What Motivates Crowdsourcing Contributors? A Cross-Platform Comparative Analysis

The crowdsourcing business model has gained increasing popularity over the last years. When requesters (companies, institutions or individuals) crowdsource tasks, they place them on a platform where contributors can view and complete them. This study assesses what factors motivate contributors to complete crowdsourcing tasks and whether and to what degree these factors differ across crowdsourcing platforms. This study compares the results of quantitative surveys of contributors on two crowdsourcing platforms: RapidWorkers and Amazon Mechanical Turk. The results show that contributors on both platforms are motivated by payment and by indirect feedback from the job. However, contributors on RapidWorkers are also motivated by enjoyment-based factors, whereas contributors at Mechanical Turk are also motivated by community-based factors and delayed payoffs. Thus, the contributors at RapidWorkers tend to be more extrinsically motivated, while the contributors at Mechanical Turk tend to be more intrinsically motivated

What Drives the Drivers? A Qualitative Perspective on what Motivates the Crowd Delivery Workforce

Crowd delivery is an emerging concept that adds flexibility to the last mile toward the customer. One factor that can hinder the success of such platforms is the availability of drivers. Against this background, this work conducted 27 interviews with current DoorDash, Postmates, and Amazon Flex drivers to gain deep insights into the motivations of these workers. Based on the observations, a self-determination theory (SDT)-based research model is derived. Despite some similarities, we find that the motivations of crowd delivery drivers differ from other crowds. For practitioners, it is important to consider these particularities to reach the critical mass of drivers and attract to most effective workforce. Scholars can use the provided qualitative perspective as a basis for future deductive-confirmatory studies