User Acceptance of Technology

User Acceptance of Technology

Statistical Analysis of Training’s Impact on Local Government Employees’ Perceived

Usefulness and Perceived Ease-of-Use

Falco, E.; Stylianou, Constantinos ; Martinez, Gilberto ; Kleinhans, R.J.; Basso-Moro, Sara ; Neophytou, Haris DOI 10.4018/IJEGR.2020070105 Publication date 2020 Document Version Final published version Published in

International Journal of Electronic Government Research (IJEGR)

Citation (APA)

Falco, E., Stylianou, C., Martinez, G., Kleinhans, R. J., Basso-Moro, S., & Neophytou, H. (2020). User Acceptance of Technology: Statistical Analysis of Training’s Impact on Local Government Employees’ Perceived Usefulness and Perceived Ease-of-Use. International Journal of Electronic Government Research (IJEGR), 16(3), 85-104. https://doi.org/10.4018/IJEGR.2020070105

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DOI: 10.4018/IJEGR.2020070105

User Acceptance of Technology:

Statistical Analysis of Training’s Impact on

Local Government Employees’ Perceived

Usefulness and Perceived Ease-of-Use

Constantinos Stylianou, Interfusion Services, Cyprus Gilberto Martinez, Backslash, Spain

Reinout Kleinhans, Delft University of Technology, The Netherlands https://orcid.org/0000-0002-5714-2128

Sara Basso-Moro, Leiden University, The Netherlands Haris Neophytou, Interfusion Services, Cyprus

ABSTRACT ThisarticleinvestigateshowtrainingpublicofficialsfromtwomunicipalitiesinSpainandCyprus withnewtechnologiesaffectsthreedependentvariables:levelofunderstandingofthetechnological innovationbeingintroduced,itsperceivedusefulness,anditsperceivedease-of-use.Theteststo determinetheimpactoftrainingwerecarriedoutbymeansofaself-constructedquestionnaire withinarepeatedmeasureexperimentaldesign.Theresultsdemonstratethatthethreevariablesare indeedpositivelyaffectedbythetrainingsessionstousersfrombothmunicipalities.Consequently, trainingplaysavitalroleinencouraginggovernmentemployeesandadministratorstoaccept,adopt andutilizee-governmenttechnologies. KEywoRdS

Electronic Governance, Electronic Government, Perceived Ease-of-Ease, Perceived Usefulness, Smart Governance, Social Media, User Acceptance

INTRodUCTIoN Theincreasedadoptionofinformationandcommunicationtechnologies(ICTs)andsocialmedia platformsovertheyearshasservedtoimprovedifferentaspectsofgovernment(suchas,efficiency, performance,productivity,responsiveness,andinvolvement).Thisinturnhasledtothedevelopment ofvariousparadigms,including,electronicgovernment,government2.0,smartgovernment,smart cities,andsmartgovernance(Layne&Lee,2001;Moon,2002;Mele,2008;Khan&Park,2013; Albinoetal.,2015;Anthopoulosetal.,2016;Meijeretal.,2016;Scholl&Alawadhi,2016;Falcoet al.,2018;Gil-Garciaetal,2018;Viale-Pereiraetal.,2018;Lemberetal.,2019).

Theadoptionanddiffusionoftechnologicalinnovationsingovernmentorganizationshas beenstudiedextensively.Twoofthemostprominenttheoriesarethediffusionofinnovation theory(Rogers,1962;1995)andtheTechnologyAcceptanceModel(TAM;Davis,1989).Inthis model,Davishighlightsthatinnovationsareonlysuccessfulwhenthetechnologyisaccepted, adopted, and used in practice. The innovation literature suggests that in private, as well as publicorganizations,itistheusers’perceptionsofaninnovationthataffectadoptionrather thantheinnovationasdefinedbyexpertsorchangeagents(Rogers,1995).Asemphasizedby Davis(1989),Rogers(1995),KortelandandBekkers(2008),users’perceivedusefulnessand ease-of-useoftechnologywithinanorganizationarekeyelementsexplainingthesuccessful acceptanceofinnovations.Similarly,scholarshavealsounderlinedtheimportanceoftraining forthesuccessfuladoptionandacceptanceofICTsbyendusers(Leeetal.,1995;Nelson& Cheney,1987;Rajagopalanetal.,2007). However,despitetheincreasingimportanceofICTsinlocalgovernments,thenumberofstudies ontheiradoptionbygovernmentemployeesislimited(forexample,Roberts&Henderson,2000; Venkateshetal.,2003;Antónetal.,2014).Thesameappliestothelimitednumberofstudiesonthe impactoftrainingonperceivedusefulnessandease-of-use(Venkatesh&Davis,1996;Xia&Lee, 2000).Therefore,thisarticleseekstofillthisresearchgapbyinvestigatingtheimpactoftraining ontheperceivedusefulnessandperceivedease-of-useofaspecifictechnologicalinnovationina sampleofgovernmentemployees,andtriestoanswerthefollowingresearchquestion:whatisthe impactoftrainingongovernmentemployees’perceivedusefulnessandperceivedease-of-useofa socialmediaplatform? Theanswertothisresearchquestionwillbenefitgovernmentorganizationsthatwishtoadopt innovativeICTsbutneedtoovercomepotentialobstaclessuchasaresistancetochangeora fearofadditionalworkorjobloss.Iftrainingdoesindeedincreasetheperceivedusefulnessand perceivedease-of-useofaparticulartechnology,thenitcanbeusedasatooltogettheworkforce onboard.Overall,itwillgiveanindicationwhetheritisworthwhileinvestingintraininginorder toencourageitsusebyofficials.Thespecifictechnologicalinnovationunderstudyinvolvesa socialmedia(SM)platform,whichallowsforthecrawlingandsentimentanalysisofsocialmedia data(posts,comments,likes,shares)fromFacebookandTwitteraccounts.StartingfromDavis’ work(1989)onuseracceptanceofinformationtechnology,perceivedusefulness,andperceived easeofuse,thispapersetsoutthroughanexperimentaldesigntoanalysetheimpactthattraining onthisnewtechnologyadministeredtopublicofficialshasonthreedependentvariables:(i) levelofunderstandingofhowthetoolworks;(ii)perceivedusefulness;(iii)perceivedease-of-use.Theaimofthepaperistogetabetterunderstandingofthenatureandsizeoftheimpact oftrainingongovernmentemployees’perceivedusefulnessandperceivedease-of-useofthis specifictechnologicalinnovationandhighlightimplicationsforpracticeastotheimportanceof trainingtoincreasetechnologyacceptanceingovernmentsettings.Thelogicunderpinningthis studyisthatasignificantincreaseinperceivedusefulnessandperceivedease-of-usefollowing thetrainingwillpositivelyinfluenceusers’acceptanceoftechnologyasthesetwodeterminants, asshownbypreviousresearch(Davis,1989),correlatesignificantlywithuser’sacceptanceof informationtechnologyandusagebehaviour. Thearticleisorganizedasfollows:thenextsectionbrieflyexaminestheliteratureon theories and models of technology acceptance and diffusion, particularly by government employees,andformulatesthreehypothesesatthebasisofourstudy.Thesubsequentsection discussestheresearchdesign,datacollectionanddataanalysis.Thefollowingsectiondescribes theresultsoftheanalysisandhighlightsstatisticallysignificantpatterns.Thisisfollowed byadiscussionoftheresultsandthelimitationsofthisstudy.Thefinalsectionpresentsthe conclusionsofourresearchwork.

