DOI: 10.4018/JGIM.2020010109

Journal of Global Information ManagementVolume 28 • Issue 1 • January-March 2020

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Trust, Risk and Alternative Website Quality in B-Buyer Acceptance of Cross-Border E-CommerceJian Mou, Xidian University, Xi’an, China

Yi Cui, Communication University of China, Beijing, China

Kerry Kurcz, University of Illinois at Chicago, Chicago, USA

ABSTRACT

Cross-bordere-commerce(CBEC)hasbecomeanimperativemodeforglobaltrade.Researchoncross-bordere-commercehistoricallyfocusesmainlyonthecustomer’sbehaviorintentiontopurchaseonaCBECplatform.However,B-buyersaremoreimportantcomparedwithC-buyersforCBECplatforms.ThisisbecauseB-buyerscancontributemoregrossmerchandisevolume(GMV)inaCBECplatform,andthusmoremarginforthefirm.Theauthorsapplytrusttransfertheory,perceivedrisk,andalternativewebsitequalitytostudyrepurchaseintention,focusingonB-buyers.Theresultsshowthatperceivedrisk,trustinprovider,andtrustinthewebsiteaffectrepurchaseintentionsignificantly,wheretrustinwebsiteisfoundtobethemostimportantfactor.Inaddition,theauthorsfoundthatthedimensionsofperceivedriskinCBECcontextcanbeclassifiedasthefollowing:customerdutiesrisk,confiscationrisk,deliveryrisk,financialrisk,andprivacyrisk.Thecontributionsofthestudyareaddressedlastly.

KEyWoRdSB-Buyers, CBEC, Cross-Border E-Commerce, Perceived Risk, Repurchase Intention, Trust

INTRodUCTIoN

Withtheflourishofinternettechnology,informationtechnology,logisticservicesandglobalizationofworldtrade,e-consumerstendtolookbeyondtheirborders.Globale-commercesalesreached6.3trillionyuan(about914billionU.S.dollars)in2016alone,basedonthedatafromtheMinistryofCommerce(MinistryofCommerce,2017).ResearchreportsfromiResearch(2017),aprofessionalconsultancycompanyconcentratingononlinemediaande-commerce,alsopredictthatthistotalturnoverwillnearlydoubleto12trillionyuan(about1.74trillionU.S.dollars)by2020.Bythattime,39%oftheworld’sentiree-commercemarketwillbecontrolledbytraditionalmarketplaces,and53%ofcross-bordersellersintheUSwilluseonlinemarketplaces.Suchrapiddevelopmentindicates the immensepotentialandopportunityofcross-bordere-commerce (CBEC) forglobaleconomicstogrowinthenearfuture.Therefore,CBECresearchplaysanimportantroleforeconomicdevelopment-globally.GiventheimportanceofCBEC,understandinganddedicatingspecialattentiontothefactorsthatinfluencebuyers’behaviorisessentialforanycompanywhowishestosurviveandthriveamongtheexponentialtrendsofglobalization.

Manystudieshaveshowntrustispriorityinthesettingofanye-commerce.However,inCBEC,trustbecomesevenmorecrucialduetothe“distance”betweenbuyersandsellers,where“distance”

Thisarticle,originallypublishedunderIGIGlobal’scopyrightonOctober4,2019willproceedwithpublicationasanOpenAccessarticlestartingonJanuary11,2021inthegoldOpenAccessjournal,JournalofGlobalInformationManagement(convertedtogoldOpenAccess

January1,2021),andwillbedistributedunderthetermsoftheCreativeCommonsAttributionLicense(http://creativecommons.org/licenses/by/4.0/)whichpermitsunrestricteduse,distribution,andproductioninanymedium,providedtheauthoroftheoriginalworkandoriginal

publicationsourceareproperlycredited.

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hasbeenrecognizedaslanguagebarriers,legalsystemsbarrier,timebarrier,deliveryservices,aswellascustomsregulations(Kim,Dekker,&Heij,2017).Althoughmulti-dimensionaltrusthasbeeninvestigatedinthee-commercesetting,thereisalackofevidenceintheeffectofmulti-dimensionaltrustintheCBECcontext.CBECisdifferentfromdomestice-commerce.Thesedifferencesmainlyreveal additional trade costs and risks from cross-border transport, import tariffs, differences intechnical standards, poor institutional quality and weak contract enforcement (Gomez-Herrera,Martens,&Turlea,2014).

GiventhecomplexnatureofCBEC,itsbuyersaremorelikelytoperceiverisks.Multiplefactorriskshavebeenconsideredinthedomestice-commercesetting(e.g.,Tandon,Kiran,&Sah,2018;Marriott&Williams,2018),albeitriskssuchascustomerdutiesrisk,confiscationrisk,deliveryriskhaveyet tobedeeplyinvestigatedinCBEC.Therefore,understandingperceivedriskinstudyingCBECisnecessary.Furthermore,mostexistingresearchfocusesonC-buyers,whileB-buyersaremore important forCBECplatform.This isbecauseB-buyerscancontributemoremargin forafirm(Kraemer,Gibbs,&Dedrick,2005). In this research,B-buyers refer tocustomerswhobuyproductsorservicesforthecompanyorworkplacewithwhichtheybelong.Infact,B2Ctransactionshavedevelopedrapidlyinrecentyearsduetotheconvenienceofhighdiscounts.Meanwhile,B2BtransactionsaregrowingfourtimesfasterthantheirB2Ccounterpart(Vakeel,Das,Udo,&Bagchi,2017).However,andperhapsmostimportantly,ithasbeenproventhatB-buyerscontributemoreGrossMerchandiseVolume(GMV)inCBECplatforms.ComparedtoB2Ce-commerce,B2Be-commerceisalessresearchedareawithsignificantdifferenceabouttransactionvolume,averagetransactionamount,logistics,customersegments,fulfilmentissues,andadvertisementobjectives(Vakeeletal.,2017).AnotherconvenientcharacteristicofB-buyersisthattheyaremorelikelytotransactwiththeirprevious sellers,with the same items, in largevolumes.Meanwhile,Kraemeret al. (2005)emphasizedthatforB2Be-commerce,highlyglobalcompaniesutilizetheInternetmorethantheirlessglobalcounterparts,whereasforB2Ce-commercetheoppositeistrue.Thisisbecauseglobalcompaniesfocusmoreonwholesalebrokerageactivityindifferentcountriesacrossvariousstagesofanindustry’svaluechain,whilelessglobalcompaniesfocusingontheretailbrokerageindustryarelessaffectedbyglobalization,andthusremainlocal.

SinceB-buyersaremorelikelytopurchaseproductsinawholesalesetting,alternativequalitysuch as service quality and system quality are more important for B-buyers. Furthermore, theynormallyqueryseveralCBECplatformsamongmultiplesellers,seekingoutthelowestpricefordozensofproducts.Foranytypeofconsumer,alternativewebsitequalitycanmakeallthedifferenceinswitchingbehaviorandtrustinthatwebsite(Sørum,2015;Kalia,Arora,&Kumalo,2016).CBECplatformsconstantlyneedtoimprovetheirqualityofproducts-whilekeepingpriceslow--andattractmoreinternationalbuyerswiththeopportunityofpromotionaldays(suchasChristmasorBlackFriday).Indeed,theperceptionsrisingfromalternativeplatformsistobeamongthetopprioritiesregardingCBECresearch.

