Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/2690
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dc.contributor.authorAnita Raja
dc.date.accessioned2020-03-16T18:19:19Z-
dc.date.available2020-03-16T18:19:19Z-
dc.date.issued2017-04-12
dc.identifier.citationPublished--Unlimited Distribution
dc.identifier.urihttps://dair.nps.edu/handle/123456789/2690-
dc.descriptionAcquisition Management / Grant-funded Research
dc.description.abstractThe overall goal of this paper is to continue our efforts to forge new ground in identifying the effects of interdependencies in large complex networked applications and, if needed, uncovering early indicators of interdependency risk so that appropriate risk mitigation actions may be taken. Specifically, we seek to study and quantify the impact of network characteristics on cascading risk. Cascading risk is defined as the propagation of programmatic issues across networked programs due to the interdependency of one program upon the other. Harnessing the extensive data that has been collected over the years in the form of Defense Acquisition Execution Summary (DAES), Selected Acquisition Reports (SARs) and Contract data for Major Defense Acquisition Programs (MDAPS), we will present our intermediate results in our ongoing efforts on leveraging network structure and sequential data to study cascading risks. We will also identify the challenges to data acquisition.
dc.description.sponsorshipAcquisition Research Program
dc.languageEnglish (United States)
dc.publisherAcquisition Research Program
dc.relation.ispartofseriesCascading Consequences
dc.relation.ispartofseriesTCU-AM-17-040
dc.subjectModeling
dc.subjectInterdependent Networks
dc.subjectDefense Acquisition Execution Summary
dc.subjectDAES
dc.subjectSelected Acquisition Reports
dc.subjectSARs
dc.titleModeling Uncertainty and Its Implications in Complex Interdependent Networks
dc.typeTechnical Report
Appears in Collections:Sponsored Acquisition Research & Technical Reports

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