Fuzzy Analysis of Industry Anisotropy

Goal. To present a new approach to the analysis of industry anisotropy, based on layer-by-layer Pareto optimization and on the assessment of industry resilience using fuzzy MAC technology. Methodology. An industry is represented by its constituent companies, each of which is represented by two factors - resilience index (RI) and return on equity (ROE). In the two-dimensional RI-ROE field, layers of non-dominated Pareto alternatives are considered, identified using the author's method of layer-by-layer Pareto optimization. A possibilistic Markov chain is built on axiological probabilities. Result. An example of analysis of industry anisotropy in dynamics is presented, using the example of the global oil and gas sector. Conclusion. The methodology for studying industry anisotropy in dynamics presented in the report makes it possible to predict the dynamics of individual companies within an industry and estimation of axiological probabilities for a company moving from one industry layer to another. Fuzzy research of industry structure also allows for fairly reliable prediction of industry behavior based on aggregated indicators.