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Purpose The purpose of this paper is to investigate the effects of multichannel integration (MCI) on customer loyalty. The specific objectives are to provide an appropriate reliable measure of the construct, and to analyse the impact of MCI on offline and online loyalty, both directly and by mediation of customer satisfaction. Design/methodology/approach The paper focusses on the retail apparel sector of Spain and the UK. The authors applied a scale development process and tested the model with data of 761 multichannel apparel shoppers. The proposed theoretical model was estimated through EQS 6.1 and a mediation test was calculated. Findings The findings show, first, that the construct of channel integration has two dimensions: reciprocity, which refers to the possibility of crossing the channels while shopping, and coordination, which refers to the alignment of offline and online offers. Second, that MCI affects positively both offline and online loyalty both directly and through satisfaction, which partially mediates the relationship. Research limitations/implications Culture might play a moderating role in the relationships found that are not analysed. Practical implications The findings have implications for the managers of multichannel retail companies as they help to understand the benefits of channel integration in creating a loyal customer base both online and offline. Originality/value This paper contributes to the literature on multichannel retailing in two main ways: first, by developing a scale to measure MCI, and second, by demonstrating that MCI has strong effects on customer satisfaction and loyalty.
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Dochannelintegrationeffortspayoffintermsofonlineandoffline
customerloyalty?
MartaFrasquetFacultyofEconomics,UniversitatdeValencia,Valencia,Spain
Maria‐JoséMiquelDepartmentofMarketingandMarketResearch,UniversitatdeValencia,
Valencia,Spain
Purpose:Theaimofthispaperistoinvestigatetheeffectsofmultichannelintegrationon
customerloyalty.Ourspecificobjectivesaretoprovideanappropriatereliable
measureoftheconstruct,andtoanalysetheimpactofmultichannelintegrationon
offlineandonlineloyalty,bothdirectlyandbymediationofcustomersatisfaction.
Design/methodology/approach:OurpaperfocusesontheretailapparelsectorofSpainand
theUnitedKingdom.Weappliedascaledevelopmentprocessandtestedourmodel
withdataof761multichannelapparelshoppers.Theproposedtheoreticalmodelwas
estimatedthroughEQS6.1andamediationtestwascalculated.
Findings:Ourfindingsshow,firstly,thattheconstructofchannelintegrationhastwo
dimensions:reciprocity,whichreferstothepossibilityofcrossingthechannelswhile
shopping,andcoordination,whichreferstothealignmentofofflineandonlineoffers;
second,thatmultichannelintegrationaffectspositivelybothofflineandonlineloyalty
bothdirectlyandthroughsatisfaction,whichpartiallymediatestherelationship.
Researchlimitations/implications:Culturemightplayamoderatingroleintherelationships
foundthatisnotanalysed.
Practicalimplications:Ourfindingshaveimplicationsforthemanagersofmultichannelretail
companiesastheyhelptounderstandthebenefitsofchannelintegrationincreatinga
loyalcustomerbasebothonlineandoffline.
Originality/value:Thispapercontributestotheliteratureonmultichannelretailingintwomain
ways;first,bydevelopingascaletomeasureMCI,andsecond,bydemonstratingthat
MCIhasstrongeffectsoncustomersatisfactionandloyalty.
Keywords:channelintegration,multichannelretailing,onlineloyalty,offlineloyalty
ArticleClassification:Researchpaper

1. Introduction
Inordertoremaincompetitiveandrelevantfortheircustomers,traditionalbrick‐and‐
mortarretailershaveaddedonlinechannels,becomingmultichannelretailcompaniesorbrick‐
and‐clicks(GallinoandMoreno,2014;Verhoefetal.,2015).Althoughpureonlineplayershave
beenfoundtoperformbetterthanbrick‐and‐clicks(Herhausenetal.,2015),multichannel
retailershaveacompetitiveadvantageoverpureplayersbasedonthepotentialsynergies
betweentheirofflineandonlinechannels.However,asBadrinarayananetal.(2012)and
Herhausenetal.(2015)report,brick‐and‐clicksarestrugglingtoachievethoseadvantages,and
thismaybeduetoalackofchannelintegration.Infact,IBM(2015),basedonasurveyandan
OmnichannelCapabilityIndexproducedfromit,concludesthatthereisroomforimprovement
inthemultichannelstrategiesofEuropeanretailers
Thelackofmultichannelintegration(MCIhereafter)canberelatedtotheevolutionofthe
industry.Intheearlystagesofe‐commerce,brick‐and‐mortarretailersjustaddedtheonline
channelasaseparatedivision,runinparalleltoratherthanintegratedwiththephysical
businessmodel.Infact,itwasdebatedwhetherchannelsshouldbeoperatedseparatelyornot
(Goersch,2002),asthecostsofdataintegrationareveryhigh(Neslinetal.,2006).Today,it
seemsclearthatmultichannelretailersshouldstriveforcoordinationandintegrationof
channels(GallinoandMoreno,2014;Herhausenetal.,2015)andthishasbecomethefocusof
retailmanagers.Recently,amovefrommultichanneltoomnichannelretailinghasbeen
reported(Brynjolfssonetal.,2013;Verhoefetal.,2015),andthissignifiesthefullintegration
ofchannelstoblurtheboundariesbetweenofflineandonlinechannels.Retailersareinvesting
considerableresourcesintointegratingonlineandofflinechannels,butthepayoffsarenotyet
clear.Itissufficientlyagreed,though,thattheshoppingexperienceisenhancedwhen
channelsareintegrated(Verhoefetal.,2015).Thus,understandinghowchannelintegration
affectskeycustomerresponsessuchascustomersatisfactionandloyaltyisofutmost
relevance.DespitethefactthatMCIhasbeenacknowledgedasastrategicpriorityforretailers,
itseffectsoncustomerreactionstowardsretailersandacrossdifferentchannelsremain
unclearandmoreresearchisneededinthisfield(Badrinarayananetal.,2014;Herhausenet
al.,2015).Addressingthisresearchgap,theaimofthispaperistobetterunderstandthe
conceptofMCIfromthecustomerperspective,anditsimplicationsforcustomerresponses.
Morespecifically,wewantto,firstly,provideareliablemeasureoftheconstructofperceived
MCI,andsecondly,analysetheimpactofMCIonsatisfactionwiththeretailerandonloyalty
towardsitsofflineandonlinechannels.
DevelopingavalidandreliablescalewithwhichtomeasuretheMCIconstruct(following
Churchill,1979)isamethodologicalcontributiontowardsclarifyingthedomainand
measurementoftheconstruct.Understandingtheimplicationsofchannelintegrationfor
customersatisfactionandloyaltywillprovideinterestingmanagerialandtheoretical
contributions.Wallaceetal.(2004)foundthatamultichannelstrategyenhancedtheportfolio
ofserviceoutputsprovidedtothecustomer,thusimprovingcustomersatisfactionand
ultimatelythecustomer’sretailerloyalty.Althoughprovidingarelevantbaseforourresearch,
Wallaceetal.(2004)didnotmeasureMCIbuthadmultichannelretailingastheresearch
context.Therearesomepapers(asdiscussedinSection2)thatexplicitlymeasureMCIandits
effectsbut,withtheexceptionofHerhausenetal.(2015),whoanalysedbehavioural
responsestowardstheonlineandofflinechannelsseparately,thepapersassessoverall
responsestowardstheretailer.Itisofrelevancetoattempttounderstandwhetherthe
benefitsofMCIaremoreevidentwhenitcomestoattitudesandbehaviourstowardsthe
onlineortheofflinechannel.IfMCIhadsimilarbenefitsforbothchannels,thiswouldsupport
theideathatthebenefitsofamultichannelstrategyweremultichannel(GallinoandMoreno,
2014),butiftheywereunequal,forexampleifofflineloyaltywerenotaffected,thiswould
meanthatMCIwasnotproducingpositiveeffectsacrossalltheretailerchannels.
