Citing this article

A standard form of citation of this article is:

Dekker, Anthony (2007). 'Studying Organisational Topology with Simple Computational Models'. Journal of Artificial Societies and Social Simulation 10(4)6 <http://jasss.soc.surrey.ac.uk/10/4/6.html>.

The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:

@article{dekker2007,
title = {Studying Organisational Topology with Simple Computational Models},
author = {Dekker, Anthony},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {10},
number = {4},
pages = {6},
year = {2007},
URL = {http://jasss.soc.surrey.ac.uk/10/4/6.html},
keywords = {Network Rewiring, Small World Networks, Self-Synchronization, Agent Simulation, Collaboration, Problem Solving},
abstract = {The behaviour of many complex systems is influenced by the underlying network topology. In particular, this applies to social systems in which people or organisational units collaboratively solve problems. Network rewiring processes are one useful tool in understanding the relationship between network topology and behaviour. Here we use the Kawachi network rewiring process, together with three simple simulation models of organisational collaboration, to investigate the network characteristics that influence performance. The simulation models are based on the Assignment Problem, the Kuramoto Model from physics, and a novel model of collaborative problem-solving which involves finding numbers with certain characteristics, the existence of which is guaranteed by Lagrange's Theorem. For all three models, performance is best when the underlying organisational network has a low average distance between nodes. In addition, the third model identified long-range connectivity between nodes as an important predictor of performance. The commonly-used clustering coefficient, which is a measure of short-range connectivity, did not affect performance. We would expect that long-range network connectivity would also influence the behaviour of other complex systems displaying global self-synchronization. The paper also demonstrates the utility of simple computational models in studying issues of organisational topology.},
}

The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.


TY - JOUR
TI - Studying Organisational Topology with Simple Computational Models
AU - Dekker, Anthony
Y1 - 2007/10/31
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 10
IS - 4
SP - 6
UR - http://jasss.soc.surrey.ac.uk/10/4/6.html
KW - Network Rewiring
KW - Small World Networks
KW - Self-Synchronization
KW - Agent Simulation
KW - Collaboration
KW - Problem Solving
N2 - The behaviour of many complex systems is influenced by the underlying network topology. In particular, this applies to social systems in which people or organisational units collaboratively solve problems. Network rewiring processes are one useful tool in understanding the relationship between network topology and behaviour. Here we use the Kawachi network rewiring process, together with three simple simulation models of organisational collaboration, to investigate the network characteristics that influence performance. The simulation models are based on the Assignment Problem, the Kuramoto Model from physics, and a novel model of collaborative problem-solving which involves finding numbers with certain characteristics, the existence of which is guaranteed by Lagrange's Theorem. For all three models, performance is best when the underlying organisational network has a low average distance between nodes. In addition, the third model identified long-range connectivity between nodes as an important predictor of performance. The commonly-used clustering coefficient, which is a measure of short-range connectivity, did not affect performance. We would expect that long-range network connectivity would also influence the behaviour of other complex systems displaying global self-synchronization. The paper also demonstrates the utility of simple computational models in studying issues of organisational topology.
ER -