Tenure and Wage Trajectories in Online Gig Platforms: A Study of Marginalized Workers in India

How does participation in online gig platforms (OGPs) influence tenure and wages of marginalized workers in emerging economies such as India? Do all workers fare equally in such platforms, or there are important distinctions that shape experiences and outcomes of workers depending on market segments? We leverage rich archival data from a gig platform that operates mostly in the last mile logistics space in business-to-business segment in India to answer these important questions. The gig platform in this study employs a very large fraction of marginalized drivers with low levels of education, socio-economic status, and background. Our analyses of 13,594 number of drivers who registered on this platform from January 2018 to December 2019 documents three findings. First, we find that the gig economy platform in India achieved significant success to reduce churn and retain drivers, compared to the reported churn rates reported in developed economies. In our setting, roughly 20% of drivers stay active with the platform after twelve months, significantly higher than the 3% figure reported for Uber in the U.S. Second, we make a distinction among enterprise, and non-enterprise drivers. We find that enterprise drivers earn in aggregate 21.8% more than non-enterprise drivers per month. Our disaggregated analyses for such earning differences suggest that enterprise drivers have 2.39 more trips than non-enterprise drivers per month, but enterprise drivers earn 11 rupees less per hour than non-enterprise drivers. Finally, our findings suggest that enterprise drivers are 11.0% less likely to stay in this platform for more than six months than non-enterprise drivers. The Cox survival model indicates that enterprise drivers are 47.9% likely to leave this platform in April 2020 than non-enterprise drivers. We propose several explanations for the interesting and counterintuitive finding that enterprise workers who are likely to earn more in aggregate are less likely to stay on the platform using interviews of drivers. In particular, we propose time flexibility, task flexibility, and informational affordances as likely explanations. Our study provides important insights on wages and tenure of drivers in gig-economy platforms in emerging markets such as India that have a very different social context than developed markets, and we discuss implications for further research and practice.