Decoding the patterns of critical factor associations driving electric vehicle recommendations

IF 6.3 1区 工程技术 Q1 ECONOMICS
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引用次数: 0

Abstract

This study aims to identify the patterns of key factor combinations that collectively influence consumers to recommend distinct Electric Vehicle (EV) types, namely hydrogen-powered Fuel Cell EVs (FCEVs) and Plug-in EVs (PEVs). To achieve this goal, we apply a non-parametric Association Rules Mining (ARM) approach which unearths latent relationships between different factors in large datasets for analysis. The study utilized the comprehensive 2019 EV user survey data from California, covering socio-economic and demographic characteristics, EV driving and charging habits, housing and parking options, the impact of incentives on EV purchase decisions, and willingness to recommend EVs, among other factors. The results revealed that individuals who find incentives important and experienced a reduced need for refuelling and waiting to refuel their EVs, as well as those who did not have to make special trips to refuel, were more likely to recommend FCEVs. Besides, the availability of home charging facilities and variable electricity rates highly influenced consumers to recommend PEVs. Also, individuals who frequently drove and had positive experiences with both EV types were highly likely to recommend them. Although FCEV users are concerned about station availability when travelling, and PEV users worry about the high cost of EVs, they are still willing to recommend them. The findings highlight critical factors that can enhance EV recommendations and increase adoption rates. Understanding these patterns enables policymakers and industry players to accelerate the transition to sustainable energy and mitigate climate change impacts.

驱动电动汽车推荐的关键因素关联模式解码
本研究旨在找出影响消费者推荐不同电动汽车(EV)类型(即氢动力燃料电池电动汽车(FCEV)和插电式电动汽车(PEV))的关键因素组合模式。为实现这一目标,我们采用了一种非参数关联规则挖掘(ARM)方法,该方法可在大型数据集中发现不同因素之间的潜在关系,以便进行分析。研究利用了加利福尼亚州 2019 年电动汽车用户综合调查数据,涵盖社会经济和人口特征、电动汽车驾驶和充电习惯、住房和停车选择、激励措施对电动汽车购买决策的影响以及推荐电动汽车的意愿等因素。结果显示,认为激励措施很重要、减少了为电动汽车加油和等待加油的需求以及无需专程去加油的人更愿意推荐 FCEV。此外,家庭充电设施的可用性和可变电价也对消费者推荐 PEV 有很大影响。此外,经常驾驶并对两种电动汽车都有积极体验的人也极有可能推荐这两种电动汽车。尽管 FCEV 用户担心出行时是否有充电站,PEV 用户担心电动汽车成本过高,但他们仍然愿意推荐这两种电动汽车。研究结果强调了能够加强电动汽车推荐和提高采用率的关键因素。了解这些模式有助于政策制定者和行业参与者加快向可持续能源过渡,减轻气候变化的影响。
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来源期刊
CiteScore
13.20
自引率
7.80%
发文量
257
审稿时长
9.8 months
期刊介绍: Transportation Research: Part A contains papers of general interest in all passenger and freight transportation modes: policy analysis, formulation and evaluation; planning; interaction with the political, socioeconomic and physical environment; design, management and evaluation of transportation systems. Topics are approached from any discipline or perspective: economics, engineering, sociology, psychology, etc. Case studies, survey and expository papers are included, as are articles which contribute to unification of the field, or to an understanding of the comparative aspects of different systems. Papers which assess the scope for technological innovation within a social or political framework are also published. The journal is international, and places equal emphasis on the problems of industrialized and non-industrialized regions. Part A''s aims and scope are complementary to Transportation Research Part B: Methodological, Part C: Emerging Technologies and Part D: Transport and Environment. Part E: Logistics and Transportation Review. Part F: Traffic Psychology and Behaviour. The complete set forms the most cohesive and comprehensive reference of current research in transportation science.
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