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Summary A collection of slides from the first 3 weeks for Network Organizations

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A collection of the slides from the first 3 weeks for Network Organizations. Everything you need to know for the midterm exam.

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Organisations are collaborations, target orientated (organisations are a means to an end), can be
formal or informal and are relatively permanent.
 We-intentions, external en internal perspective
 Organisations use resources including (information) technologies
 Within organisations there are coordination and task distribution mechanisms (hence agent-
roles)

A systems perspective on organisations:
 A system is a set of elements ('components’) with relationships between them.
 A system has relationships to its environment.
 Depending on our perspective we choose what is in or out the system
 We can perceive/describe a system from an internal or external perspective.

Systems:
 Systems have a structure defined by their components/elements and composition;
 Systems show behaviour, requiring input, processing and output of resources, including energy,
data etc.;
 Systems have interconnectivity, i.e. different system parts have functional and structural
relationships to other parts.
 Systems can be attributed with functions

Network organisations pro’s and cons:
 Economy of scale
 Specialisation & (knowledge) productivity
 Resilience and flexibility
 Vulnerability due to interconnectivity

Levels of network organisations:
 Micro level; model to understand the function(ing) of one specific model node (one
organisation)
 Meso level; model a subsystem, i.e. the nodes and edges forming a particular interconnected set
of nodes forming the subsystem of interest
 Macro level; model the system of interest in order to study the emerging effects on society
level.

Two ways of modelling:
- Knowledge-driven: search for theories and evidence, supported by empirical data
- Data-driven: search for data and inductively find relations

What is a model?
A model (M) for a system (S) and an experiment (E) is anything to which E can be applied in order to
answer questions about S.”

By definition, a model can be qualified as a system, which allows to cut out smaller pieces to
generate a new model (implying a hierarchy of models). We have to choose the level of abstraction!

A model has limitations:
- It has a domain of validity
- It only represents part of the original system
- Its output will not exactly match that of the original system (i.e. It has a limited accuracy)

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