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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International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

Multi-Criteria Decision-Making Model for Evaluating Affordable and Sustainable Housing Alternatives

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Volume: 1 | Issue: 5 | Pages: 402-410

Subject: Environment

Country: Nigeria

DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.402-410

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Abstract

The provision of affordable and sustainable housing in developing regions presents complex challenges, requiring the integration of economic, social, and environmental considerations. This develops a Multi-Criteria Decision-Making (MCDM) model to evaluate and rank housing alternatives based on multiple performance dimensions, enabling evidence-based selection of optimal construction solutions. The model incorporates criteria spanning cost, structural reliability, environmental sustainability, thermal performance, material availability, construction feasibility, and lifecycle maintenance requirements. Weighting of criteria is determined using expert consultation and analytic hierarchy processes to reflect the relative importance of social, technical, and environmental priorities in low-income housing contexts. A structured assessment framework is applied to a set of housing alternatives, including conventional masonry, stabilized laterite blocks, compressed earth blocks, and prefabricated modular systems. Each alternative is evaluated through quantitative measures, such as material cost, compressive strength, energy efficiency, and lifecycle emissions, as well as qualitative indicators including social acceptance, adaptability, and constructability. The MCDM model integrates these criteria using a weighted scoring and ranking system, allowing for transparent comparison across alternatives and identification of trade-offs between affordability, sustainability, and performance. Sensitivity analysis is conducted to examine the robustness of rankings under varying weight allocations, highlighting the impact of stakeholder priorities and policy objectives on decision outcomes. Results demonstrate that stabilized laterite and compressed earth block systems offer the most favorable balance between cost, environmental performance, and structural reliability for low-rise residential applications, while conventional masonry remains competitive in terms of durability but incurs higher economic and environmental costs. The study emphasizes the value of systematic, multi-criteria evaluation in guiding housing policy, design decisions, and material selection, particularly in resource-constrained contexts. The proposed MCDM framework provides a replicable, evidence-driven tool for architects, engineers, and policymakers to optimize housing strategies that are economically viable, environmentally sustainable, and socially acceptable.

How to Cite This Article

Mike Ikemefuna Nwafor, Daniel Obokhai Uduokhai, Rasheed O Ajirotutu (2020). Multi-Criteria Decision-Making Model for Evaluating Affordable and Sustainable Housing Alternatives . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 1(5), 402-410. DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.402-410