Ingeneral,thispaperaimstointegrateperceivedriskandalternativewebsitequalitytounderstandthecrucialtrust-buildingmechanismforpromotingrepurchasebehavioraswellasenhancingCBECplatformloyalty.Moreover,thispaperstrivestobridgethegapbetweentrustandCBECwiththeantecedentsoftrust,andtouncoverwhysomeCBECplatformssucceed,whileothersdonot(aswithMetao.com,whichwillseelater).Thesefindingsmayhelpresearcherstoextendtheirstudiesand,ofcourse,practitionerstomaketheirwebsitemoreattractivetobuyers.Thesepointsaresummedupwiththefollowingresearchquestion:

RQ: Will alterative website quality, perceived risk and trust jointly affect the consumer’srepurchaseintentioninCBEC?

The structureof this study is organized as follows: the first section reviewsexistingCBECliteratureandthecurrenttheoreticalbackground;sectiontwodemonstratesthedevelopmentoftheresearchmodelandhypothesis;thisisfollowedbythedesignofthisstudy;thentheresearchresults;last,thepaperconcludeswithdiscussions,contributionsandlimitations.

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LITERATURE REVIEW ANd HyPoTHESIS dEVELoPMENT

Cross-Border E-commerceCBEC generally refers to transactions among different countries or customs areas through ane-commerceplatformandcross-borderlogistics(Tmogroup,2015).Itisacommontrendinmoderne-commercebusiness,especiallyforsmallandmediumenterprises(SMEs),becauseitcanreducetradebarriersandpromotetradegrowthinanotherwiselimitedmarketplace(Terzi,2011).Sellers,manufacturers,andallparticipantsofCBECcanprofitfromCBECduetothelargeproductassortmentwithlowcosts;thisincludes,perhapsespecially,buyers(Kimetal.,2017).ThereareseveralstudiesfocusingonthefactorsofCBECsuccess.Forexample,cross-borderpayments(Ai,Yang,&Wang,2016),logisticinfrastructureanddevelopment(Cho&Lee,2017),andculturaladaption(Sinkovics,Mo,&Hossinger,2007)haveeachbeeninvestigatedasimperativefactorsofCBECsuccess.HuangandChang(2017)alsoillustratedthefactorsthataffectconsumers’intentiontopurchaseitemsbehindtheperspectiveofperceivedtrustandvalueaspects. Inaddition,Guoetal. (2018)demonstratedthatsellers’trustinbuyersandperceivedriskofchargebackfraudarealsocrucialtothesuccessofCBEC.Meanwhile,itisimportanttonotethereareknownrisksposedtobuyers,suchasinformationasymmetry,privateinformationmisuse,andotheruncertaintyrelatedtotransactionsandproducts(Mou,Cohen,Dou,&Zhang,2017).

CBECinChinahasbecomethemajorwayofforeigntradewithgrowthrateofsixteentimesthatcomparingtogeneraltrade.ThemainmodeisB2Be-commerce,whichaccountsfor88%ofallCBEC(Xue,Li,&Pei,2016).Moreover,theChineseCBECretailexportsaccountfor37%oftheglobalmarketshare,whichmaybecausedbytwomajormanufacturingcapacityadvantages.FirstisChina’sadvantageofbeinga“worldfactory”1andsecond,thetransformationinrecentyearsto“createinChina”ratherthan“madeinChina.”TheseachievementsattributetothesupportivepolicyofChinasuchas“internet+”(Wang,Zhang,&Sun,2017)and“theBeltandRoadInitiativeproject”2(Li&Chan,2016).Despitethisgeneralsuccess,manycross-bordere-marketplaceshavefailedinrecentyearsduetopoorperformance(Thitimajshima,Esichaikul,&Krairit,2018).Forexample,Metao.com,foundedin2013,quicklywentbankruptby2016.ItcanbearguedthatMetao.comdidnotunderstanditsownmarketplace,henceitsdemise.Therefore,itisimportanttostudyCBECtounderstandwhyitsucceedsandwhyitmightnot,inordertodrivemoredirectlytowardsuccess.

The Relationship Between Trust and Repurchase IntentionTrust is formed by indicators from various formations, including trust feature signals, symbols,orcuesprovidedbytrustees(Mou&Shin,2018).Itcanalsobereferredtoasthewillingnessofonetobevulnerabletotheactionsofanother(Mayer,Davis,&Schoorman,1995).Inaphysicalstore,trustisgenerallybuiltbythesalespersonandtheappearanceofthestore(Doney&Cannon,1997).Circumstanceschangewhenthestoreisonline.Withoutthephysicalentityofthestoreitself,uncertaintyincreases.Customerscannotfeelthe“store”bysensesdirectly,andtheantecedentsoftrustarereplacedbybothperceivedwebsitequalityandtrust-relatedstatementsprovidedbye-vendorsorplatforms(Kraemeretal.,2005).Becausetrustcanhelptoreducefearsandworries(Lu,Yang,Chau,&Cao,2011),itiscrucialintheuncertainsettingofCBEC(Kimetal.,2017).Naturally,thebesttrustishighandsteady.Thus,CBECplatformsmustasserttheirwebsitequalityismaximized,e-vendorandplatformstatementsclean,andbothconsistentlymonitoredforanythingthatcouldbeperceivedasnegativeorriskyfromthebuyerperspective.

Empirical evidence suggests that trust directly influences the purchase intention of onlinecustomers(Kraemeretal.,2005;Mou,Shin,&Cohen,2017).ForB-buyers,thetransactionsarealwaysmorefrequentandinlargescale,whichfacilitatestheformationoflong-termrelationshipswithvendors.Thus,inthisrelationshipbetweenB-buyerandvendor,trustandcommitmenttogetherwillmaintaincooperationandencourageanorganicandloyalrelationship(Li,Browne,&Wetherbe,2006).Moreover,thetheoryofreasonedaction,whichsuggeststhatindividual’sbeliefsinfluence

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behavior intention,naturallyprovidesa foundation for the relationshipbetween trustbeliefsandintentionbehavior(Fishbein&Ajzen,1975).Inthisstudy,theauthorsclassifytrustasboththatintheproviderandinthewebsite.TrustintheprovidercanenhancetherelationshipbetweenB-buyerswithaspecificvendor,whereasCBECwebsitemayreliableandownthefunctionalitythatthebuyersneeded,andthereforepromoterepurchaseintention.Thus,theauthorshypothesisthat:

H1:Trustinproviderpositivelyaffectsrepurchaseintention.H2:Trustinwebsitepositivelyaffectsrepurchaseintention.

The Relationship Between Perceived Risk and Repurchase IntentionPerceived risk describes the customers’ behavioral tendency of reducing and minimizing anyexpected negative effects associated with purchase activity (Peter & Tarpey, 1975). It has beenconsideredamajorbarrierforonlineconsumerstomakeanonlinetransaction.Varioustypesofriskinmarketresearchhavebeenidentified,including,butnotlimitedtofinancial,time,performance,physical, social, and psychological, (Tandon, Kiran, & Sah, 2018; Marriott & Williams, 2018).Financialriskreferstoanymonetarylossthroughtechnicalormarketingchannels,suchassystemerrorcausedmultiplepurchase,sellers’fraudbehavior,orreturnbarriers.Thismonetarylossmayincludeopportunitycost,time,orboth.(Bhatnagar,Misra,&Rao,2000).Whenacustomerdecidestopurchaseonline,ahighperceivedriskmayinfluencehimorhertoceasethetransaction,oreventobereluctanttoshopinthefirstplace(Antony,Lin,&Xu,2006).Thisriskdoesnotexistinatraditionalbrick-and-mortarretailstore(e.g.Tesco,Walmart),wherecustomerscaneasilyaccesstheproducttheywant,andtouch,feel,eventrytheproductbeforetheymaketheirdecision.Indeed,asthedistancebetweenbuyersandproductsdecreases,sodoestheperceivedrisk(Kraemeretal.,2005).

