Morton, C orcid.org/0000-0003-0984-9580, Anable, J orcid.org/0000-0002-4259-1641 and Nelson, J (2017) Consumer Structure in the Emerging Market for Electric Vehicles: Identifying market segments using cluster analysis. International Journal of Sustainable Transportation, 11 (6). pp. 443-459. ISSN 1556-8318
Abstract
This paper presents results from a segmentation analysis of the emerging market for Electric Vehicles (EVs). Data has been sourced through the application of a self-completion household questionnaire distributed over two cities in the United Kingdom (UK). A two stage cluster analysis methodology has been followed to identify market segments in a dataset of UK drivers. Five unique segments have been identified in the analysis and are characterised by their preferences for EVs, socio-economic characteristics, current car details, and socio-psychological profiles. These segments hold a range of different EV preference levels, from those who appear unwilling to adopt an EV to those which are clearly attracted to EVs. Moreover, the features of these segments tend to suggest that segments might be attracted to or repelled from EVs for different reasons. These results demonstrate that a significant degree of consumer stratification is present in the emerging market for EVs, with the possible implications being that policy interventions at the market, as opposed to segment, level may prove ineffective due to their inability to cater for the nuances of important segments.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Sustainable Transportation on 14 December 2016, available online: http://www.tandfonline.com/10.1080/15568318.2016.1266533. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Electric Vehicle Demand; Market Segmentation; Demographic Profiling; Psychographic Profiling |
Dates: |
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Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Dec 2016 12:17 |
Last Modified: | 14 Dec 2017 01:38 |
Published Version: | https://doi.org/10.1080/15568318.2016.1266533 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/15568318.2016.1266533 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109577 |