International Journal of Multidisciplinary Research and Growth Evaluation  |  ISSN (Online): 2582-7138  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

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     2026:7/3

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

Multi-Criteria Decision Modeling for Supplier Selection in Aviation, Oil & Gas, and Construction

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Volume: 7 | Issue: 2 | Pages: 619-627

Subject: Procurement

Country: Saudi Arabia

DOI: https://doi.org/10.54660/IJMRGE.2026.7.2.619-627

License: CC BY 4.0

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Abstract

Background: The supplier selection process in high-risk industries is extremely important to ensure suppliers are chosen to fulfil the requirements of safety and compliance, and to mitigate any potential reputational damage. Poor supplier selection can lead to just such an occurrence, as demonstrated by some of the previous high-profile cases we examine. Supplier evaluation in high-risk industries such as aviation, oil & gas, and construction is challenging due to the inherent complexity and uncertainty associated with each supplier, and therefore requires a methodical and transparent approach in providing decision support for the selection of suppliers to do business with.
Methods: In this study a systematic review of the existing literature, along with a comparative analytical methodology, is used to evaluate the current use of multi-criteria decision-making techniques used for supplier selection in these three industries. The study includes an analysis of common established supplier evaluation techniques (e.g. Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIKOR, ELECTRE, PROMETHEE and hybrid and fuzzy-based extensions), all of which focus on addressing uncertainty and incomplete data. We then conclude the study by developing a methodology to evaluate carefully selected supplier evaluation criteria, weighting those criteria based on the criteria identified, and developing an integrated conceptual framework (including sensitivity analysis) that demonstrates the effects of varying the evaluation criteria on the outcome of the evaluation process.
Results: The results show that there is no one MCDM method that works best for choosing suppliers in high-risk industrial settings. The appropriateness of a method depends on how complicated the decision is, how much data is available, how uncertain things are, and the goals of the organization. When choosing aviation suppliers, regulatory certification, safety compliance, and traceability are the most important factors. When choosing oil and gas suppliers, operational risk management, environmental compliance, and reliability are the most important factors. When choosing construction suppliers, cost efficiency, schedule adherence, and delivery performance are the most important factors. Hybrid and fuzzy MCDM models show that they are better at dealing with qualitative criteria and decision-making situations that are not clear.
Conclusion: The study finds that MCDM frameworks that are specific to a situation and can change are necessary for choosing suppliers in high-risk industries. The suggested integrated framework makes decisions more clear and strong, which helps to ensure fair procurement results. Future research ought to investigate the amalgamation of machine learning, real-time data analytics, and digital twin technologies to enhance MCDM-based supplier selection systems.

How to Cite This Article

Samir Ali Syed (2026). Multi-Criteria Decision Modeling for Supplier Selection in Aviation, Oil & Gas, and Construction . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 7(2), 619-627. DOI: https://doi.org/10.54660/IJMRGE.2026.7.2.619-627