Despite the varying distance between domestic and international e-commerce, product riskisgenerallythesameinbothsituations.However,CBECfacesmorechallengesintheprocessoftransactions.First,customsdutiesandtaxesareoneofthemostdistinctandmajorbarriersinCBEC(Turban et al., 2017). Because B-buyers commonly order products in a large volume and morefrequently,thesebarriersaremorerelevantforB2Bcustomers.Thesecostsmayalsoincludetaxescomingfromthebuyer’sowncountry.Meanwhile,itisimportanttonotethatproductsinlargequantityareoftensubjecttospecificcustomschecks(Sinkovicsetal.,2007),whichleadstothesecondpoint:confiscationriskmayoccurduetoeitherthevulnerabilityofcross-bordertransactionsorproblemsrelatedtopotentialshippingandcustoms,namelyforproductsinlargequantity.Further,thegreaterthedistance,themoredeliverytimeisimpliedtheprobabilityoflossordamageincreases.Therefore,delivery risk ismore serious inCBEC thandomestic e-commerce. In addition, large-scaleB2BtransactionsinCBECmustbeawareofexchangeratefluctuations(apartfromthefinancialriskswhichappearindomestice-commerce).Infact,exchangeratefluctuationisthemainpotentialrisk.

Priorstudiesofe-commercealreadyshowthatperceivedrisknegativelyaffectsaconsumer’sintention to purchase (Kraemer et al., 2005; Kuan & Bock, 2007), but the authors believe thisrelationshipwillbeamplifiedinCBEC,especiallyforB2B,andthereismoretobesaidonthesubject.Thus,thefollowinghypothesishasbeenproposed:

H3:Perceivedrisknegativelyaffectsaconsumer’sintentiontorepurchaseonline.

The Relationship Between Perceived Risk and TrustAccordingtotheextendedvalenceframework(Kraemeretal.,2005),thenetvalencegeneratedbyperceivedbenefitandperceivedriskiscrucialduringtheprocessofmakingapurchasedecision.Asdescribedabove,perceivedriskisthemainbarrierinCBEC.Therefore,whentheuncertaintyorriskappears,theremustbeacomplementtoneutralizetherisk:trustisthatcomplement(Kim,Ferrin,&Rao,2009).Newresearchsupplementsthatwhichhasshownthenegativeeffectsoftrust

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onperceivedriskine-commerce.Thisresearchsuggeststrustcouldbeanantecedentofrisk,thesameasrisk,oraby-productofrisk—butallinall,theyaredifferentconcepts(Kraemeretal.,2005).AsdescribedbyMayeretal.(1995),trustisconstitutedbythreecharacteristics:ability,benevolence,andintegrity.Abilityisdefinedasthecompetenceorbeliefsthatsomeoneiscapableofdoingwhatisexpected(Hallikainen&Laukkanen,2018).Benevolencereferstothebeliefthatatrusteewantstodogoodtothetrustor,asidefromanegocentricprofitmotive(Mayeretal.,1995;Hong,2018).Integrityrefers to thebelief thatacompanywillact inaconsistent, reliable,andhonestmannerwhenfulfillingitspromises(Hong,2018).Collectively,Hallikainen,Laukkanen,andHongassertthatifatrustorperceivesatrusteewithenoughofthesekeycharacteristics,trustwillbedeveloped.Therefore,consumerswouldliketoengageinariskyrelationshipwithavenderifandonlyifthetrustexceedsthethresholdofperceivedrisk.Inotherwords,trusthasaninverserelationshipwithperceivedrisk.However,thisstudiesshowthatthefunctionoftrustinaffectingbehaviorintention(e.g.repurchase)isthesameasrisk,andtheireffectmechanismsare,tosomedegree,areciprocal.Inmobilecommercecontext (Lin,Wang,Wang,&Lu,2014),perceivedriskcanbereducedbypre-trust,andhaveafunctionofdecreasingpost-trust.Further,inanonlineenvironment,empiricalevidenceshowsthatriskperceptionscannegativelyinfluencemulti-dimensionaltrust(Treiblmaier&Chong,2011).Therefore,ifB-buyersinCBECperceivedlowerriskeitherfromvendorsortheCBECplatformwebsite,theywillreducetheirworryandfears,andbecomemorerisktolerant.Thismakessense,consideringtheytrusttheirsuppliers.Thus,theauthorshypothesisthat:

H4:Perceivedrisknegativelyaffectsbuyers’trustinproviders.H5:Perceivedrisknegativelyaffectsbuyers’trustinCBECwebsites.

The Relationship Between Alternative Website Quality and TrustAmongnumerousCBECplatforms,buyerscaneasilyswitch theirchoice throughasingleclick.Accordingtotheinformationsystemsuccessmodel(DeLone&McLean,2003),thequalityofaninformationsystemisconstitutedbysystemquality,informationquality,andservicequality.Inthecontextofthisstudy,theauthorsrefertoalternativewebsitequalityastheproductqualityandpricebuyersperceiveofotherCBECplatforms.Alternativequalityisidentifiedasakeyfactortoformandstabilizecooperativerelationships(McKnight,Choudhury,&Kacmar,2002).IfconsumerneedscanbebettersatisfiedbyanotherCBECplatform,thecommitmentofthecurrentrelationshipwillbereducedandeasilyreplaced.Conversely,ifconsumersfacepoor,unstable,unsuitablealternativesorevenjustnotasgoodasthecurrent,theyaremorelikelytostayfirmlywithinthepresentrelationship.Empiricalevidencehasshownthatthequalityofoutcomeavailablefromthebestalternativerelationshippartnercanhelptomaintainabuyer-sellerrelationshipinthecontextofB2B(Anderson&Narus,1990).Inpractice,ifbuyersfindanother,betterCBECplatformwebsite,theytendtodevaluetheoldoneandbecomereluctanttomaintaintherelationship(Johnson&Rusbult,1989).Therefore,itmayreducethetrustofthecurrentwebsitealongwiththeirprovider.Thus,theauthorshypothesisthefollowing:

H6:Alternativewebsitequalitynegativelyaffectsbuyers’trustinproviders.H7:Alternativewebsitequalitynegativelyaffectsbuyers’trustinCBECwebsites.

The Relationship Between Alternative Website Quality and RiskTherearemanyaspectsassociatedwithalternativewebsitequality.OtherthantheISqualitiesdiscussedearlier,otherfactorsalsorevolvearoundalternativequality,includingpaymentprotectionmechanism,securityandprivacyprotection,andpositivereputation.Kimetal. (2008)hasdemonstratedthattheseelementsofane-commercewebsitecandecrease(orincrease)perceivedrisksfrombuyersandincrease(ordecrease)theirtrust.InthecontextofCBEC,consumersfeelmoreuncertaintyandriskduetothe“longdistance”(Kimetal.,2017)acrossbordersandaroundtheglobe.Therefore,ahigh

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qualityofaCBECplatformcanreduceriskperceptionforconsumersandmakethemlesssensitivetouncertainty.Thus,theauthorshypothesisthat:

H8:Alternativewebsitequalitypositivelyaffectsperceivedrisksfrombuyers.

Trust Transfer TheoryTrust transfer theory refers to thephenomenon that a trustor baseshis or heroriginal trust in asource,onthetrustalreadyembeddedinanotherrelatedtarget,orthesametargetinanothercontext(Stewart,2003).Generally,therearetwotypesofrelationshipsbetweensourceandtarget:similarityandbusinesstie,respectively.Asimilarityrelationshipisregardedasaninternalconnection,andsuchaconnectionreferstothesamefeaturesorattributesoftrustedsourceandtarget.Iftwoobjects(i.e.sourceandtarget)haveseveraltraitsincommon,theywillbeperceivedasbelongingtothesamecategory,andthetrusttransferoccurs.Abusinesstierelationshiprepresentsexternalconnection,whichisdisplayedasacuefromoutsidesources.Forexample,iftwoproductsarefromthesamecompany,thetwowebsitesshareinterlinks.Trusttransfertheoryisimportantinunderstandingthemechanismoftrustbuilding,especiallyforrelatedtargets(Mou&Cohen,2017).Ifacustomertrustsasalesman,thenthecustomerlikelytruststheproductsheorshesells,aswellasthecompanyheorshebelongsto(Doney&Cannon,1997).Trustcanalsobetransferredfrombrickandmortarretailerstotheironlineshop(Kuan&Bock,2007).Thisisalsoabusinesstierelationship.Todemonstratesimilarityexamples,thetrustfrominternetpaymentscanbetransferredtomobilepayments(Luetal.,2011),andfrominternetandadministrationtopublice-service(Belanche,Casaló,Flavián,&Schepers,2014).