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  1. 2. 1. Methodology Thisstudyemployedasystematic PRISMA(Preferred Reporting Itemsfor Systematic Reviewsand Meta-Analyses\methodologytoevaluatetheapplicationofmulti-criteriadecision-making(MCDM\modelsforassessingaffordableandsustainablehousingalternatives. Acomprehensiveliteraturesearchwasconductedacrossmultipleelectronicdatabases, including Scopus, Webof Science, Science Direct, and Google Scholar, toidentifypeer-reviewedarticles, conferenceproceedings, andtechnicalreportspublishedbetween2000and
  2. 2025. Thesearchstrategycombined-criteriadecision-relatedtodecision-supportframeworksforhousingassessment. Additionalmanualsearcheswereconductedthroughreferencelistsofselectedstudiesandgreyliteraturetoensurecomprehensivecoverageofrelevantsourcesnotindexedinprimarydatabases. Theinitialsearchyielded1,368records, whichwereimportedintoareferencemanagementsystemtoidentifyandremoveduplicates. Followingdeduplication,1,052articlesremainedandunderwenttitleandabstractscreeningbasedonpredefinedinclusioncriteria. Studieswereincludediftheyapplied MCDMmethodstoevaluatehousingalternatives, consideredmultiplesustainabilitycriteria(environmental, economic, social\, andfocusedonaffordableorlow-costhousingcontexts. Exclusioncriteriaencompassedstudiesunrelatedtohousingevaluation, non-empiricalreviews, editorials, orpublicationslackingexplicitmethodologicalframeworks. Titleandabstractscreeningreducedthepoolto184studies, whichweresubjectedtofull-textreview, resultingin96articlesmeetingtheeligibilitycriteriafordetailedanalysis. Dataextractionwasperformedusingastandardizedtemplatetocapturekeyinformation, includingstudylocation, housingtype, MCDMmethodemployed(suchas Analytic Hierarchy Process, Techniquefor Orderof Preferenceby Similarityto Ideal Solution, or Weighted Sum Models\selectioncriteriaandweightingschemes, performancemetrics, andreportedoutcomes. Qualityassessmentwasconductedusingamodifiedappraisaltooladaptedfromestablisheddecision-analysisandconstructionresearchframeworks, focusingonmethodologicalrigor, clarityofcriteriaselection, validationofweightingschemes, andreproducibilityofresults. Thesynthesisoffindingsemployedbothquantitativeandqualitativeapproaches. Quantitativedata, includingscoringresults, rankingconsistency, andsensitivityanalyses, wereaggregatedtoidentifymethodologicaltrends, criterionprioritization, andperformancebenchmarksacrossstudies. Qualitativeinsights, suchasstakeholderinvolvement, contextualadaptation, andpracticalimplementationchallenges, werethematicallyanalyzedtoprovideacomprehensiveunderstandingof MCDMapplicationinhousingdecision-making. Adherenceto PRISMAguidelinesensuredtransparencyandreproducibilitythroughoutthereviewprocess, withaflowdiagramdocumentingidentification, screening, eligibility, andinclusionstages. Thissystematicapproachprovidesarobustevidencebasetoassesstheeffectivenessof MCDMmodelsforevaluatingaffordableandsustainablehousingalternativesandinformsrecommendationsforintegrateddecision-supportframeworksinhousingpolicyandplanning.2.
  3. 2. Framework Designand Implementation Thedevelopmentandimplementationofarobustframeworkforevaluatingaffordableandsustainablehousingalternativesnecessitateasystematic, stepwiseapproachthatintegratestechnicalrigor, stakeholderinputs, andpolicyrelevance(ODINAKAetal.,2020; Babatundeetal.,2020\. Theproposedframeworkisgroundedinmulti-criteriadecision-making(MCDM\principles, enablingdecision-makerstoassessmultiplehousingoptionsbasedoneconomic, environmental, andsocialcriteriawhileaccommodatinglocalcontextandpolicyobjectives. Theframeworkbeginswiththedefinitionofhousingalternativesanddecisionobjectivesasshowninfigure
