Flexing and floundering in the on-demand economy: Narrative identity construction under algorithmic management

The real-time and carry-over effects of injustice on performance and service quality in a ridesharing driver scenario

The nature of gig work and its growth have important implications for organizational justice theory. Aspects of gig work, including the transactional compensation arrangement, strict algorithmic rating system, and power asymmetry between drivers and customers, have implications for understanding how dimensions of distributive, informational, and interpersonal injustice manifest and impact job performance in the gig context. An understanding of this topic can inform justice theory more broadly and help explain inconsistent findings in the literature. Here, we report the results of two studies examining the unique effects of these respective dimensions of injustice on emotions and, ultimately, the driving performance and service quality in a ridesharing service context. In Study 1, we modeled the passenger-driver interaction of the ridesharing context using a driving simulator in a laboratory setting to differentiate the real-time and carry-over effects of specific dimensions of injustice. The results from 99 participants showed that perceptions of interpersonal injustice increased anger and unhappiness during the ride, in turn impairing driving and service performance. Antecedent-focused emotion regulation strategies (ERS) reduced felt unhappiness. Moreover, unexpectedly, perceived distributive injustice as caused by the customer rating had opposite (direct versus indirect) effects on service performance in the subsequent ride. Study 2 was an online simulation vignette scenario with 294 participants. The results replicated the findings of Study 1 and revealed two moderators of the unexpected distributive justice-performance relationship.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-022-04215-3.