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dc.contributor.authorFields, Gary S.
dc.date.accessioned2020-11-25T14:55:56Z
dc.date.available2020-11-25T14:55:56Z
dc.date.issued2002-07-01
dc.identifier.other112545
dc.identifier.urihttps://hdl.handle.net/1813/77385
dc.description.abstractThis paper utilizes the data contained in the Human Resources Information System (HRIS) of a company, called here “Engineering Solutions,” and analyzes the drivers of potential for promotion among a sample of engineers. The methods used consist of basic statistical procedures, multiple regressions, ordered logits, and decompositions. The results show which variables are the main drivers of potential for promotion in this organization, which are minor drivers, and which do not matter at all.
dc.language.isoen_US
dc.subjectperformance
dc.subjectengineers
dc.subjectEngineering Solutions
dc.subjectfirm
dc.subjectwork
dc.subjectjob
dc.subjectcompany
dc.subjectpromotion
dc.titlePredicting Potential For Promotion: How The Data In Human Resource Information Systems Can Be Used To Help Organizations Gain Competitive Advantage
dc.typepreprint
dc.description.legacydownloadsWP02_14.pdf: 3269 downloads, before Oct. 1, 2020.
local.authorAffiliationFields, Gary S.: gsf2@cornell.edu Cornell University


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