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References

  1. 2. 3. Handling Qualitativeand Quantitative Decision Factors Auniquedifficultyinsupplierevaluationisthepresenceofbothhardquantitativemetricsandsoftqualitativejudgments. Youcanmeasureandverifyfinancialstability, deliveryperformance, anddefectrates. Ontheotherhand, it'shardtoputnumbersonthingslikesupplierresponsiveness, corporatesocialresponsibility, andthepotentialforinnovation[
  2. 1. MCDMframeworksaddressthisheterogeneitythroughvariousmechanisms: theemploymentoflinguisticvariablesandfuzzysettheorytoencodequalitativeevaluations; normalizationproceduresthatmakedisparatedatacomparable; andaggregationoperatorsthatconsolidatevarioustypesofevidenceintocompositescores[
  3. 1. International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com621|Page Fig1: Conceptualframeworkillustratingtheintegrated MCDM-basedsupplierselectionprocessacrossaviation, oil&gas, andconstructionsectors
  4. 3. MCDMTechniquesfor Supplier Selection3.
  5. 1. Analytic Hierarchy Process(AHP\Saaty's Analytic Hierarchy Process(AHP\isoneofthemostrecognized MCDMtechniquesusedforsupplierselection. AHPconvertsthedecision-makingproblemintoahierarchicalstructurethatincludestheoverallgoal, evaluationcriteria, sub-criteria, andalistofcandidatealternatives. Eachlevelofthehierarchysupportspairwisecomparisonsbetweeneachdecisionoption, whichareexpressedona9-pointscaletoprovideanumericalratioofhowoneoptionispreferredoveranother. Theprioritiesestablishedthroughthesecomparisonsareusedtocalculatetheweightingofeachcriterionandcandidate, leadingtoaglobalprorityrankingforallalternatives. Inregardtoselectingindustrialsuppliers, AHP'smajorstrengthliesinitsabilitytoextractandconceptualizeexpertopinioninasystematicallyandlogicallyconsistentmanner. Theconsistencyratio(CR\isanindicatorofthelogicalconsistencyofthepairwisecomparisonsmadeinthe AHPprocess, allowingfortheidentificationandcorrectionofinconsistenciesinjudgment. Numerous AHPapplicationshavebeendevelopedin MROsupplierselection[, oilandgascontractorassessment[, andconstructionsubcontractorqualification[. Inalargenumberofcases, AHPhasdemonstratedasuperiorlevelofperformancewhencomparedtotheunstructuredmethodsusedforevaluatingsuppliers. Itsprincipalweaknessisthatthemethodcanbesubjecttorankreversalwhennewalternativesareaddedtotheproblem, andthecomputationalcomplexitygrowsexponentiallywiththenumberofcriteriaandalternativesusedinthemethodology.3.
  6. 2. TOPSISThe Techniquefor Order Preferenceby Similarityto Ideal Solution(TOPSIS\, createdby Hwangand Yoon[1, ranksoptionsbasedonhowclosetheyaretoapositiveidealsolution(PIS\andhowfartheyarefromanegativeidealsolution(NIS\Themethodusesnormalizingthedecisionmatrix, calculatingweighted Euclideandistances, andarelativeclosenesscoefficientastherankingmetric. Itisbettertochooseoptionswithhigherclosenesscoefficients, sincetheyareclosetothebestperformanceprofileandfarfromtheworst[
  7. 1. TOPSISisespeciallygoodforsituationswheretherearealotofoptionsandthecriteriacanbemeasuredobjectively. Itseaseofcomputationandintuitivegeometricinterpretationhavemadeitapopularchoiceforprocurementanalytics[
  8. 1. TOPSIShasbeenusedtoranksuppliersofdrillingequipmentinoilandgasvendorassessmentsbasedontheirtechnicalability, price, anddeliverymetrics[. Limitationsencompasssensitivitytotheemployednormalizationmethodandthepossibilityofrankreversalunderspecificconditions.3.
  9. 3. VIKOR, ELECTRE, and PROMETHEEwithrespecttoindividualregretandtheoverallutilityofthemethoddoesthisbyintroducingaparameter, knownasv, reflectingthedegreetowhichthegroupwillbesatisfiedcomparedtoindividualdissatisfaction. Therefore, themethodisespeciallysuitableforsupplierselectionwhentherearemultiplestakeholdergroupswithconflictingpriorities[
