Domain-specific innovativeness: a meta-analysis in business and consumer

Availableonlineatwww.sciencedirect.com

http://www.revistas.usp.br/rai RAIRevistadeAdministraçãoeInovação13(2016)99–106

Domain-specific

innovativeness:

a

meta-analysis

in

business

and

consumer

Clecio

Falcão

Araujo

,

Wagner

Junior

Ladeira

,

Fernando

de

Oliveira

Santini

,

Claudio

Hoffmann

Sampaio

a_{PontificalCatholicUniversityofRioGrandedoSul–PUCRS,Brazil} b_{UniversityValleyRioofSinos–UNISINOS,Brazil}

Received5August2015;accepted31March2016 Availableonline13May2016

Abstract

Thespecificdomainofaproductandtheperceptionofinnovationaretopicsthatarousedinterestinresearchinthelasttwentyyears,especiallyafter thedevelopmentofthedomain-specificinnovativeness(DSI)construct.Thispaperconductedameta-analysistoassesstheconsequentsoftheDSI. Tothisend,atotalof276workswereidentifiedinninedatabases,ofwhich78wereincludedinthestudywork,generating98observationsfora samplesetof40,641.Theresultsshowedsignificantrelationshipsbetweentheconsequents:adoptionofinnovation,attitude,behavioralintention, productusage,opinionleaderandriskperception.Furthermore,itwasnotedthattheresearchmethod(surveyvs.experimental)andthecountry ofapplication(Westernvs.Eastern)weremoderatingfactorsoftherelationshipsbetweenDSI,opinionleaderandbehavioralintention.

©2016DepartamentodeAdministrac¸ão,FaculdadedeEconomia,Administrac¸ãoeContabilidadedaUniversidadedeSãoPaulo-FEA/USP. PublishedbyElsevierEditoraLtda.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/). Keywords:Domain-specificinnovativeness(DSI);Meta-analysisandconsequents

Introduction

People who have domain over certain products are more likelytoidentifyinnovationswhenthesearereleased(Bartels& Reinders,2011;Gao,Rohm,Sultan,&Pagani,2013;Goldsmith & Hofacker, 1991). For example, wine connoisseurs tend to perceivemorequicklythelaunchingofanewproductderived fromaparticularcropthanconsumersthatarenon-connoisseurs. Expertsinautomobilesare better abletoevaluatethe perfor-manceofanenginethatpromisestobepowerful.Specialistsin beautyproductswillmorequicklyidentifythepositivesand neg-ativesofanewskincream.Thisheightenedperceptionisdueto thespecificdomainofapersonforinnovationinaproductclass, whichwasproposedbyGoldsmithandHofacker(1991)through theconstructcalleddomain-specificinnovativeness(DSI).

∗_{Correspondingauthor.}

E-mails:clecioa@bol.com.br(C.F.Araujo),wjladeira@gmail.com

(W.J.Ladeira),santiniconsultores@terra.com.br(F.d.O.Santini),

csampaio@pucrs.br(C.H.Sampaio).

PeerReviewundertheresponsibilityofDepartamentodeAdministrac¸ão, FaculdadedeEconomia,Administrac¸ãoeContabilidadedaUniversidadede SãoPaulo–FEA/USP.

Inmanagementstudies,therearemanyexamplesthat demon-strate theuse ofDSI (Roehrich,2004;Zhang &Kim,2013), especiallywhenassessingtheconsequentsofthisbehavior(Gao etal.,2013;Goldsmith,d’Hauteville,&Flynn,1998;Kim,Di Benedetto,&Lancioni,2011;Sun,Youn,Wu,&Kuntaraporn, 2006).Althoughthereareasignificantnumberofstudies eval-uatingtheDSI,thereisstillnoconsensusregardingtheimpact of thisconstructonits possibleconsequents.Asan example, the relationshipbetween the DSI and the opinion seeking is indicatedin literatureinapositive way(Grewal etal., 2000; Sunetal.,2006),inanegativeway(Goldsmith,d’Hauteville,& Flynn,1998;Shoham&Ruvio,2008)andsometimesneutrally (Goldsmithetal.,1998;Kim,DiBenedetto,&Lancioni,2011). Guided inthe absence of consensus, thisarticle proposes, through the use of ameta-analysis,to consolidatethe under-standing of the relationships resulting from DSI. Forthis, a systematic review was performed, of which were raised276 studiespublishedinleadingdatabases,thesesanddissertations of the marketing andbusiness area.With thissearch, it will bepossibletoverifythemagnitudeoftheeffectsizesofeach of the raised relationships, which will provide a way to the empirical generalization of the aforementioned constructand itsconsequents(Farley,Lehmann,&Sawyer,1995).

http://dx.doi.org/10.1016/j.rai.2016.03.003

1809-2039/©2016DepartamentodeAdministrac¸ão,FaculdadedeEconomia,Administrac¸ãoeContabilidadedaUniversidadedeSãoPaulo-FEA/USP.Published byElsevierEditoraLtda.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).

