Migliore, Francesco (A.A. 2023/2024) Data-driven business models: cases of three Italian start-ups. Tesi di Laurea in Data-driven innovation, Luiss Guido Carli, relatore Niloofar Kazemargii, pp. 90. [Master's Degree Thesis]

PDF (Full text) Restricted to Registered users only Download (5MB) | Request a copy

Abstract/Index

The problem. Link to existing literature. The research gap and research question. Research methods and objectives. Literature review. Data-driven business models: an overview. Mechanisms of data-driven innovation in start-ups. Challenges and opportunities in data-driven business models. Successful companies in data-driven innovation. Emerging trends and future directions. Methods. Research design and approach. Sample selection. Data collection. Questionnaire design. Data analysis. Ethical considerations. Limitations of the methodology. Results and discussion. Start-ups overview. Case study comparisons.

References

Bibliografia: pp. 86-88.

Thesis Type:	Master's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91)
Chair:	Data-driven innovation
Thesis Supervisor:	Kazemargii, Niloofar
Thesis Co-Supervisor:	Bontadini, Filippo
Academic Year:	2023/2024
Session:	Autumn
Deposited by:	Alessandro Perfetti
Date Deposited:	22 May 2025 10:31
Last Modified:	22 May 2025 10:31
URI:	https://tesi.luiss.it/id/eprint/42199

Downloads

Repository Staff Only

View Item