{"title":"Calibrating coupling for collaboration with Kuramoto.","authors":"Alexander C Kalloniatis, Timothy McLennan-Smith","doi":"10.1103/PhysRevE.111.024314","DOIUrl":null,"url":null,"abstract":"<p><p>We calibrate a Kuramoto-model-inspired representation of peer-to-peer collaboration using data on the maximum team size where coordination breaks down. The Kuramoto model is modified, normalizing the coupling by the degree of input and output nodes, reflecting dispersion of cognitive resources in both absorbing incoming- and tracking outgoing-information. We find a critical point, with loss of synchronization as the number of nodes grows and analytically determine this point and calibrate the coupling with the known maximum team size. We test that against the known \"span of control\" for a leader/supervisor organization. Our results suggest larger maximum team sizes than early management science proposes, but are consistent with studies that focus only the relationship between supervisor and subordinates, excluding other internal interactions in the team.</p>","PeriodicalId":48698,"journal":{"name":"Physical Review E","volume":"111 2-1","pages":"024314"},"PeriodicalIF":2.2000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Review E","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1103/PhysRevE.111.024314","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, FLUIDS & PLASMAS","Score":null,"Total":0}
引用次数: 0
Abstract
We calibrate a Kuramoto-model-inspired representation of peer-to-peer collaboration using data on the maximum team size where coordination breaks down. The Kuramoto model is modified, normalizing the coupling by the degree of input and output nodes, reflecting dispersion of cognitive resources in both absorbing incoming- and tracking outgoing-information. We find a critical point, with loss of synchronization as the number of nodes grows and analytically determine this point and calibrate the coupling with the known maximum team size. We test that against the known "span of control" for a leader/supervisor organization. Our results suggest larger maximum team sizes than early management science proposes, but are consistent with studies that focus only the relationship between supervisor and subordinates, excluding other internal interactions in the team.
期刊介绍:
Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.