This study aims to systematically investigate and structure future technological developments within automation, electrification, and digitalization (AED) in the transportation sector. To address the significant complexity and uncertainty of these developments, a scenario analysis technique known as morphological analysis is used. A set of 23 AED-related technologies and various alternatives for how each technology could develop are compiled in the form of a morphological box. Then, four scenarios are mapped to illustrate future development pathways. This type of holistic analysis provides decision-makers with a comprehensive picture of the future transportation system, allowing them to make more informed decisions. The main contribution of the study is a better understanding of how to approach and structure such a complex research question.

Purpose: Electrification is a promising solution for decarbonising the road freight transport system, but it is challenging to understand its impact on the system. The purpose of this research is to provide a system-level understanding of how electrification impacts the road freight transport system. The goal is to develop a model that illustrates the system and its dynamics, emphasising the importance of understanding these dynamics in order to comprehend the effects of electrification. Design/methodology/approach: The main methodological contribution of the study is the combination of the multi-layer model with system dynamics methodology. A mixed methods approach is used, including group model building, impact analysis, and literature analysis. Findings: The study presents a conceptual multi-layer dynamic model, illustrating the complex causal relationships between variables in the different layers and how electrification impacts the system. It distinguishes between direct and induced impacts, along with potential policy interventions. Moreover, two causal loop diagrams (CLDs) provide practical insights: one explores factors influencing electric truck attractiveness, and the other illustrates the trade-off between battery size and fast charging infrastructure for electric trucks. Originality/value: The study provides stakeholders, particularly policymakers, with a system-level understanding of the different impacts of electrification and their ripple effects. This understanding is crucial for making strategic decisions and steering the transition towards a sustainable road freight transport system.

The adoption of electric heavy trucks holds great potential for decarbonising freight transportation, but the market remains nascent. Electrification of the road freight transportation system is complex, involving many interrelated variables, including vehicles, charging infrastructure, and various stakeholders. Effective policy interventions are crucial for accelerating the transition, and developing dynamic models is helpful for understanding the dynamics involved. This study develops a system dynamics model to explore the long-term adoption of electric trucks and charging infrastructure development, considering technology maturity, awareness, and cost. Using real-world data from Sweden (2017–2060), the model analyses various policy levers. The results show that increasing subsidies for charging stations leads to a considerable rise in electric truck adoption, while investments in vehicle technology maturity are the most cost-efficient when financial resources are constrained. By modelling policy interventions endogenously, the study highlights the dynamic impact of policymaking on accelerating the transition to sustainable road freight transport.

This paper explores the system-level impacts of electrification on road freight transport efficiency, a complex concept involving various stakeholders. Electrification adds further complexity by introducing new stakeholders, dynamics, and efficiency variables. The study applies System Dynamics modelling to explore interactions between efficiencies and the impact of electrification. The model is grounded in literature, expert interviews, and workshops, using Swedish data to simulate 2010-2050 for heavy trucks. Results highlight trade-offs among efficiencies and a worse-before-better behaviour in cost, as electrification initially increases costs but results in lower long-term costs. The model allows testing of policy interventions endogenously to explore their dynamic impacts. Findings show two phases of electric truck adoption. Policy analysis suggests focusing on charging infrastructure in the first phase and cost-orientated policies in the second. By increasing system-level understanding, this paper offers valuable knowledge to decision-makers navigating the transition towards a more efficient and sustainable system.

The electrification of heavy road freight is a promising pathway to decarbonise the sector, yet it depends on the electricity supply system, which itself is undergoing a complex transition to low-carbon energy. Achieving net-zero emissions requires understanding the interdependencies between transport and electricity systems. To address this challenge, we developed a system dynamics (SD) model to explore how freight electrification interacts with electricity supply capacity and market-based pricing. Drawing on literature review and expert interviews, the model integrates three modules: demand (electric truck fleet and charging behaviour), supply (capacity expansion with construction delays), and price (merit-order dispatch). Preliminary results indicate that e-truck adoption has limited direct impact on electricity prices under baseline assumptions. However, cross-sectoral competition emerges as critical, where accelerated electrification in other sectors may drive electricity prices upward, reducing electric truck competitiveness. Charging coordination strategies also influence electricity price dynamics. The model provides a holistic perspective and highlights the need for coordinated planning between transport and electricity sectors. However, model calibration is ongoing, and results should be interpreted cautiously.

The transition to electric trucks is a multi-system transition (MST), shaped by dynamic interactions between the transport and electricity systems. While scientific research has begun to consider the complexities of such MST phenomena, there is limited understanding of their temporal impact on transitions. This research provides an overview of the critical couplings shaping the e-truck MST using the technology-actor-institution structure and employs qualitative system dynamics (SD) modelling to identify emerging multi-system dynamics. We apply the SD models to develop two case studies of e-truck adoption in Swedish forestry and port hinterland transport in the Netherlands. The results show similarities and differences between cases, emphasising the context-dependency of road freight electrification transitions. The forestry case demands geographical extension of electricity grids, whilst the port case requires grid congestion management, with profound consequences for policies in both systems. We conclude that SD modelling supports mapping the multi-system dynamics of the road freight electrification transition, providing insights into temporal effects and feedback.