Unlocking Perceived Algorithmic Autonomy-Support: Scale Development and Validation

Abstract

Platform workers' autonomy and agency are recurring themes in the study of the gig-economy where narratives purporting workers' autonomy and empowerment conflict with those alleging the control and marginalization of workers. While it has been said that promoting workers' agency can threaten the valuation of platform-based companies, the benefits of supporting workers' autonomy in traditional organizations are well-established. To understand such inconsistencies, it is necessary to measure perceptions of autonomysupport; yet, no validated instruments exist that can be used to measure workers' perceptions of algorithmic autonomy-support. To address this gap, we draw on the Theory of Self-Determination to reconceptualize the notion of autonomy-support for the technoorganizational phenomenon of algorithmically managed platform work. In doing so, we introduce a new construct, namely: Perceived Algorithmic Autonomy Support (PAAS). In this work-in-progress paper, we describe our current work in developing and validating a theoretically-based measure for PAAS. Preliminary results are provided.

Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper

“…One of the ways that power asymmetry can impact gig workers is through decreasing user agency (B41) , constraining their ability to act and restricting their autonomy (selecting jobs, modifying tasks) (Huang, 2023). This took several forms which had in common constraints on gig workers' daily work routines originating in the “operational choices embedded within a platform's architecture [that] implicitly shape platform workers' autonomy such that platforms can be either autonomy supportive or controlling” (Jabagi et al, 2021, p. 6494). In some cases, user agency is constrained by technological affordances of the platform that encourage workers' awareness of the precarity of gig work (Behl, Jayawardena, et al, 2022; Huber et al, 2022; Woodcock & Graham, 2019), through, for example, the possibility of being deactivated at any time, and increasing the difficulty of connecting with other workers (Jabagi et al, 2019).…”

“…Online platforms act as digital intermediaries matching demand with supply (Wang et al, 2021), primarily through “socio‐technical phenomenon known as algorithmic management, or management‐by‐platform” (Jabagi et al, 2021, p. 6492). As a socio‐technical system, the platform‐mediated gig economy brings together three main user groups—the people selling their labor through the platform, those who seek to purchase their labor, and those who own, run, and maintain the platform (Scholz & Schneider, 2016).…”

How algorithmic management influences worker motivation: A self-determination theory perspective.

“…Conversely, results of a study by Norlander et al (2021), conducted in a gig economy context, suggest that there is no significant difference between the intrinsic motivation of people working under algorithmic management or traditional management. However, there is still much to discover about motivation at work when supervised by technology (Jabagi et al, 2019(Jabagi et al, , 2021.…”