Customers’ Perceived Risk and Trust in Using Mobile Money Services—an Empirical Study of GhanaIbn Kailan Abdul-Hamid, University of Professional Studies, Accra, Ghana
Aijaz A. Shaikh, University of Jyväskylä, Jyväskylä, Finland
Henry Boateng, University of Technology Sydney, Ultimo, Australia
Robert E. Hinson, University of Ghana and University of the Free State Business School, Accra, Ghana
Therestofthepaperisorganizedasfollows.Afterareviewofthetheoreticalbackgroundandexistingliterature,theresearchmodelandstudyhypothesesareelaborated,followedbyanaccountof samplingdesign,measures, descriptive statistics,modelmeasurement and structural equationmodelling.Thepaperconcludeswithimplications,limitationsanddirectionsforfutureresearch.
THEoRETICAL BACKGRoUNd ANd LITERATURE REVIEw
MM ServicesMMinvolvestheuseofmobilephonestoaccessfinancialservicesremotelythathavetypicallybeenprovidedoveracounter(Mothobi&Grzybowski,2017).MMserviceslargelyincludetransfersandpayments.MMisalsoreferredtoascellphonebanking,over-the-counterbanking,agentbankingandbranchlessbanking(Dinizetal.,2012).
Trust and Risk in digital ServicesItiswidelybelieved(e.g.,Safeenaetal.,2018)that‘trust’and‘risk’occupysignificantpositionsin e-business services (including e-commerce). This is perhaps because of the uncertainty andriskinvolvedinonlinetransactionsconductedremotelyusingportabledevices,whicharepronetohacking,lossandmisuse(Shaikhetal.,2018).Trustreflectsawillingnesstobevulnerablebasedonthepositiveexpectationofanotherparty’sfuturebehaviour(Kimetal.,2018).WithregardtoMMservicesinadevelopingcountry,trustreferstotheconsumer’sbeliefthatMMserviceswillbecost-andtime-effectiveandthatserviceproviderswillsafeguardtheirclients’moneyandinformation.Asathird-partyprovider,suchasanagent,normallydeliversMMservices,theroleoftrustinconsumerintenttouseMMservicesrelatesdirectlytothecustomer’strustinthatagent.
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Trust iscrucial ineconomic transactionsbecause itmayreduce the riskof fallingvictimtoopportunisticbehaviour,andlackoftrustisamongthemainreasonsconsumersdecidenottoengagewithMMandothersimilarservices(Chauhan,2015).Scholars(e.g.,Balletal.,2016;Gefenetal.,2003)havesuggestedthattrustisamultidimensionalconcept.Trustisassociatedwithperceivedrisk,anditcanbearguedthatlackoftrustincreasesperceivedrisk(Kim&Peterson,2017).Inthemobilebankingcontext,riskorperceivedriskisdefinedastheexposuretodangerthatarisesfromthepurchaseofabankingproductorservice,suchasm-banking(Shaikhetal.,2018).Inthisstudy,wehavedefinedperceivedriskastheamountofriskanunderbankedconsumerseeswhenusingMMservicesinadevelopingcountry.Asriskcanbedifficulttomeasureobjectively,theliteraturefocusesonusers’riskperceptions.Whentheperceivedriskinanytransactionishigh,consumersmaydecidenottoengageinthattransactionormayterminatetheongoingexchangerelationship(Al-Gahtani,2011).Inthepresentcontext,then,itcanbearguedthatperceivedriskmayincreaseconsumers’unwillingnesstouseMMservices.
Technology Adoption and Usage ModelsManystudieshavedeployedtheoriestoexplaintechnologyutilization;prominentamongthesearetheunifiedtheoryofacceptanceanduseoftechnology(UTAUT)(Venkateshetal.,2003),diffusionofinnovationtheory(Rogers,1995),thetheoryofplannedbehaviour(Ajzen,1991),thetechnologyacceptancemodel(TAM)(Davisetal.,1989)andthetheoryofreasonedaction(Fishbein&Ajzen,1975).Applicationofthesetheorieshasyieldedvaryingresults(Venkateshetal.,2003).Forexample,Rogers’sdiffusionofinnovationtheoryidentifiesfiveessentialfeaturesthatdriveuseradoptionofaninnovation:complexity,relativeadvantage;trialability,observabilityandcompatibility(Rogers,1995). The theories of planned behaviour and reasoned action (Ajzen, 1991) have shown thattechnologyadoptioncanbedeterminedbyperceivedbehaviouralcontrol,aswellasbysubjectivenormsandattitudes.
