Complex Workplace Incentives Can Actually Push Employees to Work Harder, According to New Research

Designing pay and bonus systems at work is often treated as a careful balancing act. Too simple, and employees may game the system. Too complex, and it might confuse everyone involved. But new research from the Cornell SC Johnson College of Business suggests something surprising: in certain cases, complex incentive systems can actually lead to higher effort and better outcomes, even when workers don’t fully understand how those systems work.

The study takes a deep look at how real employees respond to complicated pay structures, especially those where today’s performance affects tomorrow’s targets. While economic theory often assumes workers behave in perfectly rational ways, this research shows that human limitations, confusion, and cognitive differences play a much bigger role than previously thought.

Who conducted the research and where it was published

The research was led by David Huffman, the Ashley Family Professor in Behavioral Economics at Cornell’s Samuel Curtis Johnson Graduate School of Management, along with Collin Raymond, an associate professor at the same school. They were joined by Johannes Abeler, a professor of economics at the University of Oxford.

Their paper, titled Incentive Complexity, Bounded Rationality, and Effort Provision, was published in the American Economic Review, one of the most influential journals in economics. The findings are based on a mix of real-world workplace data, long-term field experiments, and controlled online experiments, making the conclusions especially robust.

Why incentive systems often fail in practice

Most companies use incentive schemes like bonuses, performance-based pay, or productivity targets to motivate employees. In theory, these systems should encourage people to work harder and smarter. In reality, they sometimes backfire.

One well-known problem is the ratchet effect. This happens when workers realize that performing well today will raise expectations tomorrow. If employees expect future targets to become tougher as a result of their current effort, they may deliberately hold back. Over time, this can reduce productivity and make incentive systems ineffective or even harmful.

Economists have long assumed that workers will anticipate these dynamics and adjust their behavior accordingly. But that assumption relies on workers clearly understanding how the incentive system works—and that’s where complexity enters the picture.

The role of complexity in incentive design

Modern incentive systems are rarely simple. They often involve changing pay rates, shifting performance benchmarks, group-based targets, random adjustments, and long-term consequences that are hard to track. According to the researchers, this complexity can make incentives opaque, meaning workers fail to fully grasp how their actions today affect their future pay or targets.

Rather than carefully optimizing their effort based on these rules, many workers simply ignore certain aspects of the system. Counterintuitively, this lack of understanding can sometimes benefit both the employer and the employee.

The researchers set out to test exactly how workers respond to these complex, dynamic incentives—and whether confusion changes behavior in meaningful ways.

Field experiment one: Individual ratchet effects

In the first major field experiment, the research team partnered with a large warehouse company and studied newly hired workers. These employees were assigned to different pay schemes.

Some workers faced fixed performance targets, while others were placed under a system where their future targets adjusted based on their past performance, creating a classic ratchet effect. Standard economic theory would predict that workers in the ratchet system would reduce effort once they realized their performance today would raise future expectations.

That didn’t happen.

The researchers observed only a 0.1% drop in effort, a change so small that it was statistically insignificant. In practical terms, workers did not meaningfully slow down at all. This suggested that many employees either did not understand the dynamic nature of the incentives or did not factor it into their decisions.

Field experiment two: Group-based incentives

The second field experiment made the system even more complex. In this setup, workers’ performance affected not only their own future targets but also the targets of their coworkers. This introduced social pressure and peer effects, which might be expected to make workers more attentive to how the system works.

Even here, the response was modest. Over a period of 10 months, worker effort declined by just 1%. Despite having time to learn and observe the system, employees still did not strongly react to the dynamic incentives embedded in their pay structure.

Once again, complexity appeared to mute strategic behavior rather than amplify it.

Online experiments and the role of cognition

To understand why workers behaved this way, the researchers conducted online experiments where incentive systems were carefully recreated in a controlled environment. Here, they could directly test how people respond when incentives are framed differently.

The results were clear. When incentives were explained in simple, concrete monetary terms, participants adjusted their effort in predictable ways. When the same incentives were described using abstract concepts like “target rates”, or when random elements were introduced, participants often failed to respond at all.

The study also measured participants’ cognitive ability using the Cognitive Reflection Test (CRT). Individuals with higher CRT scores were more likely to notice and understand complex incentives. Those with lower scores frequently overlooked or misunderstood them, even when asked directly about how the system worked.

Why ignoring incentives can increase effort

Using economic models, the researchers showed that when workers fail to account for future consequences, they may end up working harder than they would if they fully understood the system. In other words, bounded rationality—the fact that humans have limited attention and processing ability—can lead to higher effort under certain incentive schemes.

Interestingly, firms that recognize this behavior may be willing to offer more generous incentive contracts, knowing that workers are unlikely to exploit the system strategically. This creates a situation where both sides can potentially benefit, even though the system itself is not fully transparent.

What this means for employers

For employers, the findings challenge the assumption that simpler is always better. While overly complex systems can certainly cause frustration, complexity can also reduce strategic behavior like gaming or effort withholding.

That said, complexity is not universally beneficial. The effects depend on the type of incentive, the workforce, and the level of understanding among employees. What works in a warehouse setting may not translate directly to other industries.

Implications for policymakers and fairness concerns

For policymakers, the research raises deeper questions about fairness, transparency, and worker protection. Simplifying contracts might improve understanding, but it could also reduce productivity or eliminate mutually beneficial arrangements.

The study highlights the importance of considering who the workers are, not just how the incentive system is designed. Cognitive ability, education, and experience all influence how people respond to pay structures.

A broader lesson about human behavior at work

At its core, this research challenges the idea that workers always behave like perfectly rational calculators. Instead, it shows that real-world behavior is shaped by confusion, shortcuts, and limited attention. Sometimes, those human imperfections lead to unexpected positive outcomes.

As companies continue experimenting with performance-based pay, understanding how workers actually perceive incentives may matter just as much as the incentives themselves.

Research paper:
Abeler, J., Huffman, D., & Raymond, C. (2025). Incentive Complexity, Bounded Rationality, and Effort Provision. American Economic Review.
https://www.aeaweb.org/articles?id=10.1257/aer.20230751