Selection of open innovation method in the automotive industry using adaptive network-based fuzzy inference system

Previously, companies relied only on internal intellectual resources and tried to develop and commercialize ideas within the organization. The open innovation approach leads companies to make more use of external technologies in their activities and allows other companies to use their innovations. Open innovation methods have a high diversity, but each economic enterprise should use one or more methods compatible with the company's situation according to its conditions. In the current research, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been used as one of the methods of artificial intelligence and MATLAB software to choose the appropriate method of open innovation in the automotive industry. For this purpose, two inputs under the title of company's technical knowledge level and the complexity of parts technology and nine possible modes for the output, including all kinds of open innovation methods, are considered in the fuzzy inference system so that by using the existing rules, a technique suitable to the company's conditions can be extracted. In this research, 50% were considered training data for model design, and 50% were considered test data for model evaluation. The designed model selected open innovation methods with 90% accuracy. Therefore, the presented model is a suitable tool for choosing the open innovation method for the automotive industry.