Modeling complex adaptive systems

Hawryszkiewycz, IT

Modeling complex adaptive systems

Hawryszkiewycz, IT

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Business Information Processing, 2009, 20 LNBIP pp. 458 - 468
Issue Date:: 2009-01-01

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Field	Value	Language
dc.contributor.author	Hawryszkiewycz, IT https://orcid.org/0000-0003-2256-0132	en_US
dc.date.issued	2009-01-01	en_US
dc.identifier.citation	Lecture Notes in Business Information Processing, 2009, 20 LNBIP pp. 458 - 468	en_US
dc.identifier.isbn	9783642011115	en_US
dc.identifier.issn	1865-1348	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10880
dc.description.abstract	The paper describes ways to model systems that dynamically change as their environment changes. The generic term complex adaptive systems (Kovacs, 2005) is increasingly used to describe systems in such environments. Complex adaptive systems are generally defined (Holland, 1995) as made up of many agents (which may represent cells, individuals, firms, projects) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of complex adaptive systems tends to be highly dispersed and decentralized. The overall behaviour of the system is the result of a huge number of decisions made every moment by many individual agents. Processes in such systems need to be equally adaptive and we refer to them as complex adaptive processes. Currently there are no widely accepted methodologies to model and design complex adaptive processes. Most methodologies for information systems design focus on prescribed processes. The paper describes ways to model such systems. The models will differ from existing modeling techniques as they combine business functions with social structures in ways that facilitate social connectivity and interactivity needed to adapt to changing situations within the business context. At the same time the social networks will be used to define the knowledge requirements that capture the outcome of work exchanges to support process continuity. It develops the idea of collaboration graphs to integrate social network into business models. It develops a blueprint based on three parts, business models, collaboration and knowledge and develops models based on integrating these three components. It then demonstrates the methods in outsourcing environments and principles of implementation of the models using contemporary technologies. © 2009 Springer Berlin Heidelberg.	en_US
dc.relation.ispartof	Lecture Notes in Business Information Processing	en_US
dc.relation.isbasedon	10.1007/978-3-642-01112-2_46	en_US
dc.title	Modeling complex adaptive systems	en_US
dc.type	Conference Proceeding
utslib.citation.volume	20 LNBIP	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	Sydney, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	20 LNBIP	en_US

Abstract:

The paper describes ways to model systems that dynamically change as their environment changes. The generic term complex adaptive systems (Kovacs, 2005) is increasingly used to describe systems in such environments. Complex adaptive systems are generally defined (Holland, 1995) as made up of many agents (which may represent cells, individuals, firms, projects) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of complex adaptive systems tends to be highly dispersed and decentralized. The overall behaviour of the system is the result of a huge number of decisions made every moment by many individual agents. Processes in such systems need to be equally adaptive and we refer to them as complex adaptive processes. Currently there are no widely accepted methodologies to model and design complex adaptive processes. Most methodologies for information systems design focus on prescribed processes. The paper describes ways to model such systems. The models will differ from existing modeling techniques as they combine business functions with social structures in ways that facilitate social connectivity and interactivity needed to adapt to changing situations within the business context. At the same time the social networks will be used to define the knowledge requirements that capture the outcome of work exchanges to support process continuity. It develops the idea of collaboration graphs to integrate social network into business models. It develops a blueprint based on three parts, business models, collaboration and knowledge and develops models based on integrating these three components. It then demonstrates the methods in outsourcing environments and principles of implementation of the models using contemporary technologies. © 2009 Springer Berlin Heidelberg.

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http://hdl.handle.net/10453/10880