Ourpaperfocusesontheapparelsector.Despiteinitialdoubtsaboutthesellingofclothes
online,thissectorisleadingthegrowthinonlinesalesasaresultofchannelintegrationand
brand‐buildingefforts(EuromonitorInternational,2014).Allinall,integrationeffortsshould
bemorerelevantforexperientialproducts,suchasapparel(Herhausenetal.,2015).
Moreover,itisparticularlyinterestingtostudyloyaltyintheapparelcontextasinthissector
loyaltyischallengedbecauseofthemultiplealternativesandhighpurchasefrequency
(MichaelidouandDibb,2009).
2. LiteratureReview
2.1.Multichannelintegration
MCIisdefinedasthemanagementofdiversechannelssoastooffershoppersaseamless
experienceacrossallofafirm’schannels(Goersch,2002;Chatterjee,2010).Similarly,Bendoly
etal.(2005)statethatMCIaimstoprovidemutualsupportandinterchangeabilityofchannels
forcustomers.MCIinvolvesinvestmentsattwolevels:atthemarketingleveltocoordinate
brandimageandmerchandise,andattheoperationsandinformationmanagementlevelto
integratelogisticsprocessesandcustomerdatabases(PentinaandHasty,2009).Coordinating
andintegratingthedistributionchannelscanprovidesynergiesthatincreasetheeffectiveness
ofeachchannelandcontributetoenhancingtheperformanceoftheretailer.WithGallinoand
Moreno(2014:1450)stating“theimpactofamultichannelstrategyisalsomultichannel”,this
impliesarethinkingofchannelevaluationandarealignmentofchannel‐specificincentives,as
thesalesinonechannelmaycomefrominvestmentsmadeinanother.Infact,theprofitability
ofMCImaynotbeseenimmediately,andHerhausenetal.(2015)warnofitsrisksand
potentialdownsides.Nevertheless,asBendolyetal.(2005)suggest,themostinteresting
benefitsofMCIcomeintheformofpsychologicaleffectsonconsumers.
ThereviewofthelimitedliteraturethatempiricallyanalysesMCIanditseffectsonfirms’
performanceissummarisedinTable1.Thereisquitealotofdiversityamongthepapersin
termsofthedomainoftheconceptofMCI,itsmeasurement,anditsdimensionality.Theonly
commonfeatureintheoperationalizationoftheconstructisthatitincludesthepossibilityfor
shopperstocrosschannelsduringtheshoppingprocess,e.g.tobuyonlineandcollectata
store,orreturnofflineproductsboughtonline.Somestudies,suchasChiuetal.(2011)or
GallinoandMoreno(2014),limittheconstructdomaintothisdimension,butmostconsider
additionaldimensionsofMCI.Forinstance,thepioneeringcontributionofBendolyetal.
(2005)foundthatMCIhastwodimensions:physicalintegration,whichreferstotheabove‐
mentionedpossibilityofshoppingacrosschannels,andinformationalintegration,whichrefers
totheonlineandofflinechannelsprovidinginformationtooneanother.Thissecondmeaning
iscapturedbythemajorityofthesubsequentstudies,butwithdifferentnames,suchas
reciprocity(LeeandKim,2010),storelocator,orinformationmanagement(PentinaandHasty,
2009).Additionally,otherstudiesincludetheconsistencydimension(e.g.PentinaandHasty,
2009;LeeandKim,2010).GiventhediversityofapproachestakentotheconceptofMCIinthe
fewpapersmeasuringtheconstruct,weconsidereditadvisabletodevelopanew,validand
reliablescalewithwhichtomeasuretheMCIconstruct,takinganintegrativeapproach
regardingtheaspectsanalysedinthepreviousstudies.
Table1.EmpiricalstudiesanalyzingtheeffectsofMCI
Author Method MCImeasure Results
Bendolyet
al.(2005)
Surveyofmultichannelcustomers
ofthreeretailersinapparel,
electronicsandmusic(n=1598).
Logisticregression.
Author‐designed
8‐itemscale.
MCIhastwofactors:informational
integrationandphysicalintegration.
MCIreducesthelikelihoodoffirm
switchinguponavailabilityfailure.
Pentinaand
Hasty
(2009)
Sitecontentanalysisof50
multichannelretailcompanies.
Countof46
interchannel
coordination
MCIimprovesonlinesales.
parametersin6
categories.
LeeandKim
(2010)
Surveyofmultichannelshoppers
ofanyretailer(n=706).
Factoranalyses(exploratoryand
confirmatory)andstructural
equationmodelling.
Author‐designed
22‐itemscale
basedonthe
dimensionsof
Robeyetal.
(2003).
MCIhasfivefactors:information
consistency,freedominchannel
selection,emailmarketing,channel
reciprocity,andcustomerservice.
Positiverelationshipofthree
dimensionsofMCIwithcustomer
loyalty.
Schramm‐
Kleinetal.
(2011)
Surveyofmultichannelshoppers
ofretailersfromavarietyof
sectors(n=981).
Structuralequationmodelling.
7‐itemformative
scale(adequacy‐
importance).
MCIhasapositiveeffectonloyalty,
mediatedbytrustandtheimageof
theretailer.
MCIcanenablecustomermigration
tomoreefficientretailchannels.
Chiuetal.
(2011)
Surveyofcustomerswith
experienceoffree‐riding(n=716)
whenshoppingforelectronics,
hardwareorsoftware.
Structuralequationmodelling.
3itemsreferring
tophysical
integration.
MCIhasnosignificanteffecton
channellock‐in,thusdoesnot
preventfree‐riding.
Gallinoand
Moreno
(2014)
Quasi‐experiment.
Databasesofonlineandoffline
channelsofahomeequipment
retailer(1yearofdata).
1item:presence
ornotof“buy
onlineandpick
upinstore”
functionality.
MCIreducesonlinesalesand
increasestrafficandsalesatoffline
stores.
Herhausen
etal.(2015)
Experimentaldesign(3studies)
manipulatingonline‐offline
integrationforappareland
accessoriesretailers.
5itemsreferring
tophysicaland
informational
integration.
MCIdirectlyincreasesperceived
servicequalityofonlinechanneland
indirectlyaffectsbehavioural
responsesforbothchannels.
EffectofMCIisstrongerforless
experiencedInternetshoppers.
IntheliteratureonMCI,wefindauthorswhoanalysetheeffectsondifferentbehavioural
responses,suchasperceivedservicequalityandperceivedrisk(Bendolyetal.,2005;
Herhausenetal.,2015),andimageandtrust(Schramm‐Kleinetal.,2011),andmostoften
differentmeasuresofshoppingintentionsandattitudes,suchascustomerretention(Bendoly
etal.,2005;Chiuetal.,2011),loyalty(LeeandKim,2010;Schramm‐Kleinetal.,2011),online
andofflinesearchandpurchaseintentions,andwillingnesstopay(Herhausenetal.,2015).On
thebasisofthosepapers,webuiltourresearchmodelwiththeaimofinvestigatingtheeffect
ofMCIonsatisfactionandloyalty,aswediscussinthefollowingsections.
2.2.Impactofchannelintegrationonsatisfaction
Retailers’effortstointegrateofflineandonlinechannelsareexpectedtoincreasecustomer
satisfactionwithanenhancedprovisionofserviceoutputs.Wewanttoextendthefindingsof
Wallaceetal.(2004)thatamultichannelretailstrategyincreasescustomersatisfaction,by
analysingwhethertheintegrationofchannelsisthecauseofcustomersatisfaction.
