Hypotheses concerning complexity surges in modern and future industrial information systems

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.