  10. 1. The VIKORmethodhasbeensuccessfulforevaluatingconstructioncontractors, whoarecommonlyfacedwithtrade-offsamongcost, scheduleandquality[. The ELECTREmethod(Eliminationand Choice Translating Reality\usesamethodologybasedonconcordanceanddiscordanceindicestoidentifydominantalternativesthroughtheuseofanoutrankingmethod. Therefore, thismethodallowsfortheidentificationofdominantalternativeswithoutrequiringthatthealternativesbefullyaggregated(orcompensated\. Thisnon-compensatorycharacteristicofthe ELECTREmethodisespeciallybeneficialforsafety-criticalprocurementscenarios(e. g. aviation\, whereitwouldbeinappropriatetoelevateonesupplierwithanunacceptablelevelofsafetybecauseoftheirsuperiorcostperformance[4,
  11. 1. The PROMETHEEmethod(Preference Ranking Organisation Methodfor Enrichment Evaluations\usesflexiblepreferencefunctionsthatquantifythedecision-ofgeneratinganetflowscorethatallowsforrankingallrepresentation(GAIAplane\visuallyrepresentsthetrade-offsbetweenalternatives[
  12. 2. International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com622|Page3.
  13. 4. Fuzzyand Hybrid MCDMModels Onesignificantdisadvantageoftraditionalmulti-criteriadecision-making(MCDM\proceduresistheirdependenceondefiniteinputvalues. Moreover, itisn'talwayspossibletomeasuretheexactinputvaluesrequiredbyan MCDMevaluationprocessinacomplexmanufacturingenvironment. Informationmaybeincomplete, ambiguous, ordescribedusinglanguage. In1965, Lotfi Zadehfirstadvancedfuzzysettheorytoovercomethislimitationbyallowingforaninput'smembershipdegreetomeasurehowwellanentitysatisfiesanevaluationcriterionusingasetoffuzzylogic. Usingfuzzynumbers(triangularortrapezoidal\inplaceofcrisppointvaluesasinputsto AHP, TOPSIS, or VIKORimprovestherepresentationofexperts'assessmentsandprovidesresearcherswithmoreaccurateresultsthanusingconventionalmethods. Ahybrid MCDMapproachintegratesmultipletechniquesandtakesadvantageoftheirstrengthswithinacommondecision-makingframework. Forinstance, AHPcouldbeusedforcriterionweightingwhileutilizingeither TOPSISor VIKORtoranktheidentifiedalternatives. Thistypeofintegratedapproachhasbeensuccessfullyappliedtomanytypesofmanufacturingprocesses[13,
  14. 1. Moreadvancedhybrid MCDMapproacheshaveaddedgreysystemtheory, roughsettheory, and/or Delphimethodstofurtherenhancetheapplicationsofanyprevious MCDMmethodtodecreaseuncertainty. Inevaluatingsupplierswithdiverseperformancecharacteristics, Fuzzy AHPcombinedwith TOPSISisanexampleofsuperiorperformanceinevaluatingsuppliersbasedoncommercialcriteria[4, ascomparedtotheuseofonlyoneofthosetwomethods. Fig2: MCDMdecision-modelworkflowillustratingthesequentialanalyticalstagesfromdatacollectionthroughnormalisation, weighting, ranking, andsensitivityanalysistofinalsupplierselection
  15. 4. Industry-Specific Supplier Selection Criteria4.
  16. 1. Aviation: Safety, Certification, and Traceability Aviationsupplierselectionissubjecttoanextremelystringentregulatoryandsafetyframework(includingdocumentedproofofcompliancewithapplicableairworthinessstandards, AS9100 Quality Management System(QMS\Certification, Parts Manufacturer Approval(PMA\per FAAregulations, and EASAForm Onedocumentationfor Aeronautical Component Parts\[. Theforemostcriterioninevaluatingsuppliersistheirabilitytodemonstrate"traceability,"whichistheabilitytodocumenttheoriginandchainofcustodyforeveryaviationcomponentfromitstimeofmanufacturinguntilitisinstalledonanaircraft. Thisrequirementisdrivenbytheimperativesofsafetyandthemandatesofaviationregulations, andthus, itisnotnegotiable[. Keyevaluationfactorsthatareusedtodeterminewhetherasuppliermeetstheaboverequirementsincludethefinancialstabilityofthesupplier, supplierabilitytomeeton-timedeliveryperformancerequirements, supplierresponsetimein AOGsituations, andsupplierengineeringsupportcapability. Asenvironmentalcompliancebecomesamoreimportantcomponentofsupplierevaluations, managinghazardoussubstancesunder E. U. REACHregulationsisalsobecominganincreasinglyimportantelement. Ingeneral, AHPmethodologysupportsthefactthatsafetycomplianceandcertificationalwaysrankhighestwhenapplyingcriteriathrough AHPmethodology, thusreflectingthezero-toleranceregulatoryculturethatexistsincommercialaviation[. International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com623|Page4.
