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Relational network of innovation ecosystems generated by digital innovation hubs
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Resumo(s)
Collaboration plays a key role in the success attained to date by networks of innovation ecosystems generated around entities known as Digital Innovation Hubs (DIHs), recently created following European Commission initiatives to boost the digitisation of the European economic fabric. This article proposes a conceptual framework that brings together, defines, structures and relates the concepts involved in the collaborative interaction processes within and between these innovation ecosystems to allow comprehensive conceptualisation. The developed framework also provides an approach that helps to tangibilise collaboration as a management process. Here the goal is to ultimately move towards not only qualitative, but also quantitative modelling to bridge the research gap in the state of the art in this respect. The data-driven business-ecosystem-skills-technology (D-BEST) model, devised to configure DIHs service portfolios in a collaborative context, provides the reference basis for the interorganisational asset transfer methodology (IOATM). This is the keystone that structures the framework and constitutes its main contribution. Through the IOATM, this conceptual framework points out collaboration quantification, and serves as a lever for its modelling to deal with collaboration accounting by: turning it into a more controllable management element; guiding practitioners' efforts to improve collaborative processes efficiency with an approach that pursues objectivity and maximises synergies.
Descrição
Funding Information:
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The research leading to these results received funding from the European Union H2020 Research and Innovation Programme with Grant Agreements No. 872548 “Fostering DIHs for Embedding Interoperability in Cyber–Physical Systems of European SMEs” (DIH4CPS), No. 825631 “Zero-Defect Manufacturing Platform” (ZDMP), and No. 958205 “Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)”, from the European Union Horizon Europe Programme with Grant Agreement No. 101057294 “AI Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability and Resilience” (AIDEAS), and from the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana entitled “Industrial Production and Logistics Optimisation in Industry 4.0” (i4OPT, Ref. PROMETEO/2021/065).
Publisher Copyright:
© The Author(s) 2024.
Palavras-chave
Collaboration Digital innovation hubs Innovation ecosystem Interorganisational asset transfer methodology Software Industrial and Manufacturing Engineering Artificial Intelligence SDG 9 - Industry, Innovation, and Infrastructure