Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6836149 | Computers in Human Behavior | 2018 | 39 Pages |
Abstract
New forms of employment centered on the completion of simple and atomized tasks, such as online microwork, raise the question of the possible gratifications that could be derived from such work when compared to more traditional labor arrangements. Our research presented here focuses on how microworkers construct meaningfulness, based on the accounts of workers on the crowdsourcing platform Amazon Mechanical Turk. We draw upon a relational job design perspective to explore why microworkers experience meaningfulness in their work. We found four sources of meaningfulness: rewards, self-improvement, moral, and social. These four sources vary in the degree to which they were internal or external in focus, and in their level of rationalization (concrete or abstract). This may explain why such types of employment are appealing despite a lack of organizational-support structures and points to the need to better understand cue provision in virtual, platform-enabled work settings.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Dominique Kost, Christian Fieseler, Sut I Wong,