Inthisstudy, therelationshipbetweenCBECplatformwebsitesanditsproviders(sellers) issimilartotherelationshipbetweenacompanyanditssalesmen.Asdiscussedabove,thisrelationshipbelongstobusinessties,becausetheCBECplatformdoesnothavethesimilarfeaturesaswebsiteproviders,albeittheyareallbundledtogether.Therefore,theauthorshypothesisthefollowing:

H9:TrustintheCBECplatformwebsitepositivelyaffectbuyers’trustinproviders.

Control VariablesNationalculturereferstothesimilarpatternofmentalmodewithinagroupofpeople(Hofstede,1998).Ithasbeenshowntoinfluenceconsumerbehaviors(Thitimajshimaetal.,2018).Culturediffersfromcountrytocountry,aswellasamongdifferentlocationswithinasinglecountry.Researchershaveappliedculturetostudydifferentaspectsofglobalinformationmanagement,suchasITdevelopment,operations,managementanduse (Gallupe&Tan,1999).Consequently,CBECisculture-bound.Becauseofthis,cultureisacontrolvariableinthisstudy.

Inaddition toculture, thisstudyalso includesage,gender,and incomeascontrolvariables.Psychologists believe that demographics play an important role in an individual perceptual andjudgmentformationprocess.Forexample,researchersarguethatgenderdifferencesareinstrumentalinconsumerdecisionmakingprocessforonlineshoppingcontext(Stafford,Turan,&Raisinghani,2004).Previously,researchershavefoundthatmalesaremorelikelytousetheInternetthanfemales.Specifically,menaremorelikelythanwomentoparticipateinonlineauctionsandpaytodownloaddigitalcontent(Sebastianelli,Tamimi,&Rajan,2008).Inanonlineshoppingcontext,youngerandfemaleconsumersaremorelikelytoimpulsivelypurchaseonline,whileolderandmaleconsumersarenot(Leong,Jaafar,&Ainin,2018).Further,previousliteraturesalsosuggestthatonlineconsumer’sage,genderandincomemayaffecttheintentiontorepurchaseonline(Aladwani,2018;Farivar,Turel,&Yuan,2018).Ontheotherhand,buyersmaybemoresensitivetoonlinetransactions,oroverlycarefultowhenpurchasingonCBECduetouncertaintiessuchasfraud.Therefore,theauthorsusefraudasanothercontrolvariable.

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TheresearchmodelisillustratedinFigure1below.

RESEARCH METHodoLoGy

Research SettingToobtainasetofhigh-qualitydata,theauthorscollaboratedwithoneofthebiggestCBECplatformsinChina,Dhgate.com.ThisfirmisawholesalemarketwhichdelegatestohelpSMEsengageinglobalmarketplacesthroughCBECchannels.Itcovers1.2millionChinesevendorswithmorethan30millionproducts,including,butnotlimitedtothefollowing:apparel&accessories,computers&networking,consumerelectronics,toys&hobbies,health&beauty,bags&jewelry.Onthebuyerside,thereareapproximately10millionenterprisesandindividualbuyersfrom220countriesandregions.Inaddition,tofacilitatetheconsumers’purchaseinthiscross-borderfirmmoreeasily,itrunsbothaPC-basedwebsiteplatformandamobile/tablet-basedapplication.Tobettercollecttargetdata,theauthorsdistributedthesurveythroughanonlinesurveysystem.

MeasuresInthispaper,mostitemsinsurveyssuchasprivacyrisk,trustinvendor,trustinwebsiteandrepeatpurchase intentionwere adopted fromprevious literature,with small changes appropriate to theCBECcontext.Somemeasuresforconfiscationrisk,customsdutiescost,andfinancialriskhadtobedevelopedbasedoninputfromindustryexpertsandtheconceptualdefinitionsofthoseconstructs.ThiswasbecauseexistingmeasurementscaleswerenotconsideredappropriateforthecomplexnatureofCBECcomparedtoadomestice-commercesetting.Forexample,confiscationriskwasmeasuredthroughfour itemsreflecting theconsumer’sconcern thatcustomsauthoritiesmay interceptandconfiscatetheirproductwithoutcompensation.Theauthorsmeasuredcustomsdutiescostrefractingtheuncertaintysurroundingpaymentinadditionalimportduties.Theauthorsadoptedfiveitemsfrom(Lietal.,2006)tomeasurealternativewebsitequality,whichreflectthatanalternativewebsiteisattractiveandappealing.ThemeasurementitemsarepresentinAppendixB.Theauthorsadoptedthefive-pointLikert-scale,withanchorsrangingfrom“stronglydisagree,”to“stronglyagree.”

data CollectionThe authors first conducted a pilot test to determine whether the survey instruments wereunderstandableforparticipantsandwhetherthereareanyambiguousorconfusingmeasurementitems

Figure 1. Research model

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inthequestionnaires,aswellastoensurethatthesurveyitemsareappropriateintheCBECcontext.Topreventpoorresponseduetoover-sampling,therandomselectionwaslimitedtothreeoutofevery100sitevisitors(3%)whohadnotparticipatedintheprovider’ssatisfactionsurveywithinthepreviousthree-monthperiod.Basedonthesite’srulesandtominimizedisruptiontotheircustomers’shoppingexperience,thepop-upratewasdecreasedwithapproximately12respondentsperdayoveraone-and-a-half-monthperiod.Participatinginthesurveywastotallyvoluntary,andanonymitywasensuredbyconfiguringthesurveyapplicationtodisregardanyrespondentidentificationinformation.Wheninvitedtoconsiderparticipating,buyerscouldselectto“participatenow”,“maybenexttime”,or“don’taskagain”.Therewasnolossofbenefitwhetherornotarespondentchosetoparticipate.ThesurveyofthisstudywasoriginallycompiledinEnglish.

Giventheactivevisitors/usersaredifferenteveryday,thefirmdidnotletustoknowhowmanytimesintotalthepopupsoccurredduringthesampleperiod.Theauthorsdoknowthatduringtheweekdays,moresampleswerecollected,whileduringweekend,lesssampleswereavailable.Duetothevoluntarytraitofallparticipants,theauthorsbelievethattheindividualswhotookpartintheactivityweresufficientlyrandom,andthesamplewasthereforenotexhibitedbias.

RESULTS

Characteristics of demographicsAfter6weeks,theauthorshadobtainedbothC-buyerandB-buyersamples.TofocusonB-buyersrepurchaseintention,theauthorsdroppedresponsesfromC-buyers.Theauthorsultimatelyadopted243B-buyersamplesintotaltotesttheresearchmodel.DemographicstatisticsareshowninTable1,below.AllparticipantsinthisstudyindicatedthattheyhadpurchasedproductsfromanalternativeChinese cross-border website during last several months. As shown, most B-buyers were males(76.5%).Furthermore,mostoftherespondentswereoftheagerangebetween21-50,regardlessofgender.Amongtherespondents,adesirablemajorityof88.5%hadpreviouspurchaseexperienceinthiscross-borderwebsite.Inaddition,theauthorsfoundthat37%werefromtheUS,7.4%fromCanada,7.4%fromtheUK,4.1%fromAustralia,and3.7%fromBrazil;othersweremainlyfromotherEuropeancountriessuchasNetherlands,Germany,Italy,SpainandotherSouthAmericacountriessuchasChile.ThisgreaterproportionofresponsesfromNorthAmericawasnotunexpectedandisconsistentwiththisfirm’smarketingstrategies,whichislargelyfocusedonNorthAmerica,EuropeandEnglish-speakingcounties.Last,thetestofcommonmethodbias,reliability,andvaliditycanbefoundinAppendixCandD.