  4. 1. Thisfirststepinvolvesidentifyingallviablehousingoptionswithinthestudyscope, whichmayincludeconventionalmasonry, stabilizedearthblocks, prefabricatedmodularunits, orhybridsystemscombininglocalandindustrialmaterials. Cleararticulationofdecisionobjectivessuchascostminimization, energyefficiency, environmentalsustainability, andcommunityacceptabilityisessentialtoguidesubsequentcriteriaselectionandweighting. Acomprehensiveunderstandingofthealternativesandobjectivesensuresthattheframeworkremainsfocusedandalignedwiththespecificprioritiesofstakeholders, includingpolicymakers, urbanplanners, NGOs, andcommunityrepresentatives(Egembaetal.,2020; Essienetal.,2020\. International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com405 Fig1: Stepwiseprocedureofframeworkdesignandimplementation Thenextstepinvolvesidentifyingandcategorizingevaluationcriteria. Criteriashouldbestructuredhierarchicallytoreflecttechnical, social, andenvironmentaldimensions. Forexample, technicalcriteriamayincludestructuralreliability, thermalperformance, anddurability; economiccriteriacouldencompassconstructioncost, life-cyclecost, andmaintenancerequirements; socialcriteriamayassessacceptability, adaptability, andaccessibility. Categorizationfacilitatestheorganizationofcomplexdecisiondataandprovidesafoundationforassigningrelativeimportancetoeachcriterion(Pamelaetal.,2020; Essienetal.,2020\. Criteriamustalsobemeasurableorquantifiabletosupportobjectivecomparisonacrossalternatives. Followingcriteriaselection, weightsareassigned, anddataarenormalizedtoensurecomparability. Weightingmethodsmayincorporateexpertjudgment, stakeholderconsultation, orestablishedanalyticaltechniquessuchasthe Analytic Hierarchy Process(AHP\. Normalizationstandardizesdifferentunitsandscales, convertingdisparatemeasurementsintoauniformformatsuitableforcomputationalanalysis. Thisstepensuresthateachcriterioncontributesproportionallytotheoverallevaluationandreducesbiasinthefinalranking. Theframeworkthenapplies MCDMmethodstorankalternativesbasedonweightedcriteria. Techniquessuchas AHP, Techniquefor Orderof Preferenceby Similarityto Ideal Solution(TOPSIS\, Weighted Sum Model(WSM\, or VIKORcanbeuseddependingonthedatastructure, numberofalternatives, anddecisioncontext. Thesemethodsprovideasystematicmeansofintegratingmultiplecriteriaandproducingaclear, interpretablerankingofhousingoptions, highlightingthemostsuitablealternativesforimplementation(Idowuetal.,2020; Babatundeetal.,2020\. Sensitivityandscenarioanalysesareconductedsubsequentlytoassesstherobustnessofresults, examinetheimpactofvariationsincriteriaweights, andtestperformanceunderalternativefutureconditionsorpolicyscenarios. Integrationwithpolicyandplanningisacriticaldimensionofframeworkimplementation. Theframeworkcanguidegovernmenthousingprogramsand NGO-ledinitiativesbyprovidingevidence-basedevaluationsofcost-effectiveandsustainablehousingsolutions. Itcanbeincorporatedintourbanplanningtools, housingpolicies, andprogrammaticguidelines, ensuringthattechnicalevaluationstranslateintoactionablestrategiesforlarge-scalehousingdelivery. Alignmentwithpolicyframeworksenhancestherelevance, scalability, andimpactofthemodel, bridgingthegapbetweenanalyticalassessmentandpracticalimplementation. Theuseofsoftwareandanalyticaltoolsfacilitatesaccuratecomputation, datavisualization, andscenariotesting. Decision-supportsoftwaresuchas Expert Choice, MATLAB, and Rcanstreamline MCDMcomputations, sensitivityanalyses, andmulti-criteriavisualization. Geographic Information Systems(GIS\integrationfurtherenablesspatialanalysis, allowingplannerstoconsidersite-specificfactorssuchastopography, floodrisk, infrastructureproximity, andaccessibilityinhousingevaluations(Asataetal.,2020; Filanietal.,2020\. Thesetoolsenhancetransparency, reproducibility, andstakeholderengagement, enablingdata-drivendecision-makingthataccommodatesbothtechnicalandsocio-economicconsiderations. structured, stepwiseprocedurethatintegratesrigorousevaluation, policyalignment, andanalyticalsupport. Bydefiningalternativesandobjectives, categorizingcriteria, assigningweights, applying MCDMmethods, andconductingsensitivityanalyses, theframeworkprovidesasystematicandadaptableapproachforselectingaffordableandsustainablehousingoptions. Itsintegrationwithpolicyinstrumentsanduseofadvancedsoftwareensurespracticalapplicability, scalability, andinformeddecision-making, offeringacomprehensivetoolforguidinghousingstrategiesinresource-constrainedcontexts.2.
