<?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>2026-09-19T12:57:13Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/104566" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/104566</identifier><datestamp>2022-01-27T21:49:30Z</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">Hazhir Rahmandad and Hamsa Balakrishnan.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Kellogg, Erin C</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. Department of Aeronautics and Astronautics</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2016-09-30T19:35:58Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2016-09-30T19:35:58Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/104566</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">958660634</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016. 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 71-72).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">General trends in the commercial aircraft aftermarket indicate an increased reliance of leased engines in operators' spare engine strategies. A methodology for forecasting short-term engine lease demand is developed using Pratt &amp; Whitney's existing simulation capability. This method demonstrates the ability to estimate demand mean and variance. This forecast is then used in a single SKU inventory model to set inventory levels. Using historical data this method demonstrates the ability to recommend inventory levels that minimize stock outs. A less computationally intensive system dynamics model is then constructed to replicate the lease demand forecasting model. Sensitivity analysis is performed using the system dynamic model and influential parameters are identified. The results of the sensitivity study are used to propose and test a new sales strategy for short-term engine lessors.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Erin C. Kellogg.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.B.A.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">84 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>
   <dim:field mdschema="dc" element="subject" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Aeronautics and Astronautics.</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">Internal dynamics of the short-term commercial aircraft engine leasing market</dim:field>
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   	&lt;Title>Internal dynamics of the short-term commercial aircraft engine leasing market&lt;/Title>
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   	&lt;PublicationDate>2016&lt;/PublicationDate>
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    &lt;Keyword>Sloan School of Management.&lt;/Keyword>
    &lt;Keyword>Aeronautics and Astronautics.&lt;/Keyword>
    &lt;Keyword>Leaders for Global Operations Program.&lt;/Keyword>
   	&lt;Abstract>General trends in the commercial aircraft aftermarket indicate an increased reliance of leased engines in operators&amp;apos; spare engine strategies. A methodology for forecasting short-term engine lease demand is developed using Pratt &amp;amp; Whitney&amp;apos;s existing simulation capability. This method demonstrates the ability to estimate demand mean and variance. This forecast is then used in a single SKU inventory model to set inventory levels. Using historical data this method demonstrates the ability to recommend inventory levels that minimize stock outs. A less computationally intensive system dynamics model is then constructed to replicate the lease demand forecasting model. Sensitivity analysis is performed using the system dynamic model and influential parameters are identified. The results of the sensitivity study are used to propose and test a new sales strategy for short-term engine lessors.&lt;/Abstract>
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