Capital Maintenance Evolution using Outputs from Accounting System

Abstract

Decision making based on information provided by an enterprise accounting information system, is essential for sustainable development and enterprises growth. Besides widely used prediction models for an assessment of the financial distress, there is also a useful indicator of a capital maintenance evolution, that provides a deeper view to the enterprise growth or decline compared to traditional performance measures. The aim of the contribution is to develop a model for assessment of a capital maintenance evolution using available accounting outputs. Our constructed model and coefficient for a capital maintenance evolution CMEOPNN has been developed using the multi-layer (triple) artificial neural network with a feedforward signal transmission by a backpropagation method and an activation function is a sigmoid function. For construction our model we used 663 Slovak enterprises sample out of 5 most frequented industry sectors with a unified structure of the provided information in the financial statements for 2014-2017.