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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