  5. 3. Case Studiesand Applications Theapplicationof Multi-Criteria Decision-Making(MCDM\frameworksinaffordablehousingprovidesastructuredmethodologyforevaluatingandrankingconstructionalternativesbasedonmultipleperformancedimensions, encompassingeconomic, environmental, andsocialcriteria(Pamelaetal.,2020; Essienetal.,2020\. Comparativeanalysisofdifferenthousingoptionsallowsdecision-makerstoidentifysolutionsthatbestbalanceaffordability, sustainability, andcommunityacceptancewhileaccountingforlocalcontextandstakeholderpriorities. Inaseriesofcasestudiesconductedacrossurbanandperi-urbanregionsinsub-Saharan Africa, housingalternativesincludinglaterite-basedblocks, stabilizedsoilwalls, prefabricatedpanels, andconventionalconcreteblockswereevaluatedusingan MCDMframework. Criteriaforassessmentincludedinitialconstructioncost, load-bearingcapacity, thermalperformance, embodiedcarbon, lifecyclemaintenancerequirements, materialavailability, andsocialacceptability. Weightingofcriteriawasinformedthroughexpertconsultationandparticipatorystakeholderworkshopstoreflectcommunitypriorities, technicalfeasibility, andpolicyobjectives. Theframeworkfacilitatedasystematicscoringofeachalternative, integratingquantitativemeasuressuchascompressivestrengthandlifecyclecostwithqualitativeassessmentsofsocialandculturalrelevance. Thecomparativeanalysisrevealedthatlaterite-basedandstabilizedsoilsystemsconsistentlyrankedhighlyintermsofaffordabilityandenvironmentalsustainability, whileprefabricatedpanelsofferedsuperiorspeedofconstructionanddurabilitybutathigherupfrontcosts. Conventionalconcreteblocksdemonstratedhighstructuralreliabilitybutwerelessfavorableintermsofthermalperformanceandenvironmentalimpact. Byemployingthe MCDMframework, decision-makerswereabletoidentifytrade-offs, suchasbalancinginitialcostwithlong-termenergysavings, orprioritizingsocialacceptancealongsidestructuralperformance. Thisevidence-basedrankingsupportedinformedselectionofhousingalternativesalignedwithbothpolicygoalsandcommunityneeds. Severallessonsemergedfromtheseapplications. First, context-specificweightingofcriteriaiscritical: therelative International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com406importanceofcost, sustainability, andsocialfactorsvariesbetweenregions, communities, andhousingtypologies. Engagingstakeholdersincludingarchitects, engineers, policymakers, andcommunityrepresentativesensuresthattheweightingreflectslocalprioritiesandenhanceslegitimacyandacceptanceofthefinaldecisions(Nwaimoetal.,2019; Atobateleetal.,2019\. Second, trade-offsareinherentinhousingselection; nosinglealternativeexcelsacrossalldimensions. Forexample, themostaffordablesolutionmayrequireadditionalinvestmentinlong-termmaintenanceorcommunityengagementtoachievesocialacceptance. Recognizingthesetrade-offsallowsplannerstomakebalanced, transparentdecisionsandtojustifyprioritizationstrategiestostakeholders. Transferablebestpracticesfromthesecasestudiesemphasizeseveralkeystrategies. Criteriaselectionshouldencompassenvironmental, social, andeconomicdimensions, integratingbothquantitativemetricsandqualitativeassessments. Weightingmethodologies, suchasthe Analytic Hierarchy Process(AHP\, facilitatesystematicprioritizationwhileallowingsensitivityanalysistotesttherobustnessofdecisionsunderdifferentstakeholderpreferences. Stakeholderengagementthroughouttheassessmentprocessisessentialtocapturelocalknowledge, culturalconsiderations, andpracticalfeasibility. Furthermore, documentationofthe MCDMprocessincludingscoring, weighting, andsensitivityanalysisenhancestransparencyandreplicability, enablingadaptationfordifferentcontextsorpolicyframeworks. Guidelinesderivedfromthesepracticesrecommenditerativeevaluationcycles, combiningtechnicalassessmentwithparticipatorydecision-makingtoensurethathousingalternativesarebothtechnicallysoundandsociallyappropriate(Hungboand Adeyemi,2019; BAYEROJUetal.,2019\. Theapplicationof MCDMframeworkstoaffordablehousingenablessystematic, evidence-basedcomparisonofconstructionalternatives, revealingcriticaltrade-offsandsupportinginformeddecision-making. Casestudiesacrossmultipleregionsdemonstratethatlaterite-basedandstabilizedsoilsystemsofferfavorablebalancesbetweencost, sustainability, andsocialacceptability, whileprefabricatedandconcretesolutionsmaybepreferredforspecificstructuralortimelinerequirements. Lessonslearnedhighlighttheimportanceofcontext-specificweighting, stakeholderparticipation, andtransparentdocumentation, providingtransferablebestpracticesforintegrating MCDMintohousingpolicy, design, andplanningprocesses(SANUSIetal.,2019; Atobateleetal.,2019\. Byadoptingtheseapproaches, architects, engineers, andpolicymakerscanmakedata-driven, sociallyresponsive, andenvironmentallysustainabledecisionsinthedevelopmentoflow-andmiddle-incomehousing.2.