  17. 2. Oil&Gas: Operational Riskand Environmental Compliance Duetotheveryharshoperationalenvironmentswherevendorsmustwork, andseriousconsequencesofequipment/supplyservicefailures, oilandgasprocurementcriteriahavebeenshapedbyconsiderationsofoperationalrisk. Thismeansthatoperationalriskmanagement(theprincipaldimensionofevaluation\incorporatesanassessmentofavendor'spriorperformancewithregardstoblowoutprevention, wellcontrol, pipelineintegrityandhazardousmaterialmanagement. Thesecondmostimportantdimensionisriskwithrespecttoenvironmentalcompliance; thisincludesadherencetoenvironmentalimpactassessment, spillresponsecapabilities, and ESG(Environmental, Socialand Governance\reporting. Inaddition, technicallyqualifiedpersonnelandcertificationsoftheequipmentbeingusedarealsoconsideredthroughouttheentirelifecycleofoilandgasprocurement-upstreamexplorationthroughdownstreamrefining. Ofparticularconcernisthefinancialviabilityofthevendor; giventhecapitalintensivenatureofoilandgasprojectsandthecyclicalityofcommoditymarkets, thereexistssubstantialfinancialriskforthevendorduringperiodsofmarketdecline. Additionally, whileperformancerelatedtosustainabledevelopmenthashistoricallybeenconsideredsecondarybymanycompanieswithinoilandgasindustry, ithasgainedsignificantimportanceoverrecentyearsduetoseveralhigh-profileenvironmentaldisastersaswellasincreasedawarenessregardingtheaccelerating Energy Transition.4.
  18. 3. Construction: Cost Efficiencyand Sustainability Evaluationofconstructionsuppliersischaracterisedbyagreaterrangeofcriteriaweightingincomparisontoboththeaviationandoilandgasindustrieswhichisindicativeofthenumerousstructuraldifferencesbetweenthesesectorsaswellasthedegreeofcommercialcompetitionamongstbusinessesoperatinginthem. Costcompetitivenesscontinuestobethemostimportantcriterionforvirtuallyallprocurementopportunitieswithintheconstructionsector; particularlysointhepublicsectorduetoarequirementthatallconstructionprocurementoccurswithvalueformoneyinmind[6,. However, thereisagradual, butclear, progressionawayfromusingasimplepricecomparisonasthemethodtoevaluatecompetingsupplierbidstowardsusingtotalcostofownershipframeworks-whichincorporateslifecyclemaintenancecostsincurredduringprojectdelivery, contractorperformancewithregardtomanagingvariationsthatareoutsidethecontractdocumentsandriskassociatedwithanycontract(s\awarded-inmoresophisticatedprocurementoperationswithintheconstructionsector. Deliveryperformancemeasures-whichincludes, butisnotlimitedto, schedulereliability, theleadtimerequiredfororderingandreceivingmaterialsandthecoordinationoflogisticsfunctions-areadditionallyveryimportanttoconstructionprojects, especiallyconsideringhowoftentheyoccuroncriticalpathschedules. Theeffectivemanagementofqualityassurance, environmentalimpacts(includingwastegenerationandmanagement; carbonfootprint; materialsourcingandsustainability\, andworkersafetyaretheothermainevaluationcriteriaforsupplierswithintheconstructionsector[. Buildinginformationmodelling(BIM\anddigitalprojectmanagementplatformshaveledtointroducingasupplierselectioncriterionofdigitalcapabilityasanemergingtrendinmoderndayconstructionprocurement.4.
  19. 4. Weightingand Prioritisation Across Industries Anexplorationofdistinctindustriesshowssystematicdifferencesinthepriorityofcriteriaweightsduetotheuniquecharacteristicsofeachsectorregardingriskandregulatoryaspects. Aviationhasitsprimaryfocusonpre-emptingsafetyrisks, duetosevereconsequencesassociatedwithnon-compliancetoregulations; while Oil&Gashasoperationalriskmanagementasthemainfocusoftheircriteria, inadditiontotheenvironmentalcomplianceaspect, giventheirexposuretocatastrophicrisksaswellastheirincreasedenvironmentalscrutiny. Constructionfocusesprimarilyoncostefficiencyanddeliveryperformanceasthemaincriteriaweightedmostheavilyduetoahighlycompetitivemarketplaceandtheprojectschedulebeingthefundamentaldriverofprojectcosts. Thesystematicdifferencesinprioritycriteriaweightingcanhaveasubstantialimpactondesignof MCDMmodels, requiringanindustry/organisational-context-specificcustomisationofboththecriteriasetandweightingstructure, ratherthanauniversalcriteriaframework. Sensitivityassessmentsofthecriterionweightingswillassistindetermininghowrobustsupplierrankingsaretosensitivityofstakeholderpreferencechanges. Table1: Comparativeanalysisofprincipal