This paper contributes to the literature on the adoption of disruptive technologies for the transition to more sustainable societies by mapping businesses’ uptake in the Italian region of Piedmont from the perspective of innovation ecosystems. Despite their relevance for sustainability and competitiveness, evidence on the European Union indicates major weaknesses in the adoption of crucial disruptive technologies, recommending a stronger focus on the local and regional levels. This could be achieved via the perspective of innovation ecosystems so as to identify and strengthen industrial synergies in technology adoption, but current systematic research in this vein is limited by a lack of consistent and publically available data. Aiming to fill this gap, this study developed a highly scalable approach to map business actors and their uptake of emerging technologies. First, textual information on over 17,000 organizations operating in Piedmont was retrieved from the social network LinkedIn. Second, elementary text-mining techniques were used to verify their engagement with 5G Networks, Advanced Robotics, Artificial Intelligence, Autonomous Drive, Blockchain, and Drones. Third, uptakes within and across industries were statistically assessed. This identified 1273 businesses pertaining to 115 different sectors that already engaged with at least one of the above mentioned technological innovations, displayed some industrial synergies and complementarities, and confirmed key barriers to their uptake. Additional data would strengthen these results. Nonetheless, this study already provides preliminary evidence on technology adoption from the perspective of innovation ecosystems and a proof of concept for the use LinkedIn for ecosystem mapping.
Identifying Synergies and Barriers to the Adoption of Disruptive Technologies for Sustainable Societies – An Innovation Ecosystem Perspective / Spinazzola, M; Scuotto, V; Farronato, N; Pironti, M. - (2022), pp. 1-6. (Intervento presentato al convegno EEE International Conference on Technology Management, Operations and Decisions (IEEE ICTMOD).).
Identifying Synergies and Barriers to the Adoption of Disruptive Technologies for Sustainable Societies – An Innovation Ecosystem Perspective.
V Scuotto;
2022
Abstract
This paper contributes to the literature on the adoption of disruptive technologies for the transition to more sustainable societies by mapping businesses’ uptake in the Italian region of Piedmont from the perspective of innovation ecosystems. Despite their relevance for sustainability and competitiveness, evidence on the European Union indicates major weaknesses in the adoption of crucial disruptive technologies, recommending a stronger focus on the local and regional levels. This could be achieved via the perspective of innovation ecosystems so as to identify and strengthen industrial synergies in technology adoption, but current systematic research in this vein is limited by a lack of consistent and publically available data. Aiming to fill this gap, this study developed a highly scalable approach to map business actors and their uptake of emerging technologies. First, textual information on over 17,000 organizations operating in Piedmont was retrieved from the social network LinkedIn. Second, elementary text-mining techniques were used to verify their engagement with 5G Networks, Advanced Robotics, Artificial Intelligence, Autonomous Drive, Blockchain, and Drones. Third, uptakes within and across industries were statistically assessed. This identified 1273 businesses pertaining to 115 different sectors that already engaged with at least one of the above mentioned technological innovations, displayed some industrial synergies and complementarities, and confirmed key barriers to their uptake. Additional data would strengthen these results. Nonetheless, this study already provides preliminary evidence on technology adoption from the perspective of innovation ecosystems and a proof of concept for the use LinkedIn for ecosystem mapping.File | Dimensione | Formato | |
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Appreciation Award - Matteo Spinazzola, Veronica Scuotto, Nicola Farronato, Marco Pironti.pdf
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