Hypothesis TestingThestructuralmodelofthisstudywastestedbyusingSmartPLSsoftware.Theauthorsusedthebootstrapmethod(5,000re-samples)todeterminethesignificanceofthepathsintheresearchmodel.ThePLS-SEMhasbeenemployedinthisstudyduetothefollowingreasons:first,itcanestimatetheitemsloadingsofconstructsandsimultaneouslytesttherelationshipamongthevariablesinwhichtheauthorsareinterested;second,itisappropriateforthesmallsimplesize.AccordingtoChinandNewsted(1999),thesamplesizeshouldbetentimesthelargestnumberofindependentvariables.Thisstudyhas13independentvariables(includingcontrolvariables),andthesamplesizeof243exceedstentimesthatamount,thereforeitisadequateforPLS-SEManalysis.

Theconstructsofalternativewebsitequality,trustinprovider,trustinwebsiteandrepurchaseintention were modeled as first order constructs. The authors model perceived risk as a secondorder construct. For the assessment of psychological constructs, researchers normally adoptedeither reflective measurement or formative measurement (Christophersen & Konradt, 2012). Inotherwords,manyconstructallowbothreflectiveandformativemeasurementiftheapproachcanbeexplainedbyanunderlyingtheory(Chin,1998).Inthisstudy,theauthorsconsideredperceived

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riskasahigh-orderreflectiveconstruct.ThisisbecausebasedontheapproachofFeathermanandPavlou(2003),riskperceptionscouldbemodeledasareflectivemeasurementconstruct.Secondly,reflectivemeasurementsareexpectedhighcorrelationamongfirstorderconstructe.g.,customerdutiescost,confiscationrisk,deliveryrisk,financialriskandprivacyrisk.Further,thefirstorderconstructscanbeinterpretedasacriterionforhighinternalconsistency(Christophersen&Konradt,2012).Therefore,alltheconstructsinthisstudyaremodeledasreflectivefactors.Further,theinter-associationsareconsideredtobetterunderstandtherepurchaseintentionofCBEC.

AsshowninTable2,alternativewebsitequalitydidnotsignificantlyinfluencetrustinprovider,nortrustinwebsite.However,theauthorsfoundthatalternativewebsitequalitycanmediateperceivedriskandthusindirectlyinfluencetrustinwebsite.Inaddition,theauthorsfoundthatperceivedriskdidnotsignificantlyinfluencetrustinprovider.Therefore,thepathcoefficientsofH4,H6,andH7werenotsignificant.Further,theauthorsfoundthatB-buyerrepurchaseintentionisdeterminedbytrustinprovider,trustinwebsiteandriskperceptions.Moreover,theauthorsfoundtrustinwebsitesignificantlyinfluencestrustinprovider.Last,theauthorsfoundtrustinwebsitewassignificantlyinfluencedbyperceivedrisk.Theauthorsthereforeconfirmedotherhypothesis.Nocontrolvariables

Table 1. Descriptive statistics of respondents’ characteristics

Demographics Category N (n=243) Percentage (%)

Gender

Male 186 76.5%

Female 54 22.2%

Missing 3 1.3%

Age

Under21 16 6.6%

21-30 56 23.0%

31-40 65 26.8%

41-50 51 21.0%

51-60 36 14.8%

Over60 17 7.0%

Missing 2 0.8%

Country

USA 90 37.0%

Canada 18 7.4%

UK 18 7.4%

Australia 10 4.1%

Brazil 9 3.7%

Italy 8 3.3%

Mexico 6 2.5%

NewZealand 5 2.1%

SouthAfrica 5 2.1%

Others 69 28.4%

Missing 5 2.0%

Thiscross-borderwebsitepurchaseexperience

Yes 215 88.5%

No 27 11.2%

Missing 1 0.4%

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weresignificantinthisstudy.Theresearchmodelexplained53.3percentofthevarianceinrepurchaseintentionofB-buyerstousethisCBECplatform.Inaddition,accordingtoHenseleretal.(2014),theauthorsappliedthestandardizedrootmeansquareresidual(SRMR)asanindextoevaluatetheoverallmodelfit.ThevalueofSRMRis0.054,whichisbelowthecriteriavalueof0.080,indicatingagoodmodelfit.TheresultsofthehypothesistestaredepictedinFigure2.

Post-hoc Analysis of Mediating EffectsThemediatingeffectofperceivedriskonthepathbetweenalternativewebsitequalityandperceivedrisk,themediatingeffectoftrustinwebsiteonthelinkbetweenperceivedriskandtrustinproviderhavealsobeencarriedoutviaaSobeltest.TheSobeltestallowsustotestthemediatingeffectssuggestedbytheresearchmodel.Theauthorsfoundthatperceivedriskplaysafullmediationeffectonthepathbetweenalternativewebsitequalityandperceivedrisk(-2.075,p<0.05).Inaddition,supportfortrustinwebsiteasafullyexplanatoryvariablefortheeffectsofperceivedriskontrustinproviderisconfirmedbyasignificantSobelstatistic(-2.908,p<0.01).

Figure 2. PLS test of research model (dash line represents non-significant results)

Table 2. Summary of results (*p<0.05; ***p<0.001).

Hypothesis (path) Path coefficient t-Value Support

H1 0.247 2.546* Yes

H2 0.505 5.111*** Yes

H3 -0.110 2.328* Yes

H4 -0.012 0.190 No

H5 -0.194 2.103* Yes

H6 -0.041 0.648 No

H7 -0.037 0.398 No

H8 0.387 6.021*** Yes

H9 0.659 10.778*** Yes

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discussionInthisdayandage,CBECandglobaltradegohandinhand.WhileB-buyerscancontributemoremarginforthefirm,theyalsocontributemoreGMVinaCBECplatforms.TherearesomestudiesthatfocusonB-buyerbehaviorsindomesticonlineshopping,whichcanhelpscholarstogainmoreinsightinstuddinge-commerce.However,throughreviewingtheCBECliterature,therestillremainsalackofstudiestoinvestigateB-buyerbehaviorunderCBECcontext.Therefore,theauthorsapplytrust transfer theory,perceivedrisk,andalternativewebsitequality tostudyrepurchaseintentionfocusingonB-buyers.

Theauthorsfoundthatperceivedriskcannegativelyaffectthetrustinwebsite,whereasitcannotsignificantlyaffecttrustintheprovider.ThisisbecauseprovidersintheCBECwebsiteweregenerallySMEs, which were not influential in the website. As a result, consumer’s perception, trust, andbehaviorintentionweremorereliedonthewebsiteratherthantheprovider.Thiscouldalsoexplainwhytrustinwebsitecouldinfluencetrustinprovider,andwhythepathcoefficientbetweentrustinwebsiteandrepurchaseintentionwaslargerthanthatofthetrustinprovider.

