When decision-makers are satisficing, it is not hard to see why they would be more likely to choose an item that appears earlier on a list, because they stop as soon as they find one that meets their pre-existing criteria, and might not even look at every item in a list.

Contrast this strategy with rational decision making, which is a standard assumption in many economic models. It turns out that making a decision “rationally”—which in economics terms means analyzing every possible option—requires a great deal of cognitive horsepower.

Humans are neither perfectly rational decision-makers nor strict satisficers, no matter how Spock-like or impulsive any individual may seem.

A history-dependent satisficer automaton has some ability to remember what options it has seen before and to modify its criteria accordingly. The more memory this automaton possesses, the closer it gets to the choices yielded by rational decision making. The more states the automaton has, the better a decision it can make.

The effects that researchers derive using mathematical analysis show up everywhere in the real world. Humans are more likely to vote for candidates who appear first on a ballot, more likely to click on options at the top of their computer screen, and more likely to give high scores to competitors who appear first and last in a competition.

There was even a lawsuit in the 1980s in which the federal government forced American Airlines to stop putting its own flights above those of its competitors in American’s computer reservation system.