Identifying core topics in technology and innovation management studies: a topic model approach
- Authors
- Lee, Hakyeon; Kang, Pilsung
- Issue Date
- 10월-2018
- Publisher
- SPRINGER
- Keywords
- Technology and innovation management; Research topic; Topic model; Latent Dirichlet Allocation (LDA)
- Citation
- JOURNAL OF TECHNOLOGY TRANSFER, v.43, no.5, pp.1291 - 1317
- Indexed
- SSCI
SCOPUS
- Journal Title
- JOURNAL OF TECHNOLOGY TRANSFER
- Volume
- 43
- Number
- 5
- Start Page
- 1291
- End Page
- 1317
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/72556
- DOI
- 10.1007/s10961-017-9561-4
- ISSN
- 0892-9912
- Abstract
- The study of technology and innovation management (TIM) has continued to evolve and expand with great speed over the last three decades. This research aims to identify core topics in TIM studies and explore their dynamic changes. The conventional approach, based on discrete assignments by subjective judgment with predetermined categories, cannot effectively capture latent topics from large volumes of scholarly data. Hence, this study adopts the topic model approach, which automatically discovers topics that pervade a large and unstructured collection of documents, to uncover research topics in TIM research. The 50 topics of TIM research are identified through the Latent Dirichlet Allocation model from 11,693 articles published from 1997 to 2016 in 11 TIM journals, and top 10 most popular topics in TIM research are briefly reviewed. We then explore topic trends by examining the changes in topics rankings over different time periods and identifying hot and cold topics of TIM research over the last two decades. For each of the 11 TIM journals, the areas of subspecialty and the effects of editor changes on topic portfolios are also investigated. The findings of this study are expected to provide implications for researchers, journal editors, and policy makers in the field of TIM.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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