Further,trustinprovider,trustinwebsiteandperceivedriskcanexplain53.3%variance.Thisisslightlyhigherthanthestudyof(Thatcheretal.,2013),whomfoundthattrustinmerchant,trustinwebsite,and trustpropensitycanexplain51.1%of thevariance for familiar shoppingbuyers,howeversuchfactorsonlyexplain34.1%variancefornewbuyers.InanCBECenvironment,thewholetransactionprocessessuchassurfing,querying,ordering,andpaymentareachievedviawebsite.Atrustedwebsiteismorelikelytoformconsumer’spositivepurchasebehaviors,whileinavirtualenvironment,sellersandbuyersonlycaninteractivethroughwebsite,astheynormallydonotknoweachotherwell.Indeed,onlybasedontheperceptionsofseller’swebsitecantheconsumersmakeaninitialdecisionfortheirpurchase.Therefore,trustinwebsitebecomesmoreimportantthantrustinproviderinthecontextofCBEC.

Theauthorsfoundthattrustinwebsitecansignificantlyinfluencetrustinprovider(β=0.659).Thisfindingcananswerthesecondquestionofthisstudy.Theeffectbetweenthelinkishigherthanthestudyof(Vakeeletal.,2017),whoonlyfoundtheeffectas0.364inconsumerpostpurchasestageinadomesticsetting.Thisisconstantwithtrusttransfertheory,whichstatesthattrustmaytransferfromdifferentkindsofsources.Trusttransfertheoryhasbeenstudiedunderthecontextofe-commerce,mobilecommerce,aswellassocialcommerce.Asanextension,thisstudyfoundthattrustinwebsitecanalsoinfluencetrustinproviderinCBECenvironment.

Interestingly,alternativewebsitequalitydidnotaffectthetrustineithertheproviderorthewebsite.WhenaconsumerperceivesanalternativeCBECwebsiteasahighquality,she/heismorelikelytoformpositiveperceptionsforalternatives.Consumersaremoreeasilytocomparebothwebsites.Sincetheconsumersconsiderthealternativesaremuchbetter,theriskperceptionsofthiswebsitemayarise.Obviously,alternativewebsitequalitycould indirectly influencerepurchase intention.Thus,fromtheresultofthisstudytheauthorscoulddeducethatalternativewebsitequalityaffectsrepurchaseintentionthroughmechanismsotherthantrust.Inthecurrentstudy,theauthorsconfirmedthatperceivedriskmediatedthelinkbetweenalternativewebsitequalityandbehaviorintention.Theauthorsbelievetherearealsoothermediatorswhichmayplayanimportantrolebetweenalternativewebsitequalityandtrust.Thiseasilyisonefurtherresearchtopic.

Thusfar,weidentifiedthedimensionsofriskinCBECenvironmenttonamelyincludecustomerdutiescostrisk,confiscationrisk,deliveryrisk,financialriskandprivacyrisk.Multi-dimensionalriskisalsoseenrelevant,andgiventhecomplextransactionnatureofCBEC,theauthorsfoundcustomerdutiescostriskandconfiscationriskareimportantaswell.

THEoRETICAL CoNTRIBUTIoNS

Theoretically,theauthorshavefirstclassifiedtheperceivedrisksascustomerdutiescost,confiscationrisk,deliverrisk,financialrisk,andprivacyrisk.Thisisdifferentwithpriorstudies,whichclassified

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thedimensionsofriskperceptionsasfinancialrisk,performancerisk,deliveryrisk,psychologicalrisk,socialrisk,timerisk,andprivacyrisk(Featherman&Pavlou,2003).ThiscanhelpresearcherstobetterunderstandthedimensionsofriskperceptioninCBECcontext.Second,theauthorsfoundthatthetrustinwebsitecanpositivelyaffectthetrustinprovider,aswellasaffecttherepurchaseintention.Thishelps to solidify the trust transfer theory inCBECcontext.Third,we found thatalternativewebsitequalityindirectlyinfluencesconsumertrust.Priorstudieshaveconfirmedthedirecteffectofwebsitequalityontrust.Meanwhile,alternativewebsitequalityisnotafunctionofbothtrustinproviderandtrustinwebsiteinthecontextofCBEC.

PRACTICAL CoNTRIBUTIoNS

Practically speaking, this study first contributed tounderstandingperceived risk forB-buyers inCBECenvironments.ItcanhelpanyCBECwebsitetoattractmoreconsumersbydevelopingtheirownsecurityguaranteeandcompensationmechanismduetologisticissues,sincethesearethemostinfluentialperceivedrisks.Forexample,abuyersuggeststhat“thesellersshouldtrytheirbesttoreducetheriskofcustomduties,toimprovebuyer’spurchaseintentiononaCBECplatform”.Anotherbuyerleavedacomment,“...oftenoverpriceddutycharges”.Onebuyercomplainedabout“acustomdutyof$345onmyrecentorder”.Anothernotablecommentbyabuyersuggestedto“reduceshippingcostabitbecausecustomsdutythissideiscostly”.TheCBECplatformmaysatisfytheconsumersbyindicatingtheinformationaboutdutycosts.Giventhatallthetransactionsareinternational,studyingthetermofcustomdutycostisimportanttohelpCBECplatformsandlogisticservicefirmsbuildtheirappropriateservicestrategy.Confiscationriskhasalsobeenaconcernforbuyers.Forinstance,abuyermentioned,“SellersshouldannouncethebuyeriftheitemislostorholdbyChinacustomassoonastheyknowaboutit.”

Secondly, increasing trust in website can promote significant repurchase intention, therebyincreasingthequalityofwebsite.Thus,increasingwebsitetrustisimperative.ThiscanguideCBECfirmstobuildanappropriatemarketingstrategy.Forexample,bymitigatingriskperceptions,CBECfirmsmaystronglyimproveconsumertrustandasaresult,improveB-buyers’repurchasebehavior.Thedegreeoftrustinprovidercanalsodriveconsumers’behavior.Sellersshouldprovideagoodproductdescriptionintheironlineshop.

InCBECcontext,productswithdescriptionrelatedissuesarefrequentlyreported.Forexample,abuyerposted,“theproductdescriptionsareoftenpoorlywritten.WhenIcomeacrossaproductdescriptionwithpoorgrammar,typos,etc.Itendtoskipoveritbecauseitmakesmeafraidthattheproductmaybeflawedaswell”.Inaddition,anotherbuyercomplainedofreceivingproductsthatdidnotmeetexpectations,onmultipleoccasions.Thisbuyerfollowedthecomplaintwiththesuggestionthat“sellersshouldensurethattheirdescriptionisaccurate.”CBECsellersshouldtranslateappropriatelanguagetoovercomethelanguagebarriers.Thiscanhelpbuyerstobetterunderstandtheproducts,andthereforehelpthebuyersformpositiverepurchasebehaviors.CBECplatformsshouldbuildrulestoregulateseller’sbehavior,leadsellerprovidinghighqualityproducts,andthereforegainmoretrustformbuyers.Forinstance,theplatformcansetupmoreparameterswhenthesellerisuploadingaproduct.Ifandonlyiftheproductmeetsitscriterion,itmaybepublishedonline.

Last,theauthorsfoundriskperceptionsarenegativelyassociatedwithrepurchaseintentions.Thefirmsshoulddisclosethedutycost,deliveronlytheproductsunderregulations,delivertheproductsinatimelymanner,anddonotdiscloseconsumer’sprivateinformationtoanythirdparties.Thiswillpotentiallydecreasethebuyers’riskperceptions,andthereforeleadmoresales.

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LIMITATIoNS ANd FUTURE RESEARCH

Thisstudyhassomelimitations.First,theauthorschoseasingleCBECplatformtocollectthesample,whichmaypotentiallythreatgeneralizability.FutureresearchmaycollectdatafromseveralCBECplatforms.Second,thedatawascross-sectional,andtherefore,causalinferencescouldonlybemadewithreferencetotheory.FuturestudiesmayadoptlongitudinaldesignsandconsiderthetemporalchangesinhumanbeliefstowardCBECcontext.Finally,unexploredfactorsmaybealsoimportantforCBEC;thisisanotherfurtherresearchpoint.

