Total Lost in space

Abstract
Patent value varies by different means of evaluation methods. Due to the difficulties of evaluating patent value, methods of future patent value prediction are still rare. The research employs social networks analysis to analyze the citation information in patent citation networks. We introduce several factors (Effective size, constraint, efficiency, hierarchy from structural holes analysis; Call value from real options; Returns from event study) generated by several analytic models and the change of dynamic variation of information to evaluate patents. Using several factors as the predictor to predict the value of patents will get higher or lower. Moreover, we will use the top 50 highly cited patents as our main target samples to test the use of this patent evaluation process.

Keywords
Patent citation networks, Social networks analysis, Patent evaluation

Author
劉寶元 (Pao-Yuan, Liu)

Adviser
王俊程 (Jyun-Cheng, Wang)

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