PropertyValue
?:abstract
  • Vendor selection involves decisions balancing a number of conflicting criteria. Data envelopment analysis (DEA) is a mathematical programming approach capable of identifying non-dominated solutions, as well as assessing relative efficiency of dominated solutions. A simple multi-attribute utility function can be applied to a small set of alternatives, providing a tool to assess relative value, but is subject to error if estimated measures are not precise. This paper compares stochastic DEA with a multiple-criteria model in a vendor selection model involving multiple criteria, reporting simulation experiments varying the degree of uncertainty involved in model parameters. ()
?:appearsInJournal
?:citationCount
  • 54 ()
is ?:cites of
?:cites
?:created
  • 2016-06-24 ()
?:creator
?:doi
  • 10.1080/00207540601039775 ()
?:endingPage
  • 2327 ()
?:estimatedCitationCount
  • 82 ()
is ?:hasCitedEntity of
is ?:hasCitingEntity of
?:hasDiscipline
?:hasURL
?:issueIdentifier
  • 8 ()
?:language
  • en ()
?:publicationDate
  • 2008-04-15 ()
?:publisher
  • Taylor & Francis Group ()
?:rank
  • 19690 ()
?:referenceCount
  • 41 ()
?:startingPage
  • 2313 ()
?:title
  • A comparison of stochastic dominance and stochastic DEA for vendor evaluation ()
?:type
?:volume
  • 46 ()

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