Exploring the macro environment determinants behind the diffusion of electric Light Commercial Vehicles
Bibliographic Data
| ID | 19337592 |
|---|---|
| Authors | Carolina Gil Ribeiro (0000-0001-9383-9187, KTH Royal Institute of Technology, corresponding author), Jagruti Thakur (0000-0001-5742-6457, KTH Royal Institute of Technology), Maryna Henrysson (0000-0003-0253-3380, KTH Royal Institute of Technology) |
| Year | 2025 |
| Publication date | 2025-07-03 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Transportation (JOURNAL) |
| Journal identifiers | ISSN: 0049-4488 • E-ISSN: 1572-9435 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11116-025-10656-z |
| OpenAlex | W4411974435 |
| Language | EN |
| References cited | 53 |
Rising transport emissions undermine urban sustainability goals, exposing a widening gap between climate ambition and emissions trajectories. Amid these trends, in the European Union (EU), electric vehicles account for only a very small proportion of new registrations for Light Commercial Vehicles (LCVs), below the levels seen in the passenger vehicles segment. While previous studies have investigated country-specific factors, this research adopts a macro-level perspective by examining aggregate diffusion patterns of electric Light Commercial Vehicles (eLCVs) across 27 EU member states. To identify the underlying determinants of this variation, this study employed a series of panel data regression models to evaluate how a set of socioeconomic, energy, mobility, and innovation-related variables shape eLCV diffusion and, more specifically, to assess the explanatory power of these variables. Among the models tested, the Fixed Effects Model proves to be most effective in capturing these relationships, reinforcing the value of a multifactorial approach to understanding eLCV adoption dynamics. The findings enhance the understanding of structural diffusion patterns and provide an empirical basis for better aligning policy and industry efforts with the EU’s regional decarbonisation objectives
Diffusion · Economic geography · Economics · Electric cars · Electric light · Electrical engineering · Engineering physics · Macro · Macro level · Macroeconomics · Physics · Thermodynamics · Automotive Engineering · Computer Science · Electric Vehicles and Infrastructure · Energy, Environment, and Transportation Policies · Engineering · Vehicle emissions and performance
Data Analysis Using Regression and Multilevel/Hierarchical Models
Practitioners’ Corner
A Simple Test for Heteroscedasticity and Random Coefficient Variation
The influence of financial incentives and other socio-economic factors on electric vehicle adoption
Panel Data Econometrics in R
Some Tests of Specification for Panel Data
Specification Tests in Econometrics
Understanding barriers and enablers of electric vehicles in urban freight transport
The criticality of financial development and energy consumption for environmental sustainability in OECD countries
Socio-technical transitions to sustainability
Factors Affecting Electric Vehicle Uptake
Prioritizing the Chicken or Egg? Electric Vehicle Purchase and Charging Infrastructure Subsidies in Germany
Electric vehicle adoption in a mature market
Should I Use Fixed or Random Effects
| Highly cited | No |
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