1990. Achieving this target largely relies on the deployment of distributed renewable generation. Currently the deployment of renewable capacity is mostly focusing on...

In early 2024, the European Commission has proposed a climate target of 90% emissions reduction by 2040. The associated scenarios are relying heavily on the deployment of variable renewables, such as wind and solar PV. Deployment that focuses on resource-rich areas - where wind and solar...

Purpose This paper seeks to evaluate the factors that contribute to congestion at port entrances, propose a comprehensive approach to managing port gates that addresses the factors causing traffic jams and assess the outcomes of resolving the issue through an optimal model for incoming container...

We analyse time-varying tolling in the stochastic bottleneck model with price-sensitive demand and uncertain capacity. We find that price sensitivity and its interplay with uncertainty have important implications for the effects of tolling on travel costs, welfare and consumers. We evaluate...

We construct the first measure of collateral re-use at the bank and bond level for the European repo market using a regulatory transaction dataset. We show that banks materially increase the rate of re-use in response to tightened asset scarcity induced by the Eurosystem's asset purchase...

This paper discusses a capacity-based redispatch mechanism in which awarded market participants are compensated for their availability for redispatch, rather than activation. The rationale is to develop a market design that prevents so-called “inc-dec gaming” when including flexible...

We implement Pigovian transport pricing in a field experiment in urban agglomerations of Switzerland over the course of 8 weeks. The pricing considers external costs from climate damages, health outcomes and congestion and varies across time, space and mode of transport. The treatment reduces...

This paper explores how the interaction between human-driven vehicles (HVs) cruising for parking and autonomous vehicles (AVs) traveling back and forth affects travel behavior and congestion. To capture the spatial distribution of parking, we develop a continuous spatial optimization model, with...

We study how preference heterogeneity affects travel behavior and congestion pricing in a dynamic flow congestion model. We formulate and solve a multi-point optimal control problem using a Hamiltonian-based method to derive the social optimum. The properties of the travel equilibrium are...

Highly volatile, uncertain, complex and ambiguous environments (VUCA) complicate and condition project management. With the emergence of agile project management, it is proposed to co-construct it with the client's active participation. Two used agile methodologies are Scrum and Kanban. Scrum is...

Analyzing the flow of vehicles within a metropolitan area is essential to understand traffic congestion better and evaluate urban mobility for more environmentally and sustainable targets. This study uses real-time big data to conduct a spatiotemporal analysis of traffic congestion patterns in...

Background: Container terminals (CTs) have constantly administered truck appointment systems (TASs) to effectively accomplish the planning and scheduling of drayage operations. However, since the operations in the gate and yard area of a CT are stochastic, there is a need to incorporate...

In this paper, we examine the class of congestion games with player-specific payoff functions introduced by Milchtaich, I. (1996). Focusing on the special case of two resources, we give a short and simple method for identifying all Nash equilibria in pure strategies. We also provide a...

We examine the economic and environmental impacts of improvements and disruptions in multimodal transport networks. Our quantitative spatial equilibrium model incorporates routing over multiple modes and congestion at intermodal terminals. We estimate a modal substitution elasticity with highway...

Empirical evidence on the potential impacts of generative artificial intelligence (GenAI) is mostly focused on high-income countries. In contrast, little is known about the role of this technology on the future economic pathways of developing economies. This paper contributes to fill this gap by...

The suitability of agents for tasks and ranked preference of tasks for agents play a significant role in problems where several agents are available to perform various tasks. The agents should be allocated to various tasks so that the corresponding assignment schedules must provide solution...