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Dear reader,
Rail transport is a central component of the transition to sustainable mobility – ecologically, socially, and increasingly economically. In addition to technological innovations and operational optimisations, economic questions are therefore gaining prominence in research. The aim is to strengthen the efficiency, competitiveness, and economic viability of the rail system within the context of climate protection, resource efficiency, and societal value creation.
A key area of research is the cost structure of infrastructure, rolling stock, and operations. Projects such as the DZSF initiative on the macroeconomic significance of rail investments and the Fraunhofer study on rail transport research strategy examine how life-cycle costs, maintenance strategies, and investment models influence long-term economic performance. This also involves integrating sustainability indicators to systematically link economic and environmental objectives.
The question of how competition and regulation can be designed efficiently is at the centre of numerous analyses. The European Commission’s EU Railway Market Monitoring Report 2024 investigated the effects of market liberalisation, infrastructure access, and pricing at the European level. Complementing this, the study The Economic Footprint of Railway Transport by the Community of European Railway and Infrastructure Companies and Oxford Economics examines how the rail sector acts as a macroeconomic driver – in particular regarding employment, value creation, and investment.
Rail infrastructure is capital-intensive and long-term. Research projects such as the Trenolab project commissioned by DZSF (2024) analyse the efficiency and macroeconomic impacts of public funding in the railway sector. Various financing approaches are considered, including public–private partnerships, user-based models, and government subsidy schemes. The focus is on how investments in rail projects can be strategically prioritised and economically evaluated.
Macroeconomic effects are increasingly coming into focus: analyses in the DZSF project on the macroeconomic significance of rail investments demonstrate that investments in the rail network generate significant multiplier effects – both in employment and in downstream sectors. In parallel, the Fraunhofer study on rail research strategy explores how innovation and research can secure the long-term competitiveness of the European rail sector. The macroeconomic benefits thus arise not only from operational efficiency but also from societal effects such as reduced emissions, increased location attractiveness, and land-use relief.
Digital methods and data-driven models are also becoming increasingly important in economic railway research. Recent scientific work – for example, the study published on arXiv (2025) on AI-supported demand and cost forecasting – demonstrates how simulations and machine-learning models contribute to strategic planning. By combining operational, market, and financial data, future developments in the rail sector can be better quantified, and scenarios for efficiency improvements and investment prioritisation can be realistically modelled.
Economic research in the rail sector is developing into an integral component of strategic decision-making. It provides transparency regarding costs, benefits, and effects, and forms the basis for evidence-based transport and investment policy. The mentioned projects and new data-driven modelling approaches play a key role in ensuring that the economic performance of rail is measurable, comparable, and politically manageable. In doing so, research makes a central contribution to the long-term ecological and economic stability of the rail transport system.
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Your RMR-Team |
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| | Project objectives
The project investigates methods for determining railway line capacity and focuses on ensuring the quality and reliability of capacity analyses. The aim is to develop criteria for evaluating capacity assessments in order to make operational and infrastructure planning more robust. Approach
Various operational research methods are examined to assess the performance and capacity behaviour of railway systems. The methods are compared, and quality criteria are derived to guide reliable capacity analyses. Duration
Not explicitly specified in the source. Use of results
The findings will contribute to methodically improving capacity analyses in the railway network and infrastructure sector and thus support better planning of operations and network expansion. | | |
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Project objectives
The project examines the magnitude of investments in the railway sector in Germany (in infrastructure and rolling stock) and analyses their direct and indirect economic effects — including effects on value creation and employment. Approach
The study uses data‑based methods from input‑output analysis: investment volumes for 2021 in infrastructure and rolling stock form the basis. The analysis estimates direct value added and employment effects of those investments, as well as indirect effects through supplier chains and production of associated goods.
Duration
Project period: 2023‑2024. Use of results
The results are used as decision‑support for policy and infrastructure planning in the railway sector: to evaluate the economic relevance of railway investments, to understand their effect on jobs and value creation, and to support prioritisation of investment measures.
Key findings In 2021, approximately €10.9 billion were invested in rail infrastructure and €2.643 billion in rolling stock in Germany. These investments resulted in value‑added of about €8.1 billion for infrastructure and €0.8 billion for rolling stock. The employment effects were significant: approximately 119,000 full‑time equivalent jobs secured, with ~107,000 in direct infrastructure‑related industries and ~54,000 additional jobs due to increased demand for input goods (indirect effects). Per euro invested, infrastructure investments generated roughly €0.74 of value added; rolling stock investments generated less than half that amount. | |
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Project objectives
This study by CER and Oxford Economics examines the economic value-added and employment contribution of the rail sector in Europe.
Approach
A quantitative survey at the European level captures value creation, employment, investment, and cross-sector effects of the rail sector. Use of results
The findings serve as an evidence base for transport policy, infrastructure investment, and promoting rail as an economic factor. |
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Project objectives
The study develops a model for pricing network access fees in freight rail, focusing on deregulation, capacity utilisation, and external environmental costs. Approach
A logit-based model is used to analyse modal split between road and rail, coupled with simulations to determine access charges under capacity and demand dynamics, applied to Mediterranean freight corridors. Use of results
The model provides decision-making support for infrastructure managers and policymakers, showing how access charges can be structured to achieve both economic and environmental objectives. |
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Research Results Published |
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The FP6-Future project focuses on the long-term viability of regional railways by reducing the total cost of ownership while ensuring high service quality and operational reliability. The report specifies requirements for three key wayside assets – level crossings, switches, and obstacle detection systems – and includes related analyses and development measures. The concept developed is tailored to regional railways but transferable across Europe, integrating digitalisation, automation, and new technologies for signalling and control, wayside components, rolling stock, and passenger information. Its aim is to improve the efficiency, safety, and modernisation of regional railways across Europe. |
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| Planned Research Projects |
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Project objectives
The project aims to analyse employment in the German rail sector in greater detail, focusing on rail-specific labour market data and strategies to attract qualified personnel. Approach
A multi-method approach is used, combining quantitative and qualitative surveys of labour market and employer data to gain a data-driven understanding of factors influencing employer attractiveness in the railway sector. Duration
Planned project start: 1st quarter of 2026
Project duration: 12 months
Use of results
The results will help rail operators, planners, and educational institutions better address workforce and skills requirements and enhance the attractiveness of the rail sector as an employer. | |
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