In today’s rapidly expanding gig economy, companies are increasingly dependent on freelance workers whose availability they cannot reliably manage or predict. To stabilise their labour supply, many platforms turn to bonuses to attract contractors and keep them active. Yet new research led by Cornell University suggests that these incentives may not deliver the advantages firms expect. Instead, bonuses can create unintended drawbacks for both platforms and workers, with their impact varying markedly depending on labour conditions.
The study, “Bonus Competition in the Gig Economy,” published in Production and Operations Management, examines how different types of bonuses affect the delicate balance among platform profits, contractor incentives, and operational efficiency. Its central insight is that not all bonuses function in the same way, and that their success depends heavily on whether workers are plentiful or scarce. By exploring how platforms compete for labour, the research dismantles the assumption that financial incentives offer an uncomplicated means of improving workforce stability.
When the supply of gig workers is abundant, fixed bonuses—sometimes called subsidies—provide clear benefits for companies. These bonuses are embedded directly into contracts, giving platforms a tool for managing pay in a way that minimises unnecessary competition. Because firms do not need to outbid rivals for workers during periods of high labour availability, fixed bonuses help them maintain profits by allowing greater flexibility in structuring compensation. However, this flexibility tends to suppress workers’ earnings. As the researchers note, firms can adjust whether they pay more through bonuses or through commission, opting for whichever form costs them less, leaving contractors with reduced income overall.
The motivation for examining this dynamic arose from trends seen among major ride-sharing platforms such as Uber and Lyft, which began offering increasingly aggressive bonus schemes in recent years. According to Yao Cui, associate professor of operations, technology and information management, companies were “burning through” substantial sums to incentivise drivers, even as they reported significant financial losses. The apparent contradiction between high bonus spending and declining profitability prompted the researchers to investigate the underlying economic forces shaping these strategies.
Platforms like Uber, Lyft, TaskRabbit and freelancer.com operate within a highly uncertain labour environment. Contractors often work across multiple platforms, selecting whichever offers the most appealing job at a given moment. Bonuses, therefore, serve as a means of persuading workers to favour one platform over another. Yet both fixed and contingent bonuses introduce their own complications. While they can temporarily boost worker participation, they also reshape behaviour in ways that may not align with operational efficiency or long-term profitability.
The study uses game-theory modelling to compare bonus strategies, showing that the benefits of fixed bonuses disappear when labour is scarce. In such conditions, contingent bonuses—rewards given only after consistent service over time—prove more effective. These incentives help firms attract workers initially and then retain them long enough to ensure reliability. Yet contingent bonuses also create inefficiencies: workers motivated to maintain their eligibility may accept suboptimal tasks, such as jobs requiring long pickup times, to stay on track for the payout. This behaviour weakens the precision of demand matching, undermining the platform’s operational effectiveness.
Taken together, the findings reveal that bonuses are far from a one-size-fits-all solution. They reshape labour markets, influence worker behaviour, and alter platform competitiveness in complex ways. Rather than offering a guaranteed advantage, bonuses introduce trade-offs that both firms and workers must navigate carefully within the evolving gig economy.
More information: Li Chen et al, Bonus Competition in the Gig Economy, Production and Operations Management. DOI: 10.1177/10591478251389408
Journal information: Production and Operations Management Provided by Cornell University