Davisetal.(1989)developedtheTAMtoexplainuseradoption.Davisetal.(1989)notedthattheperceivedusefulnessandperceivedeaseofuseofagiventechnologydetermineuserattitudestowardit,andanumberofotherstudieshaveprovidedempiricalsupportforthisview.Forexample,TaylorandTodd(1995)reportedthatusersexhibitpositiveattitudeswhentheyperceivethatatechnologyiseasytouse.FollowingtheTAMmodel,researchershaveidentifiedmanyotherfactorsthatdriveuseradoptionoftechnology.Venkateshetal.(2003)attemptedtointegrateallofthesefactorsintheir UTAUT framework, which integrates performance expectancy and effort expectancy withperceivedusefulnessandeaseofuse.Thereisevidencethatthismodelisrobusttotheextentthatithasbeenfoundtoexplain70%ofthevarianceintechnologyusageintentions(Wuetal.,2008).However,thesedominantmodelsrarelyaddressissuesoftrustandriskthatareofconcerntomanyusersoftechnology-basedservices,especiallyinthefinancialservicessector(Yangetal.,2015).Thepresentstudyseekstobridgethatgapbyexaminingcustomerintenttousemobileservicesintermsofcustomertrustandperceivedrisk.
Research Model and Hypothesis developmentThe various dimensions of risk seem likely to differ in their influence, contributing to varyingdegreestotheeffectofoverallperceivedriskonintenttouseMMservices.Asconceptualizedhere,perceivedriskisunderstoodtoinvolveconcernsabouteconomic,functional,security,privacy,time,service,psychologicalandsocialrisk.ApositiveassociationishypothesizedtoexistbetweentrustandconsumerintenttouseMM,twocomponentsoftrust:economy-basedandserviceprovider-based.Asperceivedriskislikelytoreducetrustinmobile-basedpayments(Yangetal.,2015),itisfurtherhypothesizedthatperceivedriskisnegativelyassociatedwithbotheconomy-basedtrustandserviceprovider-basedtrust.Figure1depictstheresearchmodeldeveloped.
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TRUST, PERCEIVEd RISK ANd INTENT To USE MM SERVICES
Trustandperceivedriskareprevalentconcepts that influencebehavioural intentions touseMMservices.Themanagementofmoney(physicalorelectronic)isexpectedtoproducesomebenefitstoitsowners.Accordingly,theuseofMMservicesisexpectedtodeliverbenefitstoaswellascreatefearamonguserswhoarelargelyeitherunderbankedorunbanked.Forexample,auser’sperceptionthattheuseofaMMservicemayexposehimorhertothelossofmoneycouldinfluencetheadoptionofMMservices.MMusersmaynotbeabletopredicttheoutcomeofsuchdecisionsaccurately,andthoseoutcomesmayproveundesirable(Yangetal.,2015).Moreover,becauseofthenatureofMMtransactions,theyusuallylacktheassuranceprovidedintraditionalsettings,suchasintheformofreceipts,makingitmoredifficultforconsumerstoseekcompensationwhentransactionerrorsoccur.Basedonthesearguments,weproposethefollowinghypothesis:
Perceivedprivacyreferstoaconsumer’spreferencetocontrolwhoispresentduringamarkettransactionandthediffusionofinformationassociatedwithsuchtransactionstopersonswhowerenotpresent(Ortizetal.,2018).MMcustomersmaybeconcernedthatathirdpartycouldstealtheirinformation (personal or transactional) during MM transactions. Perceived privacy has becomeespeciallycriticalsincecustomerscannowlinktheirMMaccountstotheirbankaccounts.Theseformsofriskareknowntohavenegativelyimpactedelectronicbankingservices(SumChau&Ngai,2010)andarethereforelikelytohaveanegativeeffectonintenttouseMMservices.SomestudieshavepredictedthatthegreatestchallengeforMMserviceswillbewinningcustomers’trustinrelationtoprivacyissues(Aboobucker,&Bao,2018).Basedontheabove,weproposethefollowinghypothesis:
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OnebenefitofMMisthatcompletingatransactionrequireslittletime(Omwansaetal.,2013).However,manypotentialusersofMMservicesmayalsoperceivethisbenefitasarisk.AccordingtoYangetal.(2015),timerisk—thatis,inconvenienceandlossoftimeduetodelaysinreceivingapaymentortransferringmoney—isnegativelyassociatedwithmobilepaymenttransactions.Thisform of risk may be a consequence of functional risk. Network failure is very common amongtelecommunicationsfirmsinGhana,whichcancauseunduedelaysinsendingandreceivingmoney.Consequently,consumerswhoareverytime-orientedandconcernedabouttheriskof‘wastingtime’arelesslikelytouseMMservices(Featherman&Pavlou,2003).Thus,weproposethefollowinghypothesis:
Psychologicalriskreferstothechancethatauserwillexperiencenegativeemotionslikefear,frustration, pressure or anxiety from the use of MM services (Ortiz et al., 2018). The potentialexperienceoffearandanxietyinsendingorreceivingmoneymayaffectusers’decisionstouseMMservices.
