This article uses an interesting combination of quantitative and qualitative methods to shed light on decision-making among crowdworkers. The quantitative data demonstrated strong correlations between willingness to perform tasks and socio-economic status of the destination, while the qualitative data provided rather direct responses that implied causality. As far as the position of crowdsourcing on the tool-science spectrum, I would place it firmly on the tool side, because it’s applications are so purely commercial, and the use of the technology doesn’t contribute in itself to the furthering of geographic knowledge. This study’s focus on decision-making reminds me of my proposed masters’ research, which involves a discrete choice experiment. Choice experiments identify several variables that are of importance to interviewees in making a certain decision. The variables are then combined at different values in order to make several scenarios to present to the interviewee, after which they are asked for their preference. The interviewer can then infer which of the variables was the most important to the decision. Applying such a method could be interesting for a study like this, because several attributes of the destination neighborhoods are distinct but interrelated, e.g. socio-economic status, crime and race. The qualitative results implied that crime was an attribute about which respondents were vary open in citing as a decision driver. By contrast, the extent to which socio-economic status and race are decision drivers would be quite difficult because many people would feel ashamed to say so openly. In this case a choice experiment might not get around this problem, though choosing neighborhoods solely on the basis of race and asking whether the person would be willing to serve that neighborhood could be a viable method. Answering these questions would have important implications for the ethical value of the sharing economy.