Zoekresultaten

Preference for different urban greenscape designs: A choice experiment using virtual environments.

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.

Visualizations and virtual reality in choice behavior research

A Structural Model For Student Success And The Predictive Value Of A Study Choice Test

For my PhD research I build a structural model to predict student success. Initially to show the influence of social media use by first year students in higher education. However, for this research I use the model to investigate the predictive value of a student choice test. This test is mandatory for all students prior to their enrolment at the Amsterdam University of Applied Sciences. In this study two of the Institutes (Communication and Creative Business/Media, Information and Communication) of the Faculty of Digital Media and the Creative Industries participated with a first year enrollment in the year 2017 of 1010 students (respectively of 327 and 683), and in 2018, 1193 students (respectively 225 and 968). This study choice test involved an assignment that the student-to-be had to do at home and bring to the Institute when they took part in the second half of the study choice test. This second half involved an exam in topics central to the curriculum, a Dutch language test and all students had a final meeting with a teacher where they were given a positive or negative advice. Because of the large number of students, a substantial number of teachers and resources were used for this test. In order to see the pros and cons of the test, the predictive value was tested along with other variables which are proven to have a predictive value on student success. The best proven variables from Tinto’s theory were included, based on previous studies. The central variable in Tinto’s study is ‘satisfaction’ (which in other research is revert to as ‘engagement’ of ‘belonging’), consisting originally of a vast number of manifest variables. By using a fraction of those variables, I simplified the model, so it was an easier tool to use for teachers and management and in the meantime, avoiding the capitalization of chance. The smaller latent variable ‘satisfaction’ was tested using principal component analysis to prove the manifest variables where in fact representing one latent variable. Cronbach’s alpha and Guttman’s lambda-2 then provided the internal consistency and reliability of the variable. Along with ‘satisfaction’, the model included different background variables (gender, prior education, ethnicity), commitment and effort, expected progress and of course study success. This was measured by the time it takes a student to finish all first year exams and the average grade point (GPA). SPSS AMOS was used for testing the fit of the model and showed reasonable values for 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 advice from the study choice test and the scores were tested in the model to uncover if there was a significant difference. Furthermore, the influence of all variables in the model were compared for their influence on study success.

Decision-makers self-servingly navigate the equality-efficiency trade-off of free partner choice in social dilemmas among unequals

Cooperation is more likely upheld when individuals can choose their interaction partner. However, when individuals differ in their endowment or ability to cooperate, free partner choice can lead to segregation and increase inequality. To understand how decision-makers can decrease such inequality, we conducted an incentivized and preregistered experiment in which participants (n=500) differed in their endowment and cooperation productivity. First, we investigated how these individual differences impacted cooperation and inequality under free partner choice in a public goods game. Next, we calculated if and how decision-makers should restrict partner choice if their goal is to decrease inequality. Finally, we studied whether decision-makers actually did decrease inequality when asked to allocate endowment and productivity factors between individuals, and combine individuals into pairs of interaction partners for a two-player public goods game. Our results show that without interventions, free partner choice, indeed, leads to segregation and increases inequality. To mitigate such inequality, decision-makers should curb free partner choice and force individuals who were assigned different endowments and productivities to form pairs with each other. However, this comes at the cost of lower overall cooperation and earnings, showing that the restriction of partner choice results in an equality-efficiency trade-off. Participants who acted as third-parties were actually more likely to prioritize inequality reduction over efficiency maximization, by forcing individuals with unequal endowment and productivity levels to form pairs with each other. However, decision-makers who had a ‘stake in the game’ self-servingly navigated the equality-efficiency trade-off by preferring partner choice interventions that benefited themselves. These preferences were partly explained by norms on public good cooperation and redistribution, and participants’ social preferences. Results reveal potential conflicts on how to govern free partner choice stemming from diverging preferences ‘among unequals’.

The pros and cons of a study choice test

First year undergraduate students at the Amsterdam University of Applied Sciences of two different departments, were asked to join self-reported surveys in two succeeding years. Along with background variables, effort and commitment, the surveys asked elements of engagement. The later was analysed with factor analysis. The data of the surveys together with the results of the exams from the first year, were investigated to find out if the mandatory study choice test (SCT) taken before entering the faculty, had any predictive effect on their success. Not only basic statistical analysis like correlation was performed, but also more advanced analysis such as structural equation modelling (SEM) was used to uncover the value of the SCT. After a model was built, the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA), were used to determine the fit of the model. By comparing the influence of the variables on the SCT, the benefits of the latter will be determined and ultimately enhance the knowledge about influences upon student success in higher education.

Activities as the critical link between motivation and destination choice in cultural tourism.

Purpose: This study aimed to determine the motivations of a select group of South Africans in terms of their potential engagement with cultural tourism; more specifically, the study set out to show whether these motivations influence the cultural activities that the tourists want to participate in and whether their interest in specific cultural activities determines their destination choices. Furthermore, the mediating role of activities in the relationship between cultural motivations and destination choice was also assessed. Design/methodology/approach: An online panel survey collected responses from 1,530 potential cultural tourists across South Africa. Hypotheses were tested, using structural equation modelling. Findings: The results show that tourists' motivations for cultural tourism influence their likelihood of participating in specific cultural activities. Cultural tourism is shown to be influenced by more than learning and includes entertainment, relaxation, novelty and escape dimensions. There also seems to be a difference in the activities engaged in by destination type. For example, tourists likely to take part in indigenous cultural tourism activities are more likely to do so at hedonic destinations. Practical implications: This paper contributes to the understanding of cultural tourism activities, aiding destinations in attracting cultural tourists. Destinations need to develop activities that match visitor motivations, increase satisfaction and encourage visitors to return. Originality/value: The paper increases the understanding of cultural tourism in South Africa and underlines the importance of communities in providing distinctive tourism activities. The study also has an important social dimension, highlighting the role of social status in cultural tourism consumption and destination selection.