Comparing self-navigation and video mode in a choice experiment to measure public space preferences

3D dynamic visualization technologies are increasingly used in studying residents' preferences for urban planning and design scenarios. The techniques help concentrate respondent attention and improve the measurement quality of environmental preferences. However, little is known about differences in measurement quality between different 3D dynamic visualization modes. This paper applies two modes – a self-navigation mode and a video mode - in a virtual environment-based stated choice experiment with the aim of measuring neighborhood public spaces preferences. Based on data from 276 experiment participants and applying conditional and mixed logit techniques, we find no statistically significant differences in the model fit between the two modes. Out of six public space attributes, only one shows statistically significant differences in valuation between modes, namely ‘vertical green’. Our results suggest that the choice between video and self-navigation modes can be based on other (secondary) considerations, i.e., required sample size, respondents' experiences with navigation interfaces, the specific goals of the study or application in practice, and the costs and effort needed to conduct the experiment.