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What drives loss aversion

Two researchers set out to investigate what drives loss aversion. They found that the usual model of loss aversion does not fully explain how people make decisions—and that, rather than tallying everything up as a gain or a loss right away, people are constantly comparing options and seeking out information that supports their inclinations.

That usual model is a process called value encoding: When a decision-maker first sees an option, he or she immediately compares it to a reference point—how much money they have, say, or what the price of an item usually is—and judges relative to that whether it is a loss or a gain. When it is time to make a decision, the person picks the option that, essentially, feels best compared to the reference point, with the sense that they have gained the most, or lost the least.

Another potential mechanism is called value construction. In this process, people do not just store, or encode, a value for each option right away. Instead, they build up a preference as they learn about the different options available. Decision-makers do not objectively assess their options, however: each new piece of information biases what information they look for next, and what they make of it. Earlier studies of value construction have shown, Böckenholt says, that “people try to find, as soon as possible, something that stands out. And then after they’ve found an option that stands out, they more or less try to confirm it” by seeking out supporting information. This can be useful, if they have honed in on the right option early on, or disadvantageous, if they are overlooking something better.

Overall, the results of the study suggested that value construction was playing a bigger role in the decision-making process than thought.

The decision-makers did not generally focus on the reference point less as time went on, as a value encoding process would suggest, and they showed a tendency to focus more on the option they eventually chose as time went on, an indication that they were likely honing in on it, comparing it directly to the other options.

The order of the options, too, had a big effect on choice. “The way these choices are represented, the order in which this information is processed, has a tremendous influence on what people end up choosing,” Böckenholt says. “That should not matter at all in value encoding, because there you look at each option separately.” In value construction, however, where decision-makers tend to stick with an option they see early on, order can have a strong impact.

The researchers found, too, that they could predict a person’s eventual choice from the information they looked at early on—a pattern that is seen in all sorts of decision-making. “I think it’s true, in general, that decision-makers make up their minds much earlier than you’d think on the basis of their behavior,” Böckenholt says. “They may still be looking and checking things out, but actually they already know what they want.” This sort of data mining could be applied to many sorts of scenarios, he says. “If you look how people browse [online], then you want to predict more or less which product are they going to buy, this result suggests that very early browsing behavior already is sufficient to predict which product, let’s say, a person may end up choosing.”

It seems that value encoding and value construction are not mutually exclusive. The two mechanisms seem to be important at different stages of the decision-making process.

“There’s some initial support for value encoding, but for later stages it becomes more a constructive process,” Böckenholt says. “So value encoding more or less accounts for the first 10 seconds—or at least we can’t say it doesn’t—but then for the rest, it’s value construction.” Comparing options to the reference point may help decision-makers pick an early favorite, at which point a value construction mechanism kicks in.

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