OPTION LOGIC IN A BAYESIAN APPROACH TO MODELING INNOVATION ECOSYSTEMS

The aim of this work is to create a formalized description of the platform ecosystem of innovative entrepreneurship and to develop a logical-probabilistic model of the intellectual activity of its subjects. Studied ecosystem includes: a platform for supporting youth entrepreneurship; an innovative enterprise (startup) – the creator of a new technology; an investor (venture fund); an independent expert – a technology broker; a technology auditor; a patent office. The project activity of the startup is analyzed in detail in the course of computational experiments with one-period version of the model, constructed using the apparatus of Bayesian influence diagrams. Elements of the real options concept were used in learning the model, allowing for a more enhanced visual representation of the possibilities of quantitative analysis of the results of management decisions of start-up managers after the launch of the project in conditions of high uncertainty inherent in innovative activity. Taking into account the input conditions of the project implemented by the startup, algorithm for forming the initial graph of model, the table of unconditional probabilities and the table of utility node states of influence diagram are presented in stages. The proposed model allows not only to update the beliefs of startup managers upon receipt of new evidence, but also to evaluate the decision options that provide the greatest utility at different stages of the project implementation.