The challenge in some organizations is not taking enough risks; Employees are extremely cautious and reluctant to try new things, even when they would be beneficial to the organization on average. In other organizations, the problem is taking excessive risks. risky behavior spreads throughout the organization until something goes wrong. From poor financial decision-making to unethical behavior, excessive risk-taking can sink a company.
So how does risk-taking spread through an organization? The extreme uncertainty surrounding Covid-19 has created a unique environment for studying the issue. Since the beginning of the pandemic, people around the world have simultaneously questioned what behaviors are appropriate to reduce both individual and societal risk of exposure to the virus. This allowed us to examine how canonical theories of learning work together to promote risk-taking.
In the study of human behavior post-blocking and pre-vaccination, we document a phenomenon we call “risk creep.” This refers to an increased tolerance for risky behavior that may result from near misses, or events that could have led to a negative outcome, but, incidentally, did not.
Our research elucidates two main pathways through which risk-taking spreads: social learning and experiential learning or trial and error. Companies need to understand both and how they potentially interact to encourage or discourage risky behavior. The more managers understand what drives employee behavior, the better they can predict it. Ultimately, it can help them anticipate consequences so they can proactively communicate with employees and more appropriately measure risk.
Theories of Risk Acceptance
Decades of work on social norms show that people are often influenced observing what others are doing. These observations help people understand that behavior are common and which are likely to get them social rewards or punishment. They are often considered sufficient for new learning behavior. Researchers call inferences based on observing others “social learning.”
As any manager knows, employees respond less to what they are told is appropriate behavior and more to what they see others doing in the workplace. In strong cultures, these two go hand in hand, reinforcing each other. Southwest Airlines, for example, instructs its flight attendants to take risks for fun, but new flight attendants really learn how to behave by watching their colleagues with safety announcements or playing practical jokes. By observing others, they learn the appropriate level of risk to try something new.
But what happens when there are no obvious cues from the social environment? This occurs in situations where the culture is weak or in times of intense change, so there is little or no information to help people decide what is socially acceptable behavior. Here, people are likely to rely on their experiential trial and error learning. People can “test the waters” by taking modest risks and then evaluate the outcome; an assessment driven more by emotion than by rational calculation.
How does this work? If someone takes a risky action one week, do we expect them to do the same the next week?
The answer lies in how dangerous the outcome of the risky action is. Imagine being distracted by a text while driving and accidentally swerving into another lane. Once you’re out of breath, you’ll likely put the phone down for at least a few minutes. Alternatively, if people engage in risky behavior without serious consequences, they may develop a sense of security and be less cautious about their behavior. Imagine you replied to a text directly on your line. You might feel a little braver to continue texting. We call this last phenomenon “risk creep“.
The academic literature on the psychology of decision-making has examined both when people become more risk-averse and more tolerant (see these 2012 year and: 2016 papers). It also explored how social learning or trial and error can account for these results. However, they are studied separately rather than in the same context. Our study of Covid-19 behavior helps us measure whether risk aversion or risk tolerance prevails, taking into account possible social and experiential learning mechanisms.
“Risk Landslide” During Covid-19
In a five-month longitudinal field study after the lockdown and before vaccinations, we tracked what people did when they left their homes. We collected eight surveys from 304 students who had recently returned to campus and the surrounding neighborhood to attend part-time classes. They administered a baseline survey and seven-week follow-up “pulse” surveys that included a subset of those baseline survey questions. Seven pulse studies allowed us to track changes in behavior and perceptions over time. In all surveys, participants reported the number of times they left their home to participate in any of the six categories of activities.
We categorized activities into 1) non-discretionary activities necessary for daily living (going out to eat, run errands, or school activities) and 2) more discretionary activities that are relatively less important to the day. – daily life, and many have abandoned them during lockdown (exercise outside the home, gather with others in small social groups, attend large events). To examine social learning, we asked participants how many people they had seen engage in those same activities in the previous week. To examine experiential learning, we measured people’s perceptions of the riskiness of their own behavior a week earlier.
We found that the level of people’s non-discretionary activities (orders for things like the grocery store or pharmacy, school study groups) remained constant over time. However, people who saw others engage in activities outside the home (exercise, social gatherings, and large events) did more of the same activities the following week, indicating a creeping risk tolerance associated with social learning.
Similarly, people who said they engaged in more risky social activities one week gradually engaged in more discretionary activities the following week. Again, people show a creeping tolerance for risk due to the consequences of their own experiments.
The results of our study show that even when social learning is strong and influences behavior, it does not interfere with experiential learning. This may be especially the case when social learning is disrupted by random events (forgetting the mask and thus facing a new decision that you have not yet had to make). Thus, there is always a need for vigilance against excessive risk.
Implications for companies
The lesson for companies, in a nutshell, is: Beware of close calls. If someone does something risky, whether intentional or not, and it turns out well, they are more likely to do it again. If someone puts in an insecure password and nothing happens, their intuitive brain “learns” that everything is fine. If someone accidentally pays a customer, but no one notices, they are more likely to do it again. If someone makes a risky trade and it gets out, they will take more risk next time.
in fact “Cutting corners,” even if haphazard at first, will lead to cutting more corners going forward. When things work out, we tend to ignore or discount our success, and so the behavior or process no longer seems risky to us.
This pattern is most dangerous when the risk is relatively low, as it is combined with social learning, as the epidemic has shown. Even in 2020, a person who forgot a mask and thus went on an errand without a mask was still quite unlikely to contract the virus. The “risk creep” effect then makes them more likely to unmask next time. Social learning then reinforces the effect as others see the unmasked person and incorporate it into what they consider socially acceptable. A little success sets off a chain reaction that culminates in more risky behavior.