Consumer preferences for electric vehicles: a literature review
By F. Liao, Eric Molin, Bert van Wee. 2017
719 citations recorded by the source corpus.
ABSTRACT Widespread adoption of electric vehicles (EVs) may contribute to the alleviation of problems such as environmental pollution, global warming and oil dependency. However, the current market penetration of EV is relatively low in spite of many governments implementing strong promotion policies. This paper presents a comprehensive review of studies on consumer preferences for EV, aiming to better inform policy-makers and give direction to further research. First, we compare the economic and psychological approach towards this topic, followed by a conceptual framework of EV preferences which is then implemented to organise our review. We also briefly review the modelling techniques applied in the selected studies. Estimates of consumer preferences for financial, technical, infrastructure and policy attributes are then reviewed. A categorisation of influential factors for consumer preferences into groups such as socio-economic variables, psychological factors, mobility condition, social influence, etc. is then made and their effects are elaborated. Finally, we discuss a research agenda to improve EV consumer preference studies and give recommendations for further research. Abbreviations: AFV: alternative fuel vehicle; BEV: battery electric vehicle; CVs: conventional vehicles; EVs: electric vehicles; FCV: fuel cell vehicle; HCM: hybrid choice model; HEV: hybrid electric vehicle (non plug-in); HOV: high occupancy vehicle; MNL: MultiNomial logit; MXL: MiXed logit model; PHEV: plug-in hybrid electric vehicle; RP: revealed preference; SP: stated preference.
Subfields: Automotive Engineering, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/aeb89f14391afad9a92ae1601459792c124e7d41
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- L. Noel
- Benjamin Sovacool
- Johannes Kester
- Bert van Wee
- H. Timmermans
- S. Hardman
- G. Rubens
- Soora Rasouli
In Electrical and Electronic Engineering
- Benjamin Sovacool
- S. Hardman
- F. Liao
- L. Noel
- Anders Fjendbo Jensen
- Johannes Kester
- Bert van Wee
- G. Rubens
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Policy effects on charging behaviour of electric vehicle owners and on purchase intentions of prospective owners: Natural and stated choice experiments (2018, positive): “Research on charging behaviour has started with using travel patterns from ICE vehicles and tried to infer charging decisions from these patterns (Liu, 2012; Sathaye & Kelley, 2013). Moving beyond this, exploratory work was done which tried to model the decision to start charging. Franke & Krems (20”
- Electric carsharing and micromobility: A literature review on their usage pattern, demand, and potential impacts (2020, background): “Electric carsharing is expected to speed up the replacement of fossil-fuel-powered cars by EVs, since using shared EVs is not supposed to meet as much resistance as buying private EVs due to the high purchase costs and multiple risks and uncertainties (Liao et al., 2017).”
- Understanding the impact of reoccurring and non-financial incentives on plug-in electric vehicle adoption – A review (2019, background): “ Literature review unable to find clear trends in literature (Liao et al., 2016).”
- Willingness to pay for electric vehicles and vehicle-to-grid applications: A Nordic choice experiment (2019, background): “First, in a recent systematic review of alternative-fuel vehicle (AFV) choice experiments, only two studies from 2005 to 2015 included more than one country (8,11,17).”
- Consumer preferences for business models in electric vehicle adoption (2019, background): “The unattractiveness of EV for the mainstream market in comparison to conventional vehicles can be mainly attributed to the following shortcomings (Liao et al., 2017).”