Using conjoint analysis to gain deeper insights into aesthetic landscape preferences

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.