Customers feel good about a company when its representatives make decisions in their favor, such as approving their loan application or gold member status. But when an algorithm reaches the same favorable conclusion, those warm and fuzzy feelings tend to fade.
This surprising contradiction is revealed in a new paper that examines how customers react differently depending on whether a computer or a fellow human being decides their fate.
In the study, Wharton marketing professor Stefano Puntoni and his colleagues found that customers are happiest when they receive a positive decision from a person, less happy when the positive decision is made by an algorithm, and equally unhappy with both man and machine when the news is bad. Puntoni is a co-author “Thumbs Up or Down: Consumer Reactions to Decisions by Algorithms Versus Humans,” published in the Journal of Marketing Research.
“What’s interesting is that if you talk to companies, they’ll often tell you that they’re reluctant to let algorithms make decisions because they are worried about what would happen to customers when things go wrong. But we don’t actually find that. The negative consequences of using algorithms for companies seem to be, in fact, when the news is good,” Puntoni says.
The researchers believe the results can be explained through attribution theory, a psychology term that refers to how people translate their own experiences and perceptions to make sense of their place in the world. Simply put, people have a psychological need to feel good about themselves, and it helps to internalize a good decision and externalize a bad one. When a company representative greenlights a request, customers attribute that to their own exemplary behavior, social status, excellent credit score, or other value-adds to the firm. That’s harder to do when the decision-maker is a bot.
“These decisions are diagnostic of some characteristic of ourselves,” Puntoni says. “People find it easier to internalize the good decision when the decision was made by a person. Now they get what they want, and it feels better to them that it was a human [deciding] than if it was an algorithm.”
Read more at Knowledge at Wharton.