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dc.contributor.advisorStuart Madnick.en_US
dc.contributor.authorKaya Firat, Ayseen_US
dc.contributor.otherMassachusetts Institute of Technology. Technology and Policy Program.en_US
dc.date.accessioned2011-04-04T17:43:39Z
dc.date.available2011-04-04T17:43:39Z
dc.date.copyright2010en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/62107
dc.descriptionThesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2010.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 85-87).en_US
dc.description.abstractPublic and private organizations try to forecast the future of technological developments and allocate funds accordingly. Based on our interviews with experts from MIT's Entrepreneurship Center, Sloan School of Management, and IBM, and review of literature, we found out that this important fund allocation process is dominated by reliance on expert opinions, which has important drawbacks alongside its advantages. In this Thesis, we introduce a data-driven approach, called early growth technology analysis, to technology forecasting that utilizes diverse information sources to analyze the evolution of promising new technologies. Our approach is based on bibliometric analysis, consisting of three key steps: extraction of related keywords from online publication databases, determining the occurrence frequencies of these keywords, and identifying those exhibiting rapid growth. Our proposal goes beyond the theoretical level, and is embodied in software that collects the required inputs from the user through a visual interface, extracts data from web sites on the fly, performs an analysis on the collected data, and displays the results. Compared to earlier software within our group, the new interface offers a much improved user experience in performing the analysis. Although these methods are applicable to any domain of study, this Thesis presents results from case studies on the fields of solar and geothermal energy. We identified emerging technologies in these specific fields to test the viability of our results. We believe that data-driven approaches, such as the one proposed in this Thesis, will increasingly be used by policy makers to complement, verify, and validate expert opinions in mapping practical goals into basic/applied research areas and coming up with technology investment decisions.en_US
dc.description.statementofresponsibilityby Ayse Kaya Firat.en_US
dc.format.extent185 p.en_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.subjectTechnology and Policy Program.en_US
dc.titleEarly growth technology analysis : case studies in solar energy and geothermal energyen_US
dc.typeThesisen_US
dc.description.degreeS.M.in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentTechnology and Policy Program
dc.identifier.oclc707937789en_US


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