Predictive shift of customer satisfaction measurement: how explainable AI impacts the final perceived credibility under the influence of users' concerns
Santi, Lorenzo (A.A. 2022/2023) Predictive shift of customer satisfaction measurement: how explainable AI impacts the final perceived credibility under the influence of users' concerns. Tesi di Laurea in Marketing metrics, Luiss Guido Carli, relatore Michele Costabile, pp. 48. [Master's Degree Thesis]
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Abstract/Index
Performance measurement evolution and the AI-based predictive shift: the role of explainable AI and users’ psychology. Mar-Tech evolution: a data-driven ecosystem. AI influence on marketing domain. Performance measurement and customer experience evolution. Customer satisfaction measurement: framework and future directions. The predictive transition: technologies and their impact. AI-user interaction: psychological concerns. The role of explainable AI. Literature review. The relationship between explainable AI and credibility. The relationship between explainability and perceived intrusiveness. Psychological concerns and intrusiveness impact on credibility. Conceptual framework. Experimental research. Methodological approach. Experimental results.
References
Bibliografia: pp. 34-44.
| 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: | Marketing metrics |
| Thesis Supervisor: | Costabile, Michele |
| Thesis Co-Supervisor: | Laura, Luigi |
| Academic Year: | 2022/2023 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 03 Jun 2024 11:07 |
| Last Modified: | 03 Jun 2024 11:07 |
| URI: | https://tesi.luiss.it/id/eprint/38692 |
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