Recruiting cryptocurrency users for large-scale quantitative studies is known to be challenging due to the unknown geographic distribution, more pronounced preferences for anonymity, and a lack of reliable, non-intrusive mechanisms for confirming the individual’s status of being a cryptocurrency investor. Therefore, such common strategies used to recruit research subjects as using commercial panel or crowdsourcing services (e.g., Amazon Mechanical Turk, Prolific etc.) or surveying students, staff etc. have serious limitations and biases in cryptocurrency research.
The aim of this thesis is to develop a set of screening questions that can be used in online surveys to assess knowledge and discriminate between respondents with and without experience with cryptocurrencies. The questions need to be easy and quick to answer for individuals who own(ed) a cryptocurrency, but difficult to answer correctly for those who have no cryptocurrency experience. The designed questionnaire needs to be tested and evaluated for its efficacy in a real-world empirical study. The student may approach this problem using both qualitative and quantitive research methods (e.g., by first identifying and pre-testing questionnaire ideas in semi-structured interviews with cryptocurrency owners and then testing screening questions on a larger sample of respondents).
This thesis is targeted at students studying in the Information Systems program.