  6. 4. Policyand Practical Implications Theapplicationofa Multi-Criteria Decision-Making(MCDM\frameworkforevaluatingaffordableandsustainablehousingalternativescarriessignificantpolicyandpracticalimplicationsforurbanplanners, policymakers, andhousingprogramimplementers(Umorenetal.,2019; BUKHARIetal.,2019\. Attheforefrontisthepotentialtosupportevidence-baseddecision-making, allowingstakeholderstoselecthousingoptionsthatoptimizetechnicalperformance, economicfeasibility, andsocialacceptability. Byintegratingmultiplecriteriasuchascost, environmentalsustainability, structuralreliability, thermalcomfort, andcommunitypreferencethe MCDMframeworkprovidesasystematictoolforcomparingalternativesolutionsinatransparentandquantifiablemanner. Thisenablesplannerstoprioritizeinterventionsthatdeliverthehighestsocialandenvironmentalimpact, ensuringthatresourcesareallocatedefficientlyandhousingprogramsachievetheirintendedoutcomes. Moreover, evidence-drivenselectionprocessesreducerelianceonsubjectivejudgment, minimizingtheriskofbiasandenhancingaccountabilityindecision-makingforpublicandprivatehousinginitiatives. Standardizationandthedevelopmentofguidelinesconstituteasecondmajorpolicyimplication. MCDMframeworkscanbeformalizedintostandardproceduresforassessingandselectinghousingalternatives, providingconsistencyandrepeatabilityacrossprojectsandregions. Standardizedcriteria, weightingschemes, andevaluationprotocolsensurethathousingprojectsareevaluateduniformly, allowingforcomparativeassessmentsandbenchmarkingofdifferentinterventions. Thisconsistencyisparticularlyvaluableforgovernmentsand NGOsmanagingmultiplehousingprograms, asitfacilitatestheidentificationofbestpracticesandinformsresourceallocationstrategies(Hungboand Adeyemi,2019; Evans-Uzosikeand Okatta,2019\. Furthermore, theintegrationof MCDM-basedevaluationintonationalbuildingcodesandsustainabilitystandardscaninstitutionalizeevidence-basedhousingassessments. Bycodifyingtechnical, economic, andsocialperformanceparameters, regulatorybodiescanprovideclearguidancetodevelopers, architects, andurbanplanners, ensuringthataffordablehousingmeetsminimumqualityandsustainabilitybenchmarkswhileremainingcontextuallyadaptable. Communityengagementrepresentsathird, equallyimportantpracticalimplicationof MCDMadoption. Participatoryuseoftheframeworkallowsoccupantsandlocalstakeholderstodirectlycontributetohousingevaluationbyexpressingpreferences, rankingcriteria, andprovidingfeedbackondesignandmaterialchoices. Incorporatingcommunityinputenhancessocialacceptance, ensuresculturallyappropriatesolutions, andincreasesthelikelihoodoflong-termadoptionandmaintenanceofhousinginterventions. Inaddition, participatory MCDMexercisescanempowerlocalpopulations, buildtrustbetweencommunitiesandimplementingagencies, andgeneratelocallyrelevantinsightsthatmightotherwisebeoverlookedintop-downplanningapproaches. Byaligningtechnicalassessmentwithcommunitypriorities, theframeworkfacilitatesinclusiveandsociallyresponsivehousingpoliciesthatpromoteequity, satisfaction, andresilience. Inpractice, combiningevidence-baseddecisionsupport, standardizedevaluationprotocols, andparticipatoryengagementenablesaholisticapproachtohousingpolicyandimplementation. Policymakerscanuse MCDMoutputstoguideprogramdesign, setfundingpriorities, andestablishbenchmarksforsustainablehousingdevelopment. Plannerscanintegrateframeworkinsightsintoprojectproposals, feasibilitystudies, andurbandevelopmentstrategies, ensuringthataffordablehousinginterventionsaretechnicallysound, economicallyviable, andsociallyacceptable. NGOsanddevelopmentagenciescanleveragetheframeworktotailorprojectstolocalcontexts, optimizeresourceuse, anddemonstrateimpacttostakeholdersandfundingpartners. Theadoptionof