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dc.contributor.authorSturman, Michael C.
dc.contributor.authorJudge, Timothy A.
dc.date.accessioned2020-11-25T14:51:15Z
dc.date.available2020-11-25T14:51:15Z
dc.date.issued1995-06-01
dc.identifier.other131134
dc.identifier.urihttps://hdl.handle.net/1813/77061
dc.description.abstractTraditional utility analysis only calculates the value of a given selection procedure over random selection. This assumption is not only an inaccurate representation of staffing policy but leads to overestimates of a device's value. This paper generates a new utility model that accounts for multiple selection devices and multiple criteria. The model is illustrated using previous utility analysis work and an actual case of secretarial employees with eight predictors and nine criteria. A final example also is provided which includes these advancements as well as other researchers' advances in a combined utility model. Results reveal that accounting for multiple criteria and outcomes dramatically reduces the utility estimates of implementing new selection devices.
dc.language.isoen_US
dc.subjectresearch
dc.subjectmodel
dc.subjectorganization
dc.subjectinformation
dc.subjectpsychology
dc.subjectapplied
dc.subjectstudy
dc.subjecteffect
dc.subjecthuman
dc.subjectemploy
dc.subjectwork
dc.subjectcriteria
dc.subjectutility
dc.titleUtility Analysis for Multiple Selection Devices and Multiple Outcomes
dc.typepreprint
dc.description.legacydownloadsUtility_Analysis_for_Multiple_SelectionWP95_12.pdf: 4044 downloads, before Oct. 1, 2020.
local.authorAffiliationSturman , Michael C.: Cornell University
local.authorAffiliationJudge, Timothy A.: Cornell University


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