Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/244760
DC Field | Value | |
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dc.title | ANALYTICS IN OPERATIONS: STATISTICAL MODELING AND OPTIMIZATION UNDER UNCERTAINTY | |
dc.contributor.author | NI TU | |
dc.date.accessioned | 2023-08-31T18:00:20Z | |
dc.date.available | 2023-08-31T18:00:20Z | |
dc.date.issued | 2023-06-09 | |
dc.identifier.citation | NI TU (2023-06-09). ANALYTICS IN OPERATIONS: STATISTICAL MODELING AND OPTIMIZATION UNDER UNCERTAINTY. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/244760 | |
dc.description.abstract | In modern businesses, operations have become increasingly complex due to factors such as technological advancements, evolving customer demands, and changing environments. Organizations and firms generate data from various sources such as historical orders, supply chain activities, and customer interactions. We develop analytics solutions that apply statistical modeling and optimization techniques to make informed decisions in the face of uncertainty, and eventually gain valuable insights and drive operational improvements including cost reduction, risk mitigation, and revenue maximization. | |
dc.language.iso | en | |
dc.subject | experimental design; causal inference; hypothesis testing; process flexibility; service design; online platforms | |
dc.type | Thesis | |
dc.contributor.department | INST OF OPERATIONS RESEARCH & ANALYTICS | |
dc.contributor.supervisor | Chung Piaw Teo | |
dc.contributor.supervisor | Long He | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (IORA) | |
dc.identifier.orcid | 0000-0002-3176-4180 | |
Appears in Collections: | Ph.D Theses (Open) |
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NiT.pdf | 4.22 MB | Adobe PDF | OPEN | None | View/Download |
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