Valuing academic patents and intellectual properties: Different perspectives of willingness to pay and sell

January 2013
Publication year: 2013
Source:Technovation, Volume 33, Issue 1

tend to lack the ability of valuing technologies in their areas. We apply classification tree analysis to discover different perspectives of Willingness to Pay (WTP) and Sell (WTS) of when valuing their patents and technologies. Predictor factors considered are development environment, technology characteristics, ownership and patenting policy, and technology transfer characteristics. According to the result of Korean student data, WTS and WTP are differently perceived for the same technology: WTP is higher than WTS for the low . The ownership policy, scalability and degree of innovation of technology, among the discovery of significant , are mainly considered as the important . From the finding of this research, we provide the policy implication on academic patenting and its ownership for further development of .

Highlights

► We surveyed engineering students’ of their academic patents. ► We found different patterns in the gap between over different academic majors. ► Using Decision Tree, we found that Teacher’s exception policy is the most important variable for classification of WTS. ► In addition, possibility of expansion to relevant technology is the most important variable for classification of WTP.

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