Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market

Electric vehicles (EVs) continue to penetrate passenger vehicle markets worldwide. Most current EV markets remain in nascent stages, with buyers being categorised as early adopters or pioneers. However, if electric vehicles are to successfully contribute to the decarbonisation of transportation, the...

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Published in:Energy
Main Author: Zarazua de Rubens, Gerardo
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:https://pure.au.dk/portal/da/publications/who-will-buy-electric-vehicles-after-early-adopters-using-machine-learning-to-identify-the-electric-vehicle-mainstream-market(3613bf54-b264-4b5c-a345-264165c79083).html
https://doi.org/10.1016/j.energy.2019.01.114
https://pure.au.dk/ws/files/144290932/Who_will_buy_electric_vehicles_after_early_adopters_Using_machine_learning_to_identify_the_electric_vehicle_mainstream_market.pdf
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spelling ftuniaarhuspubl:oai:pure.atira.dk:publications/3613bf54-b264-4b5c-a345-264165c79083 2023-05-15T16:50:53+02:00 Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market Zarazua de Rubens, Gerardo 2019 application/pdf https://pure.au.dk/portal/da/publications/who-will-buy-electric-vehicles-after-early-adopters-using-machine-learning-to-identify-the-electric-vehicle-mainstream-market(3613bf54-b264-4b5c-a345-264165c79083).html https://doi.org/10.1016/j.energy.2019.01.114 https://pure.au.dk/ws/files/144290932/Who_will_buy_electric_vehicles_after_early_adopters_Using_machine_learning_to_identify_the_electric_vehicle_mainstream_market.pdf eng eng info:eu-repo/semantics/openAccess Zarazua de Rubens , G 2019 , ' Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market ' , Energy , vol. 172 , no. April , pp. 243-254 . https://doi.org/10.1016/j.energy.2019.01.114 article 2019 ftuniaarhuspubl https://doi.org/10.1016/j.energy.2019.01.114 2021-04-07T22:44:27Z Electric vehicles (EVs) continue to penetrate passenger vehicle markets worldwide. Most current EV markets remain in nascent stages, with buyers being categorised as early adopters or pioneers. However, if electric vehicles are to successfully contribute to the decarbonisation of transportation, they must reach mainstream consumer segments. To investigate the underlying causes of EV interest and to determine the potential next wave of EV buyers, this study draws data from an original dataset (n = 5067) across the five Nordic countries of Denmark, Finland, Iceland, Norway and Sweden. A machine learning model, based on the k-means method, is used for the analysis, creating six consumer segments around prospective EV adoption. The study finds that three consumer clusters, that account for 68% of the (sampled) population, are primed for EV adoption and represent the near-term mainstream EV market. The findings corroborate that price is a main determinant in reaching these mainstream consumers, while suggesting that vehicle-to-grid can contribute to the attractiveness of EVs and their uptake. The study also highlights that EV deployment strategy should focus on the technological and status aspects of EVs, as opopsed to only their environmental and financial attributes. Finally, the study stresses the importance that policy and industry decision-makers must create an equally competitive market place for EVs developing strategies and policy that considers the characteristics and interests of mainstream EV customers. Article in Journal/Newspaper Iceland Aarhus University: Research Norway Energy 172 243 254
institution Open Polar
collection Aarhus University: Research
op_collection_id ftuniaarhuspubl
language English
description Electric vehicles (EVs) continue to penetrate passenger vehicle markets worldwide. Most current EV markets remain in nascent stages, with buyers being categorised as early adopters or pioneers. However, if electric vehicles are to successfully contribute to the decarbonisation of transportation, they must reach mainstream consumer segments. To investigate the underlying causes of EV interest and to determine the potential next wave of EV buyers, this study draws data from an original dataset (n = 5067) across the five Nordic countries of Denmark, Finland, Iceland, Norway and Sweden. A machine learning model, based on the k-means method, is used for the analysis, creating six consumer segments around prospective EV adoption. The study finds that three consumer clusters, that account for 68% of the (sampled) population, are primed for EV adoption and represent the near-term mainstream EV market. The findings corroborate that price is a main determinant in reaching these mainstream consumers, while suggesting that vehicle-to-grid can contribute to the attractiveness of EVs and their uptake. The study also highlights that EV deployment strategy should focus on the technological and status aspects of EVs, as opopsed to only their environmental and financial attributes. Finally, the study stresses the importance that policy and industry decision-makers must create an equally competitive market place for EVs developing strategies and policy that considers the characteristics and interests of mainstream EV customers.
format Article in Journal/Newspaper
author Zarazua de Rubens, Gerardo
spellingShingle Zarazua de Rubens, Gerardo
Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market
author_facet Zarazua de Rubens, Gerardo
author_sort Zarazua de Rubens, Gerardo
title Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market
title_short Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market
title_full Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market
title_fullStr Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market
title_full_unstemmed Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market
title_sort who will buy electric vehicles after early adopters? using machine learning to identify the electric vehicle mainstream market
publishDate 2019
url https://pure.au.dk/portal/da/publications/who-will-buy-electric-vehicles-after-early-adopters-using-machine-learning-to-identify-the-electric-vehicle-mainstream-market(3613bf54-b264-4b5c-a345-264165c79083).html
https://doi.org/10.1016/j.energy.2019.01.114
https://pure.au.dk/ws/files/144290932/Who_will_buy_electric_vehicles_after_early_adopters_Using_machine_learning_to_identify_the_electric_vehicle_mainstream_market.pdf
geographic Norway
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genre Iceland
genre_facet Iceland
op_source Zarazua de Rubens , G 2019 , ' Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market ' , Energy , vol. 172 , no. April , pp. 243-254 . https://doi.org/10.1016/j.energy.2019.01.114
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1016/j.energy.2019.01.114
container_title Energy
container_volume 172
container_start_page 243
op_container_end_page 254
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