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2022 (English)In: International Journal of Innovation and Technology Management (IJITM), ISSN 0219-8770, Vol. 19, no 2Article in journal (Refereed) Published
Abstract [en]
This paper aims to identify global digital trends across industries and to map emerging business areas by co-word analysis. As the industrial landscape has become complex and dynamic due to the rapid pace of technological changes and digital transformation, identifying industrial trends can be critical for strategic planning and investment policy at the ¯rm and regional level. For this purpose, the paper examines industry and technology pro¯les of top startups across four industries (i.e. education, ¯nance, healthcare, manufacturing) using CrunchBase metadata for the period 2016–2018 and studies in which subsector early-stage ¯rms bring digital technologies on a global level. In particular, we apply word co-occurrence analysis to reveal which subindustry and digital technology keywords/keyphrases appear together in startup company classification. We also use network analysis to visualize industry structure and to identify digitalization trends across sectors. The results obtained from the analysis show that gamification and personalization are emerging trends in the education sector. In the finance industry, digital technologies penetrate in a wide set of services such as financial transactions, payments, insurance, venture capital, stock exchange, asset and risk management. Moreover, the data analyses indicate that health diagnostics and elderly care areas are at the forefront of the healthcare industry digitalization. In the manufacturing sector, startup companies focus on automating industrial processes and creating smart interconnected manufacturing. Finally, we discuss the implications of the study for strategic planning and management.
Place, publisher, year, edition, pages
World Scientific, 2022
Keywords
Emerging technologies; digitalization; startup; innovation; entrepreneurship; trend analysis; co-word analysis; text mining; social network analysis; Python.
National Category
Engineering and Technology
Research subject
Innovation and Design
Identifiers
urn:nbn:se:mdh:diva-56838 (URN)10.1142/s0219877022500018 (DOI)000733409600002 ()2-s2.0-85121984356 (Scopus ID)
Funder
EU, Horizon 2020, 832862
2021-12-282021-12-282022-08-29Bibliographically approved