Domain-specificinnovativeness(DSI)

The domain-specific innovativeness (DSI) construct basi-cally studies the aspects of human behavior associated with innovation within a specificinterest of a person (Midgley & Dowling,1993).Thisconstructseekstounderstandthe predis-positionofanindividualtoaclassofproductsand,atthesame time,toanalyzethetendencytolearnandadoptnewproducts (Goldsmith&Hofacker,1991;Roehrich,2004).Thus,theDSI isbasicallyconsideredapredispositiontobuynewanddifferent goodsorbrands,insteadofremainingwithprevious consump-tionpatterns(Steenkamp,Hofstede,&Wedel,1999).This pre-dispositionisperhapsaconsequenceoftheinteractionbetween theinnovationasawholeandthestronginterestinaparticular productcategory(Midgley&Dowling,1978;Roehrich,2004). TheconceptoftheDSIwasintroducedintheseminalstudyof

Robertson(1971),whentheauthorstatedthattheconsumerhas theabilitytoinnovatewithinagivencategory,and,occasionally, betweenrelated productclasses. Subsequently, otherauthors, suchasGoldsmith,Eastman,andFreiden(1996),demonstrated thefundamentalroleofthisbehavior,sinceitmaytriggervarious actions associatedwithinnovation andconsumption,wherein thecentralpointisthespecificationofsomecategoriesof prod-ucts.Thismeans thatwhileacustomeratany giventimecan adoptaninnovativebehaviorinaparticularconsumption con-text,atthesametime,heorshecanbeconservativeinanother field(Gatignon&Robertson,1991;Goldsmith &Goldsmith, 1996).

ThisstudywaselaboratedfromtheDSIconstructproposition comingfromtheworkofGoldsmithandHofacker(1991)inthe JournaloftheAcademyofMarketingScience.Overthepastfew years,withthepopularization ofthisbehavior,itsapplication hasbeenobservedindifferentcategoriesofproducts,industries andcountries(Agarwal&Karahanna,2000;Agarwal&Prasad, 1998; Flynn &Goldsmith, 1993; Goldsmith & Flynn, 1992; Goldsmith,Kim,Flyn,&Kim,2005;Roehrich,2004).

DSIconsequents

AfterthedevelopmentoftheDSIconstruct,severalworksand authorsexaminedtherelationshipofthisbehaviorandits conse-quents(Citrin,Sprott,Silverman,&Stem,2000;Goldsmith& Flynn,1995;Hirunyawipada&Paswan,2006),butinadispersed andnon-meta-analyticform.Fromthis,itwereobserved associ-ationswiththebehaviortoadoptinnovation(Citrinetal.,2000; Huotilainen,Pirttilä-Backman,&Tuorila,2006),theinfluence of theopinionleader(Goldsmith&Hofacker,1991; Feick& Price,1987;Shoham&Ruvio,2008),thebehavioralintention andthe useof aproduct (Agarwal &Karahanna, 2000),the riskperception(DelVecchio&Smith,2005;Mitchell&Harris, 2005)andtheopinionseeking(Black,1982).Basedonthese relationships,itwasbuiltameta-analyticalframeworkthatcan beseeninFig.1.Thismodel bringstherelationshipbetween theDSIanditsmainconsequents,identifiedfromtheliterature review.

Thefirstconstructanalyzedasapossibleconsequentofthe DSIistheinnovationadoption.Theprocessofadoptinganew

Domain-Specifc Innovativeness

(DSI)

Consequents H₁: Innovation Adoption

H₂: Attitude

H₃: Behavioral Intetion

H₄: Product Usage

H₅: Opinion Leadership

H₆: Opinion Seeking

H₇: Risk Perception Methodological moderators

- Method (survey vs. experimental) - Subject (students vs. non-students) - Environment (laboratory vs. field) - Object (product vs. service) - Country (Western vs. Eastern)

Fig.1.Meta-analyticalframeworkoftheDSIanditsconsequents.