THEoRy ANd BACKGRoUNd: TECHNoLoGy AdoPTIoN By GoVERNMENT EMPLoyEES ANd USER ACCEPTANCE

TheintroductionandadoptionofICTsingovernmentorganizationshashadaprofoundinfluence onworkingroutinesofgovernmentemployeesandthewayworkisperformedsincethe1990s (Roberts&Henderson,2000).CentraltotheincreasedadoptionofICTsistheachievementofvarious objectivesforemployees(suchasincreasedefficiency,performance,productivity,servicedelivery, responsiveness)andimprovementofgovernmentstructures,processes,functionsandinfrastructures (Gil-Garciaetal.,2016;Melloulietal.,2014;Falco&Kleinhans,2018a;Viale-Pereiraetal.,2018). Adoptionoftechnologyingovernmentorganizationsbygovernmentemployeeshasbeenanalysed inpublicadministrationliteraturethroughthedevelopmentofmaturitymodels(Lehmkuhletal.,2013; Mergel&Bretschneider,2013;Khan,2015)andneededcapabilities(technologyreadinesslevels, integrationofnewtechnologiesandservicesacrossdepartments,politicalsupport).Lehmkuhletal. (2013)stresstheimportanceofdifferentkindsofuserswithingovernmentorganizationstofavour technologyadoptionbygovernmentemployees:innovators, early adopters, and the early majority whoareableinturntoinfluenceandencourageadoptionbylate majorityandtheremaining staff. Melitskietal.(2010)underlinetheimportanceoforganizationalcultureandemployees’perception oforganizationandtheirimpactonindividualwillingnesstoadopttechnology.KlievinkandJanssen (2009)emphasizecentralleadershipandobtainingpoliticalsupportasessentialtotechnologyadoption bygovernmentemployees. Ingeneral,thiswidespreaddiffusionofICTsintheworkplacehasbeenextensivelyanalysed ininformationsystemsandcognitivepsychologyliteraturethroughseveraltheoriesandmodelsat bothuserlevelandorganizationlevel.Withregardtotechnologies1_{,manymodelsandtheorieswere}

developedsincetheearly1970stoexamineuser acceptance of information technology,suchasthe TheoryofReasonedAction(TRA;Fishbein&Ajzen,1975),theTheoryofPlannedBehaviour(TPB; Ajzen,1998),theTechnologyAcceptanceModel(TAM;Davis,1989),andtheInnovationDiffusion Theory(IDT;Moore&Benbasat,1991).ExtensionsofthesearetheUnifiedTheoryofAcceptance andUseofTechnology(UTAUT;Venkateshetal.,2003)and,morerecently,theGeneralExtended TechnologyAcceptanceModelforE-Learning(GETAMEL;Abdullah&Ward,2016).Discussion andreviewofalltheoriesandmodelsareoutsidethescopeofthisarticle.However,Venkateshet al.(2003)provideaninsightfulreviewofeightmodelsoftechnologyacceptance.Greenlhalghetal. (2004)provideasystematicreviewofdiffusionofinnovationstudies,whileMarangunić&Granić (2015)provideamorerecentanddetailedliteraturereviewofTAM-relatedstudiesdividingthem intothreecategories(TAMliteraturereviews,developmentandextensionsofTAM,modification andapplicationofTAM).Adoptionoftechnologicalinnovationshasalsobeenanalysedinthe scientificliteraturefromanorganizationalandpublicadministrationstudiesperspective,forexample, inthee-governmentmaturitymodelsandmodelsfortheadoptionofsocialmediaingovernment organizations(Lee&Kwak,2012;Mergel&Bretschneider,2013;Khan,2015). Oneofthemoreacademicallysuccessfultheories,thoughnotfreefromcriticism(Chuttur,2009), istheTechnology Acceptance Model(TAM;Davis,1986;1989).Davishypothesizedthatperceived usefulnessandperceivedease-of-useare“fundamentaldeterminantsofuseracceptance”(p.319)of technology.TheTAM“specifiesthecausalrelationshipsbetweensystemdesignfeatures,perceived usefulness,perceivedease-of-use,attitudetowardusing,andactualusagebehaviour”(Davis,1993, p.475).Inhisworks,Davis(1989)definesperceived usefulness (PU)“asthedegreetowhicha personbelievesthatusingaparticularsystemwouldenhancehisorherjobperformance”(p.320). Furthermore,perceived ease-of-use (PEOU)wasdefinedas“thedegreetowhichapersonbelieves thatusingaparticularsystemwouldbefreeofeffort”(p.320).Thisisalsoconsistentwiththeviews ofRogers(1995)andhistheoryofdiffusionofinnovations.Rogersclaimsthatadoptionisafunction

ofavarietyoffactorsincludingrelativeadvantage,whichcanbeconsideredanalogoustousefulness (Adamsetal.,1992,p.231),andease-of-useoftheinnovation.Greenhalghetal.(2004)providean extensivereviewofthisarea. Theimportanceoftrainingincreatingfavourableuserperceptionsofatechnology(supporting itssuccessfuladoption),anditspositiveimpactonjobperformancehavelongbeenunderlined (Leeetal.,1995;Venkatesh,1999;Nelson&Cheney,1987;Rajagopalanetal.,2007).Leeetal. (1995)intheirstudyonprivatecompanyemployeeshighlightedthatend-userability(increasedby training)waspositivelyrelatedtoend-userITacceptance.Venkatesh(1999)underlinedtheimpact oftrainingonease-of-useandhighlightedthatduringtheearlystagesoflearninganduse,ease-of-useperceptionsaresignificantlyaffectedbytraining(Venkatesh&Davis,1996).Moreover,training wasfoundtoreducecomplexityofinnovationthusincreasingwillingnesstoadopt(Haneemetal., 2019;Lagrandeur&Moreau,2014),andtoincreaseemployeejobsatisfaction,jobperformanceand intenttostayinbothgovernmentandindustry(Ellickson&Logsdon,2002;Wright&Davis,2003; Costen&Salazar,2011;Martínez-Ros&Orfila-Sintes,2012;Chen,2017). Nevertheless,littleresearchhasbeenconductedontheimpactoftrainingonperceivedusefulness andperceivedease-of-use(Venkatesh&Davis,1996;Venkatesh,1999;Xia&Lee,2000)comparedto researchonthetwodeterminants(PUandPEOU)andtheirimpactonusage.Moreresearchexamined theimpactoftrustandsourcecredibilityonperceivedusefulnessandperceivedease-of-use(Suh& Han,2002;Aghdaieetal.,2012;Li,2015).Therefore,asspecifiedintheintroduction,inthisstudy wetesttheimpactoftrainingonthetwofundamentaldeterminantsoftechnologyacceptanceofthe TAM:perceivedusefulnessandperceivedease-of-usethatarestronglypositivelycorrelatedtousage ofITandwerefoundtobestrongerpredictorsforITuseracceptance(Davis,1989;King&He,2006; Hameed&Counsell,2014).Thisstudyhasfocusedonthetwomaindeterminantsratherthanother variables(suchasmood,behaviouralintention,subjectivenorm,performanceexpectancy,oreffort expectancy)fortwomainreasons.Thefirstreasonconcernstheconstraintsanddifficultiesassociated withinvolvinggovernmentemployeesinexperimentalresearch.Thisisrevealedbythefactthatthe majorityofstudiesdonotusegovernmentemployees,buteitherstudents(Agarwal&Karahanna, 2000;Al-Khaldi&Al-Jabri,1998;Padilla-Melendezetal.,2013,Cheung&Vogel2013),private companyemployees(Venkatesh,1999;Dybaetal.,2004;Gelderman,1998;Igbariaetal.,1994; Igbaria&Iivari,1995;Sonetal.,2012),orconsumers/customers(Koufaris,2002;Hendersonetal., 1998;Henderson&Divett,2003;Nasri&Charfeddine,2012;Leeetal.,2011;Ooi&Tan,2016) asresearchsubjects.Thesecondreasonisconnectedtothenatureofthisstudy,whichhascollected dataonbothperceivedusefulnessandperceivedease-of-useonthesamedaythatthetrainingtook placeandinperson,ratherthanatvaryingintervalsafterdaysormonthsthroughmailedoronline surveys.Thissecondreasonalsorequiredustomakeaclearandselectivechoiceonthedependent variablesinordertolimitthetimeneededbytheparticipantstoanswerthesurvey. Basedonourresearchquestionandtheavailableliterature,weconstructedourstudytoinclude oneindependentvariable,namely,thetrainingofparticipantswiththeSMplatform(describedin thefollowingMaterialsandProceduresection),andthreedependentvariables: (i) participants’levelofunderstandingofthefunctionalitiesoftheSMplatform(thatis,theskills acquiredbytheparticipantsthroughtraining), (ii)participants’perceived usefulnessoftheSMplatform,and (iii)participants’perceived ease-of-useoftheSMplatform. Usingthesevariables,weformulatedthreehypothesisasfollows: Hypothesis1looksforapotentialrelationshipbetweentheindependentvariable(training)and thefirstdependentvariable(skills)andworksasaprerequisiteforthenexttwohypotheses.

