| Summary: | 碩士 === 中華大學 === 科技管理學系(所) === 96 === From OEM, ODM to OBM, enterprises gradually have their own creative ideas. Only appropriate patent strategy can lead to advantageous position. However, no matter patent alliance, co-development or self-R&D strategy, enterprises must be well-acquainted with the patent distribution.
Based on the truth that current patent classification needing citation drawing which requires time-consuming effort, this research attempts to construct a matrix analysis method. This research takes vein recognition technology in biotechnology as example. First, key words will be confirmed and the patent information in USPTO can be collected. Secondly, patent matrix composed of Core, Margin, Blue-ocean and Red-ocean types is proposed around the average value of Self-Citations and Other-Citations. Third, patent counts, patent citations, involved companies and patent age are utilizes as parameters to build four different models. For the last, patent type will be discriminated and plays the foundation of the result of verification.
This research shows, vein recognition is still in its initial stage without mainstream technology. About patent classification differentiation rate, in the whole, Self-Citations is higher than Other-Citations. Involved Assignee Patent Age Weighted Count and Involved Assignee Share both are higher than Involved Assignee Count, Assignee Patent Age Weighted Count is higher than Assignee Patent Share. D set with the highest differentiation rate shows that four parameters Age Weighted Count composition including Self-Citations Count, Patent Count, Other-Citations Count and Involved Assignee Count, are the best model to reflect patent type.
The evidence research shows, the differentiation imposes on four sets of parameters A, B, C, D, the differentiation rate will be 62.5%, 75.0%, 68.8% and 87.5% respectively. This research can fast discriminate the single patent by acquirement of related parameters. It also can be a reference to choose technical cooperation or Design Around.
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