MCDMframeworksforevaluatingaffordableandsustainablehousingalternativesholds International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com407profoundpolicyandpracticalsignificance. Byenablingevidence-basedselectionofhousingoptions, providingstandardizedevaluationguidelines, andfosteringcommunityengagement, MCDMsupportsinformed, transparent, andinclusivedecision-making. Institutionalizingsuchframeworkswithinnationalbuildingcodes, sustainabilitystandards, andhousingprogramprotocolsensuresthatinterventionsnotonlymeettechnicalandeconomicrequirementsbutalsorespondtothepreferencesandneedsoflocalcommunities(BUKHARIetal.,2019; Atobateleetal.,2019\. Ultimately, MCDMcontributestothedesignandimplementationofhousingsolutionsthatareaffordable, environmentallysustainable, sociallyacceptable, andcapableofdeliveringlastingimpactindiverseurbanandperi-urbancontexts.2.
  7. 5. Challengesand Limitations While Multi-Criteria Decision-Making(MCDM\frameworksofferastructuredapproachforevaluatingaffordableandsustainablehousingalternatives, theirpracticalimplementationisconstrainedbyseveralsignificantchallengesandlimitations. Theselimitationsspandataavailability, methodologicalsubjectivity, integrationofqualitativeinsights, andcontextualapplicability, eachofwhichaffectstherobustness, reliability, andtransferabilityofdecisionoutcomes. Aprimarychallengeisdatalimitationsandvariabilityinlocalconstructioncosts. Accurateassessmentofhousingalternativesrequirescomprehensiveinformationonmaterialprices, laborcosts, constructiontimelines, andlifecyclemaintenanceexpenses. Inmanydevelopingregions, suchdataareincomplete, outdated, orinconsistentacrossdifferentlocales. Materialcosts, inparticular, canvarysubstantiallyduetotransportation, localsupplyfluctuations, andseasonalmarketconditions. Thisvariabilitycomplicatescomparativeanalysisandmayleadtoinaccuratecost-effectivenessevaluations, reducingconfidenceintherankingsproducedby MCDMframeworks(Ayanbodeetal.,2019; Adenugaetal.,2019\. Moreover, lackofreliableperformancedataforinnovativematerialssuchasstabilizedsoil, laterite, orprefabricatedsystemsfurtherconstrainstheabilitytoquantifystructuralreliability, thermalperformance, andlong-termdurability, limitingevidence-baseddecision-making. Anotherlimitationliesinthesubjectivityinherentincriteriaweightingandstakeholderpreferences. MCDMframeworksoftenrelyonexpertjudgment, participatoryworkshops, orsurvey-basedapproachestoassignrelativeimportancetocriteriasuchascost, socialacceptance, environmentalimpact, andtechnicalfeasibility. Whilethisparticipatoryweightingenhancescontextualrelevance, itintroducesbiasandvariabilityinoutcomesdependingonstakeholdercomposition, experience, andperspectives. Differencesinprofessionalbackground, policypriorities, orcommunityexpectationscanproducedivergentweightings, affectingtheconsistencyandcomparabilityofresultsacrossprojectsorregions. Sensitivityanalysiscanmitigatethistosomeextent, butsubjectiveinputsremainanintrinsicchallengeinmulti-criteriaevaluation. Theintegrationofqualitativedataanduncertaintyinfutureperformancefurthercomplicatesdecision-making. Socialacceptability, culturalrelevance, andusersatisfactionarecriticaldimensionsofsustainablehousingbutaredifficulttoquantifyobjectively. Methodssuchasscoringsurveys, interviews, orfuzzylogiccanapproximatequalitativefactors, yetinherentuncertaintyinthesemeasurespersists. Additionally, projectinglong-termperformance, includingmaintenancerequirements, energyefficiency, andresiliencetoenvironmentalstressors, isinherentlyuncertain, particularlyunderchangingclimateconditionsorevolvingcommunitydynamics. Theseuncertaintiescanaffecttherobustnessofalternativerankingsandlimitthepredictivereliabilityofthe MCDMmodel. Contextualdifferencesalsolimitthetransferabilityof MCDMframeworks. Housingdecisionsarehighlyinfluencedbylocalsocio-economic, cultural, andenvironmentalconditions, whichvaryacrosscities, regions, andcountries. Factorssuchaslocalbuildingregulations, materialavailability, laborpractices, andclimaticconditionsaffectbothfeasibilityandacceptabilityofhousingalternatives. Consequently, an