High-quality employee motivation can contribute to an organization’s long-term success by supporting employees’ well-being and performance. Nevertheless, there is a paucity of research concerning how organizations motivate workers in non-traditional work contexts. In the algocratic context of the gig-economy, the purpose of this paper is to understand the role that technology can play in motivating workers.
Drawing on the self-determination theory, job-characteristic theory and enterprise social media research, this conceptual paper explores how the architecture of the digital labor platforms underlying the gig-economy (and the characteristics of jobs mediated through these IT artifacts) can impact key antecedents of self-motivation.
Combining theory and empirical evidence, this paper develops a mid-range theory demonstrating how organizations can support the self-motivation of gig-workers through the thoughtful design of their digital labor platforms and the integration of two social media tools (namely, social networking and social badging).
This paper answers calls for psychologically-based research exploring the consequences of gig-work as well as research studying the impacts of advanced technologies in interaction with work contexts on motivation. In theorizing around a large set of social-contextual variables operating at different levels of analysis, this paper demonstrates that individual-level motivation can be influenced by both task-based and organizational-level factors, in addition to individual-level factors.
The proposed theory provides novel insight into how gig-organizations can leverage widely accessible social media technology to motivate platform workers in the absence of human supervision and support. Theoretical and practical implications are discussed.
Jabagi, N., Croteau, A., Audebrand, L. and Marsan, J. (2019), "Gig-workers’ motivation: thinking beyond carrots and sticks", Journal of Managerial Psychology, Vol. 34 No. 4, pp. 192-213. https://doi.org/10.1108/JMP-06-2018-0255Download as .RIS
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