Sixth generation innovation model: description of a success model

Barbieri, José Carlos; Álvares, Antonio Carlos Teixeira

doi:10.1016/j.rai.2016.04.004

Cited by 36 publications

(30 citation statements)

References 4 publications

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“…Innovation is the driving factor for economic development, growth and the wealth of nations (Schumpeter, 1912) and is widely understood as a complex process (Drucker, 1985) involving different types of actors from the public and private sector (Mowery & Rosenberg, 1993;Chesbrough, 2003;Hauschildt et al, 2016), often organized in networks (Kozioł-Nadolna & Świadek, 2010;Barbieri & Álvares 2016;Taferner, 2017). These actors from the different societal sub-systems together form the National Innovation System (NIS), a term first introduced by Freeman (1987) and defined as: "[...] the network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse new technologies."…”

Section: Background and Methodologymentioning

confidence: 99%

Building up a national network of applied R&D institutes in an emerging innovation system

Kohl

Will

Prim

et al. 2020

Prod.

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Paper aims: This paper aims at answering the research question "How to successfully build up and strategically manage a new network of applied R&D in Brazil?" Originality: The paper is based on a unique experience of a strategic partnership, transferring the experiences of managing the largest network of applied research in Europe to the Brazilian National Innovation System (NIS). Research method:The research described in this paper follows an action research approach, using a participative process of rapid prototyping, pilot tests and continuous revision and adaptation. Main findings:The paper presents a comprehensive and consistent set of management models, procedures and tools for the planning, implementation and evaluation of applied R&D institutes.Implications for theory and practice: The paper's findings contribute to the empirical research on methodologies to manage knowledge-based networks and innovation actors at the interface between research and industry.

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Section: Background and Methodologymentioning

confidence: 99%

Building up a national network of applied R&D institutes in an emerging innovation system

Kohl

Will

Prim

et al. 2020

Prod.

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show abstract

“…31 Therefore, parallel or concurrent model constitutes the fifth- 28 and the sixth-generation innovation models. 32 Moreover, the scientific research phase can be parallel with other innovation phases 12,33 or within itself. 25 Other scholars refer to the parallel development of the product production process as concurrent engineering (CE).…”

Section: Literature Reviewmentioning

confidence: 99%

Rapid Response in an Uncertain Environment: Study of COVID-19 Scientific Research Under the Parallel Model

Cheng¹,

Chen²,

Tang³

et al. 2022

RMHP

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The rapid response of COVID-19 scientific research played a significant role in pandemic prevention and control but failed to block the spread of the pandemic rapidly. Besides the complexity of the virus, the effectiveness of control and prevention measures, and other factors, the adaptation of the mode of conducting scientific research is also crucial for the prevention and control of COVID-19. In this study, a parallel model was used to explore the effects of the rapid scientific response on COVID-19 to assess why pandemics continue to spread under rapid response. Analysis: This study presents the response of scientific research based on country/region and publication dimensions after analyzing COVID-19 studies in the Web of Science and PubMed databases. Co-occurrence analysis of items was used to determine the generation rate of COVID-19 research under different topics to identify the reflected innovation model. Results: More manifestations on rapid response of COVID-19 research, especially compared with the linear model of SARS research, showed that the COVID-19 research followed a parallel or concurrent innovation model. Conclusion:Early multi-stakeholder partnership, convenient information sharing, and improved research competence promote the parallel model in COVID-19. Meanwhile, the uncertainty of the COVID-19 virus and the adverse effect of rapid response may limit the time efficiency of the parallel model. In conclusion, the rapid prevention and control of the pandemic cannot fully rely on scientific research but requires more combined effort under an uncertain global setting.

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“…There are a number of innovation frameworks; those of immediate relevance to this research are diagnostic in nature and explicitly relevant to digital innovation, including: Barbieri & Teixeira Álvares, 2016;Berkhout & Duin, 2004;Binz & Trufer, 2017;BSi, 2008;Carayannis et al, 2018;Scaringella & Chanaron, 2016;Chen et al, 2018;Gkypali et al, 2018;İzadi et al, 2013;Nylén & Holmström, 2014;Silviana, 2018. Specifically, Berkhout & Duin (2004, BSi (2008), and Nylén & Holmström (2014) each present an interesting range of perspectives: technology-cyclic, innovation management, and components of digital innovation, respectively.…”

Section: Innovation Frameworkmentioning

confidence: 99%

Towards Knowledge Exchange for Effective Innovation Support

Roast¹,

Uruchurtu²,

Maswera³

2019

17th International Conference on E-Society 2019

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The term Knowledge Exchange (KE) is commonly used to describe university-industry collaborations that frequently foster innovation. Understanding such collaborations and their potential value is a difficult activity. The means of supporting collaboration vary significantly and potential for successful innovation is hard to asses. In this paper, we describe work aimed at developing an improved understanding of knowledge exchange within a digital context-both within digital sectors and also in non-digital sectors where the adoption of digital technologies can lead to new and challenging opportunities. Our work focuses upon digital innovation for Small to Medium Enterprises (SMEs) aiming to support effective Knowledge Exchange based innovation; a specific driver being the difficulty of understanding the potential for successful and productive collaborations with individual SMEs. From a number of existing digital innovation models and instruments, factors for characterizing digital innovation potential have identified. However, based on our experience and expert feedback, such characterizations appear to be inappropriate for SMEs. In response to this, an instrument has been developed to identify potential for quality digital innovation based on collaborative KE between SMEs and universities. The instrument is introduced, and its development and refinement discussed.

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Sixth generation innovation model: description of a success model

Cited by 36 publications

References 4 publications

Building up a national network of applied R&D institutes in an emerging innovation system

Building up a national network of applied R&D institutes in an emerging innovation system

Rapid Response in an Uncertain Environment: Study of COVID-19 Scientific Research Under the Parallel Model

Towards Knowledge Exchange for Effective Innovation Support

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