Abstract

Background: This paper has the central aim to provide an analysis of increases of system complexity in
the context of modern industrial information systems. An investigation and exploration of relevant theoretical
frameworks is conducted and accumulates in the proposition of a set of hypotheses as an explanatory approach for
a possible definition of system complexity based on information growth in industrial information systems. Several
interconnected sources of technological information are investigated and explored in the given context in their
functionality as information transferring agents, and their practical relevance is underlined by the application of the
concepts of Big Data and cyber-physical, cyber-human and cyber-physical-cyber-human systems.
Methods: A systematic review of relevant literature was conducted for this paper and in total 85 sources matching the
scope of this article, in the form of academic journals and academic books of the mentioned academic fields, published
between 2012 and 2019, were selected, individually read and reviewed by the authors and reduced by careful author
selection to 17 key sources which served as the basis for theory synthesis.
Results: Four hypotheses (H1-H4) concerning exponential surges of system complexity in industrial information systems
are introduced. Furthermore, first foundational ideas for a possible approach to potentially describe, model and simulate
complex industrial information systems based on network, agent-based approaches and the concept of Shannon entropy
are introduced.
Conclusion: Based on the introduced hypotheses it can be theoretically indicated that the amount information aggregated
and transferred in a system can serve as an indicator for the development of system complexity and as a possible
explanatory concept for the exponential surges of system complexity in industrial information systems.