Title
Falling short in 2030: Simulating battery-electric vehicle adoption behaviour in the Netherlands
Author
Paradies, G.L.
Usmani, O.A.
Lamboo, S.
van den Brink, R.W.
Publication year
2023
Abstract
The widespread adoption of battery electric vehicles (BEVs) is a crucial element in climate policy for the transport sector. To design effective policies to stimulate the uptake of BEVs, it is essential to understand the barriers and drivers that influence consumers' choices for a BEV. To this aim, we present a computational model named CODEC, a hybrid choice model that estimates the future market share of different vehicle types. The model gives insight into the different effects of technical, financial and other behavioural factors that influence the adoption decision. We included social factors and routine behaviour, which are rarely analysed in other research. We assessed the share in sales of BEVs and gasoline vehicles in the Netherlands between 2020 and 2030 for privately owned new cars. To initialize the model we used data from a survey on the perceptions of prospective car buyers (n = 1522). Our analysis shows that the BEV market share in new car sales will be between 26 and 40 % in 2030, well below the government target of 100 %. The analysis also shows that current barriers for BEV adoption: higher purchase price and lower driving range, will become less important over time. In 2030 routine purchasing behaviour and social factors are the main barriers for widespread BEV adoption. New policy measures are needed to lower these barriers. Factors that affect BEV adoption positively have a relatively small effect, so also measures to reduce the attractiveness of gasoline vehicles should be considered. (C) 2023 The Authors
Subject
Decision behaviour
Electric vehicles
Energy transition
Innovation adoption
Modelling
Policy support
Energy Efficiency
Energy / Geological Survey Netherlands
To reference this document use:
http://resolver.tudelft.nl/uuid:22afd051-5e6a-4047-822b-238f44ca0658
DOI
https://doi.org/10.1016/j.erss.2023.102968
TNO identifier
982774
Publisher
Elsevier Ltd
ISSN
2214-6296
Source
Energy Research and Social Science, 97 (97), 1-15
Document type
article