MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Intelligent product placement strategies for Amazon.com's worldwide fulfillment centers

Author(s)
Rubenstein, Linsey (Linsey Jill)
Thumbnail
DownloadFull printable version (8.154Mb)
Other Contributors
Leaders for Manufacturing Program.
Advisor
Stanley Gershwin and Jeremie Gallien.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Online retail has radically changed traditional supply chain operations by providing a direct-to-consumer model that eliminates the need for traditional brick-and-mortar retail stores. With this new order, retailers have had to design warehouse solutions that fit the changing operational requirements of online retail. Over the last several years, Amazon.com has become a market leader, capturing almost 8% of all online retail sales in 2005. As Amazon grows in size and scope it is faced with unique challenges in warehouse system design and strategy. A significant portion of Amazon's total fulfillment cost is in the "picking" process which is where associates pick items to fulfill customer orders. Picking costs are directly influenced by the upstream stowing process which determines where to physically store Amazon's retail items. Currently, Amazon's fulfillment centers stow inventory according to "profiling" rules which direct inventory to various locations in the warehouse in order to optimize the space utilization of the facility. However, these profiling rules do not account for the impact of the stowing decisions on the cost to pick and replenish products downstream.
 
(cont.) While facility space reaches capacity during peak season, the fulfillment centers are well below their physical space capacity the remainder of the year. Due to the cyclical nature of customer demand at Amazon, the current profiling strategy of optimizing space utilization may be sub-optimal during the low demand periods when space capacity is not a constraint. This thesis will test this hypothesis by exploring alternative product placement strategies for Amazon's fulfillment centers.
 
Description
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Manufacturing Program at MIT, 2006.
 
Page 66 blank.
 
Includes bibliographical references.
 
Date issued
2006
URI
http://hdl.handle.net/1721.1/37246
Department
Leaders for Manufacturing Program at MIT; Massachusetts Institute of Technology. Engineering Systems Division; Sloan School of Management
Publisher
Massachusetts Institute of Technology
Keywords
Sloan School of Management., Engineering Systems Division., Leaders for Manufacturing Program.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.