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on Transport Economics |
| By: | Lange, Jan-Hendrik; Speth, Daniel; Plötz, Patrick |
| Abstract: | Battery electric trucks (BETs) are the most promising option for fast and large-scale CO2 emission reduction in road freight transport. Yet, the limited range and longer charging times compared to diesel trucks make long-haul BET applications challenging, so a comprehensive fast charging network for BETs is required. However, little is known about optimal truck charging locations for longhaul trucking in Europe. Here we derive optimized truck charging networks consisting of publicly accessible locations across the continent. Based on European truck traffic flow estimates for 2030 and actual truck stop locations we construct a long-term minimum charging network that covers the expected charging demand. Our approach introduces an origin-destination pair sampling method and includes local capacity constraints to compute an optimized stepwise network expansion along the highest demand routes in Europe. For an electrification target of 15% BET share in long-haul and without depot charging, our results suggest that about 91% of electric long-haul truck traffic across Europe can be enabled already with a network of 1, 000 locations, while 500 locations would suffice for about 50%. We furthermore show how the coverage of origin-destination flows scales with the number of locations and the size of the stations. Ideal locations to cover many truck trips are at highway intersections and along major European road freight corridors (TEN-T core network). |
| Keywords: | charging infrastructure, battery trucks, megawatt charging |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:fisisi:300275&r= |
| By: | Dugoua, Eugenie; Dumas, Marion |
| Abstract: | Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry’s transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry’s markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms. |
| Keywords: | energy innovation; electric cars; fuel cells; coordination; low-carbon transitions |
| JEL: | J1 |
| Date: | 2024–06–24 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:124029&r= |
| By: | Thierry Mayer; Vincent Vicard; Pauline Wibaux |
| Abstract: | The automotive industry faces two disruptions: China’s emergence as a leading global auto exporter, and the transition from internal combustion engine (ICE) to electric vehicles (EVs). Detailed data on sales by origin/destination/model show that the automotive market is primarily local or continental, with limited sales originating from distant countries for both ICE and EV. Accordingly, foreign direct investment (FDI) is an important mode of supply for foreign markets. Insights from Japanese and Korean brands’ market penetration in the 2000s and 2010s suggest that successful models are primarily sold through local assembly; the most successful Chinese EV models in Europe are close or above the investment threshold. Examination of potential differences between EV and ICE indicates evolving comparative advantages: while EVs are not inherently more traded compared to other vehicles, China currently leads in cells and modules, but not yet in assembly. Down the value chain, the median distance between battery production and assembly is 215 km in 2022, suggesting localized sourcing in EV similar to combustion engines and larger than ICE transmissions. |
| Keywords: | Automotive industry;Electric vehicles;China;Protectionism;Foreign direct investment;Industrial policy |
| JEL: | F10 L62 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:cii:cepipb:2024-45&r= |
| By: | Rainald Borck; Peter Mulder |
| Abstract: | We study the effect of energy and transport policies on pollution in two developing country cities. We use a quantitative equilibrium model with choice of housing, energy use, residential location, transport mode, and energy technology. Pollution comes from commuting and residential energy use. The model parameters are calibrated to replicate key variables for two developing country cities, Maputo, Mozambique, and Yogyakarta, Indonesia. In the counterfactual simulations, we study how various transport and energy policies affect equilibrium pollution. Policies may be induce rebound effects from increasing residential energy use or switching to high emission modes or locations. In general, these rebound effects tend to be largest for subsidies to public transport or modern residential energy technology. |
| Keywords: | pollution, energy policy, discrete choice, developing country cities |
| JEL: | Q53 Q54 R48 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11152&r= |
| By: | Gleser, Michael |
| Abstract: | This dissertation investigates the topic of combined rail-road transport with a focus on Europe. In addition to an introduction to the subject and a description of the research design utilized, it consists of three distinct studies whose results build upon one another. In the first study, a Delphi study combined with a systematic literature review, explicit measures were identified on how combined transport can be strengthened from a practical perspective and which topic areas related research deals with. By synthesizing the results of both methods, a practice-oriented research agenda was created. It is intended to be a document of the current challenges of combined transport and an effective solution to them. The second study deals with port competition through hinterland connectivity, in which combined transport plays a major role. Using the example of the federal state of North Rhine-Westphalia, which is within the geographical scope of ports of the northern range, the influence of the CO2 tax introduced in 2021 is examined. A simulation model is used to investigate the impact of the tax, leading to interesting insights into the potential shift in competitive scope. The third and final study deals with the new possibilities of the China Railway Express, a direct train connection between Europe and China. Since the connection is enjoying increasing popularity, a simulation model, inspired by the second study, was used to examine which areas in China are economically accessible to exporters in Hesse utilizing this train connection. In addition, it was examined how this area would change if a (hypothetical) global carbon tax was introduced. All three studies together provide an overview of the current challenges of combined transport in Europe, its medium-term changes due to political and environmental regulations, and an outlook on the possibilities of intercontinental rail transport. |
| Date: | 2024–07–09 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:146674&r= |
| By: | Kevin Riehl; Anastasios Kouvelas; Michail Makridis |
| Abstract: | City road infrastructure is a public good, and over-consumption by self-interested, rational individuals leads to traffic jams. Congestion pricing is effective in reducing demand to sustainable levels, but also controversial, as it introduces equity issues and systematically discriminates lower-income groups. Karma is a non-monetary, fair, and efficient resource allocation mechanism, that employs an artificial currency different from money, that incentivizes cooperation amongst selfish individuals, and achieves a balance between giving and taking. Where money does not do its job, Karma achieves socially more desirable resource allocations by being aligned with consumers' needs rather than their financial power. This work highlights the value proposition of Karma, gives guidance on important Karma mechanism design elements, and equips the reader with a useful software framework to model Karma economies and predict consumers' behaviour. A case study demonstrates the potential of this feasible alternative to money, without the burden of additional fees. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.05132&r= |
| By: | Carolin Bauerhenne; Jonathan Bard; Rainer Kolisch |
| Abstract: | The global home healthcare market is growing rapidly due to aging populations, advancements in healthcare technology, and patient preference for home-based care. In this paper, we study the multi-day planning problem of simultaneously deciding patient acceptance, assignment, routing, and scheduling under uncertain travel and service times. Our approach ensures cardinality-constrained robustness with respect to timely patient care and the prevention of overtime. We take into account a wide range of criteria including patient time windows, caregiver availability and compatibility, a minimum time interval between two visits of a patient, the total number of required visits, continuity of care, and profit. We use a novel systematic modeling scheme that prioritizes health-related criteria as hard constraints and optimizes cost and preference-related criteria as part of the objective function. We present a mixed-integer linear program formulation, along with a nested branch-and-price technique. Results from a case study in Austin, Texas demonstrate that instances of realistic size can be solved to optimality within reasonable runtimes. The price of robustness primarily results from reduced patient load per caregiver. Interestingly, the criterion of geographical proximity appears to be of secondary priority when selecting new patients and assigning them to caregivers. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.06215&r= |