TY - GEN
T1 - Exploring Patterns of Academic-Industrial Collaboration for Digital Transformation Research
T2 - 2022 Portland International Conference on Management of Engineering and Technology, PICMET 2022
AU - Chen, Hongshu
AU - Zhang, Yi
AU - Jin, Qianqian
AU - Wang, Xuefeng
N1 - Publisher Copyright:
© 2022 PICMET.
PY - 2022
Y1 - 2022
N2 - Interactions between industry and academia provide inspiration for knowledge fusion, and more importantly serve as a stimulus for both basic and applied research, creating impact and potential opportunities. From the perspective of text mining and co-authorship network analysis, this paper aims to explore the patterns of academic-industrial collaboration using publication data. We propose a bibliometric-enhanced topic modeling method to profile the core constituents of industry and academia collaborative hotspots in digital transformation research, using a 10-year publication dataset from 2009 to 2018 extracted from Web of Science. We then examine interactions and distinctions between topics authored by only academic researchers and having industrial collaboration to further develop a comprehensive understanding of the content and driving force of industrial engagement. The empirical insights of this paper provide a detailed picture of academic-industrial linkages, which potentially can be used to lead academics to engage with industry, and assist innovation management and problem-solving in digital transformation research and practice.
AB - Interactions between industry and academia provide inspiration for knowledge fusion, and more importantly serve as a stimulus for both basic and applied research, creating impact and potential opportunities. From the perspective of text mining and co-authorship network analysis, this paper aims to explore the patterns of academic-industrial collaboration using publication data. We propose a bibliometric-enhanced topic modeling method to profile the core constituents of industry and academia collaborative hotspots in digital transformation research, using a 10-year publication dataset from 2009 to 2018 extracted from Web of Science. We then examine interactions and distinctions between topics authored by only academic researchers and having industrial collaboration to further develop a comprehensive understanding of the content and driving force of industrial engagement. The empirical insights of this paper provide a detailed picture of academic-industrial linkages, which potentially can be used to lead academics to engage with industry, and assist innovation management and problem-solving in digital transformation research and practice.
UR - http://www.scopus.com/inward/record.url?scp=85139089256&partnerID=8YFLogxK
U2 - 10.23919/PICMET53225.2022.9882847
DO - 10.23919/PICMET53225.2022.9882847
M3 - Conference contribution
AN - SCOPUS:85139089256
T3 - PICMET 2022 - Portland International Conference on Management of Engineering and Technology: Technology Management and Leadership in Digital Transformation - Looking Ahead to Post-COVID Era, Proceedings
BT - PICMET 2022 - Portland International Conference on Management of Engineering and Technology
A2 - Kocaoglu, Dundar F.
A2 - Anderson, Timothy R.
A2 - Kozanoglu, Dilek Cetindamar
A2 - Niwa, Kiyoshi
A2 - Steenhuis, Harm-Jan
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 August 2022 through 11 August 2022
ER -