Satisfactionisdefinedasasummaryaffectiveresponsetotheshoppingexperience(Oliver,
1980).Whenaretailersucceedsinintegratingitschannelsbyprovidingincreasedlevelsof
service,e.g.theopportunitytocollectatthestoreitemspurchasedonline,itisexpectedthat
customersatisfactionwillincrease.Wefindempiricalsupportforthiseffectinthehigh‐
technologybusiness‐to‐business(B2B)servicesector(Madalenoetal.,2007),andintheretail
bankingsector(SeckandPhilipe,2011),butnotinthephysicalgoodsretailsector.Unlike
services,purchasinggoodsimpliesdeliveriesandreturns,whicharestronglyaffectedbythe
degreeofchannelintegration.Withsomeretailershavingmademoreprogressinchannel
integrationthanothers,wecouldassumethat,whenaconsumerdealswitharetailerthat
offersmorepossibilitiesforshoppingseamlesslyacrosschannels,he/shewillbemore
satisfied.Omnichannelmanagementhastheobjectiveofoptimizingtheperformanceover
channelsandthecustomerexperienceacrosschannels(Verhoefetal.,2015),allowingthe
shoppertointeractsimultaneouslywithofflineandonlinechannelsatanystageofthe
purchaseprocess.Thus,weexpectthattheperceptionofMCIwillimpactoverallshopper
satisfactionwiththeretailer.
H1:Multichannelintegrationispositivelyrelatedtooverallcustomersatisfactionwiththe
retailer.
2.3.Impactofchannelintegrationonofflineandonlineloyalty
Whenaretailersucceedsinintegratingitsonlineandofflinechannelsandtheshopping
experienceisthusenhanced,customersarelikelytodeveloppositiveattitudestowardsthe
retailerandarelikelynottobewillingtoshopelsewhere.FocusingonthestudiesfromTable1
thatanalysecustomer‐levelresponsestoMCI,wenotethatBendolyetal.(2005)found
customerslesslikelytoswitchtoacompetitorwhenchannelswereintegrated,andthatLee
andKim(2010)provedtheretobeapositivedirecteffectofchannelintegrationonoverall
loyalty.Schramm‐Kleinetal.(2011)includedloyaltyasanindirectconsequenceofMCIand
foundperceivedchannelintegrationtohaveapositiveimpactoncustomerloyaltythrough
positiveeffectsonimageandtrust.
Herhausenetal.(2015)assessedtheeffectofonline‐offlinechannelintegrationon
customerevaluationsofthechannels(i.e.perceivedqualityandrisk),andtheeffectofthese
evaluationsonoverall,onlineandofflineshoppingintentions.Theyexpectedthatonline‐
offlinechannelintegrationwouldaffecttheonlinechannelpositivelyandthealternative,i.e.
offline,channelnegatively;thiswouldhaveimpliedthattheofflinechannelwascannibalized
bytheincreasedperformanceoftheonlinechannel.However,theirresultsshowedthat
integrationdidnotaffecttheofflinechannelnegatively.Thiscouldbeexplainedbycustomers
extendingtheirpositiveevaluationsoftheonlinechanneltotheofflinechannelbyvirtueof
thehaloeffect,implyingthattherearecross‐channelsynergies(Faragetal.,2007;Kwonand
Lennon,2009)andthattheofflinechannelbenefitsfromtheonline‐offlinechannel
integration.AsthemeasureofMCIisbidirectional,thatis,itreferstobothonline‐offlineand
offline‐onlinechannelintegration,webelievethatMCIwillaffectbothonlineandoffline
loyaltypositively,astheeffortstomakethetwochannelsinterchangeablewillbuildpositive
attitudesandintentionstowardstheretailer’schannels.MCImeans,forexample,that,when
shoppingatastore,acustomercanorderatakioskanitemthatisout‐of‐stockatthelocal
store,andthiswillcontributepositivelytowardsofflineloyalty.MCIalsomeansthat,when
purchasingonline,thecustomercanchoosetohavetheproductdeliveredtotheirhomeorto
astore,andthiswillcontributetoonlineloyalty.TherearefeaturesofMCIthatcannotbe
categorizedasonline‐offlineintegrationoroffline‐onlineintegration,butarereciprocalor
refertotheconsistencybetweenchannels.Additionally,thereisthehaloeffectthatmeans
thateveryaspectofMCIcouldcontributetowardsbothonlineandofflineloyalty.Thus,
H2:Multichannelintegrationispositivelyrelatedtocustomerloyaltytowardstheoffline
channeloftheretailer.
H3:Multichannelintegrationispositivelyrelatedtocustomerloyaltytowardstheonline
channeloftheretailer.
2.4.Effectofsatisfactiononofflineandonlineloyalty
Bydevelopingafullyintegratedmultichannelstrategy,theretaileraimstobettersatisfy
customerneeds,andbecausesatisfactionistheseedofloyalty,enhancingsatisfactioniskeyto
retainingcustomers(MittalandKamakura,2001).Loyaltyisakeyrelationaloutcomein
business‐to‐consumerrelationships.DickandBasu(1994:99)defineloyaltyas“thestrengthof
therelationshipbetweenanindividual’srelativeattitudeandrepeatpatronage”,reflectingthe
attitudinalandbehaviouralcomponentsoftheconstruct.Whenconsumersareloyaltoa
retailer,theyrevisittheretailer,repurchaseproductsandrecommendtheproduct/retailerto
relativesorfriends(Zeithamletal.,1996).
Thepositiverelationshipbetweensatisfactionandloyaltyhasoftenbeenconfirmedinthe
retailingliterature,intheonlinecontext(AndersonandSrinivasan,2003),andspecificallyin
themultichannelsettingbyWallaceetal.(2004),andLeeandKim(2010).Whena
multichannelshopperissatisfiedwithshoppingataparticularretailer,he/shewillbemore
likelytodeveloployaltybehaviourstowardstheofflinechanneloftheretailerbecausethe
offlineshoppingexperienceisimprovedbytheintegrationofchannels.Weexpectasimilar
connectionregardingtheonlinechannel.Switchingcostsareverylowonlineandthereis
fiercecompetition;thiscouldleadtoconsumersshoppingelsewheredespitebeingsatisfied
witharetailer’sonlinechannel(Wallaceetal.,2004).However,webelievethat,whena
retailerisabletosatisfyacustomer’sneedswithashoppingexperienceonlinethatallows
interactionwiththeofflinenetwork,theshopperwilltendtobecomeloyaltotheonline
channel.Thus,
H4:Overallcustomersatisfactionwiththeretailerispositivelyrelatedtoloyaltytoits
offlinechannel.
H5:Overallcustomersatisfactionwiththeretailerispositivelyrelatedtoloyaltytoits
onlinechannel.
2.5.Effectofofflineloyaltyononlineloyalty
Inmultichannelretailing,themostcommonpatternisstillforthenewchannelbeingadded
tobetheonlineone.Fornarietal.(2016)findthat,whenaretaileraddsanewchannel,inthe
longrun,migrationturnsintosynergyanddifferentchannelsinteractandreinforceeach
other.Researchontheinteractioneffectsbetweenchannelsclaimstheexistenceofahalo
effect,wherebyofflinebehavioursbuildonlinebehaviours;forexample,offlineshopping
frequencymayaffectonlinepurchasing(Faragetal.,2007),offlinepatronageandonline
shoppingintentions(JonesandKim,2010),orofflineattitudemayaffectonlineattitude
(Badrinarayananetal.,2012). Thus,weexpectthatcustomerstransferexistingattitudesand
beliefsbuiltfromtheofflinechanneltotheonlinechannel,andhypothesize,
H6:Loyaltytowardstheofflinechannelofthemultichannelretailerispositivelyrelatedto
loyaltytowardsitsonlinechannel.