ACKNoWLEdGMENT

We would like to thank the editor and the anonymous reviewers and Dr. Jason Cohen for theircomments,whichhavegreatlyimprovedourpaper.ThisstudysupportedbytheFundamentalResearchFundsfortheCentralUniversitiesofNo.20103176477[BX180604].

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ENdNoTES

1 DuetotheindustrialrevolutionandthedataonChina’smanufacturingvaluesadded,Chinacanproduceahugequantityofproducts,thisleadsahugeamountofmerchandiseexports.Theauthorsthereforecallita“worldfactory.”

2 TheBeltandRoadInitiativeprojectisadevelopmentstrategyadoptedbytheChinesegovernment.The‘belt’referstotheoverlandinterconnectinginfrastructurecorridors.The‘road’referstothesearoutecorridors.TheinitiativefocusesonconnectivityandcooperationbetweenEurasiancountriesandChina(Wikipedia).

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APPENdIX A: CRoSS-LoAdING

Table 3. Cross-loading

AWQ CD CR DR FR PC RPI TV TW

AWQ1 0.687 0.122 0.132 0.121 0.144 0.142 -0.066 -0.006 0.026

AWQ2 0.896 0.273 0.232 0.289 0.255 0.283 -0.287 -0.145 -0.187

AWQ3 0.842 0.310 0.282 0.368 0.311 0.338 -0.171 -0.075 -0.084

AWQ4 0.854 0.249 0.230 0.246 0.228 0.230 -0.175 -0.010 -0.018

AWQ5 0.859 0.228 0.196 0.224 0.241 0.268 -0.266 -0.200 -0.120

CD1 0.271 0.973 0.590 0.480 0.540 0.343 -0.159 -0.098 -0.163

CD2 0.301 0.933 0.569 0.457 0.532 0.367 -0.102 -0.091 -0.099

CR1 0.180 0.580 0.895 0.529 0.468 0.427 -0.044 -0.069 -0.026

CR2 0.200 0.568 0.904 0.554 0.486 0.424 -0.037 -0.047 -0.010

CR3 0.253 0.510 0.913 0.534 0.453 0.451 -0.071 -0.046 -0.032

CR4 0.268 0.592 0.966 0.589 0.489 0.472 -0.177 -0.152 -0.132

DR1 0.259 0.409 0.516 0.857 0.458 0.443 -0.273 -0.125 -0.239

DR2 0.280 0.364 0.495 0.890 0.395 0.476 -0.276 -0.168 -0.222

DR3 0.256 0.413 0.455 0.877 0.453 0.408 -0.332 -0.232 -0.281

DR4 0.265 0.450 0.583 0.792 0.535 0.469 -0.165 -0.073 -0.154

DR5 0.257 0.468 0.549 0.780 0.475 0.516 -0.239 -0.210 -0.121

FR1 0.282 0.526 0.478 0.515 0.995 0.407 -0.166 -0.118 -0.159

FR2 0.255 0.620 0.562 0.530 0.716 0.408 -0.024 0.007 -0.120

PC1 0.323 0.377 0.481 0.506 0.440 0.931 -0.199 -0.117 -0.144

PC2 0.281 0.311 0.443 0.478 0.381 0.952 -0.159 -0.075 -0.121

PC3 0.290 0.329 0.438 0.484 0.375 0.955 -0.172 -0.105 -0.140

PC4 0.291 0.351 0.425 0.484 0.399 0.812 -0.069 -0.061 -0.060

PC5 0.227 0.301 0.398 0.520 0.313 0.823 -0.107 -0.039 -0.062

RPI1 -0.235 -0.130 -0.095 -0.276 -0.137 -0.194 0.912 0.526 0.622

RPI2 -0.250 -0.139 -0.151 -0.368 -0.138 -0.184 0.876 0.545 0.618

RPI3 -0.230 -0.177 -0.174 -0.331 -0.181 -0.169 0.938 0.574 0.620

RPI4 -0.243 -0.123 -0.107 -0.259 -0.134 -0.133 0.929 0.588 0.646

RPI5 -0.271 -0.131 -0.107 -0.250 -0.139 -0.134 0.942 0.583 0.628

RPI6 -0.228 -0.093 -0.077 -0.271 -0.127 -0.138 0.932 0.550 0.672

TV1 -0.147 -0.074 -0.062 -0.197 -0.128 -0.069 0.550 0.886 0.616

TV2 -0.121 -0.140 -0.131 -0.223 -0.145 -0.079 0.536 0.909 0.630

TV3 -0.105 -0.045 -0.063 -0.192 -0.072 -0.111 0.564 0.928 0.578

TV4 -0.106 -0.148 -0.157 -0.194 -0.140 -0.128 0.550 0.903 0.605

TV5 -0.136 -0.101 -0.079 -0.174 -0.076 -0.060 0.563 0.915 0.583

TV6 -0.139 -0.080 -0.116 -0.182 -0.103 -0.112 0.605 0.961 0.632

TV7 -0.131 -0.093 -0.127 -0.165 -0.097 -0.083 0.590 0.954 0.633

TV8 -0.095 -0.055 -0.103 -0.165 -0.023 -0.060 0.528 0.917 0.628

TW1 -0.103 -0.084 -0.064 -0.170 -0.091 -0.086 0.621 0.680 0.917

TW2 -0.083 -0.114 -0.073 -0.212 -0.128 -0.098 0.609 0.633 0.931

TW3 -0.056 -0.079 -0.035 -0.228 -0.115 -0.051 0.592 0.584 0.897

TW4 -0.141 -0.198 -0.107 -0.288 -0.202 -0.211 0.667 0.605 0.925

TW5 -0.141 -0.180 -0.119 -0.264 -0.180 -0.126 0.664 0.586 0.930

TW6 -0.150 -0.135 -0.083 -0.229 -0.168 -0.129 0.662 0.604 0.949

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APPENdIX B: MEASUREMENT ITEMS

Alternativewebsitequality(Lietal.,2006)Analternativewebsiteisappealing.Analternativewebsiteisbetterthanthiswebsite.Tomyknowledge,anotherwebsiteisclosedtoideal.Analternativewebsiteisattractivetome.Myneedscouldeasilybefulfilledbyanalternativewebsite.Customsdutiescost[self-development]IfIboughtaproductfrom___,IworrythatIwillhavetopaymuchmoneyinadditionalimportduties(customstariffs)inmycountry.IfIboughtaproductfrom___,IamuncertainabouthowmuchIwillhavetopayinadditionalimportduties(customstariffs)inmycountry.Confiscationrisk[self-development]IfIboughtaproductfrom___,Iworrythattheproductwouldbeinterceptedbyauthoritiesinmycountrybeforetheyreachme.IfIboughtaproductfrom___,Iworrythattheproductwouldbeconfiscatedbyauthoritiesinmycountrywithoutcompensation.Theriskthatproductspurchasedfrom___willbeconfiscatedishigh.IfIboughtaproductfrom___,Iworrythattheproductwillnotclearcustoms.Deliveryrisk(Hong&Cha,2013)IfIboughtaproductfrom___,Iwouldbeconcernedastowhethertheproductwouldbedeliveredtothewrongaddress.IfIboughtaproductfrom___,Iwouldbeconcernedastowhethertheproductwouldbelostduringdelivery.IfIboughtaproductfrom___,Iwouldbeconcernedastowhetherawrongproductwouldbedelivered.IfIboughtaproductfrom___,Iworrythattheproductwillnotbedeliveredduetoaircraftrefusal(e.g.theproducthasmagnetism)[self-development]IfIboughtaproductfrom___,Iworrythattheproductwouldbedamagedaftershipping.[self-development]Financialrisk[self-development]IfIboughtaproductfrom___,Imaysuffermonetarylossduetofluctuationsinexchangerates.IfIboughtaproductfrom___,IworrythatIwillfaceextracoststoshiptomycity.Privacyrisk(Kimetal.,2009)Iamconcernedthat___iscollectingtoomuchpersonalinformationfromme.Iamconcernedthat___willusemypersonalinformationforotherpurposeswithoutmyauthorization.Iamconcernedthat___willsharemypersonalinformationwithotherswithoutmypermission.Iamconcernedthatunauthorizedpersons(i.e.hackers)haveaccesstomypersonalinformation.Iamconcernedabouttheprivacyofmypersonalinformationduringatransaction.Trustinvendor(adaptedfromFangetal.,2014)Ibelievethatthevendoron___isconsistentinqualityandservice.Ibelievethatthevendoron___iskeenonfulfillingmyneedsandwants.Ibelievethatthevendoron___ishonest.Ibelievethatthevendoron___wantstobeknownasonethatkeepspromisesandcommitments.Ibelievethatthevendoron___hasmybestinterestsinmind.Ibelievethatthevendoron___istrustworthy.Ibelievethatthevendoron___hashighintegrity.Ibelievethatthevendoron___isdependable.Trustinwebsite(Thatcheretal.,2013)Ithink___isveryreliable.

