Recent research in freight transportation planning has been exploring the spatial transferability of freight demand models, which can help the planning agencies of developing economies save the cost and time incurred in freight surveys. As the demand models are time-, cost-, and data-intensive, it is prudent to analyze the effects of sample size on the transferred model in a region. The findings and inferences from such analysis will save resources in freight data collection programs. Earlier, conventional models like ordinary least squares (OLS) regression were assessed for transferability. However, the predictive ability and transferability of such non-conventional models are not well studied. It is necessary to understand whether the extent of transferability of non-conventional models is greater than that of conventional models so that planning agencies can adopt more reliable modeling approaches. This paper investigates the spatial transferability of freight production models using OLS, robust regression, and multiple classification analysis (MCA). The results of the transferability assessment show that MCA models have better transferability using the naïve transfer method. In addition, transferability is assessed for different sample sizes to examine the variation in the extent of transferability. The MCA models have shown the least deviation, indicating that these models are preferred for transferability when the sample size is small.

Urban freight generates a disproportionate share of urban externalities, yet the large-scale integration of eco-friendly vehicles (EFVs) remains limited. Barriers include high capital costs, inadequate charging/refuelling infrastructure, and fragmented governance frameworks. This article examines how regulatory structures and stakeholder alignment shape EFV adoption in Rome, analysing two pilot solutions: (i) a shared hub for electric and hydrogen freight vehicles, and (ii) a cargo-bike programme combining service-trip separation with reverse logistics. The methodological approach integrates a structured review of recent scholarship—organised in line with PRISMA guidance and enriched with bibliometric analysis—with empirical insights from five Living Lab workshops involving logistics providers, energy firms, technology suppliers, and industry associations. The findings highlight that progress depends less on technological capability than on policy mixes matched to stakeholder incentives. For the hub, decisive factors include siting, governance, and scale, while for cargo-bikes, reliability of dispatch, remuneration models, and certified training are critical. The study concludes that Rome’s path to freight decarbonisation requires regulatory and financial packages continuously tailored to actors’ operational priorities and behavioural responses.