Figure1displaysourconceptualmodelwiththehypothesizedrelationshipsbetweenMCI,
customersatisfactionandloyaltyinamultichannelcontext.Ourmodelreflectsthethree
constitutiveelements–attributeperceptions,satisfaction,andloyalty–oftheshopping
processoftenreportedintheliterature(Finnetal.,2009;Ha,2006).
Figure1.Conceptualmodel

3. Methodology
3.1.Scaleitems’development
AsourliteraturereviewrevealednoconsensusonthemeasurementofMCI,wedeveloped
ascalefollowingthescaledevelopmentprinciplesofChurchill(1979)andRossiter(2002).
Basedontheliteraturereview,weproducedaninitiallistof78itemsthathadpreviouslybeen
usedbydifferentauthorsorthatwewordedbasedonthedimensionsoftheconcept
suggestedinsomeconceptualpapers.Ourapproachtothemeasurementoftheconceptand
thesubsequentscaledevelopmentprocessassumesthemeasureofMCIisreflective,basedon
Coltman’setal.(2008)framework.Thuswegeneratedalargesetofitemsthatsharedthe
domainoftheconstruct.Aftereliminatingduplicities,thenumberofitemscamedownto32.
Thenweheldeightin‐depthinterviewswithmultichannelshoppers.Asaresultofthose
interviews,alistofthemesincludedintheconceptofshoppingacrosschannelswasproduced
andcomparedtotheinitiallistofitemsfromtheliteraturetodeterminewhetherthedomain
oftheconceptfortoday’sshopperswasfullycapturedbythelistofitems.Twoitemswere
addedtoourlist,making34items.Next,thescalewaspurifiedbyapanelofexperts,
accordingtotheproceduresuggestedbyZaichkowsky(1985).Eightmarketingscholars
participatedinthisprocess;first,theywerepresentedwithadefinitionofMCIthatwe
developedforthepurposesoftheresearch:theusebytheretailerofofflineandonline
channelsinsuchawaythatthecustomerfeelshe/sheisinteractingwiththesamecompany
andisabletocrossfromonechanneltotheotherduringtheshoppingprocess;then,theyhad
toassess,from1(notatall)to3(completely),theextenttowhicheachitemwas
representativeoftheconstruct.Foranitemtoberetainedinthescaleithadtoreceivea3
fromatleasttwothirdsofthepanelmembers,andnoscoresof1.Thefinalscalehad18items.
3.2.Datacollection
InordertovalidatethenewMCIscaleandtotestourproposedmodel,aquestionnairewas
developed,whichincludeditemslinkedtotheconstructstobemeasured,usingfive‐point
scales.
FormeasuringMCI,itwasdeemedappropriatetouseanadequacy‐importancemodel
(Schramm‐Kleinetal.,2011)duetothedomainoftheconstruct.Inthecurrentmultichannel
setting,multichannelcustomershavehigherexpectationsduetotheirextensivepast
experienceofconvergedchannels(Shankaretal.,2003;WingandMahajan,2002)and
retailersaredevelopingmultichannelstrategiestorespondtothoseexpectations(Wallaceet
al.,2004).Itisthusrelevanttoconsidernotonlyhowcustomersperceivedifferentaspects
relatedtoMCI,butalsohowrelevantthoseaspectsareforthem,asthiswillsuggesthowthe
retailerisdoingaccordingtothecustomer’srequirements.Accordingly,therespondentsfirst
Multichannel
integration
Offlineloyalty
Onlineloyalty
Overall
satisfaction
H1
H3
H2
H6
H4
H5
assessedtheimportanceofeachchannelintegrationitem;then,theyhadtochoosetheir
most‐visitedretailerfromanexhaustivelistofmultichannelretailersoperatingintheir
country.Alltheretailersconsideredwereoriginallyofflineretailersthathadbecome
multichannelretailersbyaddingthetransactionalonlinechannel,andallofthemweresingle‐
brandretailers.Withthechosenretailerinmind,therespondentevaluateditoneachitem;
thisallowedustocreateaweightedvariablethatwastheresultofmultiplyingonevariableby
theotheranddividingbyfive.Satisfactionandloyaltymeasureswerealsoreferredtothe
respondent’smost‐visitedretailer.Overallsatisfactionwasmeasuredwithathree‐itemLikert
scale:(1)Consideringallyourvisits(bothofflineandonline)toRetailerX,howsatisfiedare
you?(2)ConsideringonlyyourvisitstoRetailerX’sonlinestore,howsatisfiedareyou?(3)
ConsideringonlyyourvisitstoRetailerX’sphysicalstores,howsatisfiedareyou?.Offline
loyaltyandonlineloyaltyweremeasuredthroughtwoscalesadaptedfromthatofYangand
Peterson(2004),whichwasdeemedappropriateasithadbeenappliedtothemultichannel
retailcontextandincludedelectronicword‐of‐mouth:Howlikelywouldyoubeto…(1)say
positivethingsaboutRetailerX’sonline/offlineshoptootherpeople,(2)recommendRetailer
X’sonline/offlineshoptothosewhoseekyouradvice,(3)encourageyourfriendsandrelatives
touseRetailerX’sonline/offlineshop,(4)visitRetailerX’sonline/offlineshopmoreoften,and
(5)postpositivemessagesaboutRetailerX’sonline/offlineshoponsomeInternetmessage
board?Wealsoincludeddemographicvariables,suchasgenderandage.
Datawerecollectedbymeansofasurveytargetedtothepopulationofmultichannelshoppers
intheapparelproductcategory.Thequestionnairewassentto2027membersoftwoInternet
panels,oneintheUKandtheotherinSpain,and1598responded.Afterfilteringoutthose
respondentswhodidnotsatisfytheconditionsthatdefineourpopulationandthosewhohad
notshoppedatanyofthelistedretailers,applyingthegenderandagequotas,andeliminating
incompletequestionnaires,ourfinalsamplecomprised761individuals,380inSpain(49.9%)
and381intheUK(50.1%).Genderandagequotasweresettoreplicatethesocio‐
demographicprofileofonlineshopperspresentedin“PwCGlobalOnlineShoppingHabits”
(PwC,2014).
3.3.Sampleprofileandretailers’representativeness
Thesocio‐demographicprofileofmultichannelshoppersintheapparelcategorysuggested
womenhadtobeoverrepresentedinthesample.Thus,ourfinalsamplecomprised66.6%
womenagainst33.4%men.Allageswereincludedinthesample.However,younger
consumersareslightlyoverrepresentedastheyshoponlinemoreoftenthantheotherage
groups(inoursample:18‐24years,18.7%;25‐34years,30.7%;35‐44years,25.4%;45‐54
years,16.7%;olderthan54,8.5%).
Asmentionedbefore,ourdataareretailer‐specificastherespondenthadtoanswerthe
questionnairewithaparticularretailerinmind.Thethreeretailersthataccountedformostof
theanswersinSpainwerechainsoftheInditexgroup(Zara,27.9%;Springfield,12.9%;
Pull&Bear,11.8%),whereasintheUKtwoBritishretailers(Next,23.1%;M&S,21%)werethe
mostpopularchoices,followedbyH&M(14.4%).
4. DataAnalysisandResults
4.1.MCIdimensions
ToidentifythedimensionalityoftheMCIscale,aprincipalcomponentanalysiswithOblimin
rotationandfactorextractionaccordingtotheMineigencriterionbeingequalto1was
employed(Kaiser‐Meyer‐Olkintest‐KMO:.951;Barlett:5398.48;d.f.:153;sig.:.000;Matrix
corr.determ.:9.79e‐7).Weighteditems(importanceofeachchannelintegrationitemby
evaluationofeachitem)wereusedasinputsintotheanalysis.Thetwofactorsidentified
accountforacumulative63.41%ofthevariance,andtheywerelabelledasReciprocityand
Coordination(seeTable2).Thetwodimensionsexplainquitesimilaramountsofvariance.
