Firms participating in these auctions sought the help of game theorists. In the United States, for instance, the Federal Communications Commission decided to use a format that is now called “simultaneous ascending auction” — in which all licenses are auctioned off simultaneously. At the close of each round, participants can see all bids for a set of frequencies, and then adjust their bids in the next round. Today, researchers have also developed and tested several other auction designs for applications of this sort.
To some extent, it is true that this kind of auction design was a triumph for game theory and its hyperrational approach. But on the other hand, the new auction designs were also based on experimental work. If you cannot completely trust the idea that human behavior is guided by optimization, then you also cannot truly trust an auction design without testing it experimentally to observe real human decision-making patterns.
My team and I therefore decided that our advice would be soundly based on experiments. We worked out experiments that reflected the situation of the actual auction as accurately as possible. We had long and intense discussions with the firm we advised to create the right experimental environment. Then we conducted many such auctions with student subjects, and the outcomes of these auctions guided our advice.
S+B: Can you really transfer the insight from the behavior of students and other laypeople to the multimillion-dollar decision of a telecommunications company?
SELTEN: I run experiments both with experienced managers and with university students. Overall, the students do much better. It’s always the same story: People are guided too much by little-understood experience and make the wrong generalizations. Less experience can be advantageous when it forces you to think harder.
There is an interesting experiment involving wool auctions in Australia. Penny Burns, an Australian researcher, re-created these auctions in the laboratory and told the participants how much different quantities of wool would be worth. She then asked the participants to maximize their profits, which she actually paid them. On average, the inexperienced students realized much higher profits than the professional wool buyers. What was the reason for this?
It turned out that in their professional lives, the goal of wool buyers is not to make the highest profits. Instead, they need to see to it that they get enough wool for the factory to continue operating. The professionals bid aggressively in order to be sure to get at least a minimum amount of wool. They learn this behavior by experience without quite understanding what they do. When they buy too little wool, they are heavily blamed. When they buy too much, they are blamed much less. If they pay too much, they may be blamed, but less than if they bought too little.
In the laboratory situation, their goal was to maximize profits, yet they routinely applied their past behavior to this new situation, whereas the students who had no experience whatsoever had to think freshly about what to do. You also see the same contrast between students and professionals in option trading experiments and others.
S+B: How, then, can managers improve their decision making and limit these experiential biases?
SELTEN: The most effective way to improve your decision making is to improve your intuition. It is very rare that you can derive a decision from data and calculations alone. In most situations, you have to have some intuition that is based on the knowledge of analogies. These analogies concern very simple situations in which you can clearly see the best course of action. Such simple situations, sometimes presented in game theory, can then be transferred to more complex situations with similar features. When people have in mind great stores of such simple business or game situations and their analyses, they have better intuition. They will not easily forget the important aspects of a decision problem.