MCDMmethodsappliedinindustrialsupplierselection, includingapplicationdomain, computationalcharacteristics, andrecommendedusecases Method Data Complexity Computational Effort Primary Application Expert Input Needed Decision Basis AHPHigh Low Weightderivation Moderate Pairwisecomparisons TOPSISModerate Moderate Rankingalternatives Low Idealsolutionproximity VIKORModerate Moderate Compromiseranking Low Maximumgrouputility ELECTREHigh High Outrankingrelations High Concordance/discordance PROMETHEEModerate Moderate Netflowranking Moderate Preferencefunctions Fuzzy AHPHigh High Uncertaintyhandling High Triangularfuzzynumbers Hybrid Models High High Complexmulti-stage High Integratedframeworks International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com624|Page Table2: Industry-specificsupplierevaluationcriteriaforaviation, oil&gas, andconstructionsectors, classifiedbyprincipalcriteriondimensions Criterion Aviation Oil&Gas Construction Safety&Compliance FAA/EASAcertification; MROapprovals; AS9100qualitystandards API/ISOsafetycertifications; HSEperformancemetrics; OSHAcompliance OHSAS18001compliance; sitesafetyrecords; contractorcertification Technical Capability Componenttraceability; OEMauthorisation; engineeringsupport Subsea/upstreamexpertise; technicalworkforcecapability; equipmentreliability Structuralengineeringcapacity; BIMproficiency; specialisttrades Quality Assurance Defectrates; non-conformancereporting; inspectionaudits Failuremodeanalysis; corrosioncontrol; qualitymanagementsystems Materialtesting; defectrectificationrates; workmanshipstandards Delivery Performance On-timedelivery; AOGresponse; leadtimeadherence Just-in-timesupply; offshorelogisticsreliability; inventorymanagement Projectmilestoneadherence; materialprocurementtimelines; logistics Cost Competitiveness Totalcostofownership; warrantyprovisions; pricingtransparency CAPEX/OPEXoptimisation; contractflexibility; costescalationclauses Bidcompetitiveness; valueengineering; lifecyclecosting Environmental&Sustainability Carbonfootprint; emissionsreductioncommitments; wastemanagement Environmentalimpactassessments; spillprevention; ESGreporting LEED/BREEAMalignment; sustainablematerials; circulareconomypractices Financial Stability Creditratings; insurancecoverage; bondingcapacity Reservelevels; insuranceforblowouts; financialresilience Suretybonding; paymentguarantees; solvencyratios
  20. 5. Comparative Analysisand Model Application5.
  21. 1. Comparative Strengthsand Limitations Acomparisonofthemajormultiplecriteriadecisionmaking(MCDM\methodsshowsthattherearekeytrade-offsattheheartofeachofthemethodsincluding:(1\thelevelofsophisticationofthemethod(i. e., somemethodsaremathematicallycomplexanddifficultfortheaverageusertounderstand\;(2\theamountofdata/analysesitrequires(i. e., somemethodsrequireanextensiveamount; othersdonot\; and(3\thelevelofinterpretivedifferences(i. e., somemethodshavemultipleinterpretations\withintheresultsofusingthemethod. The AHPmethodworksbestwhenthereisaneedforstructuredexpertelicitationandtransparentweightcreation. However, withlargernumbersofcriteria AHP'spairwisecomparisonapproachbecomesquitecumbersome, andthepotentialforaninconsistencybiaswithinlargergroupdecision-makingprocessesexists. Incontrast, whilethe TOPSISmethodofferscomputationalefficiencyandatheoreticallyelegantgeometricinterpretation, themethod'sconclusionsarequitesensitivetohowthealternativesarenormalisedandthecompositionofthealternatives. Inaddition, the VIKORmethodisofgreatvaluefordecision-makersseekingtocreateaconsensusinmulti-stakeholderprocurementenvironmentsbecauseofitsemphasisoncompromiseranking; however, thevalueofthedecision-makingprocessmaybenumericallycompromisedduetothesubjectivenatureofdeterminingthevalueofthecompromiseparameter(v\. Electreoffersanon-compensatoryoutrankingapproachthatessentiallyalignswellwithasafety-criticalprocurementenvironment; however, thenatureandcomplexityof Electre'sconcordance/discordanceanalysescouldmakeitdifficulttocommunicatetheresultsoftheanalysistonon-technicalprocurementparticipants. Lastly, while PROMETHEEallowsfordecision-makerstocreatetheirownpreferencefunction(thusallowingforgreaterflexibility\, theadditionallevelofparameterisationmayhavetheunintendedconsequenceofincreasingthecognitiveburdenonthedecision-maker.5.