Table2.ExploratoryfactoranalysisoftheMCIscale
Factor1
Reciprocity
Factor2
Coordination
Itiseasytocollectata(Retailer)storegoodspurchasedovertheInternet .65 
ItisconvenienttoreturngoodsIhaveboughtonlinetoanyof(Retailer’s)
physicalstores
.68 
(Retailer)enablesmetoplaceacourtesyholdonproductsinalocalstore .75 
(Retailer’s)physicalstoreallowsmetodoanorderonline .71 
At(Retailer’s)websiteitiseasytogetinformationonorderanddeliverystatus
(alsoforproductsorderedoffline)
.71 
At(Retailer’s)websiteitiseasytogetreal‐timeinformationonproduct
availabilityinalocalstore
.76 
Itiseasytosearchforstorelocationsandopeninghoursat(Retailer’s)website .68
(Retailer)offersonlineaccessories,productsupport,oradditionalproducttypes .69
(Retailer’s)onlinecustomerserviceisalmostthesameasIcangetfromthe
store
.65 
Iobserveaclearandvisibleassociationofbrandnames(includinglogosand
slogans)acrosschannels
.57 
(Retailer)sellsonlinethesameproductsasinthephysicalstores  .69
(Retailer)offersthesamepricesonlineasinthephysicalstores  .71
(Retailer)offersthesamepromotionsonlineasinthephysicalstores  .82
On(Retailer’s)websiteIcangetinformationaboutpricesinalocalstore .77
On(Retailer’s)websiteIcangetinformationaboutpromotionsinalocalstore  .72
On(Retailer’s)websiteIcanusemyloyaltycardorredeemcouponsobtained
offline
 .63
On(Retailer’s)websiteIcanobtainonlinecouponstobeusedoffline  .64
(Retailer)providesconsistentstoreimagesbetweentheonlinestoreandthe
physicalstore
 .57
%variance 33.28% 30.13%
InTable2wecancheckthatthetwodimensionsexplainquitesimilaramountsofvariance.
4.2.Psychometricpropertiesofthescales
Inordertoassessthevalidityandreliabilityofthescalesusedinthestudy,andmore
preciselytotestthefactorstructureoftheMCIconstructmorerigorously,aconfirmatory
factoranalysiswasconducted,usingEQS6.1.MCIwasintroducedintotheanalysisasa
second‐orderreflectiveconstruct.
RegardingtheMCImeasure,Table3showssomeofthecommonlyacceptedindicatorsof
convergentvalidityandreliability,providingadequatevalues:theCronbach'salpha
coefficientsexceedthethresholdof.7(NunnallyandBernstein,1994),theLagrangemultiplier
testwasreviewed,anditwasalsoverifiedthatallstandardizedfactorloadsfortheobserved
variablesweresignificantandthatthemeanoftheloadsexceeded.7(Hairetal.,2005).
Additionally,thevaluesofthecompositereliabilityfortheReciprocityandCoordination
dimensionswerecalculated,being.93and.92respectively,valueswhichexceededthecritical
thresholdof.7;thosefortheaveragevarianceextracted(AVE)were.58forReciprocityand.59
forCoordination,higherthan.5(FornellandLarcker,1981).TheCronbach’salphavalueforthe
entireMCIscalewas.96.
Table3alsoshowsadequatevaluesregardingindicatorsofconvergentvalidity(factorial
loads>.6andsignificant)andreliability(Cronbach’salpha>.7;AVE>.5)fortherestofthe
measures.Ithastobementionedthatnoitemofanyscalewasdropped,becausetheyall
reachedthecommonlyacceptedvaluesofthedifferentcriteria.
Table3.Reliabilityandconvergentvalidityofthemeasures
FactorItem
ConvergentvalidityReliability
Stand.loads(t)Mean
loadingCronbachαCRAVE
MULTICHANNEL
INTEGRATION
(MCI)
(reflective,
2ndorder)
Stand.
loads(t)
RECIPROCITY
(REC)
rec1 .60(9.05*)
.76 .93
.95 .90
rec2 .65(9.80*)
.99
(9.88*)
rec3 .73(9.32*)
rec4 .78(7.73*)
rec5 .80(9.98*)
rec6 .83(10.26*)
rec7 .78(10.16*)
rec8 .81(10.11*)
rec9 .84(10.00*)
rec10 .73(10.53*)
.91
(7.61*)
COORDINATION
(COO)
coo1 .77(9.08*)
.78 .91
coo2 .74(8.96*)
coo3 .74(9.90*)
coo4 .81(9.58*)
coo5 .81(9.64*)
coo6 .77(9.55*)
coo7 .76(9.99*)
coo8 .75(9.00*)
OVERALLSATISFACTION(SAT)
sat1 .84(14.44*)
.84 .86 .87 .70sat2 .84(17.56*)
sat3 .83(14.91*)
OFFLINELOYALTY
(OFF)
off1 .91(19.96*)
.86 .89 .93 .74
off2 .98(19.21*)
off3 .88(19.11*)
off4 .79(17.33*)
off5 .72(16.97*)
ONLINELOYALTY
(ONL)
onl1 .89(17.55*)
.82 .89 .91 .68
onl2 .86(16.44*)
onl3 .87(19.76*)
onl4 .78(18.13*)
onl5 .71(19.96*)
S‐Bχ2(424d.f.)=1017.18(p<.00);BBNFI=.87;BBNNFI=.91;CFI=.92;IFI=.92;MFI=.47RMSEA=.059
*=p<.01
Note:CR=compositereliability;AVE=averagevarianceextracted
Toanalysethediscriminantvalidity,twoprocedureswereapplied:(a)atestthatthe
confidenceintervalfortheestimationofthecorrelationbetweeneachpairoffactorsdidnot
includetheunit(AndersonandGerbing,1988)and(b)atestthattheAVE,foreachfactor,was
greaterthanthesquareofthecorrelationbetweeneachpairoffactors(FornellandLarcker,
1981).AsTable4reports,therewasanissuebetweenthesatisfactionandloyaltyscales(both
offlineandonline),andbetweentheonlineandofflineloyaltyscales.Therefore,athird
criterionwasused:thechi‐squaredifferencetest.Accordingly,thechi‐squareofthe
measurementmodelwasagainestimated,buteachtime,foreachpairoffactorsshowing
discriminantvalidityproblems,thecovariancewasfixedto1(chi‐squarecovariancemodelfor
SAT‐OFFequalto1=1715.88with425d.f.;forSAT‐ONL=1629.57with425d.f.;forOFF‐ONL=
1866.38with425d.f.);thosevalueswerecomparedwiththechi‐squaremeasurementmodel
(1595.06with424d.f.),andwecheckedthat,forthethreesituations,thechi‐square
differencewasoverthecriticalvalue(10.82;p<.001for1d.f.)(chi‐squaredifference=120.80,
34.51,271.32respectivelywithd.f.differenceforthethreesituationsequalto1).Considering
alltheindicatorsasawhole,wecanconfirmthatthemeasurementinstrumentshad
discriminantvalidity.
Table4.Discriminantvalidity
MCI SAT OFF ONL
MCI .90 .49 .46 .52
SAT [.78;.64] .70 .74 .87
OFF [.74;.61] [.90;.82].74.71
ONL [.78;.66] [.96;.91] [.88;.80].68
Underthediagonal:confidenceintervalforthecorrelationbetweeneachpairoffactors
Diagonal:averagevarianceextracted
Abovethediagonal:squareofthecorrelationbetweeneachpairoffactors
4.3. Hypothesistestingandmediationanalysis
Theproposedtheoreticalmodel(Figure1)wasestimatedusingarobustmethodologyin
EQS6.1.MCIwasintroducedasasecond‐orderreflectiveconstruct.Theresultsareshownin
Table5,andsupportfiveofthesixhypotheses:thereisasignificantandpositiverelationship
betweenMCIandoverallsatisfaction(H1)andbetweenMCIandloyalty(offline–H2and
online–H3).TheresultssuggestthattheinfluenceofMCIonsatisfactionisquitestrong,and
thatonloyaltyweaker,withasimilarinfluenceinbothcontexts,offlineandonline.Moreover,
overallsatisfactionexertsasignificant,strongandpositiveinfluenceonofflineandonline
loyalty(H4andH5respectively).Finally,theresultsdonotsupportofflineloyaltyhavingan
influenceononlineloyalty(H6).
