Abstract:

The construction of sustainability performance indicators with using neural networks is an appropriate path to measuring and optimizing sustainable corporate performance. It is described in the paper as a modern method of implementation of artificial intelligence methods. The potential of neural networks is presented in the field of the adaptation of the various company characteristics. There are discussed two nontrivially calculated indicators:  the Economic Value Added (EVA) and the Cash Flow Return on Investment (CFROI). It is known that is sufficient to have the basis of knowledge of several samples, without the knowledge of the internal links, for neural network modelling. The user friendly mathematical software Maple is introduced for the solution of those tasks. Maple has become the strong computational tool of mathematical, financial and economic modelling in education, research and practice. It allows implementing the appropriate neural network, which would be used by company managers while maintaining the complexity of values and meaningful indicators of economic performance to remove their discovered disadvantage.