Optimization and (explainable) artificial intelligence for data-driven decision support in revenue and risk management
- Dissertation on the topic of optimization and (explainable) artificial intelligence for data-driven decision support in revenue and risk management. The dissertation comprises five articles, three of which address the research area of assortment optimization, one article aims at improving an existing GLM model by using (explainable) AI and one article is targeted at the analysis of credit spread changes using (explainable) AI.
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| Author: | Julia HegerORCiD |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1214692 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/121469 |
| Advisor: | Robert Klein |
| Type: | Doctoral Thesis |
| Language: | English |
| Year of first Publication: | 2025 |
| Publishing Institution: | Universität Augsburg |
| Granting Institution: | Universität Augsburg, Wirtschaftswissenschaftliche Fakultät |
| Date of final exam: | 2025/03/06 |
| Release Date: | 2025/05/21 |
| GND-Keyword: | Optimierung; Künstliche Intelligenz; Entscheidungsunterstützung |
| Pagenumber: | 209 |
| Institutes: | Wirtschaftswissenschaftliche Fakultät |
| Wirtschaftswissenschaftliche Fakultät / Institut für Statistik und mathematische Wirtschaftstheorie | |
| Wirtschaftswissenschaftliche Fakultät / Institut für Statistik und mathematische Wirtschaftstheorie / Lehrstuhl für Analytics & Optimization | |
| Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
| Licence (German): |  CC-BY-NC 4.0: Creative Commons: Namensnennung - Nicht kommerziell (mit Print on Demand) |
