Anchoring is a cognitive tendency to focus too much on a particular reference point when making decesions. From this initial reference point, incremental adjustments are made to reach an estimate or decision. The end decision is heavily influenced by the initial starting point, thus different starting points result in different decisions. "The initial value, or starting point, may be suggested by the formulation of the problem, or it may be the result of a partial computation".(1) Also, since many decisions are made in an area of uncertainty, the initial starting point may be an unconscious attachment to a completely irrelevant point.
Anchoring was first theorized by Amos Tversky and Daniel Kahneman. In one of their early experiments, a wheel marked with the numbers 1 to 100 was spun. Subjects were then asked if the percentage of African nations which were members of the United Nations was more or less than the number on the wheel. Then the subjects were asked to give an actual estimate. The results were that the random initial reference point from the wheel had a significant effect on the answer the subjects gave. For example, when the wheel landed on 10, subjects gave an average estimate of 25%. When the wheel landed on 65, subjects gave an average estimate of 45%.(1)
Another experiment was conducted by profesor Dan Ariely and his collegues where he had a group of MBA students participate in an auction. They were shown various items then given a sheet with each product listed. Next they were instructed to write the last two digits of their social security number next to each item and asked if they would be willing to pay that amount for the products. Finally they were asked to write the maximum amount they would be willing to pay with the top bidder winning the item. The results of the experiment showed that the impact of social security numbers significantly influenced the amount each student was willing to pay. The students with above median social security numbers bid 57 to 107 percent higher than those with below median numbers.(2)