FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2023700586> ?p ?o ?g. }

• W2023700586 endingPage "116" @default.
• W2023700586 startingPage "100" @default.
• W2023700586 abstract "Prescriptive decision analysis suggests identifying the fundamental objectives—what the decision maker really cares about—and then constructing a value hierarchy by decomposing these objectives until quantifiable attributes can be identified. In many decision contexts the decision maker is presented with a list of attributes without an opportunity to consider her fundamental objectives. In this paper we explore an approach where a decision maker is given prespecified attributes and then identifies her objectives. She assesses multiattribute models to predict performance levels on each objective and a preference model over these objectives. We use simulation to explore what happens when a decision maker applies this two-step approach to model the relationships between a given set of attributes and her objectives instead of attempting to directly estimate the attribute weights in a choice problem. These simulation results suggest that the explicit consideration of objectives results in less error in expressions of preference than the direct weighting of attributes unless the number of attributes and objectives in the decision context is small." @default.
• W2023700586 created "2016-06-24" @default.
• W2023700586 creator A5021101055 @default.
• W2023700586 creator A5037020414 @default.
• W2023700586 creator A5086580821 @default.
• W2023700586 date "2006-06-01" @default.
• W2023700586 modified "2023-10-14" @default.
• W2023700586 title "Using Attributes to Predict Objectives in Preference Models" @default.
• W2023700586 cites W108558234 @default.
• W2023700586 cites W1965917161 @default.
• W2023700586 cites W1967053375 @default.
• W2023700586 cites W1972394506 @default.
• W2023700586 cites W1975335004 @default.
• W2023700586 cites W1977880816 @default.
• W2023700586 cites W1992414962 @default.
• W2023700586 cites W2012227281 @default.
• W2023700586 cites W2016096535 @default.
• W2023700586 cites W2018116907 @default.
• W2023700586 cites W2031763016 @default.
• W2023700586 cites W2043386282 @default.
• W2023700586 cites W2050588632 @default.
• W2023700586 cites W2051000470 @default.
• W2023700586 cites W2051406071 @default.
• W2023700586 cites W2051837213 @default.
• W2023700586 cites W2056418346 @default.
• W2023700586 cites W2061202913 @default.
• W2023700586 cites W2061535067 @default.
• W2023700586 cites W2073577518 @default.
• W2023700586 cites W2076033371 @default.
• W2023700586 cites W2079717418 @default.
• W2023700586 cites W2080682834 @default.
• W2023700586 cites W2106050672 @default.
• W2023700586 cites W2108860923 @default.
• W2023700586 cites W2111719258 @default.
• W2023700586 cites W2112533090 @default.
• W2023700586 cites W2114836920 @default.
• W2023700586 cites W2124766374 @default.
• W2023700586 cites W2149470562 @default.
• W2023700586 cites W2155931118 @default.
• W2023700586 cites W2163162500 @default.
• W2023700586 cites W2164224798 @default.
• W2023700586 cites W2168564181 @default.
• W2023700586 cites W4230507407 @default.
• W2023700586 cites W4255508679 @default.
• W2023700586 cites W534311 @default.
• W2023700586 doi "https://doi.org/10.1287/deca.1060.0069" @default.
• W2023700586 hasPublicationYear "2006" @default.
• W2023700586 type Work @default.
• W2023700586 sameAs 2023700586 @default.
• W2023700586 citedByCount "26" @default.
• W2023700586 countsByYear W20237005862012 @default.
• W2023700586 countsByYear W20237005862013 @default.
• W2023700586 countsByYear W20237005862014 @default.
• W2023700586 countsByYear W20237005862015 @default.
• W2023700586 countsByYear W20237005862016 @default.
• W2023700586 countsByYear W20237005862019 @default.
• W2023700586 crossrefType "journal-article" @default.
• W2023700586 hasAuthorship W2023700586A5021101055 @default.
• W2023700586 hasAuthorship W2023700586A5037020414 @default.
• W2023700586 hasAuthorship W2023700586A5086580821 @default.
• W2023700586 hasConcept C105795698 @default.
• W2023700586 hasConcept C107327155 @default.
• W2023700586 hasConcept C119857082 @default.
• W2023700586 hasConcept C126838900 @default.
• W2023700586 hasConcept C151730666 @default.
• W2023700586 hasConcept C154945302 @default.
• W2023700586 hasConcept C156201811 @default.
• W2023700586 hasConcept C162324750 @default.
• W2023700586 hasConcept C177264268 @default.
• W2023700586 hasConcept C183115368 @default.
• W2023700586 hasConcept C186116695 @default.
• W2023700586 hasConcept C199360897 @default.
• W2023700586 hasConcept C2776291640 @default.
• W2023700586 hasConcept C2779343474 @default.
• W2023700586 hasConcept C2781249084 @default.
• W2023700586 hasConcept C28901747 @default.
• W2023700586 hasConcept C2986080485 @default.
• W2023700586 hasConcept C31170391 @default.
• W2023700586 hasConcept C33923547 @default.
• W2023700586 hasConcept C34447519 @default.
• W2023700586 hasConcept C41008148 @default.
• W2023700586 hasConcept C42475967 @default.
• W2023700586 hasConcept C539667460 @default.
• W2023700586 hasConcept C71924100 @default.
• W2023700586 hasConcept C86803240 @default.
• W2023700586 hasConcept C97944126 @default.
• W2023700586 hasConceptScore W2023700586C105795698 @default.
• W2023700586 hasConceptScore W2023700586C107327155 @default.
• W2023700586 hasConceptScore W2023700586C119857082 @default.
• W2023700586 hasConceptScore W2023700586C126838900 @default.
• W2023700586 hasConceptScore W2023700586C151730666 @default.
• W2023700586 hasConceptScore W2023700586C154945302 @default.
• W2023700586 hasConceptScore W2023700586C156201811 @default.
• W2023700586 hasConceptScore W2023700586C162324750 @default.
• W2023700586 hasConceptScore W2023700586C177264268 @default.
• W2023700586 hasConceptScore W2023700586C183115368 @default.
• W2023700586 hasConceptScore W2023700586C186116695 @default.
• W2023700586 hasConceptScore W2023700586C199360897 @default.

• next