Evaluating the development and implementation of a profile-aware microtasking platform for crowdsourcing services

Crowdsourcing platforms have changed the assignment and completion of tasks from a known crowd to the anonymous crowd, which is the public. These crowdsourcing platforms allow organizations to focus on other tasks that need to be completed by a large crowd instead of the employees. However, many crowdsourcing platforms have not addressed challenges related to target audience with regards to task assignment, whereby the tasks are assigned to relevant people with appropriate core skills and qualifications. Our proposed microtasking platform from previous research is meant to address some of these challenges. This microtasking platform allows a micro-employer to design a task and assign it to be completed by a specific crowd of a specific skill and qualification. The purpose of this paper is thus to explore the proposed microtasking platform implementation, evaluating its task assignment improvements and task quality, as it was designed to improve the task assigning model and ensure better utilization of the crowd while preserving anonymity. The results obtained from this paper indicate the implementation concept from the proposed approach and revealed other shortcomings.