When Competition Between Coworkers Leads to Unethical Behavior

When competition is fierce, the need to win can blind us to ethical considerations. It’s a potential problem in all kinds of areas: colleagues who have a strong rivalry at work, managers who need to make their numbers for the quarter, even political parties that spend campaign funds to attract votes. A common theme in these situations is that there are only a few winning slots — and maybe just one — with massive stakes in terms of money, advancement, and fame. New research finds that performance evaluation schemes based on peer comparison can encourage unethical behavior. In several studies, the researchers tested how and when these comparisons influence the likelihood of unethical choices.

Many of us love competition and, more important, winning. Competition drives us toward our goals and motivates us to improve our performance, while the prestige and power that come from winning can provide a powerful morale booster. What’s more, winning increases testosterone and dopamine hormones, which, in turn, increases our confidence and willingness to take risks, and thus our chances of further success.

At the same time, the need to win can blind us to ethical considerations. It’s a potential problem in all kinds of areas: colleagues who have a strong rivalry at work, managers who need to make their numbers for the quarter, even political parties that spend campaign funds to attract votes. A common theme in these situations is that there are only a few winning slots — and maybe just one — with massive stakes in terms of money, advancement, and fame.

What’s often driving this fierce competition is the knowledge that our performance is being assessed not in absolute terms but in comparison with others’. In the workplace, such “rank-and-yank” methods — also known as the vitality curve, forced rankings, and stacking systems — are regularly used to judge performance, whereby, say, the top 20% of employees are categorized as high performers and the bottom 10% face redundancy. Similarly, the bell-curve grading in an MBA classroom ensures that students are categorized and graded relative to peers, without considering their overall performance.

In our research, recently published in the journal Human Resource Management, we found that performance evaluation schemes based on peer comparison can encourage unethical behavior. In one study, we asked 164 MBA students to read a hypothetical scenario (based on a true story) about an investment banker facing an ethical dilemma, and to estimate the likelihood that this banker would indulge in unethical behavior. The students were randomly assigned to three conditions for how the banker would be paid: a fixed salary with no bonus; a fixed salary with a bonus tied to the banker’s number of trades; and a fixed salary with a bonus tied to the banker’s performance relative to his peers. (For more details of this study and the ones below, see the sidebar “Our Studies.”) Our results showed that the students in the relative performance condition expected the banker to be more likely to behave in an unethical manner.

Study 1
We asked 164 MBA students to (1) read a hypothetical scenario about an investment banker, Sam, who faced an ethical dilemma and (2) estimate the likelihood that he would indulge in unethical behavior. The scenario was motivated by the true story of an investment banker whose trading practices ultimately drove his bank to insolvency. According to the scenario, Sam was one of the key traders for his bank’s recently launched operations in Singapore. He had a successful trading career at the bank’s London operations: In the past two years his trades made millions, accounting for 8% of the bank’s annual profit. The bank had hired 10 other traders in its Singapore office, all of whom handled independent accounts without interfering or knowing much about the others’ work. Recently, the scenario continued, Sam had noticed that he had a big trading loss on one of the accounts, costing his bank $100,000. Sam was thinking about what he should do, as performance appraisals were coming soon. Now, Sam also managed the bank’s error account. Most banks have an account like this, which is used to account for genuine trading mistakes. Sam could use the error account to hide his losses without the knowledge of the bank. Of course, this is illegal and unethical.

Participants were randomly assigned to one of the three conditions that differed in the performance management system applied to Sam: control (a fixed salary of $300,000 with no additional bonus possibilities), absolute (a fixed salary of $300,000 with additional bonus related to the total profits from his trades), and relative (a fixed salary of $300,000 with additional bonus based on his performance as compared with the other traders’). We found that the average likelihood of using the error account in the relative performance condition was significantly higher than that in the absolute and the control conditions. Our results showed that the participants under relative performance evaluation expected the banker to be more likely to behave in an unethical manner.

Study 2
We investigated people’s ethical behavior in self-reporting their performance. We invited 160 participants of U.S. origin on Amazon’s Mechanical Turk online platform to participate in a 10-question IQ quiz. They were asked to self-verify their answers and report their score to us. Again, participants were randomly assigned to one of the three groups that differed in their evaluation and compensation schemes: control, whereby all participants were given a fixed participation fee of 10 cents irrespective of their performance; absolute, with participants having a bonus possibility based on the number of correct answers they reported; and relative, where only the top scorers were to be rewarded with a bonus. Specifically, in the absolute condition, participants were informed that of the approximately 50 people who were participating, 10 of them would be randomly selected and we would pay an additional 10 cents for every point they scored. In the relative condition, participants were informed that of the approximately 50 people who were participating, at the end of the study we would award $1 to the 10 highest scorers based on their final scores. We deliberately kept the monetary incentives close to zero in order to study the effects of evaluation and comparisons instead of money and rewards.