Table5.Hypothesistesting
Hypotheses Structuralrelationship β tvalue Contrast
H1 MultichannelIntegrationOverallSatisfaction .70 12.75** Accepted
H2 MultichannelIntegrationOfflineLoyalty .14 2.75** Accepted
H3 MultichannelIntegrationOnlineLoyalty .11 2.46* Accepted
H4 OverallSatisfactionOfflineLoyalty .76 12.63** Accepted
H5 OverallSatisfactionOnlineLoyalty .75 6.18** Accepted
H6 OfflineLoyaltyOnlineLoyalty .13 1.10ns Rejected
S‐Bχ2(426d.f.)=1595.09(p<.000);BBNFI=.865;BBNNFI=.907;CFI=.915;IFI=.915;MFI=.462;RMSEA=.060
*=p<.05;**=p<.01;nsnonsignificant
ThedatainTable5showhowrelevantistheperceptionoftheretailer’sMCIonoverall
customersatisfaction,andhowthatsatisfactionstronglyinfluencesloyalty.Ontheotherhand,
althoughMCIexertsasignificantinfluenceonloyalty,bothofflineandonline,thatinfluenceis
notverystrong.TakingintoconsiderationZengetal.’s(2009)suggestionabouttheneedto
considerbothdirectandindirectimpactsofsatisfactiondeterminantsonbehavioural
intentions,weanalysedthemediationeffectofoverallsatisfactionontherelationship
betweenMCIandloyalty,forbothofflineandonlinechannels.TheresultsareshowninTable
6.WetestedthedirecteffectofMCIon(offlineandonline)loyalty,reportingthestandardized
βofthedirectrelationshipandtheR2ofthedependentvariable;then,thedirecteffectmodel
wascomparedtoitsrespectivesimplemediationmodel,providingthesizeeffect(f2)oftheR2
variation(Cohen,1988).Thedataconfirmapartialmediationeffectinbothsituations,offline
andonlineloyalty:theeffectofMCIon(offlineandonline)loyaltyispartiallymediatedby
overallsatisfaction;thismeansthat,althoughMCIhasanindirectinfluenceonloyaltythrough
overallsatisfaction,thereisalsoasignificantdirectinfluenceofMCIonofflineandonline
loyalty.Theeffectismoderateinthecaseofthemediationeffectofoverallsatisfactionon
offlineloyalty(asthef2valueishigherthan.15butlowerthan.35),but,forthemediation
effectofoverallsatisfactionononlineloyalty,theeffectsizeisstrong(asthef2valueishigher
than.35).Allinall,theroleofMCIononlineandofflinecustomerloyaltyisveryrelevant,asit
notonlyexertsadirectinfluenceonit,butalsoanindirectinfluencethroughoverallcustomer
satisfaction,whichisevenmorerelevantintheonlinecontext.
Table6.Mediationtest
DirectModel MediationModel
βR
2Β βind R2f2 Mediation
MCIOfflineLoyalty .68** .47 .14** .35** .70 .33 Partial
MCIOverallSatisfaction .70**  
OverallSatisfactionOfflineLoyalty .77**  
MCIOnlineLoyalty .71** .51 .11* .54** .88 .42 Partial
MCIOverallSatisfaction .70**  
OverallSatisfactionOnlineLoyalty .86**  
*=p<.05;**=p<.01
5. Conclusions
Thispapercontributestotheliteratureonmultichannelretailingintwomainways:first,by
developingascaletomeasureMCI,andsecond,bydemonstratingthatMCIhasstrongeffects
oncustomersatisfactionandloyalty.Veryfewstudieshavefocusedoncustomer‐perceived
MCI,andthescalesemployedwerenotbasedonathoroughevaluationofthedomainofthe
construct,nordidtheyfullycapturethemeaningofMCIinthepresentmultichannelcontext.
Itisalsorelevanttohighlightthatthepresentstudyusesanadequacy‐importancemodel
(Schramm‐Kleinetal.,2011),consideringnotonlytowhatextentthecustomerperceivesthe
retailer’sMCIbutalsohowrelevantitisforhim/her.Furthermore,theseparateeffectsofMCI
onofflineandonlineloyaltyhaveseldombeeninvestigated,exceptbyHerhausenetal.(2015),
whoexplaintheindirectinfluenceofonline‐offlinechannelintegrationonbehavioural
intentionsbothofflineandonline.
OurresultsshowthatMCIisaconstructwithtwodimensions:reciprocity,whichrefersto
thepossibilityofcrossingfromtheonlinetotheofflinechannelandviceversa,and
coordination,whichreferstothealignmentofonlineandofflineoffers.Thediscoveryofthese
twodimensionshelpstoconsolidatetheconceptofMCIasbidimensional.Thus,ourconcept
ofMCIisnotrestrictedtothephysicalintegrationofchannelsasinthepapersofChiuetal.
(2011)andGallinoandMoreno(2014),butitincorporateschannelcoordination,which
capturestheideasofinformationintegration/coordinationorconsistency,asinthepapersof
Bendolyetal.(2005),PentinaandHasty(2009),andLeeandKim(2010).Althoughboth
dimensionsarerelevant,integrationhasslightlymoreweightonperceivedMCI.Ourresults
alsorevealthat,whenchannelsshowahigherdegreeofintegrationaccordingtocustomer
expectations,customersatisfactionincreases.Theserelationshipsextendthefindingsof
Wallaceetal.(2004),whofoundthatamultichannelstrategywaslinkedtosatisfaction,by
suggestingthatitisspecificallychannelintegrationandnotjusttheadditionoftheonline
channelthatdrivescustomersatisfaction.
Regardingloyalty,ourdatasupporttheideathatthisbehaviouralconstructisstrongly
impactedbycustomersatisfaction,asevidencedbyconsiderableearlierresearch,butitisalso
positivelyinfluencedbyMCI.ThisdirecteffectofMCIonloyaltyconfirmsthefindingsof
Bendolyetal.(2005)andHerhausenetal.(2015).Anew,relevantcontributionofourresearch
isthefindingthatMCIhassimilarimpactsononlineloyaltyandofflineloyalty.Thissuggests
thattheadditionoftheonlinechanneltotheexistingstorenetworkdoesnotcannibalizethe
offlinechannel;onthecontrary,wheneffortsaremadetointegratebothchannels,thishelps
buildloyaltytowardstheofflinechannelaswellastheonline.Anotherrelevantfindingisthat
overallsatisfactionmediatestherelationshipsbetweenMCI,andofflineandonlineloyalty.
Althoughatfirstsightthedatamaysuggestthatoverallsatisfactioninfluencescustomer
offlineandonlineloyaltymuchmorethanMCI,ourmediationanalysisrevealsthatMCIaffects
loyaltythroughoverallsatisfactionaswell(thus,anindirecteffectisevident).Thepercentage
oftheexplainedvarianceincustomerloyaltywhenconsideringthemediationeffectoverall
satisfactionhasbetweenMCIandofflineandonlineloyalty,issignificantlygreaterthanthat
explainedwhenonlythedirecteffectisconsidered.Thisreinforcementofcustomerloyalty
throughanindirecteffectofMCIisstrongerfortheonlinechannel;thisconsequenceis
relevantifweconsiderthat,astheliteraturesuggests,gettingloyalcustomersismoredifficult
intheonlinecontextthanintheofflineone(Neslinetal.,2006).Accordingly,retailerstrategies
developedtoimproveperceivedMCIwillhaveagreaterbenefitfortheonlinechannel,which
isusuallytheweakestchannelintermsofnumberofcustomersforthosebrick‐and‐mortar
retailersthathaveaddedtheonlinechannelsoastobecomebrick‐and‐clicks.
