The more the merrier? Increasing group size may be detrimental to decision-making performance in nominal groups

Ofra Amir, Dor Amir, Yuval Shahar, Yuval Hart, Kobi Gal*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Demonstrability-the extent to which group members can recognize a correct solution to a problem-has a significant effect on group performance. However, the interplay between group size, demonstrability and performance is not well understood. This paper addresses these gaps by studying the joint effect of two factors-the difficulty of solving a problem and the difficulty of verifying the correctness of a solution-on the ability of groups of varying sizes to converge to correct solutions. Our empirical investigations use problem instances from different computational complexity classes, NP-Complete (NPC) and PSPACE-complete (PSC), that exhibit similar solution difficulty but differ in verification difficulty. Our study focuses on nominal groups to isolate the effect of problem complexity on performance. We show that NPC problems have higher demonstrability than PSC problems: participants were significantly more likely to recognize correct and incorrect solutions for NPC problems than for PSC problems. We further show that increasing the group size can actually decrease group performance for some problems of low demonstrability. We analytically derive the boundary that distinguishes these problems from others for which group performance monotonically improves with group size. These findings increase our understanding of the mechanisms that underlie group problem-solving processes, and can inform the design of systems and processes that would better facilitate collective decision-making.

Original languageAmerican English
Article numbere0192213
JournalPLoS ONE
Issue number2
StatePublished - Feb 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2018 Amir et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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