<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-22T07:59:49Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/90164" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/90164</identifier><datestamp>2022-01-28T15:02:42Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Leigh Hafrey and David Simchi-Levi.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Schrang, Oliver Stiles</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Leaders for Global Operations Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Leaders for Global Operations Program at MIT</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2014-09-19T21:43:33Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2014-09-19T21:43:33Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2014</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2014</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/90164</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">890199240</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M., Massachusetts Institute of Technology, Engineering Systems Division, 2014. In conjunction with the Leaders for Global Operations Program at MIT.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 55-56).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">As the commoditization of the PC market erodes product margins, increasing emphasis is placed on cost optimization within the supply chain. One critical component of this is the financial impact of inventory policies and the transportation choices affecting these policies. Overseas manufacturing and ocean transportation are the most cost-effective solutions, but this requires building products to a forecast. The uncertainty induced by forecasts affects the inventory volumes necessary to achieve specified service levels. Inventory volume and its associated holding cost can be reduced through air transport, but this must be balanced against the increased expense of this particular shipping option. This thesis seeks to develop a framework informing inventory levels, transportation policies, and replenishment decisions. Holding inventory to a target level that does not vary across product type or replenishment method has the advantages of ease of management and low inventory variability within merge centers, but is sub-optimal from a customer satisfaction and cost perspective. The model presented introduces a flexible approach that considers variations in product characteristics to determine optimal inventory and transportation strategies. Differences between generalized target inventory levels and the levels achievable through a non-uniform approach are demonstrated. The implications of these inventory levels on required forecast accuracy levels are also considered. From these differences are extrapolated cost savings under current commercial finished goods volumes for the North American region as well as target volumes for the same. Current and target ocean volumes are discussed, with an analysis of their effect on inventory levels and costs.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Oliver Stiles Schrang.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.B.A.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">56 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">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.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Leaders for Global Operations Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Modeling and analysis of commercial finished goods inventory</dim:field>
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   	&lt;Title>Modeling and analysis of commercial finished goods inventory&lt;/Title>
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   	&lt;PublicationDate>2014&lt;/PublicationDate>
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   	&lt;Abstract>As the commoditization of the PC market erodes product margins, increasing emphasis is placed on cost optimization within the supply chain. One critical component of this is the financial impact of inventory policies and the transportation choices affecting these policies. Overseas manufacturing and ocean transportation are the most cost-effective solutions, but this requires building products to a forecast. The uncertainty induced by forecasts affects the inventory volumes necessary to achieve specified service levels. Inventory volume and its associated holding cost can be reduced through air transport, but this must be balanced against the increased expense of this particular shipping option. This thesis seeks to develop a framework informing inventory levels, transportation policies, and replenishment decisions. Holding inventory to a target level that does not vary across product type or replenishment method has the advantages of ease of management and low inventory variability within merge centers, but is sub-optimal from a customer satisfaction and cost perspective. The model presented introduces a flexible approach that considers variations in product characteristics to determine optimal inventory and transportation strategies. Differences between generalized target inventory levels and the levels achievable through a non-uniform approach are demonstrated. The implications of these inventory levels on required forecast accuracy levels are also considered. From these differences are extrapolated cost savings under current commercial finished goods volumes for the North American region as well as target volumes for the same. Current and target ocean volumes are discussed, with an analysis of their effect on inventory levels and costs.&lt;/Abstract>
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