The results surprised us. Participants averaged 3.39 correct answers (out of 10 questions) with no significant differences between the three experimental conditions. However, most participants — 85.6% (137 out of 160) of our sample — overreported their performance. Moreover, both the incidence and magnitude of overreporting was higher in the relative performance condition than in the other two conditions. 100% (56 out of 56) of participants in the relative performance condition overreported their performance, which was significantly greater than the 86% (44 out of 51) in the absolute performance condition and the 70% (37 out of 53) in the control condition. The self-reported score in the relative performance condition was also significantly greater than in the absolute performance condition, as well as in the control condition. In short, the competitive pressure and comparison seemed to encourage rule breaking.

Study 3
Again on Mechanical Turk, we invited 184 participants of U.S. origin to participate in a decision-making scenario. Participants assumed the role of a university professor who is close to tenure evaluation and is being considered for nomination to a prestigious national congress. The professor has a manuscript under review with a top journal, and its publication is key to both the tenure and nomination decisions. The data analysis for the manuscript had not provided desirable results and the professor is tempted to manipulate the data. Participants were asked to provide their likelihood of manipulating data on a scale of 0 (not at all) to 100 (certainly). They were randomly assigned to one of two conditions: control and consequential reflection. The only difference between the conditions was that participants in the consequential reflection condition were asked to list possible consequences (both positive and negative) of their decision before providing their likelihood judgment. We found that the average likelihood of data manipulation in the consequential reflection condition was significantly lower than in the control condition. We replicated our findings with another study, conducted with 142 MBA students who, instead of assuming the role of the professor, were asked to assess the likelihood that the academic would indulge in such data manipulation.

Further Studies
Across three additional experiments, we found that taking a moment to reflect helped to put short-term benefits and long-term potential losses into perspective. For example, in the consequential reflection study described above, after providing their likelihood judgment, all participants were asked to rate the magnitude of both the perceived risks and the perceived benefits involved in the situation they faced, using a scale of 0 (low) to 100 (high). For each participant, we combined these assessments to construct an assessment index. Our results showed that participants in the consequential reflection condition perceived significantly higher risks vis-à-vis benefits than those in the control condition.

In another study, we investigated people’s ethical behavior in self-reporting their performance. Using Amazon’s Mechanical Turk platform, we invited 160 participants of U.S. origin to participate in a 10-question IQ quiz. They were asked to self-verify their answers and report their scores to us. Again, participants were randomly assigned to one of three compensation groups: a fixed participation fee of 10 cents, irrespective of performance; a fixed fee with a bonus based on the number of correct answers they reported; and a fixed fee with a bonus for only the top scorers. The results surprised us. The groups didn’t differ much in performance, and most participants overreported their scores. But both the incidence and the magnitude of overreporting was highest in the third group, the one in which only top performers received a bonus. Notably, every single person in the group overreported their score. In short, the competitive pressure and the comparisons encouraged rule breaking.

Organizations continue to experiment with and debate the pros and cons of comparison-based performance management systems. In recent years, for example, Yahoo endorsed them, while Microsoft abandoned them. One thing is clear, though: Relative comparisons are widespread and here to stay. Given that, what can be done to limit possible temptations of ethical breaches that accompany such competitive comparative settings?

We propose a subtle and simple intervention we call consequential reflection: prompt individuals to reflect on the positive and negative consequences of their decisions. In another study of ours, participants who took a moment to think and write down such possible consequences were less willing to act unethically. Again on Mechanical Turk, we invited 184 participants of U.S. origin to participate in a decision-making scenario. Participants assumed the role of a university professor, close to tenure evaluation, who had a manuscript under review with a top journal. The data analysis for the manuscript had not provided desirable results, and as a result the professor was tempted to manipulate the data. Participants were asked how likely it was that they would manipulate the data, with some participants being prompted to consider the consequences. We found that those participants were significantly less likely to take unethical action.

Why would this kind of prompt be effective? Research on the human mind tells us we run on autopilot much of the time. The pressures of our jobs mean we often don’t take time to pause and reflect. Therefore, our intuitive, habitual behaviors take over. In matters of ethics, this can lead to a self-centered, “me-first” attitude, focused on the immediate benefits for ourselves and ignoring the long-term consequences of ethical lapses.

To put this idea into practice, we propose that leaders try the following:

We believe the strengths of our intervention are that it’s effective, cheap and easy to implement, and unlikely to provoke strong objections from people. As our research shows, simple psychological interventions can be a valuable part of an organization’s tool kit for creating an ethical culture.

Kriti Jain is assistant professor in organizational behavior and human resources at IE Business School. Her research focuses on judgment and decision making.

When Competition Between Coworkers Leads to Unethical Behavior

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