  22. 2. Case-Based Application Acrossthe Three Industries Toconceptualize Fuzzy-AHPforselecting MROsuppliersofalargecommercialairline, apanelofexperts(includingisawareengineers, purchasingagents, andmanagers\shouldfirstestablishthecriteriahierarchytoevaluatepotential MROsuppliersbyusinglinguisticscales. Theratingsassignedfromthepairwisecomparisonscanthenbeconvertedintotriangularfuzzynumbersbeforeapplyingthemtogenerateafinalcrispratingforeachpotential MROsupplier; thuscreatinganevenbetterwaytogothroughtheinformalprocessofidentifyingpotentialvendors. Utilizingahybrid AHP-TOPSISmodelforselectingoffshoredrillingcontractorsintheoilandgasbusinesscanbeaccomplishedbyusing AHPfordeterminingtherelativeworthofeachofthevariousselectioncriteria(HSEperformance, technicalability, financialsecurity, andcosteffectiveness\assetbythesenioroperationsandpurchasingrepresentatives, andthenusing TOPSIStorankeachcontractorbasedontheirperformanceonthesefourcriteria. Thiswillletthepurchaserobjectivelyseparatetheotherwisequalifiedcontractorsfromeachotherbasedonhowtheywereratedandwhattheirrespectiverankingswere. Usingsensitivityanalysisallowsforchangingcriteriaweightsandseeinghowthataffectstheselectedcontractor. VIKORcouldbeusedinconstructiontoratestructuralsteelsubcontractorsforabiginfrastructureproject. Themethod'sfocusonbalancingthemostutilityforthegroupwiththeleastregretforeachpersonfitswellwiththewaythatlargeconstructionprojectsareprocured, wherecommercial, technical, andsustainabilitygoalsmustallbemetatthesametime. Asensitivityanalysisofthecompromiseparametervwouldshowhowstabletherankingiswhendifferentassumptionsaremadeabouthowmuchweighttogivetogroupvs. individualpreferences[6,.5.
  23. 3. Sensitivity Analysisand Robustness Sensitivityanalysisplaysanessentialroleinsupplierselectionthroughmulti-criteriadecisionanalysis(MCDM\asatooltovalidatetherobustnessofrankingsthatarecreatedbyusingarangeofinputparameters(calledperturbations\andtodeterminewhichcriteriaaremostsignificantandthereforesensitivetochangesintheirweights(i. e., basedonhowmuchtheirrankingswillchangewithsmallchangesinweight\. Therearemanydifferenttypes/techniquesforperformingsensitivityanalysesandtheyfallintothreebroadcategories: one-at-a-timeparameterperturbation(i. e., changingonlyonecriterionweightatatime\, scenarioanalysis(i. e., developingscenariosforcombinationsofchangestomultiplecriterionweights\, and Monte Carlo International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com625|Pagesimulation[20,
  24. 2. Bydemonstratingstablerankingsoverarangeofplausibleinputconfigurations, large-scalepurchasescanimprovetheircredibilityaswellashelptheirfinalselectiondecisionstobemoredefensible. Robustnesstestingshouldincludenotjustperturbingtheweightofthecriteriabutalsoperturbinganyinput(s\thatprovidethebasisfortheperformanceassessment, andespeciallywherequalitativeassessmentsaresubsequentlyconvertedtoquantitativescorevalues. Supplierswhoserankingsareverysensitivetocertaininputassumptionsrequirethattherebefurtheranalysisofthesubjectsupplieroritsproductsandmayprovidetheneedforincreasedduediligenceonthatsupplier[14,
  25. 2. Table3: Comparativeanalysisandrecommendedapplicationsof MCDMmethodsacrossaviation, oil&gas, andconstructionsupplierselectioncontexts MCDMMethod Industry Application Strengths Limitations Recommended Use Case AHPAviation MROsupplierranking Systematicweightelicitation Consistencyratiosensitivity; expertbiaspossible Bestforcriteriaweightinginstructuredenvironments TOPSISOil&Gasvendorshortlisting Geometricsimplicity; accommodatesquantitativedata Assumeslinearutility; rankreversalissues Effectiveforlargesupplierpoolswithmeasurable KPIs VIKORConstructioncontractorevaluation Balancesindividualregretandgrouputility Subjectivev/wparameterselection Suitableforcompromise-seekingacrosscompetingobjectives ELECTREMulti-sectoroutrankinganalysis Handlesincomparability; non-compensatory Complexinterpretation; thresholdsensitivity Usefulwhenstrictdominancerelationsarerequired Fuzzy-AHPAviationsafety-criticalprocurement Manageslinguisticuncertainty; expert-friendly Computationalintensity; aggregationsubjectivity Idealforqualitativecriteriainhigh-riskcontexts AHP-TOPSISHybrid Integratedsupplychainevaluation Combinesweightderivationwithranking Compoundederrorpropagationpossible Recommendedformulti-industry, multi-criteriaframeworks Fig3: AHP-derivedcriteriahierarchyandindicativeweightdistributionforsupplierselectionacrossaviation, oil&gas, andconstructionindustries, reflectingsector-specificprocurementpriorities
