Understanding the Simulation Heuristic
Much like the availability heuristic Opens in new window, the simulation heuristic is related to the ease by which people can construct scenarios that fit a particular event. The easier it is to generate scenarios that lead to the event, the more probable the event is perceived or judged to be more likely.
In their investigation, Tversky and Kahneman proposed that when people have to predict a future event, estimate the probability of an event, make a counterfactual judgment, or assess causality, they run a mental simulation of the event in question. The ease with which any outcome can be simulated becomes a basis for judging its likelihood (Tversky & Kahneman, 1982b).
Initial investigations of the simulation heuristic have tended to focus more on counterfactual judgments—the process by which people judge that an event “was close to happening” or “nearly occurred.” Emotional reactions to events are intensified when people can easily imagine that they could have turned out differently.
The psychological significance of this assessment of distance between what happened and what could have happened is illustrated in the following example:
- Mr. Crane and Mr. Tees were scheduled to leave the airport on different flights, at the same time. They traveled from town in the same limousine, were caught in a traffic jam, and arrived at the airport thirty minutes after the scheduled departure time of their flights. Mr. Crane is told that his flight left on time. Mr. Tees is told that his flight was delayed and just left five minutes ago. Who is more upset, Mr. Crane or Mr. Tees?
It will come as no surprise that 96% of a sample of students who answered this question stated that Mr. Tees would be more upset. The reason is obvious because it is easier for the respondents to imagine how Mr. Tees could have made his flight. Matter of fact, the only reason for Mr. Tees to be more upset is that it was more “possible” for him to reach his flight.
The counterfactual construction functions as would be expected. Although the story makes it clear that the expectations of Mr. Tees and Mr. Crane could not be different, Mr. Tees is now more disappointed because it is easier for him to imagine how he could have arrived 5 minutes earlier than it is for Mr. Crane to imagine how the 30 minutes delay could have been avoided.
As demonstrated in the example, investigations by Tversky & Kahneman (1982) showed that positive events which almost happened but did not were judged as more upsetting than events that did not almost happen, because it was easier to generate scenarios for undoing the “almost happened” event (e.g., if only the plane had waited a little longer, if only the traffic jam had cleared a few minutes earlier, then Mr. Tees wouldn’t have missed his plane by 5 minutes) than the “didn’t almost happen” event (e.g., Mr. Crane missing his plane by 30 minutes). They also discovered that nonroutine events were more likely to changed than routine events in counterfactual scenarios.
The simulation heuristic is also applied when judging the plausibility of both positive and adverse outcomes. Decision-makers construct scenarios that consist of causal chains, depicting the consequences of not intervening compared to the consequences of intervening. Here the simulation heuristic clarifies to the decision-maker the relative advantages of intervention versus nonintervention, as well as convinces others, at the argumentation stage, why they should support one or the other strategy. Scenarios are also used to assess the probability of events.