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I can't believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice

机译:我不敢相信您的态度:最佳最坏态度和电动汽车选择的共同估算

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摘要

The number of conventionally fuelled motor vehicles in use is increasing worldwide despite warnings about finite fossil fuel and the detrimental impacts of burning such fuels. While electric vehicles, the subject of much research, generate far less emissions and offer the potential for power from renewable sources, they are yet to significantly penetrate the market. Tangible barriers such as price and vehicle range still exist, but consumer attitudes also drive behaviour. This paper examines attributes in a framework relatively new to transportation and energy policy; best-worst scaling. This method is widely considered an improvement over traditional methods of eliciting attitudes and beliefs, where respondents select attitudes they find best or worst from a set of attitudinal statements. To avoid potential endogeneity bias, we jointly model attitudes and choice for the first time with best-worst data. It is found that energy crisis, air quality and climate change concerns influence behaviour with respect to vehicle range and that travel behaviour change and forms of government incentives are needed influences on behaviour with respect to vehicle emissions. It is argued that correctly modelling attitudes reduces the error term of the vehicle choice model and provides policy makers with an improved lens for assessing behaviour. Additionally, the methods described within can easily be adapted to other policy scenarios.
机译:尽管有关于有限的化石燃料和燃烧这种燃料的有害影响的警告,但在世界范围内,使用常规燃料的机动车的数量正在增加。尽管电动汽车是许多研究的主题,但产生的排放却少得多,并具有可再生能源发电的潜力,但它们仍未显着渗透市场。价格和车辆续航等实际障碍仍然存在,但是消费者的态度也推动了行为。本文研究了运输和能源政策相对较新的框架中的属性。最差的缩放比例。这种方法被广泛认为是对引起态度和信念的传统方法的一种改进,在传统方法中,受访者从一系列态度陈述中选择自己认为最佳或最差的态度。为了避免潜在的内生性偏见,我们首次使用最差的数据共同对态度和选择进行建模。结果发现,能源危机,空气质量和气候变化问题影响了车辆行驶里程的行为,而出行行为的变化和政府激励措施的形式也需要对车辆排放行为产生影响。有观点认为,正确的建模态度可以减少车辆选择模型的误差,并为决策者提供一种评估行为的改进方法。此外,其中描述的方法可以轻松地适应其他策略方案。

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