Disruptions in the Space Ecosystem: Early Identification
El Kawas, Zouheir
Disruptions in the Space Ecosystem: Early Identification - 2025.
38
This research investigates how incumbents can identify and interpret early indicators of disruptive innovations in high-tech, uncertain environments. Despite growing interest in weak signals and strategic foresight, systematic approaches to distinguish credible early signals from ambient noise remain underdeveloped. By integrating Disruptive Innovation Theory, Weak Signals and Strategic Foresight, and Signaling Theory, this study develops a structured, theory-informed process for detecting and validating early signals. Methodologically, it combines text mining of scientific and technical corpora with Delphi expert rounds to assess the novelty, relevance, and credibility of emerging signals. Abductive logic supports an iterative interplay between theory and data, fostering grounded insights into the dynamics of disruption. Focusing on the space ecosystem, marked by disruptive entrants, shifting market dynamics, and evolving governance structures, the framework uncovers and interprets early signals of innovation. Findings provide theoretical and practical tools for innovation monitoring and proactive decision-making under conditions of ambiguity.
Disruptions in the Space Ecosystem: Early Identification - 2025.
38
This research investigates how incumbents can identify and interpret early indicators of disruptive innovations in high-tech, uncertain environments. Despite growing interest in weak signals and strategic foresight, systematic approaches to distinguish credible early signals from ambient noise remain underdeveloped. By integrating Disruptive Innovation Theory, Weak Signals and Strategic Foresight, and Signaling Theory, this study develops a structured, theory-informed process for detecting and validating early signals. Methodologically, it combines text mining of scientific and technical corpora with Delphi expert rounds to assess the novelty, relevance, and credibility of emerging signals. Abductive logic supports an iterative interplay between theory and data, fostering grounded insights into the dynamics of disruption. Focusing on the space ecosystem, marked by disruptive entrants, shifting market dynamics, and evolving governance structures, the framework uncovers and interprets early signals of innovation. Findings provide theoretical and practical tools for innovation monitoring and proactive decision-making under conditions of ambiguity.
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