technology,productorservicecanbeseenintheworkofRogers (2003),inwhichthisbehavioriscloselylinkedtotheconcept of consumerinnovativeness.Inthisapproach,thetendencyto adoptnewproductsdoesnotdependontheindividual’s percep-tion only, butalso onthe contextin whichhe/sheis inserted (Gatignon&Robertson,1991).Thisfactsuggeststhatthereis a specificdomain to understandthe process of adoption and innovation ofconsumers(Goldsmith&Hofacker,1991).This causestheDSItobeassociatedwiththeadoptionofnew prod-ucts,asperceivedinmoststudiesonthesubject(Citrinetal., 2000;Huotilainen,Pirttilä-Backman,&Tuorila,2006).Asthe basisofthisargument,thereisthefollowinghypothesis:

H1. DSIpositivelyaffectstheadoptionofinnovation,i.e.

con-sumerswithamoreinnovativeprofileinagivendomainadopt productswithamoreinnovativefeature.

The secondrelationshipstudiedregardsthe consumer atti-tude. The attitude of anindividual is apredispositiontoward aconduitandcanbeunderstoodasafavorableorunfavorable evaluationthatthepersondoesonagivengoodorservice.Inthis case, theDSImaybeconsideredanantecedentofthis behav-ior,becauseitprecedesandproducesfavorableorunfavorable behavioralintentionsofaperson(Crespo&DelBosque,2008), afactdetectedinseveralworks,suchasKarahanna,Straub,and Chervany(1999),Gefen,Karahanna,andStraub(2003),Caro, Mazzon,Caemmerer,andWessling(2011).Thus,itisexpected that:

H2. DSIpositivelyaffectstheconsumerattitude,thatis,

con-sumers with a more innovative profile have more constant consumerattitudes.

Thethirdhypothesisproposesapositiverelationshipbetween DSIandbehavioralintention.Purchaseintentcanbedetermined as a predispositiontoperforma certainbehavior(Gao etal., 2013;Zhang&Kim,2013).Inthisscenario,consumerslikely to have specific domain of certain products or services will tend topresentgreater intention topurchasethanotherswho do not haveit, inother words, innovativeconsumers tendto havehigherpropensitytoconsumethantheconservatives(Gao, Rohm,Sultan,&Huang,2012).Thus,itisexpectedthat:

H3. TheDSIpositivelyaffects thebehavioralintentions,i.e.

innovativeconsumers for a certainproduct domain are more likelytohavepurchaseintentions.

The hypothesis number four concerns the relationship between the use of a new product and the DSI. Similar to thebehavioralintentions,itisexpectedapositiverelationship betweenthetwobehaviors(Agarwal&Karahanna,2000).This assumptionisbasedonthefactthatiftheconsumerdoesnothave aninnovativeprofile,he/shewilltendtohaveroutinebehaviors, andconsequently,itwillminimizetheuseofnewproducts.On theotherhand,withapredispositionforinnovation,therewillbe apositivepropensitytousenewproducts(Hirschman,1980),a factratifiedbyresearchersinthefield(Goldsmith,2001;Wong, 2012).Basedonthesearguments,the followinghypothesisis proposed:

H4. TheDSIpositivelyaffectstheuseofanewproduct,i.e.

consumerswithamoreinnovativeprofileinaparticulardomain usemoreinnovativeproducts.

Thefifthhypothesisstudiedinthe theoreticalmodelisthe relationshipbetweentheDSI andthe opinionleader. Innova-tiveconsumerstendmoretobeopinionleadersthanconsumers withconservativecharacteristics(Ruvio&Shoham,2007).The opinionleaderreflectstheabilityofanindividualtoinfluence otherconsumers(Ruvio&Shoham,2007).Fromthepointof viewofthecommunicationflowtheory(Lazarsfeld,Berelson, &Gaudet,1944),non-opinionleadersareseenasthereceivers of messagesfrom theleaders. Theopinions leaders are more knowledgeable andengagedwith products (Goldsmith etal., 1996),featurespresentintheDSI(Midgley&Dowling,1978; Roehrich,2004).Therefore,itisexpectedthat:

H5. TheDSIpositivelyaffectstheopinionleader,thatis,

con-sumerswithamoreinnovativeprofileinagivendomainhave morecharacteristicsofopinionleader.

The hypothesis six evaluates the possible relationship betweenDSIandthepropensitytoopiniosseeking.Consumers withlittle knowledge,or insecure,haveahigh probabilityto seekthe advice of others (Punj & Staelin, 1983). Moreover, consumers withinnovative features tend to be more open to receiving information about newexperiences andideas (Sun etal.,2006).Inthissense,GoldsmithandHofacker(1991)report astrongrelationshipbetweenconsumerinnovationandopinion seekingforbuyingvinylrecordsandfashion.Likewise,Flynn, Goldsmith, andEastman (1996) found the same relationship tofashionclothingproducts.Basedontheseassumptions,the followinghypothesisarises:

H6. The DSI positively affects the opinios seeking, that is,

consumerswithamoreinnovativeprofileseekmoreinformation onproductswithinnovativefeatures.

