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Using conjoint analysis to gain deeper insights into aesthetic landscape preferences

机译:使用联合分析对美学景观偏好有更深入的了解

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摘要

Enjoyable landscapes are important resources for recreational activities and the socio-economic development of tourism destinations. A profound understanding of landscape preferences can support landscape management and planning. Despite the increasing integration of the socio-cultural perspective in landscape preferences research, little is known about the links between landscape characteristics and individual landscape preferences. In this study, we aimed to estimate landscape preferences at the individual level based on a set of landscape indicators, allowing us to measure the preferences of each person. We thereby evaluated the suitability of conjoint analysis to identify the relative importance of selected landscape indicators and the corresponding part-worth utilities of their characteristics. We further examined whether the preferences are homogeneous or if we can identify groups with largely different preferences. We related the picture ratings from a photo-based survey of landscapes in the Central Alps to a set of 11 landscape indicators, measuring the landscape pattern and features of each picture. Each indicator was divided into two or three levels and used to calculate importance scores and part-worth utilities by hierarchical Bayes analysis for individuals. In our study area, 11 indicators were sufficient to predict the individual choice between two landscapes for ∼90% of the respondents. Our results indicate non-linear relationships between some landscape indicators and landscape preferences and revealed considerable heterogeneity for the vectors of part-worth utilities, suggesting some methodological problems when applying aggregated linear prediction models. Our findings may therefore enhance predictive models and support landscape planning and management, but further research is necessary to understand the driving forces behind the observed differences.
机译:令人愉悦的景观是休闲活动和旅游目的地社会经济发展的重要资源。对景观偏好的深刻理解可以支持景观管理和规划。尽管社会文化观点在景观偏好研究中越来越多地融合在一起,但人们对景观特征与个人景观偏好之间的联系知之甚少。在这项研究中,我们旨在基于一组景观指标来估计个人层面的景观偏好,从而使我们能够衡量每个人的偏好。因此,我们评估了联合分析的适用性,以识别所选景观指标及其特征的相应部分价值效用的相对重要性。我们进一步检查了偏好是否是同质的,或者是否可以识别出偏好差异很大的群体。我们将基于照片的中阿尔卑斯山风景调查的图片评级与一组11个风景指标相关联,以测量每张图片的风景图案和特征。每个指标分为两个或三个级别,并通过针对个人的层次贝叶斯分析来计算重要性得分和部分价值效用。在我们的研究区域中,约有90%的受访者使用11个指标足以预测两种情况之间的个人选择。我们的结果表明一些景观指标与景观偏好之间存在非线性关系,并揭示了部分价值效用向量的相当大的异质性,这在应用聚合线性预测模型时提出了一些方法学问题。因此,我们的发现可能会增强预测模型并支持景观规划和管理,但是需要进一步的研究以了解所观察到的差异背后的驱动力。

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