Incorporating individual preference and network influence on choice behavior of electric vehicle sharing using agent-based model

Agent-based modelling for market acceptance of electric vehicles: Evidence from China

“…These studies fall into two main categories, one to understand consumer influences on EV adoption, such as Wang et al (2018b), Wu et al (2019) and Ning et al (2020); and one to understand the logic of consumer decisions on EV adoption, such as Silvia and Krause (2016), Zhuge et al (2020) and Li et al (2020a). In general, two consensus were reached, firstly, the importance of charging facilities for mass EV acceptance is identified; secondly, consumer decisions are the result of a combination of factors, i.e., consumer preferences, policy interventions and social networks, and individual micro-decision making will definitely affect EV diffusion Ning et al, 2020;Song et al, 2020). However, to the best of our knowledge, conventional wisdom does not fully capture the complex social dynamics of EV adoption, and in particular, the logical role of charging facilities in consumer decision making is still missing.…”

“…The first stream investigates consumer preferences. Many empirical studies have provided theoretical support for consumer preferences, i.e., Ning et al (2020), Li et al (2020b) and Khan et al (2020), these studies have examined the vast majority of consumer preferences regarding product attributes and policy interventions, including purchase price, operation cost, driving range, charging time, vehicle security, and related policies, such as purchase subsidy, carbon trading scheme and tradable driving credits. One of the key findings is that public charging facilities are key to supporting the mass acceptance of EVs (Santos and Davies, 2020;Tan and Lin, 2020).…”

Investigating Market Diffusion of Electric Vehicles with Experimental Design of Agent-Based Modeling Simulation

“…On the other hand, external factors are those factors that are out of the direct control of manufacturers, such as consumer characteristics and preferences, fuel prices, availability of charging stations, and policy incentives such as subsidies and tax reductions; there is a growing body of literature focusing on the effects of financial incentives in facilitating EV diffusion. Social networks and interactions may play a significant role in the diffusion of any technological innovation, including EVs [16]; it has been previously discussed that technology diffusion proceeds much faster in a clustered environment [16,21].…”

“…It is argued here that these mathematical models may have limitations when considering details of the effects of individual policy measures and their interactions on diffusion. Alternatively, the agent-based modeling (ABM) approach has drawn growing attention for analysis of the EV diffusion [13][14][15][16][17][18][19]. Specifically, an ABM analysis of innovation diffusion was conducted by incorporating the context of changing social appraisal and regulatory support for eco-friendly vehicles in [13], where two different scenarios were investigated.…”

“…Exploring possible interactions between policies and consumer behavior, Kangur et al [15] used a social simulation model based on survey data to forecast the market share of PHEVs and BEVs in the Netherlands. Ning et al [16] established an ABM model of the consumer choice behavior in the context of EV sharing from the perspective of individual preference and social network influences. The market diffusion of EVs has been investigated under different regional contexts in [17][18][19].…”