Developing a fuzzy expert system to predict technology commercialization success

A majority of efforts in terms of technology commercialization have failed; however, the issue of commercialization and its high importance are agreed upon by policymakers, entrepreneurs, and researchers. This shows the high complexity of the commercialization process. One of the main solutions to overcome the commercialization problems is to predict the success of technology commercialization before its implementation. Hence, this study aims to design a fuzzy expert system to predict the technology commercialization success in the early stages of its development and before its implementation. According to the literature review and the fuzzy Delphi method, the technology commercialization success factors (TCSFs) were identified and refined. The final result of the fuzzy Delphi process consists of 32 components categorized in four dimensions: technical specifications, financial and economic specifications, market specifications and rules and regulations. These success dimensions form the inputs of the prediction model in this study. The performance of the model was evaluated by actual samples selected from different fields of technology. The accuracy of the model was estimated to be 73% according to a validation process, indicating the high accuracy of the proposed model in predicting the commercialization success. This model could be used practically by risk-taking investors, technology advocates and innovators to adopt new technology commercialization opportunities.