Assessment of Crowdsourcing Task Multidimensional Relationship Model through Application Prototype

Abstract

Crowdsourcing is a process where a company outsources a task to a large group of the digital worker through an online platform. In Malaysia, the crowdsourcing ecosystem comprises of three key role players which are job providers, platforms and digital workers. The cycle starts when a job issued by the job providers. Then the platform advertises it to the digital workers who registered themselves in the system. The digital worker is an individual having different skills, knowledge, experiences and education level. Those who are interested and has the capabilities to complete it will pull the job based on the first come first serve basis. Basically, the aim of the platform is to ensure that the tasks are taken immediately and completed within a given time by the right skill of the digital worker. However, the platform does not have a structured mechanism to classify the type of task that would confirm the task match to the digital worker. Tasks are given based on digital worker skills and knowledge. A comprehensive mechanism to define and describe the task properties is important. Apart from enabling the determination of the remuneration value, it will also specify skill required and their level of competency. To solve that issues, this paper present the flow and process development and measured the relationships between the types of tasks and the digital workers in alluvial chart apps prototype. 76% of respondents agreed that the alluvial chart shows a comprehensive relationship.  As a conclusion, this study defined the comprehensive relationships among the variables will facilitate a platform to match between digital workers to the tasks.