A Systematic Review of Innovation Ecosystem Subcategory Metaphors: Towards Evidence-Based Policymaking(مقاله علمی وزارت علوم)
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In recent years, ecological metaphors have gained popularity in the field of innovation. Such excessive preoccupation of researchers with common ecological metaphors, such as ecosystems, and a lack of due attention to the development of other ecological principles, challenges the systematic conceptual framework of the field. This raises the metaphorical concept of a "boundary object," which could hinder the connection between theoretical discussions on innovation ecosystems and their practical applications and policy development. Therefore, there is a need for an evidence-based approach to define and map the innovation ecosystem metaphorically. The concepts deployed would form a part of the conceptual network of the innovation ecosystem. As part of an effort to implement evidence-based practice in the field of innovation ecosystems, this study employs Scaringella's and Radziwon's (2019) systematic review framework and the comparative-qualitative content analysis method. The analysis is based on a structured matrix that is rooted in metaphor mapping. Upon analyzing the content of the selected articles, the ecological metaphors grounded in innovation ecosystems can be classified into two general categories: metaphors related to actors (species, population, and community) and metaphors related to the environment (landscape, biome, and ecotone). The developed framework serves as a tool for innovation policymakers, enabling them to make informed decisions by gaining a comprehensive understanding of the seven hierarchical metaphorical layers within innovation ecosystems. Consequently, policymakers should not restrict their governance to the suggestions offered by the prevailing literature on ecosystems. Instead, they should also give equal attention to the various dimensions of innovation ecosystems, including actors, the environment, and the relationships between them, from an ecological perspective.