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How to identify metaknowledge trends and features in a certain research field? Evidences from innovation and entrepreneurial ecosystem

Chao Zhang and Jiancheng Guan ()
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Chao Zhang: University of Chinese Academy of Sciences
Jiancheng Guan: University of Chinese Academy of Sciences

Scientometrics, 2017, vol. 113, issue 2, 1177-1197

Abstract: Abstract Identifying the trends and features of metaknowledge will help scholars track knowledge through topics. This paper designs a new methodology to make it in a certain field. The proposed novel design performs well in the interdisciplinary domain where there are plenty noisy data and conflicting findings. This study applies this research design to a typical interdisciplinary domain, i.e. innovation and entrepreneurial ecosystems. To identify the scope of research and rationalize data collection process, this paper makes a definition of innovation and entrepreneurial ecosystems based on previous researches. Next, we design two data filtering procedures, which can handle the noisy data and provide the datasets for sequence analyses. Then, we adopt the co-citation analysis and network meta-analysis to clarify the trends and features of multiple metaknowledges. Finally, we draw conclusions about emerging trends, mainstream and hotspots, current situation, future challenges or other features of metaknowledge. We also integrate some conflicting findings, which provide more accurate evidences for the field. Evidences show that this novel research design is an effective tool for analyzing metaknowledges and also suitable for other fields.

Keywords: Metaknowledge; Co-citation; Network meta-analysis; Innovation ecosystem; Entrepreneurial ecosystem (search for similar items in EconPapers)
Date: 2017
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