Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Energizing collaborative industry-academia learning

A present case and future visions

Bibliographic Data

ID13058628
AuthorsPetri Kettunen (0000-0002-2928-5885, University of Helsinki, corresponding author), Janne Järvinen (0000-0002-2000-6552, Business Finland), Tommi Mikkonen (0000-0002-8540-9918, University of Jyväskylä), Tomi Männistö (0000-0001-7470-5183, University of Helsinki)
Year2022
Volume10
Issue1
Publication date2022-04-25
Open AccessYes
TypeARTICLE
VenueEuropean Journal of Futures Research (JOURNAL)
Journal identifiersISSN: 2195-2248 • E-ISSN: 2195-4194
PublisherSpringer Nature (PUBLISHER • SG)
DOI10.1186/s40309-022-00196-5
OpenAlexW4224313548
LanguageEN
Citations received1
References cited16

In Industry-Academia Collaborations (IAC) both academic, scientific research results and industrial practitioner findings and experiences are produced. Both types of knowledge should be gathered, codified, and disseminated efficiently and effectively. This paper investigates a recent (2014–2017) large-scale IAC R&D&I program case (Need for Speed, N4S) from a learning perspective. It was one of the programs in the Finnish SHOK (Strategic Centres of Science, Technology, and Innovation) system. The theoretical bases are in innovation management, knowledge management, and higher education (university) pedagogy. In the future, IAC projects should be more and more commonplace since major innovations are hardly ever done in isolation, not even by the largest companies. Both intra-organizational and inter-organizational learning networks are increasingly critical success factors. Collaborative learning capabilities will thus be required more often from all the participating parties. Efficient and effective knowledge creation and sharing are underpinning future core competencies. In this paper, we present and evaluate a collaboratively created and publicly shared digital knowledge repository called “Treasure Chest” produced during our case program. The starting point was a jointly created Strategic Research and Innovation Agenda (SRIA), which defined the main research themes and listed motivating research questions to begin with—i.e., intended learning outcomes (ILO). During the 4-year program, our collaborative industry-academia (I-A) learning process produced a range of theoretical and empirical results, which were iteratively collected and packaged into the Treasure Chest repository. Outstandingly, it contained, in addition to traditional research documents, narratives of the industrial learning experiences and more than 100 actionable knowledge items. In conclusion, our vision of the future is that such transparently shared, ambitious, and versatile outcome goals with a continuous integrative collection of the results are keys to effective networked I-A collaboration and learning. In that way, the N4S largely avoided the general problem of often conflicting motives between industrial firms seeking answers and applied solutions to their immediate practical problems and academic researchers aiming at more generalizable knowledge creation and high-quality scientific publications

Business · Collaborative learning · Knowledge management · Sociology · Treasure · Underpinning · Vision · Computer Science · Digital Transformation in Industry · E-Learning and Knowledge Management · Engineering · University-Industry-Government Innovation Models

  • The advancement of Artificial Intelligence in Education

    Roshasfarizan Che Ghazali, Mohd Fadzil Abdul Hanid et al.•Journal of Research on Technology…•2026

  • Knowledge growth in university-industry innovation networks – Results from a simulation study

    Open Access•Chongfeng Mao, Xianyun Yu et al.•Technological Forecasting and…•2020

  • The futures Map and its quality criteria

    Open Access•Osmo Kuusi, Kerstin E Cuhls et al.•European Journal of Futures…•2015

Citations per year1
Citation span2026 - 2026 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae