Analysing the effect of heterogeneous preferences on electric vehicle adoption: The case of Denmark

Abstract

For the next decade, car markets are expected to see a large increase in the adoption of batteryelectric vehicles (BEVs) by many segments of the population. These segments have different preferences, making the design of transport policies more complicated. This research aims to identify groups of car buyers who could be expected to drive BEV adoption and those who are likely to be laggards. To do so, we estimate preferences related to car technology, charging facilities and car characteristics such as size and environmental impacts, using a discrete choice experiment with three fuel types and six car segments. Using a Latent Class (LC) modelling approach, we find four classes to capture the varying preferences across the population. Each class captures different preferences for attributes and effects of sociodemographic variables, providing insights for a detailed analysis of the car users’ preferences and perceptions.