Search results

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’.

Effects of local policies on charging behaviour of Electric Vehicle owners and on purchase intentions of prospective owners

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.

The predictive value of a study choice test

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.

Policy effects on charging behaviour of electric vehicle owners and on purchase intentions of prospective owners: Natural and stated choice experiments

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.

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.