Trustinvolvesapositiveexpectationregardingservicesinriskysituations(Das&Teng,2012).Aneconomy-basedtrustisaformoftrustbasedoneconomicbenefits(Chai&Kim,2010).Theperceptions of MM users about the time- and cost-saving benefits and economical use of MMservicesrelatetotheireconomy-basedtrustinsuchservices(Chai&Kim,2010).WhencustomersbecomeconsciousofMMservicechargesorcoststhatexceedtheirgainfromtheMMservicetheyturntolosetrustintheservice.Consequently,perceivedriskofusingMMservicescouldaffecttheeconomy-basedtrust.Weproposethefollowinghypothesis:
H2:Perceivedriskinfluenceseconomy-basedtrust.
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TrustplaysacentralroleinMMutilization(Tobbin&Kuwornu,2011).Forpresentpurposes,trust is understood to relate to both economic and service-provider factors, essential aspects ofcustomerdecision-makinginanelectronicenvironment(Chai&Kim,2010).Assuch,trustaffectstherelationshipbetweenriskandMMserviceuseintent.Sincetrustisrelatedtopositivecustomerattitude(Song&Zahedi,2002),itislikelytofavourablyinfluenceMMtransactionintent;conversely,lackoftrustislikelytoadverselyaffectusageofMMservices.AccordingtoGefenetal.(2003),customersmakerationalassessments inelectronicenvironments toensure that theyobtainvaluefortheirmoney.Thereisalsoevidencethatcustomersdonotwanttowastetimeintheirbusinesstransactionsandthereforefavourelectroniccommerce,whichreducestransactiontime(Kuismaetal.,2007).Astudyby,ChaiandKim(2010)showsthateconomy-basedtrustinfluencesconsumerbehaviour,consequently,wealsoarguethataconsumer’slevelofeconomictrustislikelytoaffectconsumerbehaviourinrelationshiptoMMservicesusage.Ascustomersprefertodealwithvendorstheycantrust(Pavlouetal.,2007),itseemslikelythattrustinMMserviceproviders(telecoms,banksandagents)willaffectcustomerintenttouseMMservices.Onthatbasis,weproposethefollowinghypotheses:
ResultsWeusedthepartialleastsquaresstructuralequationmodelling(PLS-SEM)approachtoassessourmeasurementmodelandthehypothesesof thisstudybyrunningSmartPLS3.0(Ringle,Wende,&Becker, 2015).PLS is appropriate for testinghierarchical latent variablemodels, hierarchicalcomponentmodelsorhigher-orderconstructs.Comparedtocovariance-basedstructuralequation
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modelling, PLS-SEM is designed to handle observable lower-order components (LOCs) andunobservablehigherordercomponents(HOCs)toreducemodelcomplexityandthismakesitmoretheoreticallyparsimonious(Lohmöller,1989).
Table 1. Demographic characteristics
Details Frequency Percent
Gender Male 364 54.2
Female 307 45.8
Educationallevel HND 31 4.6
Degree 481 71.7
Postgraduate 52 7.7
Other 107 15.9
Age 18-27years 560 83.5
28-37years 57 8.5
38-37years 27 4.0
48-57years 21 3.1
58yearsandabove 6 .9
Network MTN 327 48.7
AirtelTigo 202 30.1
Vodafone 142 21.1
ThefrequencyofUse(Month)
1-5times 501 74.7
6-10times 97 14.5
11-15times 39 5.8
16-20times 12 1.8
morethan20times 22 3.3
Religion Christian 630 93.9
Moslem 36 5.4
Region GreaterAccra 226 33.7
CentralRegion 83 12.4
EasternRegion 117 17.4
WesternRegion 23 3.4
VoltaRegion 87 13.0
AshantiRegion 79 11.8
Brong-AhafoRegion 19 2.8
NorthernRegion 15 2.2
UpperEastRegion 15 2.2
UpperWestRegion 7 1.0
Total 671 100.0
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Measurement Model AssessmentTheassessmentofthemeasurementmodelsisthefirststepinanySEMprocess,asitensuresthatstatements(unobservedvariables)areactuallymeasuredconstructs(observedvariables).Weassessedourmeasurementmodelusingthreemaincriteria:convergentvalidity,reliabilityanddiscriminantvalidity,followingthesuggestionofHairetal.(2014).
