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dc.contributor.advisorShardul Phadnis.en_US
dc.contributor.authorXu, Xia, M. Eng. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.date.accessioned2014-12-08T18:50:23Z
dc.date.available2014-12-08T18:50:23Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/92122
dc.descriptionThesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, 2014.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 57).en_US
dc.description.abstractBeing able to quickly adapt to changes in the business environment has been widely acknowledged as essential for sustainable success by business leaders. Scenario planning is recognized as an effective tool used to explore ambiguous business environment dynamics over a long time horizon and identifying ways to translate uncertainty into potential future strategies. After the potential scenarios are developed and formulated into business strategies, the practical decision-making process then requires continuous review. Existing literature suggests that companies must actively monitor the business environment using appropriate indicators and understand their implications. This research specifically aims to develop a systematic, quantitative approach to identifying potential leading indicators for scenario monitoring. This approach is a framework that calculates correlation between various datasets from public databases, identifying, screening then consolidating the key driving forces of particular business scenarios. This process, in concert with a thorough qualitative assessment by business leader practitioners, enables an effective practice of scenario planning that allows the business to adapt its strategic long term plans in a constantly shifting global environment.en_US
dc.description.statementofresponsibilityby Xia Xu.en_US
dc.format.extent60 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.titleHow to Identify leading indicators for scenario monitoringen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Logisticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc895890384en_US


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