Business management (and operations) has many intertwined aspects, which constantly interact with each other, raising the complexity of it, as a 'system'. Modelling a complex system is difficult due to dependencies and adaptive behaviour. However, such complex 'systems' self-re-organise and become sustainable. A close-related concept of chaos indicates that a change in the initial conditions can bring out randomness, even with deterministic laws. Though the chaos and complexity theories are interrelated and multi-disciplinary in nature, very less application found in business management research.
The onset of Covid-19 pandemic has presented a unique social context for chaos and complexity.
Fellow scholars of this RG are requested to highlight:
a) recent trends in research in this area (how chaos is measured, analysed?).
b) recent applications of chaos and complexity theories in the field of business management
c) modelling techniques, related to chaos and complexity theories
This is an important and topical query but attempts to "measure" chaos are usually considered pointless: in a chaotic context, the relationships between cause and effect shift constantly and are therefore impossible to determine. In other words, chaos is the realm of unknowables in which no manageable patterns exist. What organizations can do is to design for emergence: to that intent, for instance, it is helpful to conceive of agile organizations.
Article Information and Communication Technology in Organizations: P...
Concepts (e.g. chaos, fractals) from the broad field of complexity are casually used in many fields, often with little understanding of their original meanings. So I would urge anyone wishing to apply them to study complexity theory itself, as treated in introductory mathematical and physics texts.
This answer focusses only on one aspect of your question, which will help to narrow your search domain: entropy measures. Within complex systems are being developed and increasingly applied complex systems measures based on the notion of entropy.
Entropy measures were originally developed by Ludwig Boltzmann and Shannon in twodisciplines: statistical statistical physics and information theory.
In the last about fourth years, a whole array of complexity measures were developed that measure the observed system, make some distribution of measurable properties that are subsequently inserted into the well know Boltzmann or Shannon entropy measures.
This procedure helps to asses the state of the observed system even without being capable to observe its every single detail. How exactly is this done can be found in our paper on the prediction of Torsades de Pointes arrhythmia, all details of the procedure are explained there.
A very important note. Very probably your measures will be impossible to classify by humans. This leads to the application of AI and machine learning methods, which are described in the same paper.
The notion of entropy had been proven a very valuable way of classifying of the operational mode of systems. Definitely something that you would like to think about in your case.
Thanks Jiří Kroc and Lee De Cola , for useful inputs.
We do have research work, using deterministic, stochastic/ probabilistic models (in study of 'chaos', 'resilience' measures), Olivier Serrat . Thanks for your inputs.
Regards