Crowdsourcing and Digital Workforce in the Gig Economy
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ItemWhat Drives the Drivers? A Qualitative Perspective on what Motivates the Crowd Delivery Workforce( 2020-01-07)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.
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ItemPerceived Organizational Support in the Face of Algorithmic Management: A Conceptual Model( 2020-01-07)Organizational support theory proposes that employees develop global beliefs concerning the degree to which an organization values their contributions and cares about their well-being. These beliefs, known as perceived organizational support (POS), are related to a number of positive employee outcomes, including: job satisfaction, work effort, performance, etc. Three categories of POS antecedents have been recognized in the literature: perceived supervisor support; fairness of organizational procedures; and organizational rewards and job conditions. In this paper, we explore these antecedent categories in the gig-work context where organizations replace human managers with algorithmic management practices and data-driven procedures. In doing so, we develop a new conceptual model that centers on the role that a gig-organization’s algorithm plays in engendering POS by promoting perceptions of fairness and support, and by managing the provision of performance-based rewards. Contributions and future research avenues are discussed.
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