Modelling the Impact of Management Practices on Retail Store Productivity.docx
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Modelling the Impact of Management Practices on Retail Store Productivity.docx
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ModellingtheImpactofManagementPracticesonRetailStoreProductivity
ModellingtheImpactofManagementPracticesonRetailStoreProductivity
1Introduction
Wheninvestigatingthebehaviourofcomplexsystemsthechoiceofanappropriatemodellingtechniqueisveryimportant.Differentapproacheswillsuitdifferentpurposesandanswerdifferentquestions.
Weareinterestedinunderstandingandpredictingtheimpactofdifferentmanagementpracticesonretailstoreproductivity.Currently,wefocusonaparticulardepartmentstorewiththeaimofmodellingindividualsalesdepartments.Inthefutureweconsiderexpandingourhorizonandmodeldifferentdepartmentstoresandconductcross-countrycomparisons.Forthemoment,however,wekeepitassimpleaspossiblewhilststillobtainingmeaningfulresults.
Withregardstotheoutputofthestudyweareprimarilyinterestedincapturingemergentphenomena.Emergenceoccurswheninteractionsamongobjectsatonelevelgiverisetodifferenttypesofobjectsatanotherlevel.Moreprecisely,aphenomenonisemergentifitrequiresnewcategoriestodescribeitwhicharenotrequiredtodescribethebehaviouroftheunderlyingcomponents(GilbertandTroitzsch,2005).Capturingemergentphenomenaisnecessarytonotjustmeasurebutunderstandtheimpactofthemanagementpractices.Therearethreequestionswehaveusedtostructureourliteraturereview:
1.Whichareasareworthinvestigatinginordertofindasuitablemodellingapproach?
2.Doanymodelscurrentlyexist,thatmodeltheimpactonmanagementpracticesonproductivityintheretailsector?
3.Whatmodellingapproachesarecommonlyusedwithinrelatedareas?
Weincluded196documentsinourreviewinordertofindanswerstothequestionsraised.Fromthesewehaveidentified28keydocumentswhichwecitethroughoutthetext.Thenextsectionincludesadiscussionofthesequestionswhilethelastsectionpresentstheconclusionsfromthereviewandgivessomeideasregardingourfutureplans.
2ReviewofRelevantLiterature
2.1Whichareasareworthinvestigatingtofindasuitablemodellingapproach?
Figure1:
Reviewareas,modellingapproaches,andapplicationtypes
Withourfocusonunderstandingandpredictingtheimpactofdifferentmanagementpracticesonretailstoreproductivity,wehavesearchedtheliteratureforsuitablemodellingmethods.AnoverviewoftheareasthatweconsideredforthereviewispresentedinFigure1.Thisfigurealsoshowsthecommonlyusedmodellingapproachesand/orapplicationtypeswithinthedifferentareas.
2.2Doanymodelsexist,thatmodeltheimpactonmanagementpracticesonproductivityintheretailsector?
Afterdefiningtheareasofinterestweextensivelyreviewedmaterialavailableonthesubject,withparticularemphasisonthosethatinvestigatethelinkbetweenmanagementpracticesandproductivityintheretailsector.Wefoundalimitednumberofpapersthatinvestigatemanagementpracticesinretailatfirmlevel.Themajorityofthesepapersfocusonmarketingpractices(e.g.Cao,1999;Kehetal.,2006).OnenoteworthyexceptionisBermanandLarson(2004),whoinvestigatetheefficiencyofcrosstrainedworkersinstores.Byfarthemostfrequentlyusedmodellingtechniqueinallthesepapersisagent-basedmodellingwhichwillbediscussedinmoredetaillater.Thisseemstobeanaturalwayofsystemrepresentationforthesepurposes.
Mostpapersthatinvestigateretailproductivityfocusprimarilyonconsumerbehaviourandefficiencyevaluationwithlessemphasisonretailmanagementpractices.Thesepaperscanbefurthersegmentedintothoseinvestigatinghighstreetretailingandthosefocusingononlineretailing,i.e.physicalandelectronicdistributionchannels.Anadvantageoflookingatonlineretailingistheavailabilityofdata,duetoeveryclickbeingrecorded.Ontheotherhand,datainmanyhighstreetstoresisavailablefromloyaltycards,creditcards,salesslipsandcustomersurveys.AninterestingcontributionismadebyNicholsonetal.(2002),whocomparedifferentmarketingstrategiesformultichannel(physicalandelectronic)retailing.Theyconcludethattherearebigdifferenceswithintheconsumerdecisionmakingprocessintermsofthedifferentchannels.
Regardingtheinvestigationofcross-countrydifferencesinrelationtotheapplicationandimpactofretailmanagementpracticesonproductivity,wefoundnopapersthatattempttomodelthisissue.
Intermsofcommercialsoftware,anexamplewasfoundwhichsimulatestherelationshipbetweencertainmanagementpracticesandproductivity.ShopSim(SavannahSimulations,2006)isadecisionsupporttoolforretailandshoppingcentremanagement.Itevaluatestheshopmixattractivenessandpedestrianfriendlydesignofashoppingcentre.Thesoftwareusesanagentbasedapproach,wherebehaviourofagentsdependsonpolldata.Itisagoodexampleofthekindoftoolwewouldliketodevelop,althoughourtoolwouldoperateonadepartmentlevelratherthanonashoppingcentrelevelandwouldinvestigatedifferentkindsofmanagementpractices,ratherthanashoppingcentrelayout.Furthermore,theinputdatawouldcomefrommanagementandstaffratherthanfromacustomerpoll.
