摘要
不同技术领域有不同的技术复杂性,同等的技术知识流可以产生不同的技术创新度。专利技术价值评估是目前创新管理和科学计量学领域共同面对的技术难题,其困境之一是缺乏指标间相互关系的研究。本研究对基于"专利向心引用网络"的专利结构指标与传统指标在映射专利技术价值方面的相关性进行了实证观察分析,并应用蒙特卡罗模拟,验证了研究结果的有效性。结果表明,这些结构指标可以对现实中专利技术价值的全面判断提供有意义参考。
Technological areas differ in technological complexity,it is well-known that similar amounts of technological knowledge can produce different numbers of patented innovation as output.There is no optimal solution and few relations among indicators for evaluating patent technological value in the field of scientometrics as well as in innovation management.In this study,the relationships between the structural indicators of ego patent citation networks and traditional indicators of technological value of a patent were investigated using sampling data of real patents,and then testified by Monte Carlo Simulation.The results suggest that the structural indicators are significant for providing a multilayered picture of patent technological value.
出处
《科学学研究》
CSSCI
北大核心
2014年第3期343-351,共9页
Studies in Science of Science
基金
国家自然科学基金资助项目(71173185)
关键词
专利技术价值
相对评价
专利向心引用网络
结构指标
蒙特卡罗模拟
patent technological value
relative evaluation
ego patent citation network
structural indicator
Monte Carlo Simulation
