Abstract
The methods of paired comparison and ranking play an important role in the analysis of preference data. In this study, first we show how asymmetric multidimensional scaling allows to represent in a diagram the preference order that comes out in a paired-comparison task concerning architectural façades. A ranking task involving the same stimuli and the same subject sample further enriched the preference analysis, because multidimensional unfolding applied to the ranking data matrix allows to detect the relationships between subjects and architectural façades. The results show that high curved façade is the most preferred, followed by the medium curved, angular and rectilinear ones. Rectilinear stimuli were always the least preferred and not angularity as expected.
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Acknowledgements
We thank the architect Stefania Lamaddalena for sharing with us her professional knowledge and for producing the AutoCAD 2-D render of the stimuli we used in this study.
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Bove, G., Ruta, N., Mastandrea, S. (2019). Preference Analysis of Architectural Façades by Multidimensional Scaling and Unfolding. In: Greselin, F., Deldossi, L., Bagnato, L., Vichi, M. (eds) Statistical Learning of Complex Data. CLADAG 2017. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-030-21140-0_6
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DOI: https://doi.org/10.1007/978-3-030-21140-0_6
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