The double-edged sword effect of algorithmic transparency: An empirical study of gig workers’ work disengagement under algorithmic management

Abstract

To mitigate algorithmic management's negative impacts on gig workers, gig economy platforms have begun to make their algorithms transparent. Prior studies have mostly focused on how the intensity of algorithmic management influences workers’ job outcomes while have neglected algorithms’ transparency features. To fill this gap, our study draws on the job demands–resources (JD-R) model by viewing algorithmic management as a job demand and conceptualizing purpose and process transparency as different job resources. The empirical findings show the direct positive effects of algorithmic management, purpose and process transparency on challenge appraisal, which in turn alleviate gig workers’ work disengagement. Interestingly, empirical results demonstrated that purpose and process transparency exert different moderating effects on the relationship between algorithmic management and challenge appraisal: While purpose transparency strengthens the positive relationship, process transparency weakens it. Our results enrich prior information systems research on algorithmic management and transparency as well as on the JD-R model.