Thefindingsdiscussedabovesuggesttheimportanceformanagersofmultichannelcompanies
offullyintegratingtheirchannelssoastoprovideshopperswithaseamlessexperienceacross
channels,andchannelinterchangeability(Chatterjee,2010;Verhoefetal.,2015).Insodoing,
theretailernotonlyshouldcoordinatetheassortmentofproducts,promotions,and
transmissionofthesamebrandimage,butalsoshouldspeciallyprovideincreased
opportunitiestocrosschannelsduringtheshoppingprocess(i.e.byallowingthecustomerto
returntoalocalstoreanitemboughtonline).Thiswillbenefitcustomersatisfactionand
loyaltytotheretailer,bothonlineandoffline.Althoughitcouldseemthatoverallsatisfaction
isthemainkeyvariableforenhancingcustomerloyaltyinwhateverthecontext,duetoits
stronginfluenceonloyaltycomparedtothatofMCI,thatisnotcompletelytrue.Retailersjust
developingstrategiestoenhanceoverallsatisfactioninordertoincreasecustomerloyalty
(bothonlineandonline)willbeunderestimatingthepowerofMCIoncustomerloyalty.This
meansthatdevelopingstrategiestomeetcustomerexpectationsregardingMCI,togetherwith
strategiesaimedatincreasingoverallcustomersatisfaction,willgeneratesynergiesin
increasingcustomerloyalty,mainlyintheonlinecontext,asthemediationeffecthasprovedto
bestrong(versusmoderate)whenconsideringonlineloyalty(versusofflineloyalty).
Accordingly,improvingonlineandofflinefactorsdeterminingcustomersatisfaction(suchas
personalcustomerserviceorestablishmentofatmosphereintheofflinecontext,sitedesignor
financialsecurityintheonlineone,orproductofferingsandproductinformationineither
channel),togetherwiththeintegrationandcoordinationofbothchannels,willenhance
altogethercustomerloyaltymorebroadly.
ItisworthtorememberthattheseresultscomefromtheconsiderationofMCIfromthe
customerperspective,whichmeansthattheretailernotonlyhastoconsiderhowcustomers
perceiveitseffortsregardingMCI;itisalsonecessarytoidentifywhichaspectsoftheMCI
domainaremorerelevanttocustomers,inorderforretailers’effortstobemoretargeted,and
toreinforceandpromotethoseperceived‐relevantissues,asthatwillhavestronger
consequencesintermsofcustomersatisfactionandloyalty.
Ourpaperhascertainlimitationscomingfromtheresearchdesign:differentshopping
motivationsoftherespondentsmightintroducesomebias,andinthisregardmotivations
couldbeintroducedintothemodelsothattheireffectsonMCIperceptions,customer
satisfactionandloyaltymightbeanalysed.Moreover,culturemightplayamoderatingrolein
therelationshipsfound,andthatisnotanalysedhere;amulti‐groupanalysiscouldbeapplied
toidentifythisinfluence.Futureresearchcouldalsopayattentiontotheonlineretailersthat
aremovingofflinebyopeningbrick‐and‐mortarstoresorcollectionpoints,andanalyse
whethertheeffectswehaveobservedalsoholdinthiscontext.Additionally,itcouldbe
interestingtotestwhetherthoseresultsareconsistentacrossretailersofdifferentsizes,or
shoppersofdifferentagesandspendingbehaviours.
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... This evolution is reshaping every facet of the retail transaction experience, from the initial customer interaction to post-purchase engagement. Empirical research examining customer behavior across 51 retail organizations demonstrates that consistent cross-channel experiences directly correlate with a 32% increase in purchase frequency and a 24% increase in average transaction value [5]. ...
... The technical foundation for this cross-platform compatibility often involves a clear separation between presentation logic and business rules, with the latter implemented as platform-independent services accessible through standardized APIs. Studies of customer journey patterns reveal that 78% of retail transactions now involve multiple touchpoints, with consumers regularly moving between mobile applications, web interfaces, and in-store systems during a single purchase journey [5]. Equally [6]. ...
... Research examining customer satisfaction drivers in omnichannel retail environments identifies inventory accuracy as the single most influential factor in purchase completion, with 82% of customers abandoning transactions after encountering inventory discrepancies between online and in-store systems [5]. ...
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The retail industry is undergoing a transformative shift as organizations evolve from legacy transaction processing systems toward cloud-native architectures. This technical article explores how modern, event-driven UI architectures are revolutionizing retail operations by addressing critical limitations of traditional systems. Legacy infrastructures characterized by tightly coupled monolithic designs create fragmented customer experiences, impose scalability constraints, perpetuate vendor lock-in, and impede innovation. By contrast, modern architectural approaches featuring decoupled microservices, cross-platform compatibility, event-driven communication patterns, and cloud infrastructure deliver measurable improvements in customer experience, cost optimization, innovation velocity, and business agility. The implementation considerations highlight the importance of phased migration strategies, API-first design principles, security-by-design practices, and comprehensive staff training to maximize successful outcomes.
... Studies that investigated the effect of customers' perceptions of retailers' online and offline channel integration (see Table 1) demonstrate that channel integration may positively influence customer satisfaction ( [21,44]), empowerment and trust [64], engagement [37], cognitive and affective experiences [22], purchase intention ( [24,31,37,54,65]), loyalty [21], customer retention [44], and word of mouth [37]. It may decrease firm switching [3]. ...
... Studies that investigated the effect of customers' perceptions of retailers' online and offline channel integration (see Table 1) demonstrate that channel integration may positively influence customer satisfaction ( [21,44]), empowerment and trust [64], engagement [37], cognitive and affective experiences [22], purchase intention ( [24,31,37,54,65]), loyalty [21], customer retention [44], and word of mouth [37]. It may decrease firm switching [3]. ...
... In the no-ISMCAI condition, the online store was not integrated, i.e., the retailer did not provide a mobile channel. In the ISMCAI condition, we aligned the scenario with conceptualizations from extant research ( [3,9,21]): The retailer was presented as offering a mobile channel, such as a website or app, accessible via smartphone, tablet, or tablet kiosk. The channels were integrated, and customers who purchased products using the mobile channel could pick them up at a store or choose home delivery. ...
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This research examined a specific case of retailers’ digitalization, that of in-store–mobile channel asymmetrical integration (ISMCAI), a growing strategy in practice that has received scant attention in extant literature. ISMCAI retailers’ online/mobile channels are integrated with the shopping experience in their physical stores, in which an asymmetrical assortment strategy is the goal, such that customers can enjoy both a physical shopping experience and access to the digital store through tablet kiosks or mobile apps to order products not offered in the brick-and-mortar stores. This research comprises three studies that demonstrate that ISMCAI creates cross-channel synergies by increasing purchase intentions, perceived convenience, and perceived assortment variety, and by decreasing customer anger. However, these studies also highlight ISMCAI’s potential downsides: shoppers with less experience shopping online and shoppers seeking experiential products receive fewer benefits from this type of digitalization.
... Lee and Kim (2010) argue that keeping channels integrated by facilitating switching channels increases customer loyalty toward multichannel retailers. Similarly, Frasquet and Miquel (2017) find that channel integration increases overall satisfaction, which in turn enhances both online and offline loyalty. Customers enjoy the availability of multiple channels and use them in the research and purchase processes (Verhoef et al., 2007). ...
