A metaphorical framework for measuring the resilience of innovation ecosystems: a systematic review

Purpose The purpose of this paper is to identify the key factors influencing the resilience of innovation ecosystems and propose strategies for proactively managing disruptions to ensure their continued viability. Enhancing resilience within innovation ecosystems is a fundamental prerequisite for ensuring their sustainable development. The resilience of such ecosystems is commonly associated with their capacity to recover from disturbances. Consequently, to ensure their continued viability, innovation ecosystems must proactively manage disruptions by identifying the factors that influence resilience. Design/methodology/approach Given the relatively limited attention afforded to indicators impacting the resilience of innovation ecosystems thus far, this article endeavors to present a framework for assessing resilience within such ecosystems, drawing upon the metaphorical understanding of resilience in natural ecosystems. To achieve this objective, the present research adopts the metaphor research method, which involves delineating the research problem and elucidating the origin of the metaphor. Findings Subsequently, through content analysis, the indicators for evaluating resilience in natural ecosystems are identified, and corresponding indicators and components are derived for the innovation ecosystem. These indicators are categorized into five dimensions, encompassing ecosystem capabilities, ecosystem interactions and structure, ecosystem status, ecosystem capacity and ecosystem environment. Originality/value This article endeavors to present a resilience framework for innovation ecosystems, drawing on the metaphorical concept of resilience evident in natural ecosystems. Through the method of metaphor research, the article first elucidates the research problem and selects ecology as the primary source of metaphor. Subsequently, evaluation indicators of resilience in natural ecosystems are determined using theme analysis.