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The effect of attribute representation methods on noise valuation: A choice experiment study

机译：属性表示方法对噪声评估的影响：一项选择实验研究

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摘要

Traffic noise has been known to severely affect human population. The valuation of traffic noise pose a significant challenge in choice experiments as respondents have little understanding of the physical measure of noise and its associated perception. As a result, several techniques have been developed that represent noise using different methods, either based on the level of noise exposure or the respondent’s level of noise annoyance. This study examines the effect of different methods of attribute representation on respondents’ attribute understanding and valuation. The study is focussed on residential choice and residential view and sunlight are important attributes that are examined along with traffic noise. The study demonstrates that the methods of attribute representation have an important effect on respondents’ understanding of the attributes as well as in the subsequent valuation. It was found that attribute such as view is better represented using the location representation while noise is better represented using the linguistic method. Moreover, the method of attribute modelling also plays a significant role in the analysis as certain data input techniques are more suitable for some representation methods.
机译：众所周知，交通噪声会严重影响人口。由于受访者对噪声的物理度量及其相关感知知之甚少，因此在选择实验中，对交通噪声的估值提出了重大挑战。结果，已经开发出了几种技术，这些技术可以使用不同的方法来表示噪声，这些方法可以基于噪声暴露程度或被调查者的噪声烦恼程度。这项研究研究了不同的属性表示方法对受访者的属性理解和评估的影响。该研究集中在住宅选择上，住宅景观和阳光是与交通噪声一起检查的重要属性。该研究表明，属性表示方法对受访者对属性的理解以及随后的评估具有重要影响。发现使用位置表示可以更好地表示诸如视图之类的属性，而使用语言方法可以更好地表示噪声。此外，属性建模方法在分析中也起着重要作用，因为某些数据输入技术更适合某些表示方法。

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