Leveraging complexity for ecosystemic innovation

Martha G. Russell and Nataliya Smorodinskaya

Technological Forecasting and Social Change, 2018, vol. 136, issue C, 114-131

Abstract: This paper looks at innovation ecosystems through the lens of complexity science, considering them as open non-linear entities that are characterized by changing multi-faceted motivations of networked actors, high receptivity to feedback, and persistent structural transformations. In the context of the growing organizational complexity of economies, driven by their adaptation to high uncertainty, and the central role of collaboration, we differentiate the innovation capacity of various types of business networks by the complexity of their internal interactions, thus identifying the place of innovation ecosystems in the world of business networks, as well as the place of innovation clusters among other innovation ecosystems. We observe how innovation ecosystems have been viewed in four different research streams: management literature; the inter-firm and business network stream of economic and sociological literature; the innovation policy and competitiveness agenda in economic literature; and the dichotomy of localized and economy-wide innovation ecosystems in policy studies (in economic literature, evolutionary geography, and regional research). We then describe generic properties of innovation ecosystems in terms of complexity science, viewing them as complex adaptive systems, paying special attention to the complexity of innovation clusters. We compare complexity thinking of modern economies, deriving from their emerging ecosystem design, with traditional thinking conceived for industrial era, drawing insights for a better transition to innovation-led growth. We conclude with a summary of key findings, practical and policy implications and recommendations for further study.

Keywords: Business network; Collaboration; Complexity; Innovation ecosystem; Innovation cluster; Global economy; Non-linearity (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (53)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:136:y:2018:i:c:p:114-131

DOI: 10.1016/j.techfore.2017.11.024

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