Exploring the Influence of the Visual Attributes of Kaplan’s Preference Matrix in the Assessment of Urban Parks: A Discrete Choice Analysis

Marjan Shayestefar, Mahdieh Pazhouhanfar, Clarine van Oel and Patrik Grahn
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Marjan Shayestefar: Department of Architecture, Faculty of Engineering, Golestan University, Gorgan 4918888369, Iran
Mahdieh Pazhouhanfar: Department of Architecture, Faculty of Engineering, Golestan University, Gorgan 4918888369, Iran
Clarine van Oel: Faculty of Architecture and the Built Environment, Delft University of Technology, P.O. Box 5043, 2600 GA Delft, The Netherlands
Patrik Grahn: Department of People and Society, Swedish University of Agricultural Sciences, P.O. Box 190, 234 56 Alnarp, Sweden

Sustainability, 2022, vol. 14, issue 12, 1-19

Abstract: A significant majority of the literature on natural environments and urban green spaces justifies the preferences that people have for natural environments using four predictors defined by Kaplan’s preference matrix theory, namely coherence, legibility, complexity, and mystery. However, there are no studies implicitly focusing on the visual attributes assigned to each of these four predictors. Thus, the aim of this study was to explore the influence of nine visual attributes derived from the four predictors of Kaplan’s matrix on people’s preferences in the context of urban parks. A discrete choice experiment was used to obtain responses from a sample of 396 students of Golestan University. Students randomly evaluated their preferences towards a set of potential scenarios with urban park images. The results of a random parameter logit analysis showed that all of the attributes of complexity (variety of elements, number of colors, and organization of elements) and one attribute each of coherence (uniformity), mystery (visual access), and legibility (distinctive elements) affect students’ choices for urban parks, while one attribute each of mystery (physical access) and legibility (wayfinding) did not affect the choices. Furthermore, the results indicated a preference for heterogeneity of the attributes. The findings of this study can provide instructions for designing parks.

Keywords: information processing theory; landscape design; multinomial logit model; predictors of preference (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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