• Hypothesis1:TrainingproducesasignificantincreaseinthelevelofunderstandingoftheSM platform’sfunctionalities. Hypothesis2investigateswhetherarelationshipexistsbetweentheindependentvariable(training) andtheseconddependentvariable(perceivedusefulness).Itislinkedtothepreviouslyreplicated researchresultsthatperceivedusefulnessofacomputersystemispositivelycorrelatedtoITusage (Davis,1989). • Hypothesis2:Trainingproducesasignificantincreaseinthelevelofperceivedusefulnessofthe SMplatform,thereforeinfluencingitsacceptancebygovernmentemployees. Hypothesis3examinesiftheindependentvariable(training)isrelatedtothethirddependent variable(perceivedease-of-use).Itislinkedtothepreviouslyreplicatedresearchresultsthatperceived ease-of-useofacomputersystemispositivelycorrelatedtoITusage(Davis,1989). • Hypothesis3:Trainingproducesasignificantincreaseinthelevelofperceivedease-of-useof theSMplatform,thereforeinfluencingitsacceptancebygovernmentemployees.

METHod: dESIGN ANd PARTICIPANTS

Awithin-subjectsrepeatedmeasuresexperimentaldesignwasused.Thesubjectswereemployees oftwosmallandmedium-sizedmunicipalitiesinCyprusandSpain(around100,000inhabitantsand 25,000inhabitants,respectively).ThesetwomunicipalitieswerepartnersofanEU-fundedprojectand thesurveyparticipantswereselectedonbehalfofthemunicipalitiesbytheproject’srespectivecontact persons.Participantswereemployedindepartmentsrelatedtothepolicyareasinwhichthetoolwas beingtested:mobilityandwastemanagementinonemunicipality,andeducationandinfancyinthe other.Randomsamplingcouldnotbeguaranteedasparticipantsneededtobeemployedinthetwo policyareastobetrainedontheplatform.Duetotheirpositions,thelevelofsocialmediaexpertise requiredintheworkplacefromtheparticipantsdiffered.TheywerenotrequiredtospeakEnglish asthesurveywasadministeredinGreekandSpanishtoallowparticipantstotakepartinthestudy. Theimpactoftrainingonthethreedependentvariableswastestedbymeansofaself-constructed surveyadministeredimmediately before and afterthetrainingtookplace,whichisprovidedinfullin Appendix1.Aself-constructedsurveywasalsoadministeredbeforethetrainingtocollectdemographic datasuchastheparticipants’gender,agerange,jobfunctions(forprivacyreasonsreportedonlyas departmentaffiliation),andself-reportedSMexpertiselevel(questionsD1-D4investigatingtheSM expertiselevel).ThesedemographicdataarealsoreportedinAppendix1. Thefinalsampleconsistedoftwogroupswith22participantsintotal.Group1inCyprus (10participants)andgroup2inSpain(12participants).Table1belowshowsasummaryofthe demographicdata.AnswerstoquestionsmeasuringtheSMexpertiselevelwerecodedona5-point Likert-typescalewhere1correspondedto“notatall”and5correspondedto“extremely”.Therange wasminimum4andmaximum20,whereahigherscoreindicatedahigherlevelofself-reportedSM expertise.Theoriginalsampleincluded27participants:2droppedoutduringthetrainingsession astheywerecalledupbythemayor,whereas2morechangedjobsinthetimebetweenrecruitment andtheactualtrainingsession;1participantingroup2wasremovedfromthesampleastheonly participantwithscoresabove2standarddeviations(SD)fromthemean(M)inthestartinglevelof twoofthethreedependentvariablesunderconsideration(i.e.,skillsandperceivedusefulness).

Materials and Procedure Thethreedependentvariablesweremeasuredtwice(beforeandafterthetraining)bymeansofa self-constructedsurveyconsistingofpurpose-derivedscales(providedinAppendix1).Thesurvey wasdividedintothreeclustersoffouritemseach:thefirstcluster(questions1-4)investigatedthe levelofskills(e.g.,Whichofthefollowingistrueregardingthesettingsoftheschedulerresponsible forexecutingdatacrawling?).Questionsintheskillsclustercontainedfourpossibleanswerswhere onlyonewascorrectandparticipantscouldindicateonlyoneanswer.Subsequently,theiranswers werecodedasabinaryvariablewhereawronganswercorrespondedto0whileacorrectanswer correspondedto1.Thescorerangethereforevariedbetween0(participantansweredallquestions wrongly)and4(participantansweredallquestionscorrectly).Ahigherscoreindicatesabetter understandingoftheSMplatformfunctionalities.Thesecondcluster(questions5-8)investigated perceived usefulness(e.g.,HowusefulistheSMplatformtoimproveyouraccesstocitizens’ knowledgeandopinion?);thethirdcluster(questions9-12)investigatedperceived ease-of-use(e.g., HowpracticalistheSMplatformforeverydayuse?).Answerswithinthesecondandthirdcluster werecodedona5-pointLikert-typescalewhere1correspondedto“notatall”and5corresponded to“extremely”.Therangeforbothclusterswasminimum4andmaximum20,whereahigherscore indicatedhighlevelofperceivedusefulness/ease-of-use.Allcollecteddataweretreatedconfidentially inacodedway. Afterselectionoftheparticipantsandpriortothestudy,participantswereinformedaboutthe procedurethroughaninformationletter.Atthebeginningofthetrainingparticipantssignedan informedconsentformandwerenotifiedoftheirrighttowithdrawfromthestudyatanymoment withoutanyconsequence.Thetrainingwasconductedbytwoprojectresearchersattheparticipants’ workplaceintheirnativelanguageandtookplaceduringthecourseofaworkingdaylastingbetween6 and8hours.BothresearcherswereequallytrainedtoteachparticipantshowtousetheSMplatform. Thesurveywasadministeredonthesamedaybeforeandafterthetraining.Participantsweregiven15 to20minutestocompletethesurveyonpaperandweretrainedonthefunctionalities,theirpurposes andapplicationintheSMplatform.Trainingbeganwithageneralpresentationbrieflyexplaining theoverallconceptoftheplatformandthefeaturesitincluded.Then,eachfeaturewasexplainedand demonstratedindetailbythetrainers.

