Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses

Kajikawa, Y; Mejia, C; Wu, M; Zhang, Y

Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses

Kajikawa, Y Mejia, C Wu, M

Zhang, Y

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Publisher:: ELSEVIER SCIENCE INC
Publication Type:: Journal Article
Citation:: Technological Forecasting and Social Change, 2022, 182
Issue Date:: 2022-09-01

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Field	Value	Language
dc.contributor.author	Kajikawa, Y
dc.contributor.author	Mejia, C
dc.contributor.author	Wu, M https://orcid.org/0000-0003-3956-7808
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-7731-0301
dc.date.accessioned	2023-03-17T06:02:40Z
dc.date.available	2023-03-17T06:02:40Z
dc.date.issued	2022-09-01
dc.identifier.citation	Technological Forecasting and Social Change, 2022, 182
dc.identifier.issn	0040-1625
dc.identifier.issn	1873-5509
dc.identifier.uri	http://hdl.handle.net/10453/167496
dc.description.abstract	Technology and innovation management is vital emerging research fields. Technological Forecasting and Social Change (TFSC) has worked as a major forum in this field and is currently regarded as the leading journal. However, an increasing number of publications hamper a comprehensive understanding of the field and journal. In this study, we conducted a systematic review of TFSC with the support of bibliometric analysis. We used citation network analysis and topic models to extract research landscapes and trends. Our results illustrate how technology and innovation management research has developed through the interactions among theories, methods, and cases, both qualitatively and quantitatively. Based on our analysis and findings, we discuss the major branches of research, topics in the journal, and future perspectives.
dc.language	English
dc.publisher	ELSEVIER SCIENCE INC
dc.relation.ispartof	Technological Forecasting and Social Change
dc.relation.isbasedon	10.1016/j.techfore.2022.121877
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	10 Technology, 14 Economics, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Science Studies
dc.title	Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses
dc.type	Journal Article
utslib.citation.volume	182
utslib.for	10 Technology
utslib.for	14 Economics
utslib.for	15 Commerce, Management, Tourism and Services
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2024-09-01T00:00:00+1000Z
dc.date.updated	2023-03-17T06:02:36Z
pubs.publication-status	Published
pubs.volume	182

Abstract:

Technology and innovation management is vital emerging research fields. Technological Forecasting and Social Change (TFSC) has worked as a major forum in this field and is currently regarded as the leading journal. However, an increasing number of publications hamper a comprehensive understanding of the field and journal. In this study, we conducted a systematic review of TFSC with the support of bibliometric analysis. We used citation network analysis and topic models to extract research landscapes and trends. Our results illustrate how technology and innovation management research has developed through the interactions among theories, methods, and cases, both qualitatively and quantitatively. Based on our analysis and findings, we discuss the major branches of research, topics in the journal, and future perspectives.

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http://hdl.handle.net/10453/167496