The transition from traditional government-led space programs to the commercial New Space Economy presents a critical context for understanding the evolution of nascent industries, where pervasive multidimensional uncertainty requires heterogeneous actors to engage in recursive actions to navigate developmental milestones. This thesis investigates how the collective interpretation of uncertainty evolves and refines throughout the emergence of a nascent industry. The research adopts a qualitative single-case study with a longitudinal design focused on the Italian Space Economy ecosystem. The empirical data cover five editions of a Space Economy Research Center (2020–2025), comprising 28 workshops and extensive secondary documentation, which were systematically analyzed to trace the interactions of heterogeneous actors. The findings reveal a process of Uncertainty Refinement that unfolds through three distinct interpretive states: Vision Framing, where uncertainty is interpreted through broad optimism, Reality Grounding, where specific constraints become explicit, and Priority Alignment, where the ecosystem converges on a bounded, actionable agenda. Adopting established knowledge-building mechanisms as an analytical lens, the study characterizes their functional evolution based on the uncertainty state, demonstrating how they shift from expanding options to stabilizing shared reference points. Ultimately, this dissertation reframes uncertainty reduction as a qualitative interpretive refinement rather than mere knowledge accumulation, revealing how knowledge-building mechanisms functionally evolve from diagnosing constraints to structuring convergence.
La transizione dai tradizionali programmi spaziali guidati dallo Stato alla New Space Economy offre un contesto cruciale per comprendere l’evoluzione delle industrie nascenti, in cui l’incertezza pervasiva richiede che gli attori coinvolti intraprendano azioni per attraversare le principali tappe dello sviluppo. La presente tesi indaga come l’interpretazione collettiva dell’incertezza evolva e si raffini durante l’emergere di un’industria nascente. La ricerca adotta uno studio di caso singolo, qualitativo e longitudinale, focalizzato sull’ecosistema italiano della New Space Economy. I dati empirici coprono cinque edizioni di un centro di ricerca sulla Space Economy (2020–2025) e includono 28 workshop e un’ampia documentazione secondaria. Il materiale è stato analizzato in modo sistematico per ricostruire e interpretare le interazioni tra gli attori eterogenei. I risultati evidenziano un processo di raffinamento dell’incertezza che si articola in tre distinti stati interpretativi: Vision Framing, in cui l’incertezza è letta in chiave ottimistica, Reality Grounding, in cui si rendono espliciti vincoli specifici, e Priority Alignment, in cui l’ecosistema converge su un’agenda operativa. Adottando i meccanismi consolidati di knowledge-building come lente analitica, lo studio ne caratterizza l’evoluzione in funzione dello stato dell’incertezza. Nel complesso, la tesi riformula la riduzione dell’incertezza come un processo di raffinamento interpretativo, piuttosto che come un’accumulazione di conoscenza, mostrando come i meccanismi di knowledge-building evolvano in funzione dello stato dell’incertezza.
The rise of the italian new space economy: a multi-actor longitudinal observation
De Manna, Stefano Andrea;Duval, Vittorio
2024/2025
Abstract
The transition from traditional government-led space programs to the commercial New Space Economy presents a critical context for understanding the evolution of nascent industries, where pervasive multidimensional uncertainty requires heterogeneous actors to engage in recursive actions to navigate developmental milestones. This thesis investigates how the collective interpretation of uncertainty evolves and refines throughout the emergence of a nascent industry. The research adopts a qualitative single-case study with a longitudinal design focused on the Italian Space Economy ecosystem. The empirical data cover five editions of a Space Economy Research Center (2020–2025), comprising 28 workshops and extensive secondary documentation, which were systematically analyzed to trace the interactions of heterogeneous actors. The findings reveal a process of Uncertainty Refinement that unfolds through three distinct interpretive states: Vision Framing, where uncertainty is interpreted through broad optimism, Reality Grounding, where specific constraints become explicit, and Priority Alignment, where the ecosystem converges on a bounded, actionable agenda. Adopting established knowledge-building mechanisms as an analytical lens, the study characterizes their functional evolution based on the uncertainty state, demonstrating how they shift from expanding options to stabilizing shared reference points. Ultimately, this dissertation reframes uncertainty reduction as a qualitative interpretive refinement rather than mere knowledge accumulation, revealing how knowledge-building mechanisms functionally evolve from diagnosing constraints to structuring convergence.| File | Dimensione | Formato | |
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2026_03_De Manna_Duval_Executive Summary.pdf
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2026_03_De Manna_Duval_Tesi.pdf
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https://hdl.handle.net/10589/252719