The growing adoption of artificial intelligence in healthcare is fostering the emergence of new entrepreneurial ventures capable of transforming clinical, organizational, and relational processes. However, the technological potential of AI-based healthcare startups does not automatically translate into actual benefits for patients, healthcare professionals, and organizations. While AI solutions may improve the quality and personalization of care, optimize resource allocation, accelerate processes, and support knowledge discovery, they may also generate negative effects related to errors, algorithmic bias, limited interoperability, increased workload, privacy concerns, and difficulties in integrating technologies into existing workflows. This thesis investigates the mechanisms of value creation and value destruction associated with healthcare startups developing or adopting artificial intelligence solutions. The study first examines the digital transformation of healthcare, the main applications of AI, the characteristics of digital entrepreneurship, and the business models adopted by healthcare startups. It then explores the concept of value within the healthcare ecosystem, distinguishing between value proposition, value creation, value delivery, and value capture. The empirical analysis is based on the collection and processing of online reviews concerning the startups included in the research database. These reviews are used as a source of information to identify users’ perceptions and detect evidence related to potential mechanisms of value creation and destruction. By describing the data sources, sample selection criteria, data-processing procedures, and variables considered, the study aims to provide a structured interpretation of the contribution of AI-based healthcare startups to the digital healthcare ecosystem, as well as of the main factors that may limit their impact.
La crescente diffusione dell’intelligenza artificiale nel settore sanitario sta favorendo la nascita di nuove iniziative imprenditoriali capaci di trasformare i processi clinici, organizzativi e relazionali. Tuttavia, il potenziale tecnologico delle soluzioni sviluppate dalle startup healthcare non si traduce automaticamente in benefici effettivi per pazienti, professionisti e organizzazioni sanitarie. L’adozione dell’AI può infatti contribuire al miglioramento della qualità dell’assistenza, alla personalizzazione delle cure, all’ottimizzazione delle risorse e all’accelerazione dei processi, ma può anche generare effetti negativi connessi a errori, bias, scarsa interoperabilità, incremento del carico di lavoro, problemi di privacy e difficoltà di integrazione nei flussi operativi. La tesi analizza le dinamiche di creazione e distruzione di valore associate alle startup healthcare basate sull’intelligenza artificiale. Dopo aver ricostruito il quadro teorico relativo alla trasformazione digitale della sanità, alle principali applicazioni dell’AI e ai modelli di business delle nuove imprese, il lavoro approfondisce il concetto di valore nell’ecosistema sanitario, distinguendo tra proposta di valore, valore effettivamente prodotto e valore catturato dall’impresa. L’analisi empirica si basa sulla raccolta e sul trattamento delle recensioni online riferite alle startup incluse nel database di ricerca. Le recensioni vengono utilizzate come fonte informativa per rilevare le percezioni degli utilizzatori e individuare evidenze riconducibili a meccanismi di creazione o distruzione di valore. Attraverso la descrizione delle fonti, dei criteri di selezione, delle procedure di trattamento dei dati e delle variabili considerate, lo studio mira a offrire una lettura strutturata del contributo delle startup all’ecosistema sanitario digitale e delle principali criticità che possono limitarne l’impatto.
INTELLIGENZA ARTIFICIALE E IMPRENDITORIALITÀ DIGITALE IN SANITÀ: CREAZIONE E DISTRUZIONE DI VALORE NELLE STARTUP HEALTHCARE
RUGGIERO, MARA
2025/2026
Abstract
The growing adoption of artificial intelligence in healthcare is fostering the emergence of new entrepreneurial ventures capable of transforming clinical, organizational, and relational processes. However, the technological potential of AI-based healthcare startups does not automatically translate into actual benefits for patients, healthcare professionals, and organizations. While AI solutions may improve the quality and personalization of care, optimize resource allocation, accelerate processes, and support knowledge discovery, they may also generate negative effects related to errors, algorithmic bias, limited interoperability, increased workload, privacy concerns, and difficulties in integrating technologies into existing workflows. This thesis investigates the mechanisms of value creation and value destruction associated with healthcare startups developing or adopting artificial intelligence solutions. The study first examines the digital transformation of healthcare, the main applications of AI, the characteristics of digital entrepreneurship, and the business models adopted by healthcare startups. It then explores the concept of value within the healthcare ecosystem, distinguishing between value proposition, value creation, value delivery, and value capture. The empirical analysis is based on the collection and processing of online reviews concerning the startups included in the research database. These reviews are used as a source of information to identify users’ perceptions and detect evidence related to potential mechanisms of value creation and destruction. By describing the data sources, sample selection criteria, data-processing procedures, and variables considered, the study aims to provide a structured interpretation of the contribution of AI-based healthcare startups to the digital healthcare ecosystem, as well as of the main factors that may limit their impact.| File | Dimensione | Formato | |
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RUGGIERO_tesi.pdf
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Descrizione: Tesi di laurea magistrale in Ingegneria Gestionale (Strategia e Organizzazione Aziendale), versione definitiva comprensiva di liberatoria.
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1.34 MB | Adobe PDF |
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https://hdl.handle.net/20.500.14253/110943