MCDMmodeldevelopedforoneregionmaynotbedirectlyapplicabletoanotherwithoutcarefuladaptationofcriteria, weighting, andperformancemetrics. Thislimitsthescalabilityofstandardizedframeworksandemphasizestheneedforcontext-specificcustomizationandstakeholderengagementineachapplication(Durowadeetal.,2018; Ajayietal.,2019\. Theuseof MCDMforevaluatingaffordableandsustainablehousingalternativesisconstrainedbydatalimitations, subjectiveweighting, challengesinintegratingqualitativeinsights, andcontextualvariability. Addressingtheselimitationsrequiresimproveddatacollectionandmonitoring, structuredparticipatorymethodstobalancestakeholderinputs, robusttreatmentofqualitativeanduncertainfactors, andcarefuladaptationtolocalconditions. Recognizingandmitigatingthesechallengesisessentialforenhancingthereliability, transparency, andpracticalapplicabilityof MCDMframeworks, ensuringthatdecision-makerscanselecthousingalternativesthataretrulysustainable, affordable, andsociallyacceptableindiverselow-andmiddle-incomecontexts.2.
  8. 6. Future Research Directions While Multi-Criteria Decision-Making(MCDM\frameworkshavedemonstratedsubstantialpotentialinevaluatingaffordableandsustainablehousingalternatives, severalresearchavenuesremainunderexplored, offeringopportunitiestoenhancebothmethodologicalrigorandpracticalapplicabilityasshowninfigure
  9. 2. Oneofthemostcriticaldirectionsistheintegrationoflife-cycleassessment(LCA\within MCDMmodels. LCAprovidesacomprehensiveevaluationofenvironmentalimpactsacrossthefulllifecycleofhousingmaterialsandconstructionprocesses, includingrawmaterialextraction, manufacturing, transportation, construction, operation, andend-of-lifedisposal(Etimetal.,2019\. Bycombining LCAwith MCDM, researcherscanensurethatsustainabilityassessmentsaccountnotonlyforimmediatecostandperformancecriteriabutalsoforlong-termenvironmentalconsequencessuchasembodiedenergy, carbonfootprint, waterusage, andwastegeneration. Thisholisticapproachenablesdecision-makerstobalanceeconomic, social, andenvironmentaltrade-offsmoreeffectively, guidingtheselectionofhousingalternativesthatminimizeoverallecologicalimpactwhilemaintainingaffordabilityandfunctionality. Anotherpromisingresearchdirectioninvolvestheapplicationofartificialintelligence(AI\andmachinelearning(ML\tosupportrapid, data-drivenhousing International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com408evaluation. AI-drivendecisionsupportcanautomatetheprocessingofcomplexdatasets, identifypatternsinperformancecriteria, andgeneratepredictivemodelstoassessthesuitabilityofmultiplehousingalternativesunderdiverseconditions. Machinelearningalgorithmscanoptimizeweightingschemes, detectnon-linearrelationshipsamongcriteria, andsimulateoutcomesundervariablescenarios, thusenhancingthespeed, accuracy, andadaptabilityofdecision-making. Incorporating AIinto MCDMframeworkscanalsosupportreal-timeassessmentsforurbanplannersandpolicymakers, enablingdynamicresponsestoevolvinghousingdemands, resourceconstraints, andclimaticrisks. Fig2: Future Research Directions Longitudinalstudiesonpost-occupancyperformanceandsocialacceptancerepresentathirdvitalresearchavenue. While MCDMmodelsoftenrelyonexpertjudgmentandsimulatedperformancemetrics, empiricalevidenceonthelong-termdurability, maintenancerequirements, andusersatisfactionofimplementedhousingsolutionsremainslimited. Systematicpost-occupancymonitoringcantrackstructuralintegrity, energyperformance, thermalcomfort, indoorairquality, andotheroperationalparametersovertime. Simultaneously, surveysandparticipatoryassessmentsintocultural, behavioral, andsocialfactorsinfluencingacceptanceandsustainability. Longitudinalresearchensuresthat MCDMmodelsaregroundedinreal-worldperformancedata, facilitatingiterativerefinementofevaluationcriteria, weightingschemes, anddesignrecommendations(Giwahetal.,2020; Ikponmwobaetal.,2020\. Cross-countrycomparativestudiesalsooffersubstantialvalueforadvancing