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Tome,___isdependable.___performsinapredictableway.Ithink___hasthefunctionalityIneed.___hastheabilitytodowhatIwantittodo.Overall,___hasthecapabilitiesIneed.Repeatpurchaseintention(Chiuetal.,2014;Gefen,2002)Iplantocontinueusing___forcross-borderpurchase.Iconsider___tobemyfirstchoiceforcross-bordertransactionsinthefuture.ItislikelythatIwillcontinuepurchasingproductsfrom___inthefuture.Iwouldrecommend___toothers.Iwouldencourageotherstouse___.Iaminclinedtodomorebusinesswith___.

APPENdIX C: CoMMoN METHod BIAS

Harman’sone-factortestisoneofthewidelyemployedtechniquestotestcommonmethodbias.Theauthorsfirstcheckedforcommonmethodbiasbyperformingthistest(Podsakoff&Organ,2006).Anexploratoryfactoranalysisofallthescaleitemsrevealedfactorsexplaining77.8%ofthevarianceinthisstudy’sconstructs,withthefirstfactorexplaining29.7%,andthelastexplaining3.0%ofthetotalvariance.Theseresultssuggestthatnosinglefactorexplainedamajorityofthevariance,thussupportingtheideathatcommonmethodbiaswasnotathreattothisstudy.Secondly,theauthorsfollowedtherecommendationsproposedbyRönkköandYlitalo(2011)usingthePLSmarkervariableapproach.Theauthorscalculatedthemeancorrelationbetweenthemarkeritemsandthestudyitemsandfoundthatthemeancorrelationis0.06,whichisslightlyhigherthantherecommendedvalueof0.05.Then,amethodfactorwasalsocreatedusingthemarkerindicatorsasanexogenousvariablepredictingendogenousconstructinthemodel.Theauthorscomparedthemethodfactormodelwiththebaselinemodelandfoundthatthesignificantpathsinthebaselinemodelremainsignificantinthemethodfactormodel.Hence,thePLSmarkervariableapproachrevealsthatcommonmethodbiasmightnotbeathreatinthedataofthisstudy.Inaddition,theauthorsfoundthehighestcorrelationis0.689,whichislowerthanthethresholdvalueof0.9(Pavlou,Liang,&Xue,2007).Insum,alltheseevaluationsindicatethattheCMVisnotathreatofthisstudy.

APPENdIX d: RELIABILITy ANd VALIdITy

Theauthorsappropriatelytestedforthereliabilityandvalidityofthemeasurementmodel.Theresults,includingmean,standarddeviation(SD),averagevarianceextracted(AVE),compositereliability(CR),andCronbach’salphavalue,areshowninTable4.Allitemswereloadedintheirexpectedconstructswiththevalueabove0.7withtheexceptionofAWQ1(0.687)(seeAppendixA).TheAVEvalueforeachconstructwasabovetherecommendedthresholdvalueof0.5.Allconstructreliabilitiesfit between 0.855–0.978, exceeding the criterion of 0.7. Therefore, composite reliability of themeasurementmodelwasconfirmed.TheCronbach’salphavaluewastestedtoverifythereliability.AllCronbach’salphavalueswereabovetherecommendedvalueof0.7.Usingthesebenchmarks,themeasurementmodelissuitableforsubsequentanalysis.Table5showsthecorrelationsbetweeneachconstruct.Toprovediscriminantvalidityofthemodel,thesquarerootofAVEwascomparedwithintercorrelationsofeachconstruct.AllthesquarerootsofAVEexceededtherespectivecorrelation;discriminantvaliditywasconfirmed.

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Table 4. Results of reliability, validity and means of the construct

Variable Items Mean S.D. AVE CR Alpha value

Alternativewebsitequality(AWQ)

AWQ1

3.051 0.853 0.690 0.917 0.893

AWQ2

AWQ3

AWQ4

AWQ5

Customerdutiescost(CD)CD1

2.938 1.345 0.908 0.952 0.904CD2

Confiscationrisk(CR)

CR1

2.694 1.301 0.846 0.956 0.951CR2

CR3

CR4

Deliveryrisk(DR)

DR1

2.626 1.094 0.706 0.923 0.897

DR2

DR3

DR4

DR5

Financialrisk(FR)FR4

2.656 1.203 0.751 0.855 0.781FR5

Privacyrisk(PC)

PC1

2.711 1.165 0.804 0.953 0.941

PC2

PC3

PC4

PC5

Repurchaseintention(RPI)

RPI1

3.957 1.060 0.850 0.971 0.964

RPI2

RPI3

RPI4

RPI5

RPI6

Trustinprovider(TP)

TV1

3.500 1.056 0.850 0.978 0.975

TV2

TV3

TV4

TV5

TV6

TV7

TV8

Trustinwebsite(TW)

TW1

3.770 0.989 0.855 0.973 0.966

TW2

TW3

TW4

TW5

TW6

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Jian Mou is a Lecturer of the School of Economics and Management, Xidian University. His research interests include e-commerce, human computer interaction, trust and risk issues in e-service and the dynamic nature in systems use. His research has been published in Computers in Human Behavior, Electronic Commerce Research, Information Development, Behaviour and Information Technology, IT & People, International Journal of Human-Computer Interaction and Information Technology and Tourism, as well as in the proceedings such as ICIS, ECIS and PACIS.

Yi Cui is a lecturer of School of Economics and Management, Communication University of China. His research focuses on electronic commerce, organizational culture and technology adoption.

Kerry Kurcz earned a Bachelor of Science in Information and Decision Science from the University of Illinois at Chicago in 2018. Shortly after graduation, she started working for Chicago-based insurance company CNA as a data engineer and application developer.

Table 5. Construct correlations (Diagonal bold values are square root of AVE)

AWQ CD CR DR FR PC RPI TV TW

AWQ 0.831

CD 0.295 0.953

CR 0.262 0.608 0.920

DR 0.311 0.492 0.603 0.840

FR 0.291 0.561 0.510 0.539 0.867

PC 0.315 0.368 0.486 0.541 0.425 0.897

RPI -0.263 -0.143 -0.128 -0.317 -0.155 -0.172 0.922

TV -0.133 -0.099 -0.113 -0.202 -0.106 -0.096 0.609 0.922

TW -0.123 -0.144 -0.088 -0.252 -0.161 -0.128 0.689 0.665 0.925