Table 1. Demographics. A demographics self-constructed survey collected participants’ age range, gender, job functions, and SM expertise level. N: Number; M: Mean; SD: Standard Deviation; SM: Social Media

      Group 1 - Cyprus       Group 2 - Spain

Participants (N)       10       12

Age (N in each range)

range18-34:0 range35-49:5 range50-65:4 >65:1       range18-34:3       range35-49:3       range50-65:6       >65:0 Females (N)       6       7 Job function

(N for department affiliation)

      Clerical:2       Waste:1       EuropeanAffairs:1       InformationTechnology:2       Political:1       PublicRelations:2       Mobility:1       Education:4       Infancy:1       InformationTechnology:1       Mobility:2       OpenGovernment:3       Police:1 SM expertise index (M±SD)       7.8±4.0       12.2±2.9

Platform Characteristics and Training Tobeginwith,useraccountswerecreatedforeachparticipantinordertoallowthemtologintothe platformandbetrained.Specifically,eachparticipantwasgiventheirownuniqueusernameandwas thenaskedtocreateapasswordtocompletetheircredentialsforsigningintotheplatform.Because eachplatformuserisrequiredtobeassignedtoatleastonerole,eachparticipantwasgivenarole soastoshowthedifferentfeaturesoftheplatform.However,thisdidnotaffectthetrainingsinceall participantsreceivedtheexactsametraining.Theavailablerolesare: • Decisionmakers,whoarehighrankingofficialslikeamayororsomeheadofadepartment/ branch.Theyhaveapersonalinterestintheresultsthattheplatformgeneratesandassignanalytical taskstofacilitatorsanddomainexperts. • Domainexperts,whohaveprofoundknowledgeandexperienceintheirdomain.Theycanbe internalorexternaltotheorganization. • Facilitators,whoareabletogenerateresultsintheplatformbycombiningthemintheappropriate wayforaspecificproblemandthenreporttheresultstothedomainexpertforfurtheranalysis. • Communicators,whoareexpertsinsocialmediausageandpublicrelations.Theysupportthe decisionmakerininteractingwiththepublicandhaveadeepunderstandingofthemechanisms ofsocialandtraditionalmedia. • Systemadministrators,whohaveanimportantroleinmaintainingtheplatformfortheir organization.Whilenotusingthesystemtoproduceresults,theymaintaintheuserbase(creating useraccounts,resettingpasswords,etc.)andsupporttheotherrolesinusingtheplatform. Next,theparticipantswereshownhowtosetupandmanagecampaigns.Campaignsarethe meansthroughwhichusersareabletoengagetheopinionsofcitizens.Theyprovideaccesstoall thee-governancetoolsavailableintheplatformandtheirassociateddata(Figure1).Acampaignis createdbyafacilitatoronbehalfoftheinitiator(i.e.,thedecisionmakerinterestedintheresults). Theparticipantswereshownhowafacilitatormanagesthecampaign,includinghowtosetthestart andenddataofacampaign,howtoaddteammembersfromtheorganizationwhowillhaveaccess totheresultsofthecampaign,andhowtosetthegoals(targets)ofthecampaign.

Participantswerethendemonstratedthefeaturesrelatedtothe“activeparticipation”ofcitizens throughtwoe-governmenttools:opinionmapsandquestionnaires.Specifically,usersoftheplatform cancollectgeoreferencedopinionsrelatedtoaparticularcampaignfromcitizensinteractivelyby publishinganopinionmaponline(Figure2).Theopinionsarestoredaspointswithattributeson amaplayerandcanbeviewedbyteammembers.Theparticipantswereshownhowtoselectthe geographicboundariesofthemap,howtosetpermissions,aswellashowtopublishthemaponline eitherbyembeddingitinawebsiteorbysendingalinktothemapbyemail. Withregardstoquestionnaires,usersoftheplatformareabletocreateonlinesurveysrelatedtoa campaignwithspecificquestionsforcitizenstoanswer.Thequestionnairetoolprovidestheoptionof varioustypesofquestions(yes/no,multipleanswer,Likert-typescales,etc.)foruserstoselectfrom. Theparticipantswerepresentedthestepsneededtoinitiateaquestionnaire,howtoformquestions, howtosetpermissions,aswellashowtodistributethequestionnaireonlineorbyemail. Finally,participantswereshownfeaturesregardingthe“passiveparticipation”ofcitizensbymeans ofsearchingthroughsocialmediapostsandconductingsentimentanalysis.Inparticular,theplatform allowsuserstocreateandmanagemultiplesocialmediawindowsforacampaign.Asocialmedia windowisthekeymechanismresponsibleforextractingpostsfromsocialmedianetworksbasedon keywordsprovidedbyusers.Theresultsofthesearchcanthenbefilteredbyusersforfurtheranalysis (Figure3).Theparticipantswereshownindetailthefeaturesforcreatingcategoriesofkeywords,for constructingsocialmediawindowsinacampaign,andfilteringresults.Furthermore,participants wheredemonstratedhowtoperformsentimentanalysisontheretrievedresultstodeterminethedegree towhichthecontextofthepostscollectedcontainseitherpositiveornegativeopinions. Duringthedemonstrations,practicalexerciseswereprovidedtohelpusersnavigatethroughand familiarizethemselveswithdifferentaspectsoftheplatform.Furthermore,adiscussiontookplace amongparticipantsinordertodiscusstheusageoftheplatforminrelationtotheirmunicipality’s pilotactivitiesandgoals. data Analysis Theresponsesgivenateachmeasurementweresummedresultinginthreepre-trainingandthree post-trainingscoresforeachparticipant,describingthelevelofskills(sumoftheanswervaluesto questions1to4),perceivedusefulness(sumoftheanswervaluestoquestions5to8),andperceived ease-of-use(sumoftheanswervaluestoquestions9to12).Appendix2providesacompletereportof participants’scores.Additionally,theself-reportedresponsestothepre-trainingdemographicquestion regardingaparticipant’sSMexpertiselevelweresummedresultinginoneSMexpertiseindexfor

therewasnosignificantdifferencebetweenthetwogroups(i.e.,betweenparticipantsfromCyprus andSpain)inthestartinglevelsofthethreedependentvariables.Toachievethis,thepre-training means/medians(Mdn)forthethreedependentvariableswerecomparedbetweengroupsthrough independent-samplest-testsorMann-WhitneyUtestdependingondatadistribution.Totestthethree hypotheses,wecomparedthemediansbeforeandafterthetrainingforthethreedependentvariables usingWilcoxonsigned-ranktests.Finally,bymeansofSpearman’scorrelation,wetestedifthere wasarelationshipbetweentheSMexpertiselevelandthedeltalevels(calculatedbysubtractingpre-trainingscorestopost-trainingscores)ofthethreedependentvariables.Allanalyseswereperformed usingIBMSPSSStatisticsSoftware(version24).Thesignificancelevelwassetatp<.05.

