Entrepreneurship policy and innovative indicators of industrial companies: Evaluation by MCDM and ANN Methods

The present paper presented a methodology for prioritizing the innovative and entrepreneurial indicators using Multi Criteria Decision Making (MCDM) and Artificial Neural Networks (ANNs), taking into account three individual, organizational and cultural dimensions simultaneously in decision making procedure. This methodology has two main advantages: first, the speed of operation in the accounting process and its simplification, and the other is the high precision with the elimination of errors in the calculations. Hence, a combination of findings was considered and identified in the Meta synthesis framework in the form of group categorization of indicators. Then, the entrepreneurship and innovation experts' opinion were gathered based on Metaanalysis. Next, the indicators were prioritized using Analytical Network Process (ANP) and the Decision-Making Trial and Assessment Laboratory (DEMATEL). The results obtained from Meta-analysis and multi criteria decision making methods were used as input and output data, respectively, to create an Artificial Neural Network model. Finally, the Artificial Neural Network model was designed in the form of Multi-layer Perceptron (MLP) Neural Network.