Irrational time allocation in decision-making

Abstract

Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate this by showing that it is possible to improve subjects' time allocation with a simple intervention that cuts them off when their decisions take too long. Thus, we provide a novel form of evidence that organisms systematically spend their valuable time in an inefficient way, and simultaneously offer a potential solution to the problem.

Keywords: decision-making; evidence accumulation; neuroeconomics; optimality; sequential-sampling model; speed-accuracy trade-off.

Figure 1.

Task design. (a) Example screen from the value-based food-choice task from study 1. Subjects simply chose the item that they would prefer to consume at the end of the study. To improve readability, we increased the font and dot size for both panels of this figure. (b) Example screens from the perceptual ‘twinkling-stars’ task from study 2 (also used in study 3, which is reported in the electronic supplementary material). The dots randomly appeared and disappeared, so that at any given point in time only approximately 80% of them were visible. Subjects had to decide which of the two fields had more dots. (Online version in colour.)

Figure 2.

RT versus difficulty. Mean RTs (black dots with standard error bars) as a function of (a) the difference in WTP between the two food items in study 1 (n = 49 subjects), and (b) the difference in the number of stars in study 2 (n = 40 subjects). Choice problems with a low absolute difference in the number of stars or WTP are more difficult and yield lower relative rewards from a correct decision. Although difficult choices benefit less from a correct decision, subjects spend more time on them, which reduces their earnings. Linear fits represent regressions of mean RT on absolute difference in WTP (study 1), and on the absolute difference in number of stars (study 2).

Figure 3.

Choice performance by block. (a) Choice surplus earned by n = 49 subjects in each of the five blocks. (b) Points earned by n = 40 subjects in each of the five blocks. All subjects began with a non-intervention block (first block T). In the second block, subjects either experienced another non-intervention (N) block (left half-panels) or an intervention (I) block (right half-panels). After that, the blocks alternated between I and N. To better reflect the within-subjects nature of the design, the data were individually de-meaned by subtracting, for each subject, the mean of blocks 2–5. Thus a positive bar means that in this block, on average, participants did better than the average from blocks 2–5, and vice versa for negative bars. Performance in I is always higher than in the previous N trials. The higher performance in I trials also holds when we control for experience.