Gig Workers and Performance Pay: A Dynamic Equilibrium Analysis of an On-Demand Industry
In many online product markets, firms manufacture and supply products almost immediately after receiving orders. Thus, firms need to ensure that their workers satisfy product demand, which can vary over time, in a cost-effective way. This paper develops and estimates a dynamic equilibrium model of firm and worker behavior in an "on-demand" production context. The firm solves a dynamic discrete choice cost minimization model in which it faces uncertainty about future product demand and workers' productive capacity. The firm chooses to employ two types of workers – gig workers and permanent workers – and it sets parameters of a compensation scheme that is a mix of salary and performance-based incentives to elicit worker effort. Heterogeneous workers solve a daily effort choice problem given the compensation scheme offered by the firm. I estimate the model and perform an out-of-sample validation of the model using panel data from an online, global manufacturer that produces customized items. The data include detailed measures of workers’ output and output quality under varying compensation schemes. I find that gig workers and permanent workers exhibit different production patterns and that gig workers are much more responsive to incentive pay. I embed the workers' optimal effort decisions into the firm's dynamic cost minimization problem and use simulation methods to derive optimal labor force composition and compensation schemes. I show that varying the compensation scheme over time and using a mix of gig and permanent workers provides the flexibility that the firm needs to effectively operate in an on-demand customized production environment.
Labor Economics, Health Economics, Personnel Economics, and Applied Econometrics.