Nature in cities serves a multitude of purposes, one of which is that it provides citizens opportunities to recover from stressful daily urban life. Such stress recovering effects of nature can be experienced through urban green, which in urban planning and design contexts can be divided into large natural areas - urban green space - and small scale elements in urban streets: the urban greenscape. The current study aims at finding the extent to which various small scale natural elements in residential streets and their possible configurations influence citizens' preferences for those streets. The research was conducted through an online survey in four cities in the Netherlands (n = 4,956). It used stated choice methods in a virtual environment street design. The method yielded high quality data, indicating that the use of virtual environments and imagery is suitable for stated choice research in the built environment. The results show that especially trees very strongly influence preference, indicating they deserve more attention and space in cities. Grass, which is typically favored by local governments, and vertical green have the smallest effects in residential streets. Furthermore, the concept of greenscape intensity is introduced as the intensities of both the element and the configuration were found to be highly relevant. The results clearly show that the higher either of these intensities, the more likely a respondent will prefer the greenscape design. Furthermore, low intensity on the one can be compensated by high intensity on the other. With these results, urban design professionals and local governments can better trade-off the different aspects of costs versus positive effects of urban greenscape designs.
MULTIFILE
Policy makers are looking for effective ways to promote the adoption of electric vehicles (EVs). Among the options is the roll-out and management of charging infrastructure to meet the EV drivers’ refuelling needs. However, policies in this area do not only have a long-term effect on the adoption of EVs among prospective owners, they also have short-term impacts on the usage of public charging infrastructure among current EV owners and vice-versa. Presently, studies focusing on both effects simultaneously are lacking, missing out on possible cross-pollination between these areas. This study uniquely combines stated and revealed preference data to estimate the effect of particular policy measures aimed at EV adoption, on the one hand, and charging behaviour, on the other. Using a large dataset (1.7 million charging sessions) related to charging behaviour using public charging infrastructure in the Netherlands we quantify the effects of (i) daytime-parking (to manage parking pressure) and (ii) free parking (to promote purchase of EVs) policies on charging behaviour. To estimate the effects of these particular policies on EV purchase intentions, a stated choice experiment was conducted among potential EV-buyers. Results show that cross-pollinations between EV charging and adaptation policies exist and should be taken into account when designing policies for EV adoption.
MULTIFILE
Since 2016, it is mandatory for all future students at the department of Media, Information and Communication, to participate in a study choice test (SCT), prior their enrollment. However, the outcome is not binding and students are still entitled to enter the first year after receiving negative advice. With the help of a structural model, built for my PhD research, the predictive value of the SCT is tested by comparing the time it takes the students to finish all first year exams, their average grade point and attrition, against the results of the SCT. By using the structural model, various background variables are also measured, such as engagement, effort and commitment are also measured. By using the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA), the fit of the model is established. In addition, a comparison of the direct and indirect influence of the SCT will provide more knowledge about the correlations between the different variables, the SCT and ultimately student success.