RESULTS: dIFFERENCE BETwEEN GRoUPS IN THE STARTING LEVEL oF PERCEIVEd USEFULNESS, PERCEIVEd EASE-oF-USE, ANd SKILLS

Inordertodetermineifpriortothetrainingthetwogroupsweresimilarandcouldbetreatedas onesinglegroup,thestartinglevelsofskills,perceivedusefulness,andperceivedease-of-usewere comparedbetweengroup1(Cyprus)andgroup2(Spain). AMann-WhitneyUtestwasruntodetermineiftherewasadifferenceinpre-training skills scoresbetweenthetwogroups.Fortestingthisvariable,thechoiceofusinganon-parametric testwasdeterminedbytheviolationoftheassumptionofanormaldistributioninbothgroups, asassessedbyShapiro-Wilk’stest(ps<.05).Thetestshowedthatthestartinglevelofskills wasnotstatisticallysignificantlydifferentbetweengroup1(Mdn=.5)andgroup2(Mdn= 1.0),U=51,z=-.642,p=.582. Subsequently,twoindependent-samplest-testswereruntodetermineifthereweredifferences betweenthetwogroupsregardingthepre-traininglevelofperceived usefulnessandperceived

ease-of-use.Perceivedusefulnessscoresandperceivedease-of-usescoresforeachgroupwerenormally

distributed,asassessedbyShapiro-Wilk’stest(ps>.05).Perceivedease-of-usescoresshowed

perceivedusefulnessscoreswasviolated,asestablishedbyLevene’stestforequalityofvariances(p =.056,p=.016,respectively).Asforthestartinglevelofskills,therewerenostatisticallysignificant differencesbetweenthetwogroupsinthepre-traininglevelsofperceivedusefulness,t(12.68)=1.045, p=.315(resultsadjustedforhomogeneityviolation),andperceivedease-of-use,t(20)=.304,p=.764. Inconclusion,theabsenceofstatisticallysignificantdifferencesinthestartinglevelsof participants’skills,perceivedusefulness,andperceivedease-of-usebetweenthetwogroupsallowed ustoproceedwiththestatisticalanalysistreatinggroup1andgroup2asonesinglegroup.

within-Subject differences in The Level of Skills, Perceived Usefulness, and Perceived Ease-of-Use

ThreeWilcoxonsigned-ranktestswereconductedtodeterminetheeffectofthetrainingon:(i)skills, (ii)perceivedusefulness,and(iii)perceivedease-of-use.Thechoiceofusinganon-parametrictest insteadof,forexample,apaired-samplet-test,wasdeterminedbytheviolationoftheassumption ofanormaldistributioninthetwodependentvariables,skillsandperceivedusefulness,asassessed byShapiro-Wilk’stest(ps<.05).Additionally,thischoicewasjustifiedbythepresenceofmultiple outliersinthedifferencescoresofthethreevariables(skillsn=4,perceivedusefulnessn=1, perceivedease-of-usen=6),astheWilcoxonsigned-ranktestisnotaffectedbythepresenceof outliersinthedifferencescores. Hypothesis1:Trainingproducesasignificantpositiveeffectontheparticipants’levelofskills regardingthefunctionalitiesoftheSMplatform. AsevidencedbytheWilcoxonsigned-ranktest,therewasastatisticallysignificantincreasein theunderstandingoftheSMplatform’sfunctionalitiesfrombeforethetraining(Mdn=1.0)compared toafterthetraining(Mdn=3.0),z=3.84,p<.001.Thisresultsuggeststhattrainingwastherefore appropriate,andparticipantsunderstoodthewaytheplatformfunctioned. Hypothesis2:TraininghasasignificantimpactonperceivedusefulnessoftheSMplatform. AsevidencedbytheWilcoxonsigned-ranktest,alsointhiscasetherewasastatisticallysignificant increaseinusefulnessperceptionfrombeforethetraining(Mdn=14.0)comparedtoafterthetraining (Mdn=15.0),z=2.56,p=.011. Hypothesis3:Traininghasasignificantimpactonperceivedease-of-useoftheSMplatform. Contrarytotheprevioustwovariablesandresearchresults(VenkateshandDavis,1996),the Wilcoxonsigned-ranktestshowednostatisticallysignificantincreaseinperceivedease-of-usefrom beforethetraining(Mdn=13.5)comparedtoafterthetraining(Mdn=15.0),z=1.58,p=.114.ù Relationship Between SM Expertise Level and delta Levels of

Skills, Perceived Usefulness and Perceived Ease-of-Use

ASpearman’scorrelationwasruntoassesstherelationshipbetweentheSM expertise levelandthe

delta levels of skills, perceived usefulness,andperceived ease-of-use.Fortestingthesevariables,the

choiceofusinganon-parametrictestwasdeterminedbytheviolationoftheassumptionofanormal distributioninthedependentvariables,skillsandperceivedusefulness,asassessedbyShapiro-Wilk’s test(p=.020,p=.005,respectively),andthenon-linearrelationshipbetweenSMexpertiselevel andtheothervariables,asassessedbyvisualinspectionofthescatterplot.

.201,p=.369,orthedeltalevelofperceivedease-of-use,rs(20)=-.095,p=674.Theabsenceofany correlationbetweenSMexpertiselevelandtheothervariablesallowedustoexcludeanyinfluence oftheparticipants’self-reportedSMexpertiselevelonthethreedependentvariablesofthisstudy. dISCUSSIoN Whereasthemajorityofpreviousstudiesonuseracceptanceoftechnologytreatperceivedusefulness (PU)andperceivedease-of-use(PEOU)asindependentvariables,theyhavebeentreatedhere,ina sampleofgovernmentemployees,asdependentvariables.Studies(suchasVenkatesh&Davis,1996; Venkatesh,1999;XiaandLee,2000)wherePUandPEOUhavebeentreatedasdependentvariables toanalysetheimpactoftrainingareactuallyscarce.Forexample,somestudiesexaminedtheimpact oftrustandsourcecredibilityonperceivedusefulnessandperceivedease-of-use(Suh&Han,2002; Aghdaieetal.,2012;Li,2015).Thelattertwovariableshavebeenusedinourstudytoindirectly exploretheimpactoftrainingonuseracceptanceofatechnologicalinnovationintheworkplace, giventheirpositivecorrelationwithuseracceptanceintheTAM(Davis,1989).Participantsinour studyshoweddifferentSMself-reportedexpertiselevels,andthiscouldhaveaffectedbothperceived usefulnessandperceivedease-of-use.However,nosignificantcorrelationwasfoundbetweenSM self-reportedexpertiselevelsandthethreedependentvariables(skills,p=.657;perceivedusefulness, p=.369;perceivedease-of-use,p=674),thusallowingustoexcludeadirectimpactofSMself-reportedexpertiselevelsonthescoresofthethreedependentvariablesbeforeandafterthetraining. Theresultsofoursurveyshow,firstly,thatthetrainingadministeredtothepublicofficials effectivelyproducedastrongandsignificantincreaseintheirunderstandingofthefunctioningof theSMplatform.Thisemergesclearlythroughtheverysignificantincreaseinthelevelofthefirst dependentvariable,thatis,skills(p<.001).Thiswasaprerequisitetoproceedandtestwhetherthe traininghadasignificanteffectonPUandPEOU.Weassumedthatanunsuccessfultrainingwould nothavepositivelyaffectedPUandPEOU. Secondly,thisstudyhascontributedtotheliteraturebyincreasingourunderstandingofPUand PEOUbyrevealingthenatureandsizeoftheeffectsoftrainingofgovernmentemployees.Theresults showthattraininghasasignificantpositiveimpactonperceivedusefulness(p=.011),whereasthe impactonperceivedease-of-useisnotsignificant(p=.114).Whileourfindingsdifferfromsome ofthepreviousstudies(Venkatesh&Davis,1996),theyareinlinewithotherpartsoftheliterature. Previousquantitativemeta-analysesconfirmperceivedusefulnesstobethestrongerpredictorofIT acceptanceandintentiontouse,andashavinghighercorrelationcoefficientswithusagebehaviour thanperceivedease-of-use(Ma&Liu,2004;King&He,2006;Schepers&Wetzels,2007).Infact, Schepers&Wetzels(2007)intheirmeta-analysisof63studiesunderlinethat“evidence existed

for a stronger dependence of an individual on utility than on lower complexity when adopting new technologies. Both correlations and path coefficients are higher for relationships with perceived usefulness than those with perceived ease-of-use”(p.99).Othermeta-analysesachievedcomparable

resultsandarrivedatsimilarconclusions(Ma&Liu,2004;King&He,2006).Thisisimportantfor ourstudyasthesignificantpositiveimpactoftrainingonperceivedusefulnesscouldleadtoagreater influenceonuser’sacceptanceandintentiontouse.

