Nudging is a well-known and popular concept in behavioral economics. It refers to non-coercive interventions that influence the choices people make by changing the way a situation is presented. A well-known example of this is placing the salad bar near the cafeteria entrance to promote a healthy diet. It has been shown that simple change has an effect on the food people choose to eat for lunch. However, is a light salad really the best option from the employee’s perspective, or is it their employer who will benefit from staff who perform better in the afternoon? And, is improving the decisions we make really that simple?
Measuring the quality of a decision
Whether a nudge ultimately results in a person making decisions that are better suited to their needs is an important factor in assessing the effectiveness of nudges. This is the starting point of the research work of Nick Netzer and Jean-Michel Benkert from the Department of Economics at the University of Zurich. How do you measure whether a nudge improves a decision in the eyes of the person being nudged? “We can’t determine whether a nudge improves the choices a person makes until we understand how they reach their decisions,” says Nick Netzer, putting the hype surrounding nudging into perspective. “Depending on which behavioral model we take as a starting point, it is possible to measure the effectiveness of nudges – or not.”
Traditional economics assumes that a person’s preferences can be inferred from their decisions and behavior. According to the rational behavior model, a person’s decision to have a salad or a steak for lunch is based on which meal meets their needs. When it comes to assessing nudges, however, this model is problematic, since nudging manipulates precisely the behavior that is supposed to shed light on a person’s preferences. The researchers therefore looked to alternative behavioral models to determine the assumptions under which a nudge can be assessed in a meaningful way.
According to the “satisficing” model, a person will consider their alternatives subsequently and choose the first one that meets their needs in a satisfactory way. The person will order the salad because it is the first option that adequately fulfills their requirements. Although they might have enjoyed the steak more, they will not consider that option, since they have already made up their mind. In this model, hardly any conclusions can be drawn about the true preferences of a person, and their decisions cannot be improved through nudging either.
If we assume decisions are made according to the limited attention model, however, the situation changes: This model is based on the idea that a person will only ever consider a certain number of possibilities – for example, only the first three meals on a menu that features five options. The person will then ponder these options and choose the best meal out of this selection. Unlike with the satisficing model, conclusions can be drawn about a person’s preferences, as the UZH researchers have now shown. Decisions that are based on such a decision-making process can be improved by nudging. Therefore, if you know that a salad is indeed an ideal meal, then placing it among the first three items on the menu will ensure that a person will at least consider this meal and maybe also choose it.
Success of nudges depends on decision-making process
It is therefore necessary to know what a person’s true needs and preferences are in order to assess the success of nudges when it comes to improving decisions. If we do not have this information, any nudging that takes place is done without knowing what is in a person’s best interests. “Our findings show that the success of nudging greatly depends on how we view the human decision-making process,” says Nick Netzer. “We can’t conclusively determine whether nudging makes sense as long as current scientific knowledge in economics, psychology and neuroscience doesn’t allow nudging to be assessed in a consistent manner.”
Nick Netzer, Jean-Michel Benkert. Informational Requirements of Nudging. Journal of Political Economy. December 2018. DOI: 10.1086/700072