Multidimensional social support and gig workers’ performance in digital platforms: a chain-mediated model integrating emotion and autonomy

Digital gig platforms grant gig workers greater autonomy and flexibility, yet they also introduce challenges such as self-management and feelings of isolation, making social support increasingly vital within gig work. To address the existing gap in research regarding how social support influences gig work performance and its underlying mechanisms within emerging digital gig platforms, this study integrates Social Support Theory and Affective Events Theory to systematically examine the effects of platform organizational support, customer review support, and family emotional support on gig work performance. The findings reveal that platform organizational, customer review, and family emotional support indirectly impact work performance by affecting gig workers’ work engagement and burnout. Furthermore, the chain mediation analysis indicates that these three forms of support reduce burnout through enhanced work engagement, subsequently improving work performance. Notably, greater autonomy in work decision-making attenuates the positive effect of work engagement on work performance and lessens the negative impact of burnout on work performance. This study innovatively develops a chain mediation model based on gig workers’ emotional responses, systematically exploring the deep impact mechanisms of multidimensional social support and decision-making autonomy on gig work performance. These insights offer platform managers new theoretical perspectives and practical pathways for optimizing gig work environments and enhancing work performance.