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Updated: Jun 8, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
The breakdown of coordinated decision making in distributed systems
Christopher Bearman1, Susannah B F Paletz, Judith Orasanu
1University of South Australia, Adelaide, South Australia, Australia. chris.bearman@unisa.edu.au
Objective:
This article aims to explore the nature and resolution of breakdowns in coordinated decision making in distributed safety-critical systems.
Background:
In safety-critical domains, people with different roles and responsibilities often must work together to make coordinated decisions while geographically distributed. Although there is likely to be a large degree of overlap in the shared mental models of these people on the basis of procedures and experience, subtle differences may exist.
Method:
Study 1 involves using Aviation Safety Reporting System reports to explore the ways in which coordinated decision making breaks down between pilots and air traffic controllers and the way in which the breakdowns are resolved. Study 2 replicates and extends those findings with the use of transcripts from the Apollo 13 National Aeronautics and Space Administration space mission.
Results:
Across both studies, breakdowns were caused in part by different types of lower-level breakdowns (or disconnects), which are labeled as operational, informational, or evaluative. Evaluative disconnects were found to be significantly harder to resolve than other types of disconnects.
Conclusion:
Considering breakdowns according to the type of disconnect involved appears to capture useful information that should assist accident and incident investigators. The current trend in aviation of shifting responsibilities and providing increasingly more information to pilots may have a hidden cost of increasing evaluative disconnects.
Application:
The proposed taxonomy facilitates the investigation of breakdowns in coordinated decision making and draws attention to the importance of considering subtle differences between participants' mental models when considering complex distributed systems.
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