Platformic Management, Boundary Resources for Gig Work, and Worker Autonomy - Jarrahi, Mohammad Hossein; Sutherland, Will; Nelson, Sarah Beth; Sawyer, Steve (Computer supported cooperative work, 2020)
We advance the concept of platformic management, and the ways in which platforms help to structure project-based or “gig” work. We do so knowing that the popular press and a substantial number of the scholarly publications characterize the “rise of the gig economy” as advancing worker autonomy and flexibility, focusing attention to online digital labor platforms such as Uber and Amazon’s Mechanical Turk. Scholars have conceptualized the procedures of control exercised by these platforms as exerting “algorithmic management,” reflecting the use of extensive data collection to feed algorithms that structure work. In this paper, we broaden the attention to algorithmic management and gig-working control in two ways. First, we characterize the managerial functions of Upwork, an online platform that facilitates knowledge-intensive freelance labor - to advance discourse beyond ride-sharing and room-renting labor. Second, we advance the concept of platformic management as a means to convey a broader and sociotechnical premise of these platforms’ functions in structuring work. We draw on data collected from Upwork forum discussions, interviews with gig workers who use Upwork, and a walkthrough analysis of the Upwork platform to develop our analysis. Our findings lead us to articulate platformic management -- extending beyond algorithms -- and to present the platform as a “boundary resource” to illustrate the paradoxical affordances of Upwork and similar labor platforms. That is, the platform (1) enables the autonomy desired by gig workers, while (2) also serving as a means of control that helps maintain the viability of transactions and protects the platform from disintermediation.