The Value of Flexible Work: Evidence from Uber Drivers

By M. Keith Chen, Judith A. Chevalier, Peter E. Rossi, Emily Oehlsen. Journal of Political Economy, 2019

428 citations recorded by the source corpus.

Technology has facilitated new, nontraditional work arrangements, including the ride-sharing company Uber. Uber drivers provide rides anytime they choose. Using data on hourly earnings and driving, we document driver utilization of this real-time flexibility. We propose that the value of flexibility can be measured as deriving from time variation in the drivers’ reservation wage. Measuring time variation in drivers’ reservation wages allows us to estimate the surplus and labor supply implications of Uber relative to alternative, less-flexible work arrangements. Despite other drawbacks to the Uber arrangement, we estimate that Uber drivers earn more than twice the surplus they would in less-flexible arrangements.

Subfields: Automotive Engineering, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/7ad6ba488ea06997fcd0d7f3350abbe7097b04b1

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Citations in the corpus

Marketing in the Sharing Economy (2019, background): “Likewise, Uber provides the benefits of flexible work arrangements (Chen et al. 2017) and improved resource usage efficiency (Cramer and Krueger 2016) and may increase consumer welfare (Cohen et al. 2016).”
What Do Platforms Do? Understanding the Gig Economy (2020, background): “These forms of autonomy are widely advertised by the platforms, and surveys show that workers place high value on them and on the ability to be their own boss (Chen et al. 2017, Forde et al. 2017, Hall & Krueger 2018, Manyika et al. 2016, Pew Research Center 2016, Schor 2020).”
Surge Pricing Solves the Wild Goose Chase (2017, neutral): “More distantly related is work on driver labor supply (Chen and Sheldon, 2015; Hall and Krueger, 2016; Hall et al., 2017b; Chen et al., 2017; Angrist and Caldwell, 2017; Cook et al., 2018) and rider demand (Cohen et al.”
Uber happy? Work and well-being in the ‘Gig Economy’ (2019, methodology): “, for night-shift driving) in shaping the variation in hourly payouts and capacity utilization among Uber drivers (e.g., Cramer and Krueger, 2016; Chen et al., 2017; Cook et al., 2018), we leave a detailed analysis of the determinants of individual productivity among London drivers for future work.”
Ridesourcing systems: A framework and review (2019, methodology): “…and Wang, 2018a, 2018b ); auction pricing for ridesourcing ( Asghari et al., 2016; Asghari and Shahabi, 2017 ); dynamic pricing with dispatching ( Chen et al., 2017b ); pricing with reservation cancellation ( He et al., 2018 ); and surge pricing with strategic timing and information asymmetry (…”
Frictions in a Competitive, Regulated Market: Evidence from Taxis (2015, background): “They develop and estimate a model that 8See, for instance, Chen et al. (2017), who discuss the value of flexibility for Uber drivers.”
Flexible employment relationships and careers in times of the COVID-19 pandemic (2020, neutral): “Those who advocate gig work claim that it provides career opportunities by providing resources like greater work autonomy and a high potential for work-nonwork integration (Chen, Rossi, Chevalier, & Oehlsen, 2019) , resulting in more boundaryless, individualized, and whole life careers (Ashford, Caz”
The Effect of Home-Sharing on House Prices and Rents: Evidence from Airbnb (2021, neutral): “Such literature covers a wide array of topics, from the effect of the sharing economy on labor market outcomes (Chen et al., 2017; Hall and Krueger, 2017; Angrist et al., 2017), to entry and competition (Gong et al., 2017; Horton and Zeckhauser, 2016; Li and Srinivasan, 2019; Zervas et al., 2017),…”