Exploring the role of technology innovations in the diffusion of electric vehicle with an agent-based spatial integrated model

Identifying Promising Technologies of Electric Vehicles from the Perspective of Market and Technical Attributes

“…The existing research on the technological innovation of EVs focuses on the improvement and optimization of specific sub-fields such as batteries and charging stations in combination with quantitative analysis methods. The role of battery and charging technologies in the diffusion of EVs was explored, and an agent-based spatial integrated model (SelfSim-EV) was applied to simulate consumers' responses to these technological innovations [13]. A machine learning-based text mining model and co-occurrence network analysis were employed to analyze the impact of artificial intelligence on technological innovation in EV automation [19].…”

“…However, relatively little attention has been paid to identifying promising technologies in EVs, and there are some limitations. Firstly, most of the research on EVs has focused on specific aspects such as batteries, charging stations, and control systems [12,13]; the research methods are mainly based on experiments and investigations; and less systematic analysis of promising EVs technologies has been carried out from an overall perspective. Secondly, from the research perspective, previous studies on EVs rarely link technical attributes with market attributes for multi-perspective analysis [14,15].…”

A Systematic Review of the Agent-Based Modelling/Simulation Paradigm in Mobility Transition

“…Out of 86 papers, 43 studies (50 %) exclusively focussed on the diffusion of EVs. The main aim of these studies was to investigate EVs market share penetration from different perspectives: (i) user behaviour and social aspects (e.g., Brown, 2021a, 2021b;Pagani et al, 2019), (ii) the effects of different policies (e.g., Huang et al, 2021;Querini and Benetto, 2014), (iii) charging technology/demand and battery capacities (e.g., Zhuge et al, 2021;Rodemann et al, 2019), (iv) manufacturers impact (e.g., Vouzavalis, 2020;Kieckhäfer et al, 2017), and (v) willingness of purchasing/using of EVs (e.g., Klein et al, 2020;Ning et al, 2019).…”

“…In other words, consumers exclude factors such as social influence and preferences in their decisions, implying that they exclusively focus on rational behaviour. Forty-four studies (51 %) exclusively used random utility maximization concept to form the decision-making process of the agents (e.g., Adepetu et al, 2016;Buchmann et al, 2021;Gnann et al, 2018;Hörl et al, 2019;Martinez and Viegas, 2017;Oh et al, 2020;Zhuge et al, 2021).…”

“…Moreover, Noori and Tatari (2016) showed that consumer subsidies have the most impact on EVs diffusion. Many reported that a decrease in battery costs results in increased uptake of Plug-in Hybrid EVs (PHEVs) (Eppstein et al, 2011;Kangur, 2014;Kangur et al, 2017;Zhuge et al, 2021). Regarding the role of shared automated vehicles, most studies showed a positive impact on future mobility and environment in terms of emissions (Fagnant and Kockelman, 2014;Hörl et al, 2019;Martinez and Viegas, 2017), while one study concluded that such emerging mobility may be a threat for public transit services (Liu et al, 2017).…”