Theresultscanbeusedtoidentifyseveralimplications for practice.Firstofall,thattraining insmallgroupsisaneffectivemethodtofacilitateacceptanceoftechnologicalinnovationsby individualgovernmentemployees.Thenon-significantfindingonperceivedease-of-usealsocarries apracticalimplication.TheSMplatformwasdevelopedwithinanEU-fundedresearchproject,but therewasnoa-prioricertaintyastowhethertheplatformwouldactuallybe‘officially’implemented bytheparticipatinglocalgovernments.Therefore,trainingparticipantsweremuchmoreconcerned inunderstanding“what”theycoulddowiththeplatformintermsofpolicyanddecisionmaking (usefulness)ratherthan“how”theywoulddoit(ease-of-use).Inotherwords,maximisingtheimpact

oftrainingonperceivedeaseofuse(PEOU)canonlybeguaranteedifgovernmentemployeesknow inadvancethattheywillusethetechnologicalinnovationintheirworkroutines. Intheearlyphaseofthestudy,weencounteredsomeapprehensionamongtheparticipants, manyofwhomregardedtheSMplatformasanewtechnologythatwouldrequiretimeandresources tomaster,ontopofcivilservants’fullplates.Thetrainingexerciseshelpedovercomethisinitial hesitanceand,infact,madeparticipantsunderstandthattheplatformwouldhelpthemobtaininsights thatotherwisewouldnotbecollected.Moreover,theplatformitselfwaspresentedasan“easy-to-use” toolsothattheywouldnotgetfrightenedandrefusebeinginvolvedintheproject.Becauseofthis,a possiblebiasfromthestartwasthattheyexpectedtheplatformtobeeasytouse.However,afterthe 8-hourtrainingtookplaceandhavinghadthechancetoactuallyusetheSMplatform,participants mighthaverealizedthatitwasnotassimpleastheywereexpectingittobe.Asamatteroffact,for fiveparticipants(outof22)thetotalvalueofpost-trainingease-of-usescorewaslowerthanthepre-trainingscore.Wedonothaveenoughdatatodeterminewhetherthiswasduetotheparticipants’ technologicalproficiency,age,position,orothervariables.Theimplicationsforpracticearethatthe lengthofthetraining(orthenumberoftrainingsessions)mustbebeyondacertain‘tippingpoint’ toconvincetheparticipantsthatthetechnologicalinnovationatstakeiseasytouse.Moreover,any technologicalinnovationthatwillmoveintotheimplementationandtrainingphaseshouldalready haveproventobeeasytouseinprecedingtesttrials.Otherwise,toomuchstruggleduringthetraining sessionsmightnegativelyaffectboththeperceivedusefulnessandtheperceivedease-of-use. Limitations Afirstandforemostlimitationconcernsthenumberofparticipants.Studieswithgovernment employeestendtohavefewerparticipantsthan,forexample,studieswithstudents,asitisharder torecruitgovernmentemployees.Inourcase,thesmallandmediumsizeofthecitiesinvolved (between25,000and100,000inhabitants),increasedthisissueastheadministrativeapparatuswas,by definition,smallandwecouldnotrecruitparticipantsfromjustanypolicyarea.Thelimitednumber ofparticipantswasalsoduetothenatureofourstudy,whichincludedin-persontrainingandcould notbecarriedoutbyalsodistributingandadministeringaquestionnaireviaemailoronlineasdone, forexample,inthestudybyVenkatesh(1999),whichhadasampleofaround35trainees.Thesecond limitationconcernsthepurpose-derivedfive-pointscalethatonlypartiallyusedDavis’scale(1989). Weneededtoadaptthescale(4itemand5point-scale)tothecontextandtrainingtoincreaseclarity fortheparticipantsandreduceresponsetimetofittheneedsofgovernmentemployees.However, wedonotexpectresultstobedifferenthadweusedDavis’scale. CoNCLUSIoN Theever-growingdigitalizationofgovernmentfunctionsandgovernancesettingshaspushedlocal governmentadministrationstoadoptnewinformationtechnologiestomeetnewneedsandsatisfynew modelsofcommunication.Whilegovernmentorganizationsatalllevelsadoptsocialmediaandmicro-bloggingsites(FacebookandTwitter)tocommunicateandengagewithcitizensandinvolvethemin policydecisions,acceptanceofsuchinnovationsultimatelycomesdowntoindividualgovernment employees.Todate,theliteraturehashardlyaddressedthisperspective.Thisstudycontributestothe literaturebyrevealingthenatureandsizeoftheeffectsofandimportanceoftrainingforgovernment employees’acceptanceoftechnologytodeliverincreaseddigitalizationintheworkprocessesinline withparadigmsofsmart-governmentandsmart-governance.WithinthecontextofanEU-funded project,whichemployedasocialmediaplatformtoanalyzetheinteractionsonFacebookandTwitter betweentwosmall/medium-sizedmunicipalitiesandtheircitizensintwopolicyareas,wetestedthe impactoftrainingonperceivedusefulnessandperceivedease-of-useoftheplatform.Thestudywas conductedthroughawithin-subjectrepeatedmeasureexperimentaldesignon22subjects.Perceived

