4.3 Article

A new measure of group decision-making efficiency

Journal

Publisher

SPRINGER
DOI: 10.1186/s41235-020-00244-3

Keywords

Systems factorial technology; Workload capacity; Group decision-making

Funding

  1. Ministry of Science and Technology, Taiwan [MOST 107-2410-H-006 -055 -MY2, MOST 105-2410-H-006 -020 -MY2, MOST 108-2321-B-006 -022 -MY2]

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It has widely been accepted that aggregating group-level decisions is superior to individual decisions. As compared to individuals, groups tend to show a decision advantage in their response accuracy. However, there has been a lack of research exploring whether group decisions are more efficient than individual decisions with a faster information-processing speed. To investigate the relationship between accuracy and response time (RT) in group decision-making, we applied systems' factorial technology, developed by Townsend and Nozawa (Journal of Mathematical Psychology 39, 321-359, 1995) and regarded as a theory-driven methodology, to study the information-processing properties. More specifically, we measured the workload capacityC(AND)(t), which only considers the correct responses, and the assessment function of capacityA(AND)(t), which considers the speed-accuracy trade-off, to make a strong inference about the system-level processing efficiency. A two-interval, forced-choice oddball detection task, where participants had to detect which interval contains an odd target, was conducted in Experiment 1. Then, in Experiment 2, a yes/no Gabor detection task was adopted, where participants had to detect the presence of a Gabor patch. Our results replicated previous findings using the accuracy-based measure: Group detection sensitivity was better than the detection sensitivity of the best individual, especially when the two individuals had similar detection sensitivities. On the other hand, both workload capacity measures, C-AND(t) and A(AND)(t), showed evidence of supercapacity processing, thus suggesting a collective benefit. The ordered relationship between accuracy-based and RT-based collective benefit was limited to theA(AND)(t) of the correct and fast responses, which may help uncover the processing mechanism behind collective benefits. Our results suggested that A(AND)(t), which combines both accuracy and RT into inferences, can be regarded as a novel and diagnostic tool for studying the group decision-making process.

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