2014
DOI: 10.1016/j.erss.2014.07.008
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Consumer preferences and the influence of networks in electric vehicle diffusion: An agent-based microsimulation in Ireland

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Cited by 105 publications
(53 citation statements)
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“…Cost-benefit-analyses of electric mobility Baum et al (2010), Carlsson and Johansson-Stenman (2003), Funk and Rabl (1999), Massiani (2015) Analyses of EV market potential and determinants of EV demand Augenstein (2015), Brown et al (2010), Daziano (2013), Diamond (2009), Driscoll et al (2013), Ewing and Sarigöllü (2000), Green et al (2014), Hackbarth and Madlener (2013), Hidrue et al (2011), Kihm and Trommer (2014), Koetse and Hoen (2014), Krause et al (2013), Kurani et al (1996), Lieven et al (2011), Longden (2014), Nykvist and Nilsson (2014), Plötz et al (2014), Rezvani et al (2015), Shafiei et al (2012), Sierzchula et al (2014), McCoy and Lyons (2014) Impacts of EVs on energy demand and supply Davies andKurani (2013), De Gennaro et al (2014), Friedman and Grossweiler (2014), Huang et al (2012), Jargstorf and Wickert (2013), Loisel et al (2014), Lyon et al (2012), Redelbach et al (2014), Wu and Aliprantis (2013), Wu et al (2015) Effects of EV related tax incentives and fiscal effects Hao et al (2014), Hirte and Tscharaktschiew (2013a), Jenn et al (2015), Sánchez-Braza et al...…”
Section: Research Topic Studiesmentioning
confidence: 99%
“…Cost-benefit-analyses of electric mobility Baum et al (2010), Carlsson and Johansson-Stenman (2003), Funk and Rabl (1999), Massiani (2015) Analyses of EV market potential and determinants of EV demand Augenstein (2015), Brown et al (2010), Daziano (2013), Diamond (2009), Driscoll et al (2013), Ewing and Sarigöllü (2000), Green et al (2014), Hackbarth and Madlener (2013), Hidrue et al (2011), Kihm and Trommer (2014), Koetse and Hoen (2014), Krause et al (2013), Kurani et al (1996), Lieven et al (2011), Longden (2014), Nykvist and Nilsson (2014), Plötz et al (2014), Rezvani et al (2015), Shafiei et al (2012), Sierzchula et al (2014), McCoy and Lyons (2014) Impacts of EVs on energy demand and supply Davies andKurani (2013), De Gennaro et al (2014), Friedman and Grossweiler (2014), Huang et al (2012), Jargstorf and Wickert (2013), Loisel et al (2014), Lyon et al (2012), Redelbach et al (2014), Wu and Aliprantis (2013), Wu et al (2015) Effects of EV related tax incentives and fiscal effects Hao et al (2014), Hirte and Tscharaktschiew (2013a), Jenn et al (2015), Sánchez-Braza et al...…”
Section: Research Topic Studiesmentioning
confidence: 99%
“…[23,[25][26][27][28]. Energy and environment related consumer technology adoption has been a particular area of growth in the development and applications of ABM [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. Because the underlying components of the system and how they interact with each other are modeled explicitly in ABM, the processes that lead to observable emergent phenomena (such as the rate and pattern of adoption) can be altered through simulation experiments, creating virtual laboratories [24,45,46].…”
Section: Introductionmentioning
confidence: 99%
“…Cui et al [36] have introduced a multi-agent based simulation network for demonstrating the spatial distribution of PHEV ownership in a neighborhood in a local region and assessing the effect of PHEVs' charging load on a private electric distribution network. McCoy et al [25] have proposed a threshold model for the adoption decision-making process of consumers. Agent-based modeling is used to study agents' interactions in a micro-simulation perspective.…”
Section: Agent-based Modeling and Its Applications In Ev Diffusionmentioning
confidence: 99%
“…Subsequently, in local diffusion of EVs, observability and word of mouth are influential factors. According to [25], there are studies that have defined a utility function for EV adoption. Herein, we defined a utility function based on word of mouth as an observability factor for each agent.…”
Section: Utility Function Formulationmentioning
confidence: 99%
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