Farnam Street helps you make better decisions, innovate, and avoid stupidity.

With over 350,000 monthly readers and more than 87,000 subscribers to our popular weekly digest, we've become an online intellectual hub.

Sequence of presentation influences choices

When several choice options are sampled one at a time in a sequence and a single choice of the best option is made at the end of the sequence, which location in the sequence is chosen most often? We report a large-scale experiment that assessed tasting preferences in choice sets of two, three, four, or five wines. We found a large primacy effect—the first wine had a large advantage in the end-of-sequence choice. We also found that participants who were knowledgeable about wines showed a recency effect in the longer sequences. We conclude with a process model that explains our findings.

The model they propose to explain their findings is interesting:

We propose that two biases operated within that sequential competitive evaluation process. First, a first-is-best bias accounts for the consistent primacy effect. Second, a bias in favor of each new wine among high-knowledge participants accounts for the recency effect, and for an interesting reason: Compared with the low-knowledge participants, the high-knowledge participants were more persistent in looking for a better wine later in the sequence—a plausible result of greater expertise. Thus, high-knowledge participants were likelier to make a comparison between their current favorite and the new wine when each new wine was sampled. Thus, there was a substantial chance that each new wine would beat the current favorite, and this habit produced the pronounced recency effect in longer sequences, especially for high-knowledge participants. For example, suppose that each new wine has a .30 chance of beating the current favorite, and the current favorite remains the preferred choice with a .70 probability. Note that these values are consistent with the size of the observed primacy effects (e.g., the first wine was chosen with approximately .70 probability in the two-option sets) and with the recency effects for the high-knowledge participants (the last wine was chosen with approximately .30 probability in the four-option and five-option sets).

We account for the lack of recency effects among the low-knowledge participants by proposing that they followed the pair-wise competitive-evaluation strategy less vigorously than the high-knowledge participants, eliminating the potential recency advantage. We speculate that the low-knowledge participants were more likely to be overwhelmed by the cognitive demands of the pair-wise competitive strategy as memory load and interference increased across the sampling trials.

The pair-wise model provides an almost perfect fit to the data if we add one more assumption about the comparison process. Thus far, we have assumed that all current favorites have a .70-versus-.30 advantage in all pair-wise comparisons. But if we suppose that the current-favorite advantage increases for later favorites (e.g., if the third option wins its pair-wise competition, its advantage increases to .75 vs. .25; if the fourth wins, its advantage is .80 vs. .20), then the model fits the data almost perfectly. This pair-wise-competition process model is impressive; its one failing is that it predicts a small recency effect for the three-option set for high-knowledge participants.