Tosummarise,wecansaythattodateonlylimitedworkhasbeenconductedinthisfield.Therefore,inthenextsectionwebroadenourviewandreviewdifferentmodellingtechniquesthatarecommonlyusedintheareasofinterestidentifiedinthebeginningofthesection.Wealsoincludeothersectorsinourreview(e.g.manufacturingsectorandotherservicesectors)toinvestigatethemethodsusedtheretounderstandandpredictsystembehaviour.
2.3Whatmodellingapproachesarecommonlyusedwithinrelatedareas?
Table1:
Papersfound,sortedbymodellingapproachandapplicationsector
Themodellingapproachesrelevanttothisfieldofstudycanbebroadlydividedintothreedifferentcategories:
analyticalapproaches,heuristicapproaches,andsimulation.Thissectionfirstcomparestheseapproachesinageneralsenseandthencontinuestodiscussthemostimportantmethodsindividually,describingwhattheyare,wheretheyarenormallyused,andhowtheyfitinwithourresearchproject.Table1presentsasummaryofthenumberofpapersfoundineachcategoryfordifferentsectors.
FromtheoccurrenceswithintheliteratureTable1indicatesthatAgent-BasedModellingandSimulation(ABMS)andDataEnvelopmentAnalysis(DEA)arethemostfrequentlyusedmodellingtechniqueswithinourareaofinterest.WhilemostoftheABMSpapersstudiedrelatetotheretailsectormostoftheDEApapersarefromthemanufacturingsector.
Inmanycasesitwasfoundthatacombinationofmodellingtechniqueswasusedwithinamodel.Wherethisisthecasetheindividualmodellingtechniqueshavebeenlistedinthetable.Commoncombinationsaresimulation/analyticalforcomparingefficiencyofdifferentnonexistingscenarios(e.g.Greasley,2005),andsimulation/analyticalorsimulation/heuristicwhereanalyticalorheuristicmodelsareusedtorepresentthebehaviouroftheentitieswithinthesimulationmodel(e.g.Yildizoglu,2001;SchwaigerandStahmer,2003).
AnalyticalModellingApproaches:
Oncedatahasbeencollecteditiscommonineconomicsandsocialsciencetouseanalyticalanalysistoolstoquantifycausalrelationshipsbetweendifferentfactors.Oftensomeformofregressionanalysisisusedtoinvestigatethecorrelationbetweenindependentanddependentvariables.AgoodexampleofthistypeofanalysiscanbefoundinCleggetal.(2002)whoinvestigatetheuseandeffectivenessofmodernmanufacturingpractices.Surveydataisanalysedusingparametricandnonparametricanalyticaltechniques,asappropriatetothenatureoftheresponsescalesandthedistributionsofscoresobtained.Theresultsofthisanalysisarethenoftenusedasadatasourceforheuristicandsimulationmodels.
Anumberofpaperswerefoundthatusedifferentanalyticalmodellingapproachestoinvestigateveryspecificindividualhypothesesinrelationtomanagementpracticesandconsumerbehaviour.AnoteworthypaperisbyPatelandSchlijper(2004)whouseamultitudeofdifferentanalyticalandothermodellingapproachestotestspecifichypothesesofconsumerbehaviour.
Anotherareaofinterestwhereanalyticalmodelshavebeenusedquitefrequentlyisintheassessmentofrelativeefficiencyofcomparablealternatives.ThemostfrequentlyusedtechniquesdescribedintheliteratureareDataEnvelopmentAnalysis(DEA)andMultiLevelModelling(MLM).DEAwasoriginallyusedforassessingtheefficiencyofthepublicsector,buthassinceevolvedandisinuseinothersectors,oftenasananalysisinstrumentfortheoutputofsimulationexperiments.TheobjectiveofDEAistoassesstherelativeefficiencyofanumberofdecisionmakingunitsusingavarietyofinputandoutputdata.Itisabenchmarkingtechniquewhichhasgainedincreasingpopularityduringthelastfewyears.AninterestingapplicationofDEAcanbefoundinSoteriouandStavrinides(1997)wherecustomerservicequality,operatingefficiencyandprofitabilitybetweendifferentbankbranchesiscompared.MLMisaformofhierarchicalregressionanalysis,designedtohandlehierarchicalandclustereddata.Itenablesonetocontextualisetherawoutcomestakingintoaccountthedifferentlevelsofaggregationinthedata.Mostexamplesreviewedwereusedtoassesseducationalserviceslikeschools(e.g.Goldstein,2003)anduniversities(e.g.Johnes,2003).
MajordifferencesbetweenDEAandMLMareexplainedinThanassoulisetal.(2003).ThemaindifferenceisthatDEAisanon-parametricmethodwherethefocusineachinstanceistheunitbeingassessedwhileMLMisaparametr
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