| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000329837 |
| 005 | | 20241016155016 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438376687 |
| 035 | |
▼a (MiAaPQ)AAI10823700 |
| 035 | |
▼a (MiAaPQ)duke:14756 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 658 |
| 100 | 1 |
▼a Modaresi, Sajad. |
| 245 | 10 |
▼a Data-Driven Learning Models With Applications to Retail Operations. |
| 260 | |
▼a [S.l.] :
▼b Duke University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 214 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: A. |
| 500 | |
▼a Adviser: Fernando Bernstein. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Duke University, 2018. |
| 520 | |
▼a Data-driven approaches to decision-making under uncertainty is at the center of many operational problems. These are problems in which there is an element of uncertainty (e.g., customer demand) that needs to be estimated (learned) from data (e. |
| 520 | |
▼a The first two essays in this dissertation study the classic exploration (i.e., parameter estimation) versus exploitation (i.e., optimization) trade-off from different perspectives. The first essay takes a theoretical approach and studies such |
| 520 | |
▼a The second essay considers the dynamic assortment personalization problem of an online retailer facing heterogeneous customers with unknown product preferences. We propose a prescriptive approach, called the dynamic clustering policy, for dynami |
| 520 | |
▼a Further focusing on retail operations, the final essay studies the interplay between a retailer's return and pricing policies and customers' purchasing decisions. We characterize the retailer's optimal prices in the cases with and without produc |
| 590 | |
▼a School code: 0066. |
| 650 | 4 |
▼a Business administration. |
| 690 | |
▼a 0310 |
| 710 | 20 |
▼a Duke University.
▼b Business Administration. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-02A(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0066 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998596
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |