2026-09-20T12:42:26Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1516252023-08-01T03:19:34Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Welsch, Roy
Ghoniem, Ahmed
Hopkins, Jacob
Massachusetts Institute of Technology. Department of Mechanical Engineering
Sloan School of Management
2023-07-31T19:54:01Z
2023-07-31T19:54:01Z
2023-06
2023-07-14T19:58:22.336Z
https://hdl.handle.net/1721.1/151625
Businesses are rapidly pursuing investments in sustainable technologies to meet their climate goals, but performing actionable evaluations of technologies is difficult, especially in decentralized businesses. Actionable evaluations have high accuracy, high precision, and address uncertainty. Sustainable technologies are not well characterized and their expected performance is uncertain. For numerous reasons, approaches used in industry do not currently address these concerns. This research investigated tools to improve accuracy and precision and proposes a methodology to address uncertainty. The methodology includes a Monte-Carlo simulation tool and a method to assess data quality that address the concerns in traditional approaches. We believe this methodology can help decentralized businesses perform more actionable evaluations of sustainable technologies.
M.B.A.
S.M.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
Performing Actionable Evaluations of Sustainability
Investments
Thesis
application/pdf
Master
Master of Business Administration
Master of Science in Mechanical Engineering
Publication
unknown
unknown
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<Abstract>Businesses are rapidly pursuing investments in sustainable technologies to meet their climate goals, but performing actionable evaluations of technologies is difficult, especially in decentralized businesses. Actionable evaluations have high accuracy, high precision, and address uncertainty. Sustainable technologies are not well characterized and their expected performance is uncertain. For numerous reasons, approaches used in industry do not currently address these concerns. This research investigated tools to improve accuracy and precision and proposes a methodology to address uncertainty. The methodology includes a Monte-Carlo simulation tool and a method to assess data quality that address the concerns in traditional approaches. We believe this methodology can help decentralized businesses perform more actionable evaluations of sustainable technologies.</Abstract>
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