DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Taesik | ko |
dc.contributor.author | Shin, Kyohong | ko |
dc.contributor.author | Song, Yoorim | ko |
dc.date.accessioned | 2021-03-18T01:50:23Z | - |
dc.date.available | 2021-03-18T01:50:23Z | - |
dc.date.created | 2021-03-15 | - |
dc.date.issued | 2019-10-23 | - |
dc.identifier.citation | 2019 INFORMS annual meeting | - |
dc.identifier.uri | http://hdl.handle.net/10203/281668 | - |
dc.description.abstract | In many decision making problems in healthcare, decision makers are different from those who perform them, and compliance with optimal solution is often a concern; optimal policy is not followed and it results in suboptimal outcomes. Based on a conjecture that compliance with optimal decisions is influenced by preferences (or biases) of the decision performer, we formulate a sequential decision making problem that accounts for decision performers’ preferences. A policy solution from this formulation is sub-optimal to the original decision problem, but yields better outcome under less than full compliance environment. Characteristics of the policy solutions are illustrated with examples. | - |
dc.language | English | - |
dc.publisher | INFORMS | - |
dc.title | Decision Making under Compliance Uncertainty | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 2019 INFORMS annual meeting | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Washington State Convention Center & Sheraton Seattle Hotel | - |
dc.contributor.localauthor | Lee, Taesik | - |
dc.contributor.nonIdAuthor | Song, Yoorim | - |
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