Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/13513
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dc.contributor.authorDoljanin, Ivan Andrewen
dc.contributor.authorThompson, Johnen
dc.contributor.authorGriffith, Garryen
dc.contributor.authorFleming, Euanen
dc.date.accessioned2013-10-14T11:48:00Z-
dc.date.created2012en
dc.date.issued2013-
dc.identifier.urihttps://hdl.handle.net/1959.11/13513-
dc.description.abstractThe international measure of beef quality has largely been associated with the increased presence of intramuscular fat, also known as marbling. Using a palatability analysis critical control point (PACCP) process, consumer research collated by Meat Standards Australia (MSA) over the last 20 years has demonstrated the interconnectivity of pre and post-slaughter treatments with the traditional measurements in relation to consumer palatability scores. This has enabled consumer grading of beef - predicting the consumers' assessment of the specified meal as either 3 star (good everyday), 4 star (better than everyday), or 5 star (premium) eating quality for six cooking methods (grilling, roasting, stir-frying strips, slow cooking cubes, thin sliced, corned). A commercial dataset (n=3,735) was collated over an eight year period that described the eating quality and yield of beef product offered to consumers using the MSA grading matrix of eating quality and cooking method. This dataset created an opportunity to overlay financial terminology to the various steps of beef production by aligning consumer choice about the predicted quality of beef with the production input variables. This financial information can overlay the PACCP process with economic weights for the production input variables, thereby contributing toward the creation of its financial equivalent (FACCP) for the beef industry. Generating effective long-term financial modelling by accurately linking consumer demand to production variables would help to secure future investment. Ongoing investment in the industry is essential to keep beef a competitive source of protein. In this thesis, six measures of carcase yield - primal, trim, waste and fat, bone, loss, and saleable meat (SMY%) - were assessed to determine the most appropriate indicator of carcase value. The analysis found SMY% was the best indicator of carcase value, with a 0.85 coefficient of determination (R²). SMY% was followed by waste and fat, trim, primal, loss, and bone with an R² of 0.72, 0.69, 0.42, 0.29, 0.28 respectively.en
dc.languageenen
dc.titleAligning price signals throughout the beef value chain to reflect consumer preferences by assigning economic weights to the Meat Standards Australia (MSA) model inputsen
dc.typeThesis Masters Researchen
dcterms.accessRightsUNE Greenen
dc.subject.keywordsAgricultural Economicsen
local.contributor.firstnameIvan Andrewen
local.contributor.firstnameJohnen
local.contributor.firstnameGarryen
local.contributor.firstnameEuanen
local.subject.for2008140201 Agricultural Economicsen
local.subject.seo2008830301 Beef Cattleen
dcterms.RightsStatementCopyright 2012 - Ivan Andrew Doljaninen
dc.date.conferred2013en
local.thesis.degreelevelMasters researchen
local.thesis.degreenameMaster of Economicsen
local.contributor.grantorUniversity of New Englanden
local.profile.schoolSchool of Business, Economics and Public Policyen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolUNE Business Schoolen
local.profile.schoolUNE Business Schoolen
local.profile.emailidoljani@une.edu.auen
local.profile.emailjthompso@une.edu.auen
local.profile.emailggriffit@une.edu.auen
local.profile.emailefleming@une.edu.auen
local.output.categoryT1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune_thesis-20120702-160127en
local.access.fulltextYesen
local.contributor.lastnameDoljaninen
local.contributor.lastnameThompsonen
local.contributor.lastnameGriffithen
local.contributor.lastnameFlemingen
dc.identifier.staffune-id:idoljanien
dc.identifier.staffune-id:jthompsoen
dc.identifier.staffune-id:ggriffiten
dc.identifier.staffune-id:eflemingen
local.profile.orcid0000-0002-5276-6222en
local.profile.roleauthoren
local.profile.rolesupervisoren
local.profile.rolesupervisoren
local.profile.rolesupervisoren
local.identifier.unepublicationidune:13725en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleAligning price signals throughout the beef value chain to reflect consumer preferences by assigning economic weights to the Meat Standards Australia (MSA) model inputsen
local.output.categorydescriptionT1 Thesis - Masters Degree by Researchen
local.thesis.borndigitalyesen
local.search.authorDoljanin, Ivan Andrewen
local.search.supervisorThompson, Johnen
local.search.supervisorGriffith, Garryen
local.search.supervisorFleming, Euanen
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/44fffb79-0e1b-4bb9-bfb8-f5039b2e7634en
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/9a07bddf-53e7-4d98-aeaa-0be1fef48297en
local.uneassociationYesen
local.year.conferred2013en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/9a07bddf-53e7-4d98-aeaa-0be1fef48297en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/44fffb79-0e1b-4bb9-bfb8-f5039b2e7634en
local.subject.for2020380101 Agricultural economicsen
local.subject.seo2020100401 Beef cattleen
Appears in Collections:Thesis Masters Research
UNE Business School
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