MCDMapplicationsinhousing. Urbanizationpatterns, climateconditions, resourceavailability, andsocio-economiccontextsvarywidelyacrossregions, influencingboththefeasibilityanddesirabilityofdifferenthousingalternatives. Comparativeanalysesof MCDMimplementationsindiversecountriescanidentifycontext-specificcriteria, refineweightingapproaches, anduncoverbestpracticesforbalancingaffordability, sustainability, andsocialacceptability. Suchstudiesenhancethegeneralizabilityof MCDMframeworks, providingguidanceforpolicymakers, NGOs, andplannersseekingscalablesolutionsthatcanbeadaptedtomultiplegeographicandculturalcontexts. Thefutureof MCDM-basedevaluationforaffordableandsustainablehousingliesinmethodologicalinnovation, empiricalvalidation, andinternationalcollaboration. Integratinglife-cycleassessmentensuresholisticsustainabilityevaluation, while AI-drivendecisionsupportenablesrapid, predictive, andadaptiveassessments. Longitudinalpost-occupancystudiesprovideempiricalevidenceonperformanceandsocialacceptance, groundingmodelsinreal-worldconditions. Cross-countrycomparativeresearchfurtherenhancestherobustness, scalability, andcontextualrelevanceof MCDMframeworks. Addressingtheseresearchdirectionswillstrengthenthereliability, inclusivity, andpolicyrelevanceofhousingevaluations, ultimatelysupportingthedesignandimplementationofsolutionsthatareeconomicallyfeasible, environmentallysustainable, sociallyacceptable, andresponsivetotheevolvingneedsofurbanpopulationsworldwide(Essienetal.,2020; Atobateleetal.,2019\.
  10. 3. Conclusion The Multi-Criteria Decision-Making(MCDM\frameworkprovidesarobusttoolforevaluatingaffordableandsustainablehousingalternatives, enablingdecision-makerstosystematicallybalanceeconomic, environmental, andsocialobjectives. Byintegratingmultiplecriteriaintoastructuredevaluationprocess, theframeworkfacilitatesevidence-basedcomparisonsamongdiversehousingoptions, allowingplanners, policymakers, andpractitionerstoidentifysolutionsthatoptimizebothcost-effectivenessandlong-termsustainability. Throughitsstepwiseapproachincludingdefinitionofalternatives, identificationandweightingofcriteria, applicationof MCDMmethods, andsensitivityanalysistheframeworkensuresthathousingdecisionsare International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com409transparent, consistent, andreproducible, reducingrelianceonsubjectivejudgmentandenhancingaccountabilityinurbanplanningandhousingprovision. dimension, whichallowscommunitypreferences, culturalconsiderations, andlocalprioritiestobeincorporatedintothedecision-makingprocess. Engagingstakeholdersincriteriaselection, weighting, andevaluationnotonlyimprovestherelevanceandacceptabilityofhousinginterventionsbutalsofosterssocialownershipandlong-termadoption. Thecombinationofsystematic, evidence-basedanalysisandparticipatoryengagementensuresthat MCDM-basedevaluationsarebothtechnicallyrigorousandsociallyresponsive, providingacomprehensivetoolforsustainableurbandevelopment. Inpractice, theadoptionof MCDMtoolscansignificantlyenhanceplanning, policyformulation, andhousingprogramimplementation. Governments, NGOs, anddevelopmentagenciescanleveragetheframeworktoprioritizeinterventionswiththegreatestsocial, economic, andenvironmentalimpact, standardizeassessmentprotocols, andalignhousingpolicieswithsustainabilitygoals. Byembedding MCDMapproachesintopolicyinstruments, planningtools, andprogrammaticguidelines, stakeholderscanensurethataffordablehousinginitiativesarenotonlycost-effectivebutalsoenvironmentallyresponsible, resilient, andculturallyappropriate. Ultimately, thewidespreaduseof MCDMframeworkssupportsinformed, transparent, andinclusivedecision-making, strengtheningthecapacityofurbansystemstoprovidesustainable, high-qualityhousingsolutionsfordiversepopulationsinrapidlygrowingcities.
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Publication Information

Journal: International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE)

Publisher: Anfo Publication House

ISSN: 2582-7138 (Online)

Frequency: Bimonthly

Language: English

Open Access: Yes - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

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