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基于专利分析的高新技术项目技术前景风险研究。

Research on technology prospect risk of high-tech projects based on patent analysis.

机构信息

School of Management and Engineering, Capital University of Economics Business, Beijing, China.

Research Center for Information Science Methodology, Institute of Scientific and Technical Information of China, Beijing, China.

出版信息

PLoS One. 2020 Oct 5;15(10):e0240050. doi: 10.1371/journal.pone.0240050. eCollection 2020.

DOI:10.1371/journal.pone.0240050
PMID:33017432
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7535056/
Abstract

The uncertainty of high technology has determined the high-risk character of high-tech projects. Thus, it is of great importance to effectively avoid the risk of high-tech projects by thoroughly analyzing projects' methodologies and fully understanding the technology prospect risk of projects in the feasibility study phase. This study proposes a systematic research framework to identify and analyze the technology prospect risk of projects based on patent analysis. Thus, text mining technology and principal component analysis are used to improve the traditional patent map method and construct a technology prospect risk map. Moreover, patent value evaluation and correlation analysis methods are combined to identify technology potential areas and calculate the value of technology prospect risk. At the same time, an empirical study is conducted with project cases in the field of optical communications, and the technology prospect risk situations of these projects are ascertained through qualitative and quantitative methods. The study is innovative and practical and offers a better combination of analysis methods for current technology development and specific projects.

摘要

高科技的不确定性决定了高科技项目的高风险性。因此,在可行性研究阶段,通过彻底分析项目方法和充分了解项目的技术前景风险,有效避免高科技项目的风险具有重要意义。本研究提出了一个基于专利分析的系统研究框架,以识别和分析项目的技术前景风险。因此,文本挖掘技术和主成分分析被用于改进传统的专利图方法,并构建技术前景风险图。此外,专利价值评估和相关分析方法被结合起来,以识别技术潜力领域并计算技术前景风险的价值。同时,通过光通信领域的项目案例进行实证研究,通过定性和定量方法确定这些项目的技术前景风险情况。本研究具有创新性和实用性,为当前技术发展和具体项目提供了更好的分析方法组合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/fb6c00ba7f8e/pone.0240050.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/e53d27f2d5dc/pone.0240050.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/def4e4ec9e78/pone.0240050.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/3eee822c9d08/pone.0240050.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/49b389bc0129/pone.0240050.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/c482c7d32d86/pone.0240050.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/24bc0ee88163/pone.0240050.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/fb6c00ba7f8e/pone.0240050.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/e53d27f2d5dc/pone.0240050.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/def4e4ec9e78/pone.0240050.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/3eee822c9d08/pone.0240050.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/49b389bc0129/pone.0240050.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/c482c7d32d86/pone.0240050.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/24bc0ee88163/pone.0240050.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7499/7535056/fb6c00ba7f8e/pone.0240050.g007.jpg

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