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 autonomy-support; 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 techno-organizational 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.