Strategic Infrastructure Sequencing for Freight Transport Decarbonization Under Declining Demand Using Data from Latvia

This study addresses a critical policy paradox in transport infrastructure planning: the necessity for substantial decarbonization investments amid declining freight demand forecasts in less developed territories. Despite reduced demand, such investments remain justified for advancing sustainability, regulatory compliance, and long-term system resilience. Herein, an integrated decision support framework is developed that optimizes infrastructure investment sequencing while maximizing private capital participation and ensuring technology–regulation alignment. Using comprehensive freight transport data from Latvia (2012–2023), a scenario tree analysis integrated with S-curve technology adoption models is employed to evaluate optimal infrastructure sequencing strategies for hydrogen fuel cell vehicles (HFCVs) and battery electric vehicles (BEVs). The methodology combines Autoregressive Integrated Moving Average (ARIMA) demand forecasting with total cost of ownership (TCO)-based technology adoption curves and hierarchical modal split modeling. The analysis further identifies distinct market segments and adoption trajectories, demonstrating how strategic infrastructure sequencing can accelerate low- and zero-emission technology uptake across different freight distances and policy scenarios. The results demonstrate that strategic sequencing generates net present value (NPV) savings of approximately EUR 18.2 million (at a 4% discount rate) compared to immediate full-scale deployment while maintaining regulatory compliance timelines. The framework provides policymakers with systematic evidence-based criteria for infrastructure investment timing, contributing to the efficient allocation of scarce public resources in the transition to sustainable freight transport.