Deep-tech startups operate in contexts characterized by high technological uncertainty, long development cycles and significant capital intensity. Consequently, they often face prolonged pre-revenue phases during which revenues from the core technology remain absent for several years. Although entrepreneurship research has extensively examined financing constraints and pivoting as adaptation mechanisms, limited attention has been devoted to understanding how deep-tech ventures strategically navigate extended periods without revenues. This study addresses this gap by investigating how deep-tech startups manage prolonged pre-revenue phases and how strategic adaptation mechanisms emerge. Adopting a qualitative multiple case study design, the research analyses seven startups within the Italian space economy belonging to the Galaxia portfolio. Data were collected through semi-structured interviews with founders, complemented by secondary sources. Iterative within-case and cross-case analysis led to the development of a process-oriented model linking drivers, resource mobilization and strategic pathways. Findings show that adaptation during prolonged pre-revenue phases takes the form of structured, application-level reconfiguration rather than radical technological change. Four key drivers (financial sustainability needs, application domain ambiguity, validation requirements and stakeholder feedback) activate distinct resource mobilization processes, giving rise to three strategic pathways: Synergy-driven portfolio, Validation-oriented portfolio and Market-pull portfolio. The first two reflect a technology-push logic, while the third follows a market-pull logic. Across all cases, the core technology is preserved, while adaptation occurs at the level of applications and market positioning. By moving beyond pivot-centric explanations, this study offers a configurational framework for understanding deep-tech adaptation under prolonged pre-revenue conditions.
Le startup deep-tech operano in contesti caratterizzati da elevata incertezza tecnologica, lunghi cicli di sviluppo e significativa intensità di capitale. Di conseguenza, affrontano spesso fasi pre-revenue prolungate, durante le quali i ricavi derivanti dalla tecnologia core rimangono assenti per diversi anni. Sebbene la letteratura imprenditoriale abbia ampiamente analizzato i vincoli finanziari e il pivoting come meccanismi di adattamento all’incertezza, risulta ancora limitata la comprensione di come le imprese deep-tech gestiscano strategicamente periodi estesi in assenza di ricavi. Questo studio affronta tale lacuna indagando come le startup deep-tech navigano le fasi pre-revenue prolungate e come emergono i meccanismi di adattamento strategico. La ricerca adotta un approccio qualitativo di multiple case study, analizzando sette startup operanti nella space economy italiana e appartenenti al portfolio Galaxia. I dati sono stati raccolti tramite interviste semi-strutturate con i founder, integrate da fonti secondarie. Attraverso un’analisi iterativa intra- e cross-case, è stato sviluppato un modello processuale che collega driver, mobilitazione delle risorse e percorsi strategici. I risultati mostrano che l’adattamento durante le fasi pre-revenue prolungate assume la forma di riconfigurazioni strutturate a livello applicativo, piuttosto che di cambiamenti tecnologici radicali. Emergono quattro driver principali (esigenze di sostenibilità finanziaria, ambiguità del dominio applicativo, necessità di validazione e feedback degli stakeholder) che attivano specifici processi di mobilitazione delle risorse, dando origine a tre percorsi strategici: Synergy-driven portfolio, Validation-oriented portfolio e Market-pull portfolio. I primi due riflettono una logica di technology-push, mentre il terzo segue una logica di market-pull. In tutti i casi analizzati, la traiettoria tecnologica di base è preservata, mentre l’adattamento avviene a livello di applicazioni e posizionamento di mercato. Superando una visione centrata esclusivamente sul pivot, lo studio propone un framework configurazionale per comprendere l’adattamento delle startup deep-tech in condizioni di pre-revenue prolungata.
Strategic adaptation in deep-tech startups during prolonged pre-revenue phases: evidence from the space economy sector
PISATI, CHIARA
2025/2026
Abstract
Deep-tech startups operate in contexts characterized by high technological uncertainty, long development cycles and significant capital intensity. Consequently, they often face prolonged pre-revenue phases during which revenues from the core technology remain absent for several years. Although entrepreneurship research has extensively examined financing constraints and pivoting as adaptation mechanisms, limited attention has been devoted to understanding how deep-tech ventures strategically navigate extended periods without revenues. This study addresses this gap by investigating how deep-tech startups manage prolonged pre-revenue phases and how strategic adaptation mechanisms emerge. Adopting a qualitative multiple case study design, the research analyses seven startups within the Italian space economy belonging to the Galaxia portfolio. Data were collected through semi-structured interviews with founders, complemented by secondary sources. Iterative within-case and cross-case analysis led to the development of a process-oriented model linking drivers, resource mobilization and strategic pathways. Findings show that adaptation during prolonged pre-revenue phases takes the form of structured, application-level reconfiguration rather than radical technological change. Four key drivers (financial sustainability needs, application domain ambiguity, validation requirements and stakeholder feedback) activate distinct resource mobilization processes, giving rise to three strategic pathways: Synergy-driven portfolio, Validation-oriented portfolio and Market-pull portfolio. The first two reflect a technology-push logic, while the third follows a market-pull logic. Across all cases, the core technology is preserved, while adaptation occurs at the level of applications and market positioning. By moving beyond pivot-centric explanations, this study offers a configurational framework for understanding deep-tech adaptation under prolonged pre-revenue conditions.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/252687