Recently, many researches have been made to find the impact of human resources on firm performance. Many of these studies are conducted on the basis of statistical approaches and find the correlation between the human resource management (HRM) measures and firm performance. In this paper, the main aim is to estimate the firm performance through the use of nonlinear model. One method which is used for this nonlinear approach is Artificial Neural Networks (ANN). Artificial Neural Networks are computing systems made up of a number of simple highly interconnected signal or information processing units that are called as artificial neurons. In this work, we used one of the ANN approaches which is called as back-propagation algorithm. In order to collect data, a questionnaire is structured that contains questions related with human resource management and firm performance measures. The data are collected mainly from the manufacturing companies operating in Turkey. Using the data collected, the model is checked whether it is capable of forming the relationship between the HRM input variables and firm performance output variables or not. The experimental results show that through the use of this algorithm, the relationship between the input and output variables can be constructed and moreover, the model can be used as an estimator of firm performance for the companies that are not used in the training of the model
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