  26. 6. Managerialand Practical Implications6.
  27. 1. Decision Supportfor Procurement Managersand Policymakers Theoutcomesofthisreviewhavemajorramificationsforprocurementofficialsandaffectedpolicy-makersacrossallsectorsoftheaviationindustry, oil&gassectorandconstructionindustry. Forprocurementexecutives, thistransitionfromselectingsuppliersbasedprimarilyonintuitionandstakeholderrelationshipstosystematicandevidence-basedevaluationsofsuppliersusingthe MCDMframeworkrepresentsamajorchange. Inregulatedindustries, suchasthosementionedabove, therewillalsobeincreasedassurancethatprocurementdecisionswillstand-uptoscrutinyfromregulators, auditors, orlegalproceedingsduetothe MCDMbeingatransparent, auditable, anddefensibleevaluationmethodology[3,
  28. 1. Policymakersandstandard-settingorganizationsmayconsiderusing MCDMevaluationattributestocreatesector-specificsupplierqualificationstandardsandincorporate MCDMmulti-dimensionalcriteriaintopre-qualificationstandards. Forinstance, inaviation, regulatoryauthoritiescoulduse MCDM-influencedsupplierevaluationtoprovide International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com626|Pageadditionalguidancetomeetexistingairworthinessdirectivesthroughastructuredmethodforevaluatingtheoverallperformanceofsuppliersaboveandbeyondtheircompliancewithregulatoryrequirements[. Intheconstructionindustry, publicsectorprocurementregulationsrelatedtoawardingcontractsmayrequirethatbidsmeetmulti-criteriaevaluationrequirementstocomplywiththepublicsectortenderprocess.6.
  29. 2. Integrationwith Digital Procurement Systems Introducing Multi-Criteria Decision Making(MCDM\methodsontodigitalmarketplacesisanimportantrequirementforwide-scaleimplementationandongoinguseofdigitalcontractingsystems. Many ERPsystems, Supplier Relationship Management(SRM\systems, and E-Procurement Portalsnowcomewithanalyticalmodulesthatallowpurchaserstoperform MCDMcalculations, normalisesupplierperformancedataacrossmultiplesuppliers, andassesstheimpactofchangingconditionsontheirsupplierselectionprocess--allalmostinreal-time[
  30. 2. Thecreationofstructuredsupplierperformancedataavailablethroughtheintegrationoftraditionaldatalogsanddigitalsystemshassubstantiallyreducedtheburdenrelatedto MCDMdatacollectionandhasprovidedcontinuousassessmentsofsuppliersinsteadofhavingone-timeassessments. Inadditiontotheseintegratedsystems, manynewtechnologieshavethepotentialtoradicallyenhancefutureprocurementdecision-makingcapabilitiesartificialintelligence(AI\, machinelearning, andnaturallanguageprocessing, forexample. AI-enabledriskmodelsforsupplierscandrawbothstructuredandunstructureddatafrommanydifferentareasincludingfinancialfilings, regulatorydatabases, socialmedia, Environment, Social, and Governancereportsandcanbeprocessedasnormalisedriskscoresthatcanserveasdynamicinputsto MCDMframeworks[23,
  31. 2. Atthesametime, digitaltwintechnologywillcreatereal-timedigitalrepresentationsofentiresupplychainnetworksthatcanbeusedtoevaluatehowsupplierselectionswillperforminhypotheticaloperationalandmarketscenarios.6.
  32. 3. Contributionto Risk Mitigation, Sustainability, and Strategic Sourcing Theuseof MCDMtoassesssuppliersdoesnotonlyallowfirmstobeefficient, butitalsohelpstoreduceorganisationalriskbymakingvisibleandquantifiablethevulnerabilitiesofsuppliers. Byincorporatingfinancialstability, operationalriskandcompliancemetricsintothesupplierevaluationprocess, organisationscanidentifysuppliersatriskmuchearlieron, enablingproactiveinterventionandcontingencyplanning[11,
