Document Type : Original Article
Authors
1
Ph.D. Candidate, Department of Technology Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2
Professor, Department of Information Technology Management, Tarbiat Modares University, Tehran, Iran
3
Faculty Member, School of Business-Capilano University, Vancouver, Canada
10.22034/jstp.2024.11529.1710
Abstract
In this research, a systematic review was conducted to assess the impact of complexity and chaos theory on understanding and explaining the development and evolution of innovation ecosystems. To this end, the theoretical foundations required for this study were collected by first reviewing the literature on these two theories. Then PRISMA protocol was followed, and published articles from 2005 to the end of 2023 in the field of innovation ecosystems that directly or indirectly utilized complexity and chaos theory or their characteristics for analysis were selected and filtered in four stages upon document type and language, relation to innovation ecosystem development and evolution and using complexity as a theory not as a common word, that resulting in 43 articles. The findings indicate that selecting the most suitable framework for understanding the development and evolution of innovation ecosystems depends on several factors, including the research objective, the nature of the ecosystem, the level of analysis, and the available data. Accordingly, by combining the findings and results obtained from this systematic review and the principles and characteristics of complexity theory, chaos theory, and complex adaptive systems, a new and comprehensive theoretical framework is proposed for understanding the development and evolution of innovation ecosystems. This framework includes the key components of actors and relationships, innovation processes, environment, dynamics and evolution, co-opetition performance, the role of enabling technologies, the importance of data and information, the role of government and policymaking, the role of culture and society, novelty and self-organization, time horizons and the edge of chaos, sensitivity to initial conditions, and state space and strange attractors. It can be applied for policy design, ecosystem assessment, prediction, and education planning.
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