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

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

Scientometrics, 2017, vol. 113, issue 2, No 27, 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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-017-2503-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:113:y:2017:i:2:d:10.1007_s11192-017-2503-y

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-017-2503-y

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().