title: It's a small world after all: contrasting hierarchical and edge networks in a simulated intelligence analysis task.
abstract: This article presents the rationale behind an important enhancement to a socio-technical model of organisations and teams derived from military research. It combines this with empirical results which take advantage of these enhancements. In Part 1, a new theoretical legacy for the model is developed based on Ergonomics theories and insights. This allows team communications data to be plotted into the model and for it to demonstrate discriminate validity between alternative team structures. Part 2 presents multinational data from the Experimental Laboratory for Investigating Collaboration, Information-sharing, and Trust (ELICIT) community. It was surprising to see that teams in both traditional hierarchical command and control and networked 'peer-to-peer' organisations operate in broadly the same area of the model, a region occupied by networks of communication exhibiting 'small world' properties. Small world networks may be of considerable importance for the Ergonomics analysis of team organisation and performance.
  This article is themed around macro and systems Ergonomics, and examines the effects of command and control structures. Despite some differences in behaviour and measures of agility, when given the freedom to do so, participants organised themselves into a small world network. This network type has important and interesting implications for the Ergonomics design of teams and organisations.
authors.affiliation: Faculty of Engineering and the Environment, University of Southampton, Highfield, Southampton, UK. N.stanton@soton.ac.uk
authors.forename: Neville A
authors.initials: NA
authors.lastname: Stanton
authors.forename: Guy H
authors.initials: GH
authors.lastname: Walker
authors.forename: Linda J
authors.initials: LJ
authors.lastname: Sorensen
mesh_terms: D001519:Behavior; D006804:Ergonomics; D006801:Humans; D008889:Military Personnel; D008962:Models, Theoretical; D013647:Task Performance and Analysis