  33. 1. Thestructuredevaluationofsuppliersusingan MCDMframeworkisparticularlyattractivenowduetotherisingnumberofdisruptionstoglobalsupplychainsdrivenbygeopoliticalinstability, climatechangeandpandemic-relatedevents. Additionally, theexplicitinclusionofsustainabilitycriteriainthe MCDMsupplierevaluationframeworkisadirectresponsetotheincreasingdemandfromstakeholdersforenvironmentalandsocialperformanceinallsegmentsoftheindustrialsupplychain[
  34. 2. Givingquantitativeweightstoenvironmentalcompliance, carbonperformanceandsocialresponsibilitythroughthe MCDMframeworkprovidesasystematicwaytoincorporatesustainabilityintoprocurementprocesseswithoutsacrificinganalyticalrigor. Thisintegrationallowsorganisationstomeettheircommitmentstoward ESGobjectives, satisfytheirinvestors/regulatoryorganisations, andhelpmeettheoverallgoalofsustainableindustrialdevelopment[25,2.
  35. 7. Conclusion Inthispaper, theauthorpresentsathoroughanalyticalreviewoftheapplicationofmulti-criteriadecision-making(MCDM\methodsforevaluatingsuppliersinthethreerelevantindustries: aviation, oil&gas, andconstruction. Theseindustriesinherentlypossesshighlevelsofoperationalcomplexity, largesafetyandregulatoryrequirements, andveryhighrisksassociatedwithsupplier-relatedfailure. Accordingtotheauthor, MCDMframeworkapproachesforevaluatingsuppliersareasignificant, evidence-basedimprovementoverthetraditional, single-criterion, orqualitativeevaluationmethodsbecausetheyprovidetransparency, reproducibility, andarefarmoreanalyticallyrichthanwhatisnecessarytosupportthestrategicimportanceofsupplierselectiondecisionsintheseindustries. Whileanentitycanuseabetter MCDMmethod, one MCDMmethodwillnotbeoptimalforalldecision-makersandalldecisions. Theanalyticalstrengthsandweaknessesofeach MCDMmethodincludethefollowing: theanalyticalhierarchyprocess(AHP\forstructuredexpertinputandweightassignment; thetechniquefororderofpreferencebysimilaritytoanidealsolution(TOPSIS\forcomputationalefficiencyonasignificantnumberofalternatives; the VIKORmethodformulti-stakeholdersettingstoachievecompromise-basedrankings; theeliminationandchoiceexpressingreality(ELECTRE\methodforutilityfunction-basedrankings; andthepreferencerankingorganisationmethodfortheevaluationofalternatives(PROMETHEE\methodforprovidingavisuallyintuitivedescriptionofpreferencestructure. Hybridsandfuzzyextensionsofthese MCDMmethodologiesallowfortheapplicationof MCDMmethodstouncertaindecisionalternativesinunabletohavecompleteinformationenvironments. Thechoiceof MCDMmethodologyshouldbecarefullyconsideredbythedecision-makerbasedonthestructuralcharacteristicsofthedecisionproblem, thenatureofthedataavailable, andtheanalyticalcapabilitiesoftheorganisationapplyingthedecision-makingframework. Theanalysisofspecificindustriesindicatesthatthereisapatterninthewayriskandrulesareanalyzed. Theaviationindustryusessafetyandabilitytofindtheoriginofcomponentswhendeterminingwhattobuy; theoilandgasindustryfocusesonriskandhowtheworkwillaffecttheenvironment; andtheconstructionindustrylooksatthecosttogetwhatisbuiltaswellastheabilitytodeliveritontime. Therefore, MCDMmethodsmustbedesignedspecificallyforeachindustry, ratherthanusinggeneralmethodsacrossallindustries. Thereareseveralareasofresearchwherefurtherinvestigationisneeded. Empiricalevidenceof MCDMsystemshas, forthemostpart, notbeenexaminedintheoilandgasorconstructionindustrieswithrespecttoimplementationsacrossmanyorganizationsoveranumberoflocationsaroundtheworld. Anotherareaofstudyistheuseofreal-timemeasurementofsuppliers'performanceandtheintegrationofintelligentpredictiontoolswithinthe MCDMsystems. Thecreationofindustrystandard MCDMtemplateswouldmakeiteasierfororganizationstoadoptthesesystems International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com627|Pageandexpandtheiruse. Finally, conductinglong-termstudiescomparing MCDMversustraditionalpurchasingwouldprovideevidenceofthevalidityof MCDMsystemsandtheirabilitytocreatevalueforbusinessesengagedinanyofthethreeindustriesmentionedpreviously. References
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Journal: International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE)

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