Who will buy electric cars? An empirical study in Germany

Lieven, Theo; Mühlmeier, Silke; Henkel, Sven; Waller, Johann F.

doi:10.1016/j.trd.2010.12.001

Cited by 233 publications

(116 citation statements)

References 2 publications

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“…Moreover, with mainstream consumers purchasing a new car tending not to consider greenhouse gas emissions to be particularly important in their purchasing decisions (Caulfied et al 2010), one of the unique benefits of EVs has often proven to be inhibited. These identified limitations coincided with low expectations regarding the future potential of the EV market (Train, 1980;Lieven et al 2011) which have generally been validated by observed EV sales rates.…”

Section: Past Researchsupporting

confidence: 52%

“…Following an assumption that such price and performance parities are realised and that demand for EVs grows substantially in the future, attention is shifting towards understanding the likely nuances and dynamics of this demand (Lieven, et al 2011;Shepherd et al 2012;Zubaryeva et al 2012;Plötz et al 2014). With the importance of accounting for the idiosyncrasies of different groups in the transport market well established (Anable, 2005;Burkhardt and Milard-Ball, 2006;Barr and Prillwitz, 2012;Al-Alawi and Bradley, 2013;Budd et al 2014;Fürst, 2014), it is assumed that exploring the response of different market segments to EVs will likely prove rewarding.…”

Section: Past Researchmentioning

confidence: 99%

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Consumer structure in the emerging market for electric vehicles: Identifying market segments using cluster analysis

Morton

Anable

Nelson

2016

International Journal of Sustainable Transportation

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Article: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 ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. 1 Consumer Structure in the Emerging ABSTRACTThis 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.

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Section: Past Researchsupporting

confidence: 52%

Section: Past Researchmentioning

confidence: 99%

Consumer structure in the emerging market for electric vehicles: Identifying market segments using cluster analysis

Morton

Anable

Nelson

2016

International Journal of Sustainable Transportation

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“…In addition, the influence of environmental concern has gained increasing attention from researchers. Research in this context has shown that car owners' environmental concerns have led to switching behavior toward electric cars or other modes of transport, including public transport (25,26).…”

Section: Modeling Household Car Ownership Background Literature On Homentioning

confidence: 99%

Changing Influence of Factors Explaining Household Car Ownership Levels in the Netherlands

Maltha

Kroesen

Wee

et al. 2017

Transportation Research Record

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To contribute to existing research on the influence of various factors on household car ownership in the Netherlands, this study addressed the question whether and to what extent the influence of economic, socio demographic, and spatial factors on the number of cars owned by house holds has changed over time. There seems to be an absence of studies investigating the changing influence of these factors on car ownership in recent decades, and in the Netherlands. The study used the statisti cal method of ordered logistic regression on household mobility data on 162,593 households, collected by the National Traffic Survey of the Netherlands in

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“…Rezvani et al [20], Lieven et al [32], and Adepetu and Keshav [33] showed that compared to the same level of fuel vehicles, BEV's higher acquisition cost was a major factor hindering purchase. Furthermore, repair (once a problem occurred) and maintenance costs were higher.…”

Section: Attribute Factors That Hinder Bev Purchase Intentionmentioning

confidence: 99%

Low Purchase Willingness for Battery Electric Vehicles: Analysis and Simulation Based on the Fault Tree Model

Long

Chen

et al. 2017

Sustainability

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Purchase intention is the key to popularizing battery electric vehicles (BEVs) and to developing the industry. This study combines classical theoretical and qualitative research, and applies fault tree analysis (FTA) methods to study factors that hinder BEV purchase, and identify the logical relationship between top fault events and basic events, by calculating minimal cut sets and minimal path sets. Activity based classification analysis was used to investigate the key basic event and key event combination (i.e., minimal cut sets) that hinders purchase intention, with the effectiveness and feasibility of the proposed method verified by Monte Carlo simulation. The results indicate (1) there were 26 minimal cut sets and 18 minimal path sets in the fault tree model, and the fault tree was defined by four key event combinations and five key basic events; and (2) by reducing key events' failure probability, the probability of fault tree cumulative occurrence was reduced from 0.86021 to 0.57406 over 100,000 Monte Carlo simulations, i.e., the willingness to purchase BEVs was significantly increased. Thus, the proposed FTA method was feasible and effective for addressing low purchase intentions. Consequently, some policy implications are suggested.

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Who will buy electric cars? An empirical study in Germany

Cited by 233 publications

References 2 publications

Consumer structure in the emerging market for electric vehicles: Identifying market segments using cluster analysis

Consumer structure in the emerging market for electric vehicles: Identifying market segments using cluster analysis

Changing Influence of Factors Explaining Household Car Ownership Levels in the Netherlands

Low Purchase Willingness for Battery Electric Vehicles: Analysis and Simulation Based on the Fault Tree Model

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