... The present study adopts repurchase intention and positive word-of-mouth as measures of customer loyalty. Repurchase intention can be understood as the desire expressed by the customer to repeat a purchase from the same provider and opposing the change to alternative brands existing in the market (Frasquet and Miquel, 2017). Word-of-mouth communication (WOM), on the other hand, is a general concept of International Journal of Retail & Distribution Management interpersonal interaction through which people share their personal opinions about products, companies, or services. ...
... The questions assessed showrooming benefits (Goraya et al., 2022;Shareef et al., 2011), showrooming costs (Ariffin et al., 2018;Gensler et al., 2017), internet savviness (Daunt and Harris, 2017), showrooming behaviour (Schneider and Zielke, 2020), showrooming satisfaction (Flavi� an et al., 2016), and customer loyalty in terms of repurchase intention and positive word-of-mouth (Frasquet and Miquel, 2017;Zeithaml et al., 1996). Showrooming satisfaction is a second-order construct, composed of satisfaction with the brick-and-mortar store and satisfaction with the online store. ...
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... ; process consistency fromShen et al. (2018) ; assortment consistency fromRahman et al. (2022) ; price consistency fromFrasquet and Miquel (2017) andGao et al. (2021) ; and promotion consistency fromFrasquet and Miquel (2017) andGao et al. (2021) . Regarding assortment consistency, we made minor modificationsto the items employed by Rahman et al. (2022) (AST1 and AST2) , adding an item indicating online availability (AST3) . ...
... ; process consistency fromShen et al. (2018) ; assortment consistency fromRahman et al. (2022) ; price consistency fromFrasquet and Miquel (2017) andGao et al. (2021) ; and promotion consistency fromFrasquet and Miquel (2017) andGao et al. (2021) . Regarding assortment consistency, we made minor modificationsto the items employed by Rahman et al. (2022) (AST1 and AST2) , adding an item indicating online availability (AST3) . ...
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Channel integration to provide a seamless customer journey experience plays a central role in omnichannel marketing. However, not all dimensions of channel integration enhance customer experience. We decompose the dimensions of customer-perceived consistency in channel integration and investigates the impact on two customer experience types: continuous and predictable customer experience and serendipitous and unpredictable customer experience. The analysis reveals that content consistency, process consistency, and promotion consistency significantly affect both continuous and serendipitous customer experience, but price consistency and assortment consistency do not considerably impact serendipitous customer experience. These insights offer valuable direction in shaping omnichannel integration strategies.
... Dynamic capability is a particular type of capability that not only helps enterprises improve and sustain their long-term CADs [14][15][16][17] but also positively influences other internal capabilities such as innovative capability [14,16,18], multichannel capability [19,20], or marketing capability [21] before these capabilities affect SCAD [16,[22][23][24]. However, in the context of GDC research, empirical studies examining their relationships and impacts on other enterprise capabilities have not received much attention. ...
... Verhoef et al. (2015) discussed the transition from Multichannel to Omnichannel Retailing and Pantano et al. (2018) reviewed the dimensions of "smart retailing" in this context. Also, Frasquet and Miquel (2017) analyzed the benefits of channel integration on consumer loyalty and satisfaction both online and offline. Quite recently, Loupiac and Goudey (2020) found that consumers' expectations of the conventional store (e.g. ...
Chapter
Consumer behavioral patterns radically changed during the last decades, as well as during the COVID-19 pandemic. In parallel, digital technologies continuously substitute traditional business practices in the context of digital transformation attempts that were also significantly accelerated due to the pandemic. However, since technology cannot totally replace all human aspects in the retailer-consumer interaction process, an optimum blending of technical and human resources is crucial. This chapter reviews the latest developments and key aspects of this blending and emphasizes the consumers' needs for the provision of value-added services by retailers in the post-COVID-19 era. It advocates that retailing remains a retailer-consumer affair, where both humans and technologies take part in diversified interactions. It develops an integrated framework of human and technology components and channels between retailer-consumer interactions, aiming to provide a holistic view of the available capabilities and trends from both the retailer and the consumer perspective in the post-COVID-19 era.
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The world of retailing has changed dramatically in the past decade. The advent of the online channel and new additional digital channels such as mobile channels and social media have changed retail business models, the execution of the retail mix, and shopper behavior. Whereas multi-channel was in vogue in the last decade in retailing, we now observe a move to so-called omni-channel retailing. Omni-channel retailing is taking a broader perspective on channels and how shoppers are influenced and move through channels in their search and buying process. We discuss this development conceptually and subsequently discuss existing research in this multi-channel retailing. We also introduce the articles in this special issue on multi-channel retailing and position these articles in the new omni-channel movement. We end with putting forward a research agenda to further guide future research in this area.
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Purpose – Our aim is to investigate the topic of multi-channel retailing. Specifically, our research intends to determine if and to what extent the opening of physical stores by a former web-only retailer reduces or extends overall retail sales, and whether such effects tend to change over time. Empirical analysis focuses on data elaboration from a retailer who has passed from the initial mono-channel model (pure online), to a multi-channel one with the opening of stores. Design/methodology/approach - Through the analysis of an internal dataset of a leading consumer electronics retailer applying Probit and Logit estimation techniques, we extract information about actual customers’ purchases (or rather retail sales) in three newly-opened stores and about online purchases (through an e-commerce website managed by the same retailer with the same store brand) by people living in the new store service areas before and after the openings. Findings - The paper shows that, for the single customer, the probability of purchasing online is reduced by the store opening in the short-term, but tends to increase in the long-term. Besides, results indicate that long-term synergy between the two channels depends mainly on indirect influence due to the mere presence of the store brand in the area rather than on the direct experience of shopping in the store. Research implications - The study highlights that channel portfolio enlargement from mono to multi-channel retailing tends to activate a sort of life cycle; while in the early phase of store addition web sales tend to be cannibalized because the two channels are perceived as “substitutes” for each other, in the long run migration turns into a synergy effect; different channels tend to interact with and reinforce each other as customer touch points of the same retailer, in an omni-channel perspective. Originality/value - The paper herein presents various original elements concerning types of available data (actual sales rather than consumers’ intentions/perceptions and individual level data rather than aggregate level ones), estimation technique used (binary choice model) and research hypotheses (distinguishing between “direct” and “indirect” synergy effects in multi-channel retailing).
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This research examines the impact of online–offline channel integration (OI), defined as integrating access to and knowledge about the offline channel into an online channel. Although channel integration has been acknowledged as a promising strategy for retailers, its effects on customer reactions toward retailers and across different channels remain unclear. Drawing on technology adoption research and diffusion theory, the authors conceptualize a theoretical model where perceived service quality and perceived risk of the Internet store mediate the impact of OI while the Internet shopping experience of customers moderates the impact of OI. The authors then test for the indirect, conditional effects of OI on search intentions, purchase intentions and willingness to pay. Importantly, they differentiate between retailer-level and channel-level effects, thereby controlling for interdependencies between different channels. The results of three studies provide converging evidence and show that OI leads to a competitive advantage and channel synergies rather than channel cannibalization. These findings have direct implications for marketers and retailers interested in understanding whether and how integrating different channels affects customer outcomes.
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Online stores of multichannel retailers continue to lag pure internet retailers with reference to consumers' shopping intentions and sales. This study develops and tests a framework in which (a) trust and attitude (conceptualized as a second-order construct with hedonic and utilitarian dimensions) influence purchase intentions, (b) congruity between the multichannel retailer's land-based and online stores (conceptualized as a second-order constructs made up of seven dimensions: aesthetic appeal, navigation convenience, transaction convenience, atmosphere, service, price orientation, and security) influences trust in and attitude toward the online store, and (c) congruity between consumers' self-image and perceived image of the online store influences trust in and attitude toward the online store. The findings provide robust support for the framework and have strong implications for theory and practice.