In recent years, much governmental investment has been committed to R&D in the area of information technology industry. However, its commercialization rate is reported to be lower than expected. In order to prevent such waste, feedback information obtained from the rigorous evaluation of the finished R&D project needs to be utilized for future selection of new projects. The main purpose of our study is to provide the roadmap of the effective technology commercialization projects using the Decision Tree (DT) of data envelopment analysis (DEA) results when a company tries to develop or transfer its new technology. The environmental variables representing the characteristics of technology provider, receiver and technology itself are used as input variables for DT where the DEA results are used as a target variable. It is expected that our proposed approach can be effectively used to obtain the efficient scenario among the alternatives of several technology projects.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence