Faculty Opinions recommendation of Concepts from complex adaptive systems as a framework for individual-based modelling.

To date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical analysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks.

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The crucial roles of the artificial information systems web in intelligent human organizations

Human Systems Management ◽

10.3233/hsm-2003-22303 ◽

2003 ◽

Vol 22 (3) ◽

pp. 115-124

Author(s):

Liang Thow Yick

Keyword(s):

Information Systems ◽

Complex Adaptive Systems ◽

Adaptive Systems ◽

Collective Intelligence ◽

Physical Structure ◽

Current Status ◽

Human Beings ◽

Intelligent Structure ◽

Complex Adaptive ◽

Human Thinking

Human organizations with human beings as interacting agents are complex adaptive systems. Such organizations continuously consume information, make decisions, and evolve with the changing environment. In this respect, all human organizations including businesses must enhance their collective intelligence in order to learn faster and compete more effectively. Thus, adopting an intelligent structure is vital to all businesses as the world moves deeper into the knowledge economy. The paradigmatic shift in thinking, structure, management and operation requires all intelligent human organizations to be designed around intelligence. An intelligent structure encompasses an orgmind, an intangible deep component, as well as a physical component. At the physical structure perspective, being able to identify, design and develop an artificial information systems network that synchronizes well with the orgmind is critical. The connectivity of the organization, and the manner in which it behaves, communicates and collaborates, depend on the effectiveness of its information systems network and its orgmind. The orgmind which is at least the collection of all the interacting human thinking systems must be fully aware of both the internal and external environments. Inevitably, in the new economy, intelligent human organizations must be equipped with a well-integrated intelligent information network which functions similarly to the nervous system in biological beings. This study examines the current status of artificial information systems and their networks in businesses with respect to the above concepts.

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Agile Innovation to transform healthcare: innovating in complex adaptive systems is an everyday process, not a light bulb event

BMJ Innovations ◽

10.1136/bmjinnov-2020-000574 ◽

2021 ◽

pp. bmjinnov-2020-000574

Author(s):

Richard J Holden ◽

Malaz A Boustani ◽

Jose Azar

Keyword(s):

Project Management ◽

Complex Adaptive Systems ◽

Adaptive Systems ◽

Design Thinking ◽

Healthcare Delivery ◽

Light Bulb ◽

Innovation Development ◽

Agile Project Management ◽

Complex Adaptive ◽

Behavioural Sciences

Innovation is essential to transform healthcare delivery systems, but in complex adaptive systems innovation is more than ‘light bulb events’ of inspired creativity. To achieve true innovation, organisations must adopt a disciplined, customer-centred process. We developed the process of Agile Innovation as an approach any complex adaptive organisation can adopt to achieve rapid, systematic, customer-centred development and testing of innovative interventions. Agile Innovation incorporates insights from design thinking, Agile project management, and complexity and behavioural sciences. It was refined through experiments in diverse healthcare organisations. The eight steps of Agile Innovation are: (1) confirm demand; (2) study the problem; (3) scan for solutions; (4) plan for evaluation and termination; (5) ideate and select; (6) run innovation development sprints; (7) validate solutions; and (8) package for launch. In addition to describing each of these steps, we discuss examples of and challenges to using Agile Innovation. We contend that once Agile Innovation is mastered, healthcare delivery organisations can habituate it as the go-to approach to projects, thus incorporating innovation into how things are done, rather than treating innovation as a light bulb event.

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