Test of the Hierarchical Factor StructureThepresentstudyviewsperceivedriskasasecond-orderfactor.PLSwas,therefore,suitableforthisanalysis;perceivedriskwastreatedasanHOCwithitsLOCseconomicrisk,functionalrisk,privacyrisk,psychologicalrisk,securityrisk,serviceriskandsocialrisk.Thefindingsshowthatthesecond-orderandfirst-orderfactorloadingsarehighandstatisticallysignificant.Economicrisk(γ=.676;p<.001),functionalrisk(γ=.642;p<.001),privacyrisk(γ=.737;p<.001),psychologicalrisk(γ=.620;p<.001),securityrisk(γ=.789;p<.001),servicerisk(γ=.601;p<.001)andsocialrisk(γ=.372;p<.001)exhibitedsignificantcoefficientsinsupportofH1a,H1b,H1c,H1d,H1e,H1f,H1gandH1h.Theseresultsprovidestrongsupportforthecustomerperceivedriskscaleasasecond-orderconstruct.
Structural Model AssessmentAftervalidatingthemeasurementmodel,weassessedourstructuralmodel,whichinvolvedtestingourhypothesis.Ofthefivehypotheses,one(1)wasnotsupported;therelationshipbetweenperceivedriskandeconomy-basedtrustwasnotsignificant(β=0.021;p=0.605).However,therelationshipbetweenperceivedriskandcustomerintent touseMMserviceswassignificant(β=0.065;p=0.016).Additionally, therewasa significant relationshipbetweenperceived riskand trust in theserviceprovider(β=0.159;p=0.000).Thestructuralpathsshowedasignificantrelationshipbetweeneconomy-basedtrustandcustomerintenttouseMMservices(β=0.441;p=0.000)andbetweentrustintheserviceproviderandcustomerintenttouseMMservices(β=0.266;p=0.000),asseeninTable4.Figure2showsthestructuralmodel.
Managerial and Theoretical ImplicationsFor practitioners, these findings confirm that MM service providers must assure customers thattheywillsafeguardtheirmoneyandanypersonalinformationthatthecustomersmakeavailable.AttractingmorecustomerswillalsorequireserviceproviderstoreassurecustomersthatMMservicesaretime-savingandcost-effective.Althoughfunctionalriskwasnotasignificantissue,itcannotbedismissedasirrelevant.MMserviceprovidersmustensurethattheirservicesarethefastestmeansofsendingmoneytoothers.ThefindingsalsoindicatethattheriskassociatedwithMMservicesshouldbestudiedfromacustomerperspective,focusingonspecifickindsofriskratherthanoverallrisk.ItfollowsthataddressingperceivedriskinMMserviceswillalsorequirespecificstrategiesfordealingwiththevariousdimensionsofrisk.
Figure 2. Structural model
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Limitations and directions for Future StudiesAll studies naturally confront some limitations. First, this study used only MM users withoutconsideringtheviewsofnon-users.Theviewsofnon-usersofMMservicesmayprovideadditionalinsights into the risk and trust issues in MM services. Future studies may also address certainmethodological(ordemographical)issues.Forinstance,therespondentsherecouldallreadandwrite,butasMMservicesareseenasawayofpromotingfinancialinclusion(seePWC,2016),futurestudiesshouldfocusontheruralpoorandtheuneducated.AnotherlimitationofthisstudyisthatitdidnotexplorehowtheperceivedriskassociatedwithMMservicesmightbereduced,andfuturestudiesshouldaddressthisissue.AsYangetal.(2015)noted,customers’trustevolves,soitisreasonabletolookforwaystoenhancecustomertrustinMMservicesovertime.WhencustomerstrustMMserviceprovidersorMMservice,thetrustmightinfluencetheircommitmentstotheMMserviceproviderorMMservice.Accordingly,MMserviceprovidersmayconsiderbuildingtrustoftheircustomers.
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Ibn Kailan is a PhD Candidate at the University of Ghana and a faculty at the University of Professional Studies, Accra. His research interested are in marketing, sustainability marketing, market orientation, mobile commerce, corporate social responsibility, and emerging market research.
Shaikh is a faculty at the Jyväskylä University School of Business and Economics.
Henry Boateng holds a PhD in Knowledge Management from the University of Technology, Sydney. His research experience covers knowledge management, branding, electronic business and commerce and internet application in marketing. Email: [email protected]
Robert E. Hinson is Professor in the University of Ghana Business School, Legon, Ghana and a Research Associate at the University of the Free State Business School in South Africa. Email contact: [email protected]
