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Author:

Huang Lu-cheng (Huang Lu-cheng.) (Scholars:黄鲁成) | Liu Chun-wen (Liu Chun-wen.)

Indexed by:

CPCI-S

Abstract:

Evaluating the quality of patents and identifying high-quality patents from numerous patents can promote economic activities such as patent transfer, acquisition and custody, and pledge financing; assisting enterprises to understand the status quo of technology development, determine R&D direction, defend themselves against patent trolls and product infringement. In order to evaluate patent quality simply and effectively, a patent quality evaluation model based on entropy weight method and improved TOPSIS is proposed. First, the evaluation indicator system for patent quality were established, which included 5 categories and a total of 11 indicators. Then, the weights of each indicator were calculated by entropy method. Finally, we employ the improved TOPSIS and traditional TOPSIS to calculate the ranking of performance for each patent, and then compare the results of these two methods to verify the superiority of the improved method. The suggested methodology was applied to the Geriatric technology. The identifying of high quality patents is of a great significance to decision makers and can also serve as a useful reference for future studies, which may be of a great interest to the general audience.

Keyword:

TOPSIS Entropy Patent quality Vertical projection distance

Author Community:

  • [ 1 ] [Huang Lu-cheng]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 2 ] [Liu Chun-wen]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China

Reprint Author's Address:

  • 黄鲁成

    [Huang Lu-cheng]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China

Email:

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Source :

2018 25TH ANNUAL INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE & ENGINEERING

ISSN: 2155-1847

Year: 2018

Page: 156-164

Language: English

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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