Weconcludethattrainingsignificantlyincreasedperceivedusefulnessasthemaindeterminantof useracceptanceandITusage.However,contrarytoresultsofpreviousresearch(Venkatesh&Davis, 1996;Venkatesh,1996),trainingdidnotproduceasignificantincreaseinperceivedease-of-use. Thismightbeduetothelimitedtrainingsubjectsreceived(8hoursintotal),theirgenerallymodest leveloftechnologicalproficiency,andthefactthattheplatformwasnotgoingtobeintroducedin theirworkroutinesbutratherwasgoingtobeusedbytheresearchteamincollaborationwiththe municipalities.Thelattermadethesubjectsmoreinterestedin“what”couldbedonewiththeplatform toaidpolicymakingratherthan“how”todoitsincetheywerenotgoingtouseitdirectly.Future researchcouldconsistofalarger-scalestudyusingagreaternumberofparticipantsfromagovernment organization.Furthermore,astudycouldbecarriedoutinvolvingthetrainingofparticipantsonthe sametechnologyacrossdifferentgovernmentorganizationstoinvestigatewhetheraparticulartype oforganizationrespondsdifferentlytotrainingintermsofperceivedusefulnessandperceivedease-of-use.Thiscouldprovideinsightstowardstheeffect,ifany,ofanorganization’sstructure,culture, procedures,etc.,ontraining.Inaddition,differenttrainingmethodscouldbeexaminedinorderto ascertainifaparticularapproachtotrainingleadstodifferencesinparticipants’perceptions. Despiteitslimitations,therelativelylownumberofsubjectsandthenon-mandatoryintroduction ofthesocialmediaplatforminthegovernmentemployees’workroutines,ourstudypresentsinteresting resultsasitconfirmstheimportanceandimpactthattraininglocalgovernmentemployeeshason creatingfavorableperceptionsamongthemregardingusefulnessandease-of-useofITinnovations, which“inturnshouldleadtoacceptanceandusage”(Venkatesh,1999,p.239).Thisisessential consideringthecurrentdevelopmentofsmartgovernmentfunctionsandactivities,aswellasthe struggleofgovernmentstousethedatatheygenerate,toproduceclearstrategiesintheirdepartments, andtodevelopcapacitiesamongtheiremployees(Macnamara&Zerafass,2012;Mergel,2013; Mickoleit,2014).Thearticleunderlinestheneedtomovebeyondthetechnologyitself,byshowing thatadoptingICTinnovationsnotonlypresentsatechnologicalchallenge,butalsoanorganizational, humanresourcemanagementchallenge(seealsoFalco&Kleinhans,2018b).Theintroductionof newtechnologywithinpublicadministrationsmustthereforebeaccompaniedbycarefullyconsidered training.Thistrainingshouldbeofsufficientintensityanddurationtoensurethatitnotonlyincreases perceivedusefulness,butalsoperceivedease-of-use.Onlyifbothfactorsmovebeyondacertainlevel orthreshold,therespectiveICTinnovationmightbeultimatelyacceptedandusedbygovernment employeesandadministrators.

REFERENCES

Abdullah,F.,&Ward,R.(2016).DevelopingaGeneralExtendedTechnologyAcceptanceModelforE-Learning (GETAMEL)byanalysingcommonlyusedexternalfactors.Computers in Human Behavior,56,238–256. doi:10.1016/j.chb.2015.11.036

Adams,D.A.,Nelson,R.R.,&Todd,P.A.(1992).PerceivedUsefulness,EaseofUse,andUsageof InformationTechnology:AReplicationSource.Management Information Systems Quarterly,16(2),227–247. doi:10.2307/249577

Agarwal,R.,&Karahanna,E.(2000).Timeflieswhenyou’rehavingfun:cognitiveabsorptionandbeliefsabout informationtechnologyusage.MIS Quarterly,24(4),665–694.

Aghdaie,S.F.A.,Sanayei,A.,&Etebari,M.(2012).Evaluationoftheconsumers’trusteffectonviralmarketing acceptancebasedonthetechnologyacceptancemodel.International Journal of Marketing Studies,4(6),9–94. doi:10.5539/ijms.v4n6p79

Ajzen,I.(1998).Attitudes, Personality and Behavior(2nded.).OpenUniversityPress.

Al-Khaldi,M.A.,&Al-Jabri,I.M.(1998).Therelationshipofattitudestocomputerutilization:Newevidence fromadevelopingnation.Computers in Human Behavior,14(1),23–42.doi:10.1016/S0747-5632(97)00030-7 Albino,V.,Berardi,U.,&Dangelico,R.M.(2015).Smartcities:Definitions,dimensions,performance,and initiatives.Journal of Urban Technology,22(1),3–21.doi:10.1080/10630732.2014.942092

Anthopoulos,L.,Janssen,M.,&Weerakkody,V.(2016).AUnifiedSmartCityModel(USCM)forSmartCity ConceptualizationandBenchmarking.International Journal of Electronic Government Research,12(2),77–93. doi:10.4018/IJEGR.2016040105

Antón,C.,Camarero,C.,&SanJosé,R.(2014).PublicEmployeeAcceptanceofNewTechnologicalProcesses: Thecaseofaninternalcallcentre.Public Management Review,16(6),852–875.doi:10.1080/14719037.2012 .758308

Chen,B.T.(2017).ServiceInnovationPerformanceintheHospitalityIndustry:TheRoleofOrganizational Training,Personal-JobFitandWorkScheduleFlexibility.Journal of Hospitality Marketing & Management,

26(5),474–488.doi:10.1080/19368623.2017.1264344

Cheung,R.,&Vogel,D.(2013).Predictinguseracceptanceofcollaborativetechnologies:Anextension ofthetechnologyacceptancemodelfore-learning.Computers & Education,63,160–175.doi:10.1016/j. compedu.2012.12.003

Chuttur,M.Y.(2009).Overviewofthetechnologyacceptancemodel:origins,developmentsandfuturedirections.

Sprouts: Working Papers on Information Systems,9(37),1–21.

Costen,W.M.,&Salazar,J.(2011).TheImpactofTrainingandDevelopmentonEmployeeJobSatisfaction, Loyalty,andIntenttoStayintheLodgingIndustry.Journal of Human Resources in Hospitality & Tourism,

10(3),273–284.doi:10.1080/15332845.2011.555734

Davis,F.D.(1986).A technology acceptance model for empirically testing new end-user information systems (PhDThesis).Cambridge,MA:MassachusettsInstituteofTechnology.Availableat:https://dspace.mit.edu/ handle/1721.1/15192

Davis,F.D.(1989).Perceivedusefulness,perceivedeaseofuse,anduseracceptanceofinformationtechnology.

Management Information Systems Quarterly,13(3),319–340.doi:10.2307/249008

Davis,F.D.(1993)Useracceptanceofinformationtechnology:systemcahracheristics,userperceptionand behaviouralimpacts.Man-Machine Studies,36,475-487.

Dyba,T.,Moe,N.B.,&Mikkelsen,E.M.(2004).Anempiricalinvestigationonfactorsaffectingsoftware developeracceptanceandutilizationofelectronicprocessguides.Proceedings of the 10th IEEE International

Symposium on Software Metrics (METRICS’04),220–231.doi:10.1109/METRIC.2004.1357905

Ellickson,M.C.,&Logsdon,K.(2002).DeterminantsofJobSatisfactionofMunicipalGovernmentEmployees.

Falco,E.,&Kleinhans,R.(2018a).BeyondInformation-Sharing.ATypologyofGovernmentChallenges andRequirementsforTwo-WaySocialMediaCommunicationWithCitizens.The Electronic.Journal of

E-Government,16(1),18–31.

Falco,E.,andKleinhans,R.(2018b).BeyondTechnology:IdentifyingLocalGovernmentChallengesforUsing DigitalPlatformsforCitizenEngagement.International Journal of Information Management,40,17–20. 10.1016/j.ijinfomgt.2018.01.007

Falco,E.,Malavolta,I.,Radzimski,A.,Ruberto,S.,Iovino,L.,&Gallo,F.(2018).SmartCityL’Aquila:An Applicationofthe“Infostructure”ApproachtoPublicUrbanMobilityinaPost-DisasterContext.Journal of

Urban Technology,25(1),99–121.doi:10.1080/10630732.2017.1362901

Fishbein,M.,&Ajzen,I.(1975).Belief, Attitude, Intention and Behavior: An Introduction to Theory and

Research.Addison-Wesley.

