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A digital business ecosystem (DBE) is a closed or semi-closed system of small and medium enterprises (SMEs), which will come together in cyberspace in the same way that companies gather in a business park in the physical world. These companies will interact with each other through buyer-seller relationships. The purpose of this study is to develop a methodology that will allow one to study the ecosystem under various conditions and I present here a model for the mutual interactions between companies in a DBE and a methodology that can allow one to study the dynamics of a digital business ecosystem. Furthermore I present a quantitative model for studying the dynamics of such a system, inspired by human physiology and attempting to capture many aspects of the way companies interact with each other, including the quantitative modelling of trust and mistrust. This is a situation of competitive co-existence, where each unit receives excitatory and inhibitory signals from all other units in the system. Such systems exist in biology, and their states are known to oscillate between extremes, rather than to converge to a single.
About the author
Surbhi Gautam is an expert in mathematics with focus on Machine Learning and Neural Networks. She completed her PhD in Neural Networks working with distinguished prof Maria Petrou in Imperial College London 2011.She has two degrees in applied mathematics prior to her Phd (MSc & MPhil).She has four years of experience in teaching engineering student
