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Technology Innovation Management:Topic Evolutions and Research Trends from 1968 to 2022
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作者 Xinhang Zhao Xuefeng Wang +2 位作者 Hongshu Chen Yuqin Liu Zhinan Wang 《Innovation and Development Policy》 2023年第2期100-122,共23页
The technology innovation management(TIM)field attracts an increasing amount of attention.This paper takes a retrospective look at high-quality publication output in the TIM field over the 55 years from 1968 to 2022,r... The technology innovation management(TIM)field attracts an increasing amount of attention.This paper takes a retrospective look at high-quality publication output in the TIM field over the 55 years from 1968 to 2022,revealing topics,their evolutions,and research trends.A total of 31,498 articles and proceeding papers published during this period are analyzed.The paper first extracts the fine-grained topic words using the tool ITGInsight.Then Linlog algorithm is used to cluster topics based on the cooccurrence of the topic words.Time is integrated within the topic cluster results so that topic evolutions and research trends are analyzed.The TIM field has four main topic clusters:technology research,product research,firm research,and future research.In every topic cluster,there are many fine-sorted macro-topics and micro-topics.There is an obvious increase in diversity in the topic clusters of technology research and firm research.Especially,the evolution of technology research has been closely connected with society.In contrast,product research has declined in its topic size.At the same time,future research maintains a certain stability of its scientific publications.The research predicts that all the four topics will retain their popularity,and play an important role in the TIM field.Among them,technology research will continue to expand and enrich the TIM field.The other three topics will deepen their research for a better development of the TIM field.The paper also proposes some advice for industry professionals,policymakers,and researchers. 展开更多
关键词 technology innovation management word co-occurrence topic cluster topic evolution research trend ITGInsight
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