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008181129s2018 ||| | | | eng d
020 ▼a 9780438125339
035 ▼a (MiAaPQ)AAI10902926
035 ▼a (MiAaPQ)umichrackham:001229
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 658
1001 ▼a Jiang, Yuchen.
24510 ▼a Supply Chain and Revenue Management for Online Retailing.
260 ▼a [S.l.] : ▼b University of Michigan., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 125 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Advisers: Siqian May Shen
5021 ▼a Thesis (Ph.D.)--University of Michigan, 2018.
520 ▼a This dissertation focuses on optimizing inventory and pricing decisions in the online retail industry. Motivated by the importance of great customer service quality in the online retail marketplace, we investigate service-level-constrained inven
520 ▼a The first essay studies multi-period production planning problems (with or without pricing options) under stochastic demand. A joint service-level constraint is enforced to restrict the joint probability of having backorders in any period. We us
520 ▼a The second essay investigates the dynamic versions of the service-level-constrained inventory control problems, in which retailers have the flexibility to adjust their inventory policies in each period. We formulate two periodic-review stochasti
520 ▼a The third essay is motivated by the exploding use of sales rank information in today's internet-based e-commerce marketplace. The sales rank affects consumers' shopping preference and therefore, is critical for retailers to utilize when making p
590 ▼a School code: 0127.
650 4 ▼a Industrial engineering.
690 ▼a 0546
71020 ▼a University of Michigan. ▼b Industrial & Operations Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0127
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000437 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자