Author: Belinda Ongaro
Institution: University of Alberta
Image by Belinda Ongaro
Advertisers can be impressively accurate when it comes to predicting the behavior of consumers, but traditional economic behavioral models merely describe average consumer behavior. As recent research has shown, economic decision-making is multifaceted, and influenced by a consumer’s emotions, beliefs, and social status. Today, in a novel branch of behavioral psychology known as neuroeconomics, researchers are taking such factors into account by developing new models that they hope will bring economic “mind reading” to a new level.
"Consumers are finicky,” said Colin Camerer, a professor of behavioral finance and economics at the California Institute of Technology. “Companies put out a new flavor of cereal that does well in focus groups, but then it sits on a shelf and people don't buy it. So any method that helps predict actual sales could be useful.”
Using Blood-Oxygen Level Dependant Functional Magnetic Resonance Imaging (BOLD-fMRI) technology, Camerer and his colleagues measured the brain activity of participants as they engaged in various tasks, including economically themed games and consumer-oriented activities such as product rating. BOLD-fMRI measures changes in local magnetic fields by detecting the inflow and outflow of oxygenated and deoxygenated hemoglobin respectively, which occurs when neurons fire.
The brain is divided into 50,000 three-millimeter cubed “neighbourhoods” called voxels. An approach known as neural decoding associates the BOLD signal, or blood flow to these voxels, with particular neural activity. Rather than deriving generalized conclusions from outdated models that show how consumers should respond, the goal of neural decoding is to retrieve information directly from the brain and observe how the consumers actually respond.
"It's almost like a brain polygraph, where you may be saying one thing, but your brain is saying another and is more predictive of what you ultimately will do,” Camerer explained.
In one study by Camerer’s team, published in 2011, the researchers asked participants to rate 100 snack food items after each was flashed in front of them for 2.75 seconds. Data from the entire brain was taken into consideration, and based on the neural activity measured during the rating phase, the researchers could accurately predict the choice the consumer would make 68% of the time.
According to Camerer, “The question we ask is: Can we find the voxels in the brain that correlate most strongly with subjective value—the rating of the food—and what they later choose?”
Of course, the goal is to eventually achieve 100% predictability by means of a sharper measure of neural activity. By supplementing fMRI data with neurometric data including pupil dilation, muscle movement, and facial temperature, researchers may detect discrepancies between true tendencies and hypothetical statements with finer accuracy.
In an earlier study, Alan Sanfey and Luke Chang of the University of Arizona used similar MRI technology to identify brain networks involved in decision-making; in this case, in the context of the Ultimatum Game. The objective of the game is for a pair of individuals, a proposer and a responder, to split a sum of money. If the responder accepts the offer that is presented by the proposer, then the money is divided as stated, and the game is over. On the other hand, if the proposal is rejected, then no one receives payment. Of course, it is in the best interests of the proposer to offer the smallest fraction of the money without frustrating their partner and thus eliciting rejection.
Intriguingly, the researchers found that the inclination to reject an offer was augmented when the participants were informed of how others in their situation had responded, with fewer rejections given when low offers were perceived as typical. Brain imaging highlighted activity in the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the insula—areas associated with emotions like guilt, which can lead individuals to comply with expectations.
From Journal of Economic Literature Vol. XLIII (March 2005), pp. 9–64
The far-reaching applications of these findings will likely challenge the way economists interpret the consumer mind and give rise to new marketing studies that better reflect real-life decision-making. Ultimately, the goal of modern behavioral economists like Sanfey, Chang, and Camerer is to abandon the archaic and largely inaccurate decision-making models in favor of methods that better predict consumer behavior.
"We are trying to get the correct psychology about human nature into the theory of economics," expressed Camerer. "We need a theory that can explain both when people are acting rationally, and when they are not. We are trying to add in the missing elements.”
This feature was written under the guidance of science writing mentor Jennifer 'Jef' Akst.