Employment
As part of the CCAM-ERAS project, Cambridge Econometrics’ role focuses on understanding how Connected, Cooperative and Automated Mobility (CCAM) technologies will reshape Europe’s employment landscape. These technologies are changing how goods and people move, and they’re going to change the labour market too.
In this WP, we build a modelling framework based on Cambridge Econometrics’ E3ME model to assess how CCAM will affect jobs across sectors and occupations, helping policymakers and educators plan for a fair, future-ready transition.
At the bottom of this page, the Power BI tool showcases the outcomes on employment by Member States, sector and occupation of the scenario analyses of the different CCAM deployment use cases. The Power BI illustrates three deployment scenarios (warehousing, passenger, and freight), each analysed under different adoption pathways to reflect differing CCAM uptake dynamics. It provides an overview of prospective CCAM deployment trajectories and their implications for the EU labour market, including anticipated shifts in skills requirements and employment structures.
The Power BI tool is composed of five sheets: one overview sheet, three scenario specific sheets (warehousing, freight, passenger) and one information sheet. Please read the information sheet for more details about the scenarios.
For a detailed description of results, please read “D4.4 Analytical report on employment effects”, D4.4-CCAM_ERAS_Deliverable_D4.4_v06
For more information about the E3ME model, please visit https://www.camecon.com/e3me .
Background analysis and context
This economic tool was informed by two items of analysis and research of:
Supply Chain Mapping Report
This report establishes the structural backbone of the CCAM-ERAS analysis by mapping how Connected, Cooperative and Automated Mobility (CCAM) reshapes the traditional transport supply chain. Using input-output tables and sectoral classifications, it identifies how value creation shifts across industries—highlighting, for example, the growing importance of ICT, sensing technologies, and advanced infrastructure relative to conventional transport systems.
By translating emerging CCAM activities into measurable economic sectors, the report provides a critical bridge between technological change and economic modelling. It reveals where disruptions, investments, and new interdependencies are likely to occur—laying the groundwork for quantifying downstream impacts on production, value chains, and ultimately employment within the model.
Read the full report here D4.1 Supply chain mapping report
Scenario Assumptions and Economic Background Report
This report defines the analytical lens through which CCAM deployment is explored, building a coherent set of scenarios grounded in economic evidence, technology readiness, and real-world use cases. It outlines key assumptions—such as adoption speed, regulatory constraints, and varying uptake across freight and passenger transport contexts—that shape how CCAM may unfold across Europe.
Crucially, the report transforms uncertainty into structured, model-ready pathways. By linking deployment dynamics (e.g. faster adoption in controlled environments versus slower uptake in public transport) to economic drivers, it ensures that the subsequent modelling reflects realistic transition patterns. This scenario framework underpins the economic model, enabling robust comparison of alternative futures and their implications for jobs, sectors, and skills.
Read the full report here D4.2 Report on scenario assumptions and their economic background
