Artificial intelligence adoption across firm sizes: a systematic review of drivers, barriers and strategies
Venturi, Luca (A.A. 2024/2025) Artificial intelligence adoption across firm sizes: a systematic review of drivers, barriers and strategies. Tesi di Laurea in Business and marketing analytics, Luiss Guido Carli, relatore Andrea De Mauro, pp. 106. [Master's Degree Thesis]
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Abstract/Index
Theoretical background. SMEs and LCs: characteristics and differences. Frameworks for interpreting AI adoption. AI adoption in SMEs: general overview from literature. AI adoption in large enterprises: general overview from literature. Identifying key comparative dimensions from existing literature. Methodology. Adherence to PRISMA guidelines. Search strategy. Inclusion and exclusion criteria. Data extraction. Quality appraisal/risk of bias assessment. Data synthesis method. Drivers of AI adoption through TOE and RBV (RQ1). Barriers and enablers: a resource and capabilities perspective. Technologies and application patterns: adoption logic and innovation types. Benefits and strategic impact: short-term value vs long-term advantage. Strategic models and implementation logics.
References
Bibliografia: pp. 81-93.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Marketing (LM-77) |
| Chair: | Business and marketing analytics |
| Thesis Supervisor: | De Mauro, Andrea |
| Thesis Co-Supervisor: | Pelaez Martinez, Andrea |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 25 Sep 2025 14:05 |
| Last Modified: | 25 Sep 2025 14:05 |
| URI: | https://tesi.luiss.it/id/eprint/43315 |
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