Gil-Garcia,J.R.,Dawes,S.S.,&Pardo,T.A.(2018).Digitalgovernmentandpublicmanagementresearch: Findingthecrossroads.Public Management Review,20(5),633–646.doi:10.1080/14719037.2017.1327181 Gil-Garcia,J.R.,Zhang,J.,&Puron-Cid,G.(2016).Conceptualizingsmartnessingovernment:Anintegrative andmultidimensionalview.Government Information Quarterly,33(3),524–534.doi:10.1016/j.giq.2016.03.002 Greenhalgh,T.,Robert,G.,MacFarlane,F.,Bate,P.,&Kyriakidou,O.(2004).DiffusionofInnovationsin ServiceOrganizations:SystematicReviewandRecommendations.The Milbank Quarterly,82(4),581–629. doi:10.1111/j.0887-378X.2004.00325.xPMID:15595944

Hameed,M.A.,&Counsell,S.(2014).UserAcceptanceDeterminantsofInformationTechnologyInnovation inOrganizations.International Journal of Innovation and Technology Management,11(5),17–32.doi:10.1142/ S0219877014500333

Hamid,A.A.,Zaidi,F.,Bakar,A.A.,&Abdullah,W.S.B.(2016).TheeffectsofperceivedusefulnessandPEOU oncontinuanceintentiontousee-government.Procedia Economics and Finance,35,644–649.doi:10.1016/ S2212-5671(16)00079-4

Haneem,F.,Kamaa,N.,Taskinb,N.,Pauleenb,D.,&AbuBakara,N.A.(2019).Determinantsofmaster datamanagementadoptionbylocalgovernmentorganizations:Anempiricalstudy.International Journal of

Information Management,45,25–43.doi:10.1016/j.ijinfomgt.2018.10.007

Henderson,R.,&Divett,M.J.(2003).Perceivedusefulness,easeofuseandelectronicsupermarketuse.

International Journal of Human-Computer Studies,59(3),383–395.doi:10.1016/S1071-5819(03)00079-X

Henderson,R.,Rickwood,D.,&Roberts,P.(1998).Thebetatestofanelectronicsupermarket.Interacting with

Computers,10(4),385–399.doi:10.1016/S0953-5438(98)00037-X

Igbaria,M.,Schiffman,S.J.,&Wieckowski,T.J.(1994).Therespectiverolesofperceivedusefulnessand perceivedfunintheacceptanceofmicrocomputertechnology.Behaviour & Information Technology,13(6), 349–361.doi:10.1080/01449299408914616

Khan,G.F.(2015).TheGovernment2.0utilizationmodelandimplementationscenarios.Information

Development,31(2),135-149.

Khan,G.F.,&Park,H.W.(2013).Thee-governmentresearchdomain:Atriplehelixnetworkanalysisof collaborationattheregional,country,andinstitutionallevels.Government Information Quarterly,30(2), 182–193.doi:10.1016/j.giq.2012.09.003

King,W.R.,&He,J.(2006).Ameta-analysisofthetechnologyacceptancemodel.Information & Management,

43(6),740–755.doi:10.1016/j.im.2006.05.003

Korteland,E.,&Bekkers,V.(2008).ThediffusionofelectronicservicedeliveryinnovationsinDutchE-policing: Thecaseofdigitalwarningsystems.Public Management Review,10(1),71–88.doi:10.1080/14719030701763195 Koufaris,M.(2002).Applyingthetechnologyacceptancemodelandflowtheorytoonlineconsumerbehavior.

Layne,K.,&Lee,J.(2001).DevelopingfullyfunctionalE-government:Afourstagemodel.Government

Information Quarterly,18(2),122–136.doi:10.1016/S0740-624X(01)00066-1

Lee,G.,&Kwak,Y.H.(2012).Anopengovernmentmaturitymodelforsocialmedia-basedpublicengagement.

Government Information Quarterly,29(4),492–503.doi:10.1016/j.giq.2012.06.001

Lee,S.M.,Kim,Y.R.,&Lee,J.(1995).Anempiricalstudyoftherelationshipsamongend-userinformation systemsacceptance,training,andeffectiveness.Journal of Management Information Systems,12(2),189–202. doi:10.1080/07421222.1995.11518086

Lee,W.,Xiong,L.,&Hu,C.(2011).TheeffectofFacebookusers’arousalandvalenceonintentiontogoto thefestival:Applyinganextensionofthetechnologyacceptancemodel.International Journal of Hospitality

Management,31(3),819–827.doi:10.1016/j.ijhm.2011.09.018

Lehmkuhl,T.,Baumol,U.,&Jung,R.(2013).TowardsaMaturityModelfortheAdoptionofSocialMediaas aMeansofOrganizationalInnovation.46th Hawaii International Conference on System Sciences.Availableat: https://www.computer.org/csdl/proceedings/hicss/2013/4892/00/4892d067.pdf

Lember,V.,Brandsen,T.,&Tõnurist,P.(2019).Thepotentialimpactsofdigitaltechnologiesonco-production andco-creation.Public Management Review,21(11),1665–1686.doi:10.1080/14719037.2019.1619807 Li,C.Y.(2015).Theeffectsofsourcecredibilityandargumentqualityonemployees’responsestoward informationsystemusage.Asia Pacific Management Review,20(2),56–64.doi:10.1016/j.apmrv.2014.12.003 Ma,Q.,&Liu,L.(2004).Thetechnologyacceptancemodel:Ameta-analysisofempiricalfindings.Journal of

Organizational and End User Computing,16(1),59–72.doi:10.4018/joeuc.2004010104

Macnamara,J.,&Zerfass,A.(2012).SocialMediaCommunicationinOrganizations:TheChallengesofBalancing Openness,Strategy,andManagement.International Journal of Strategic Communication,6(4),287–308.doi: 10.1080/1553118X.2012.711402

Marangunić,N.,&Granić,A.(2015).Technologyacceptancemodel:Aliteraturereviewfrom1986to2013.

Universal Access in the Information Society,14(1),81–95.doi:10.1007/s10209-014-0348-1

Martínez-Ros,E.,&Orfila-Sintes,F.(2012).Trainingplans,manager’scharacteristicsandinnovationinthe accommodationindustry.International Journal of Hospitality Management,31(3),686–694.doi:10.1016/j. ijhm.2011.09.004

Meijer,A.J.,&Bolívar,M.P.R.(2016).Governingthesmartcity:Areviewoftheliteratureonsmarturban governance.International Review of Administrative Sciences,82(2),392–408.doi:10.1177/0020852314564308 Mele,V.(2008).Explainingprogrammesforchange:ElectronicgovernmentpolicyinItaly(1993–2003).Public

Management Review,10(1),21–49.doi:10.1080/14719030701763179

Melitski,J.,Gavin,D.,&Gavin,J.(2010).Technologyadoptionandorganizationalcultureinpublicorganizations.

International Journal of Organization Theory and

Behavior,13(4),546–568.doi:10.1108/IJOTB-13-04-2010-B005 Mellouli,S.,Luna-Reyes,L.F.,&Zhang,J.(2014).Smartgovernment,citizenparticipationandopendata. Information Polity,19(1,2),1-4.Doi:10.3233/IP-140334 Mergel,I.(2013).Aframeworkforinterpretingsocialmediainteractionsinthepublicsector.Government Information Quarterly,30(4),327–334.doi:10.1016/j.giq.2013.05.015 Mergel,I.,&Bretschneider,S.I.(2013).AThree-StageAdoptionProcessforSocialMediaUseinGovernment.

Public Administration Review,73(3),390–400.doi:10.1111/puar.12021

Mickoleit,A.(2014).Social Media Use by Governments: A Policy Primer to Discuss Trends, Identify Policy

Opportunities and Guide Decision Makers.OECDWorkingPapersonPublicGovernance,No.26.OECD

Publishing.

Moon,M.J.(2002).TheEvolutionofE-GovernmentamongMunicipalities:RhetoricorReality?Public