The rise of quantum technologies represents one of the most radical frontiers of contemporary innovation, promising to redefine entire industrial sectors through unprecedented computational and precision paradigms. In this scenario, venture capital acts as the financial architect of a revolution characterised by extreme information asymmetry and the absence of conventional benchmarks. Despite the strategic and geopolitical importance of the sector, the logic behind the allocation of private capital in a domain so fraught with scientific uncertainty remains largely unexplored. This thesis aims to fill this gap by analysing the decision-making criteria and capital allocation models in the quantum sector, to determine whether the intrinsic nature of this technology imposes screening logic and risk parameters on investors that differ from other deep-tech segments. The methodology follows a mixed approach: a quantitative analysis based on a proprietary census of approximately 570 startups and a qualitative case study conducted through semi-structured interviews with eight venture capital firms. The latter phase, developed through systematic coding, reconstructs investors' evaluation practices, risk perceptions and strategic constraints. The results highlight a non-neutral allocation of capital: investors favour infrastructure and enabling layers over end applications, thereby reducing dependence on downstream market uncertainty. Interviews validate this risk mitigation approach showing a preference for solutions based on rigorous science and cross-sector technological relevance. The evaluation of startups follows a precise hierarchy: the team and its scientific credibility are fundamental, followed by the solidity of the technical roadmap and intellectual property, and finally, market valuation acts as an investment multiplier. Quantum technologies differ from other deep-tech domains because uncertainty extends beyond technical execution to encompass market discovery. The limitations of this thesis stem primarily from the structural immaturity of the quantum ecosystem, which results in significant constraints regarding data availability, transparency and temporal stability. Furthermore, the high degree of technological heterogeneity within the industry complicates the development of universal frameworks or models applicable to all startups in the sector. Future studies should extend the analysis longitudinally, examining the impact of public capital and procurement on private venture capital through comparative surveys of geopolitical ecosystems with different innovation policies.
L'ascesa delle tecnologie quantistiche rappresenta una delle frontiere più radicali dell'innovazione contemporanea, promettendo di ridefinire interi settori industriali attraverso paradigmi computazionali e di precisione senza precedenti. In questo scenario, il Venture Capital agisce come l'architetto finanziario di una rivoluzione caratterizzata da un’asimmetria informativa estrema e dall’assenza di benchmark convenzionali. Nonostante l'importanza strategica e geopolitica del comparto, le logiche che guidano l'allocazione del capitale privato in un dominio così denso di incertezza scientifica rimangono ampiamente inesplorate. Questa tesi si propone di colmare tale lacuna analizzando i criteri decisionali e i modelli di allocazione del capitale nel comparto quantistico, al fine di determinare se la natura intrinseca di questa tecnologia imponga agli investitori logiche di screening e parametri di rischio divergenti rispetto ad altri segmenti deep-tech. La metodologia segue un approccio misto: un’analisi quantitativa basata su un censimento proprietario di circa 570 startup e uno studio di caso qualitativo condotto tramite interviste semi-strutturate a otto società di Venture Capital. Quest'ultima fase, elaborata tramite codifica sistematica, ricostruisce le pratiche valutative, le percezioni del rischio e i vincoli strategici degli investitori. I risultati evidenziano un’allocazione del capitale non neutrale: gli investitori privilegiano infrastrutture e livelli abilitanti rispetto alle applicazioni finali, riducendo così la dipendenza dall'incertezza del mercato a valle. Le interviste confermano questa strategia di mitigazione del rischio: vengono privilegiate soluzioni con una solida base scientifica e una rilevanza trasversale della tecnologia. La valutazione delle startup segue una gerarchia precisa: il team e la sua credibilità scientifica sono fondamentali, seguiti dalla solidità della roadmap tecnica e della proprietà intellettuale e, infine, dalla valutazione del mercato, che agisce come moltiplicatore dell'investimento. Il Quantum si distingue da altri ambiti deep-tech perché l'incertezza non riguarda solo la capacità realizzativa, ma risiede anche nel trovare il mercato finale. I limiti di questa tesi derivano principalmente dall'immaturità strutturale del mercato quantistico e dai conseguenti vincoli in termini di disponibilità di dati, trasparenza e stabilità temporale. A questo si aggiunge l’eterogeneità delle tecnologie nella stessa industria, che rende difficile la creazione di framework e modelli validi per tutte le startup del settore. Studi futuri potrebbero estendere l'analisi in senso longitudinale, esaminando l’impatto dei capitali e degli appalti pubblici sul venture capital privato, attraverso indagini comparative tra ecosistemi geopolitici con diverse politiche di innovazione.
Venture capital decision-making in quantum technologies: an analysis of investment criteria and risk mitigation
EVANGELISTI, MIRKO
2024/2025
Abstract
The rise of quantum technologies represents one of the most radical frontiers of contemporary innovation, promising to redefine entire industrial sectors through unprecedented computational and precision paradigms. In this scenario, venture capital acts as the financial architect of a revolution characterised by extreme information asymmetry and the absence of conventional benchmarks. Despite the strategic and geopolitical importance of the sector, the logic behind the allocation of private capital in a domain so fraught with scientific uncertainty remains largely unexplored. This thesis aims to fill this gap by analysing the decision-making criteria and capital allocation models in the quantum sector, to determine whether the intrinsic nature of this technology imposes screening logic and risk parameters on investors that differ from other deep-tech segments. The methodology follows a mixed approach: a quantitative analysis based on a proprietary census of approximately 570 startups and a qualitative case study conducted through semi-structured interviews with eight venture capital firms. The latter phase, developed through systematic coding, reconstructs investors' evaluation practices, risk perceptions and strategic constraints. The results highlight a non-neutral allocation of capital: investors favour infrastructure and enabling layers over end applications, thereby reducing dependence on downstream market uncertainty. Interviews validate this risk mitigation approach showing a preference for solutions based on rigorous science and cross-sector technological relevance. The evaluation of startups follows a precise hierarchy: the team and its scientific credibility are fundamental, followed by the solidity of the technical roadmap and intellectual property, and finally, market valuation acts as an investment multiplier. Quantum technologies differ from other deep-tech domains because uncertainty extends beyond technical execution to encompass market discovery. The limitations of this thesis stem primarily from the structural immaturity of the quantum ecosystem, which results in significant constraints regarding data availability, transparency and temporal stability. Furthermore, the high degree of technological heterogeneity within the industry complicates the development of universal frameworks or models applicable to all startups in the sector. Future studies should extend the analysis longitudinally, examining the impact of public capital and procurement on private venture capital through comparative surveys of geopolitical ecosystems with different innovation policies.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/250872