2026-09-21T05:54:57Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1571582024-10-10T03:23:34Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Trancik, Jessika E.
Roberts, Matthew R.
System Design and Management Program.
2024-10-09T18:25:12Z
2024-10-09T18:25:12Z
2024-09
2024-09-20T19:32:34.344Z
https://hdl.handle.net/1721.1/157158
Forecasts of technological progress are used to inform decisions in the public and private sectors that shape the modern technology landscape on a global scale. Technology performance curves are the quantitative, model-based representations of technological change employed in industrial, economic, and integrated assessment models to inform decision-making processes. Technology performance curves have evolved from their origins in the 1920s modeling of airframe manufacturing labor cost to consider mechanisms of technological progress, including learning-by-doing, learning-by-searching, economies of scale, and exogenous improvement. Examining changes to the performance and prevalence of technologies can provide insight that is relevant for product strategy and market forecasts. This knowledge can also help estimate the potential impact of government market policy and funding for research and development. This thesis seeks to consolidate the available literature on the various models of technology performance curves into a conceptual framework that can be used to understand the features and limitations of models, and their potential use cases.
S.M.
Massachusetts Institute of Technology
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https://rightsstatements.org/page/InC-EDU/1.0/
Technology Performance Curves to Inform Government and Private Investment
Thesis
application/pdf
Master
Master of Science in Engineering and Management
Publication
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unknown
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<Abstract>Forecasts of technological progress are used to inform decisions in the public and private sectors that shape the modern technology landscape on a global scale. Technology performance curves are the quantitative, model-based representations of technological change employed in industrial, economic, and integrated assessment models to inform decision-making processes. Technology performance curves have evolved from their origins in the 1920s modeling of airframe manufacturing labor cost to consider mechanisms of technological progress, including learning-by-doing, learning-by-searching, economies of scale, and exogenous improvement. Examining changes to the performance and prevalence of technologies can provide insight that is relevant for product strategy and market forecasts. This knowledge can also help estimate the potential impact of government market policy and funding for research and development. This thesis seeks to consolidate the available literature on the various models of technology performance curves into a conceptual framework that can be used to understand the features and limitations of models, and their potential use cases.</Abstract>
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