Identifying electric vehicle charging styles among consumers: a latent class cluster analysis

IF 3.9 Q2 TRANSPORTATION
Elham Hajhashemi, Patricia Sauri Lavieri, Neema Nassir
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引用次数: 0

Abstract

The market share of electric vehicles (EVs) is growing rapidly, making it crucial to understand the charging behaviour of current and prospective users. Such understanding is essential for designing policies that positively influence consumers’ charging behaviour and facilitate EV adoption. In this study, we examined the heterogeneity in charging preferences of 994 respondents across Australia using a latent class cluster model that considers indicators of charging behaviour as outcomes of interest. We used sociodemographic characteristics, travel needs, and EV adoption status as covariates to predict class membership. Our findings indicate five segments of consumers with distinct charging preferences: routine-focused frugals, cost-oriented deliberators, range seekers, flexibility seekers, and indifferent late adopters. These segments differ in the importance they attach to charging attributes, their coping strategies with limited battery resources, and their risk attitude. Our results suggest that a uniform approach to EV-related policies is not appropriate, as each consumer segment has unique charging preferences and requirements. Furthermore, the study emphasizes the significance of accounting for charging behaviour heterogeneity in demand modelling, as assumptions in current models may not accurately represent the decision-making of most segments.

识别消费者的电动汽车充电方式:潜类聚类分析
电动汽车(EV)的市场份额正在迅速增长,因此了解当前和潜在用户的充电行为至关重要。这种了解对于设计积极影响消费者充电行为的政策和促进电动汽车的采用至关重要。在本研究中,我们采用潜类聚类模型,将充电行为指标作为研究结果,考察了澳大利亚994名受访者充电偏好的异质性。我们将社会人口特征、出行需求和电动汽车采用状况作为协变量来预测类别成员资格。我们的研究结果表明,有五类消费者具有不同的充电偏好:日常节俭型、成本导向型、续航能力追求者、灵活性追求者和冷漠的后期采用者。这些群体对充电属性的重视程度、对有限电池资源的应对策略以及风险态度各不相同。我们的研究结果表明,对电动汽车相关政策采用统一的方法并不合适,因为每个消费者群体都有独特的充电偏好和要求。此外,研究还强调了在需求建模中考虑充电行为异质性的重要性,因为当前模型中的假设可能无法准确代表大多数细分市场的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
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