The role of different dimensions of social responsibility in non-financial performance of companies based on MLP neural network model and genetic algorithm

The present study investigates the effects of various dimensions of social responsibility on improving the non-financial performance of companies based on the MLP model of the neural network of genetic algorithms. For this purpose, the information of 107 companies listed on the Tehran Stock Exchange for a period of ten years in the period from 2009 to the end of 1397, was extracted and the research variables were calculated and the necessary statistical tests were performed. The method of the present study is descriptive-correlational and its design is experimental and the post-event approach is used. Using statistical and econometric methods, the hypotheses were examined and tested. Findings indicate that based on non-financial performance indicators, social dimension of social responsibility on structural capital changes, positive and significant effect, legal dimension of social responsibility on human capital change, positive and significant effect, social dimension of social responsibility on human capital change, It has had a positive and significant effect. By analyzing the data with the help of artificial neural network model and calculations of perceptron and hyperbolic tangent equal to 1 from MATLAB software, which out of the six existing hypotheses, three hypotheses are significant and confirmed that the social dimension of social responsibility on structural capital changes with the highest tangent Hyperbolic 1 The maximum effect factor is set as the optimal output.