| LDR | | 02484nam u200457 4500 |
| 001 | | 000000422404 |
| 005 | | 20190215170111 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438177802 |
| 035 | |
▼a (MiAaPQ)AAI10828673 |
| 035 | |
▼a (MiAaPQ)washington:18909 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 658 |
| 100 | 1 |
▼a Nabi-Abdolyousefi, Sareh. |
| 245 | 10 |
▼a Study of Customer Behavior in a Revenue Management Setting Using Data-Driven Approaches. |
| 260 | |
▼a [S.l.]:
▼b University of Washington.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 101 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Adviser: Hamed Mamani. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Washington, 2018. |
| 520 | |
▼a The objective of this study is to propose novel dynamic pricing mechanisms in the presence of strategic customers using data-driven approaches. Dynamic pricing is the latest trend in pricing strategies and allows optimal response to real-time de |
| 520 | |
▼a In chapters 1 and 2, we study a retailer who is pricing dynamically to maximize his expected cumulative revenue. We assume that the retailer has no information regarding expected demand nor the type of customers he is facing, whether they are my |
| 520 | |
▼a We start our analysis with a Bernoulli demand scenario in chapter 1 and extend our work to a Normal demand scenario in chapter 2. For both Bernoulli and Normal demand scenarios, we demonstrate numerically that the retailer's long run price offer |
| 520 | |
▼a Our objective in chapter 3 is to improve our starting point by building an informative prior and more specifically, an empirical Bayes prior for the Bayesian online learning algorithm that performs binary prediction. The underlying model used in |
| 590 | |
▼a School code: 0250. |
| 650 | 4 |
▼a Operations research. |
| 650 | 4 |
▼a Artificial intelligence. |
| 650 | 4 |
▼a Management. |
| 690 | |
▼a 0796 |
| 690 | |
▼a 0800 |
| 690 | |
▼a 0454 |
| 710 | 20 |
▼a University of Washington.
▼b Business Administration. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0250 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999202
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |