2025/10/02 by Batenko, Agnese, Jurgelāne-Kaldava, Ingūna, Kukjans, Igors +4
#Infrastructure sequencing #Social and Behavioral Sciences #cold chain decarbonization #heavy duty technology adoption
paper · doi:10.17605/osf.io/bcdak
This study develops a decision support framework for planning low-carbon freight transport infrastructure in regions with declining demand. Using Latvia’s freight data (2012–2023), it integrates demand forecasting (ARIMA), technology adoption modeling (TCO-based S-curves), and modal split analysis to evaluate optimal sequencing of investments in hydrogen fuel cell and battery electric vehicle infrastructure. The results show that phased investment strategies can save approximately €18.2 million (NPV at 4% discount) compared to immediate large-scale deployment, while ensuring compliance with regulatory decarbonization targets. The framework offers policymakers practical, evidence-based guidance for timing infrastructure investments and mobilizing private capital in the transition to sustainable freight transport.