Theriskperceptionisthelatestconstructevaluatedinthe the-oreticalmodel.Riskperceptioncomesfromtheuncertaintythat consumersfacewhentheycannotpredicttheconsequencesof their purchasingdecisions(Aldás-Manzano, Lassala-Navarré, Ruiz-Mafé,&Sanz-Blas,2009),negativelyinfluencingthe deci-siontoadoptnewproducts.Studiesontheareashownegative

(Eastlick&Lotz,1999;Nakata&Sivakumar,1996)andneutral associations betweenthetwo relations(DelVecchio&Smith, 2005;Mitchell&Harris,2005).Inthisstudy,itisassumedthe negativerelationship,basedonresearchwhichrealizethatthis behaviorisatypicalfeatureoftheinnovativeprofile(Eastlick& Lotz,1999;Nakata&Sivakumar,1996;Truong,2013).Given this,itisproposedthefollowinghypothesis:

H7. TheDSInegativelyaffectstheperceptionofrisk,i.e.

con-sumerswithamoreinnovativeprofileinagivenareahavelower riskperception.

Methodology

The methodological approach used in this article is the deskresearch,whichischaracterizedbyaliteraturesearchon secondarydata,i.e.onstudiesalreadypublished.Forthe perfor-manceofthismeta-analysis,aregistrationprotocolwasadopted assuggestedbyMoher,Liberati,Tetzlaff,andAltman(2009),in whichwereincludedtheeligibilitycriteriatospecifythe charac-teristicsofthestudy.Thesecharacteristicsinvolved(i)definition of informationsources;(ii) collectionprocessandresearched variables;and(iii)datamanipulationmethodsandcombination of theresults.Theseproceduresweresimilartothoseusedin otherstudiesofthesamekind,appliedinthemarketingcontext (Santini,Ladeira,&Araujo,2014;Vieira,2010).

Definitionofinformationsources

Datacollectionbeganwithasurveyofallempiricalstudies usedinarecentsystematicreviewaboutconsumer innovative-ness (Bartels &Reinders, 2011).In addition,it has been set amanualsearchdirectlyinvolvingninedatabases,asfollows:

Jstor,Emerald,PsycINFO,ElsevierScienceDirect,SCOPUS,

Proquest,Scielo,GoogleScholarandEBSCO.Furthermore,it

were collectedstudiesinbanksof thesesanddissertationsof the leadingmasters anddoctorateprograms of themarketing andbusinessarea,whichwerewritteninEnglish,Portugueseor Spanish.

Collectionprocessandresearchedvariables

Thesearch variableswerebasedonthe studyproposedby

Goldsmith andHofacker (1991),which waspublished in the Journal ofthe Academy of MarketingScience. To searchfor workthatusedtheconstructdevelopedbytheauthors,therewas asearchfor theterms“MeasuringConsumerinnovativeness”, “Domain-SpecificInnovativeness”,“DSI”and“Goldsmithand Hofacker’sscale”inthefields“documenttitle”and“abstract”, using the search tools of the databases. Later, abook report waspreparedforeachstudy,beingpossibletoviewthemethod employed, key findings andfuture recommendations of each work,aswellasvariablesthatcouldinterferewiththe hetero-geneityofthestudies,suchasstudynaturemethod(surveyvs. experimental),subject(studentsvs.non-students),objectiveof study(productvs.service),evironment(laboratoryvs.field)and countryofapplicationoftheresearch(Westernvs.Eastern).

Intheinitialphaseofcollection,276studieswereidentified. Out of this, it was observedthat 68 could not bepart of the finalsample,bynotgeneratingquantitativedata.Ofthose276, 108 werenotanalyzedfor having aqualitativenature and22 fornothavingconstructsrelatedtotheobjectiveofthestudy. Fromthejustifiedexclusions(205),afinalsamplewasreached, consistingof78studies(76publishedworksandtwoworking papers),whichgenerated98validobservationsfortheanalysis ofthiswork.

Datamanipulationmethodsandcombinationoftheresults

Inthecoding,itwereincludedthetitlesofthepapers,journal, author(s),yearofpublication,statisticalindicesofthestudied relationships,reliabilityindicesandnumberofvariablesofthe appliedscales. Inaddition,itwereraisedvariablesthatcould causeheterogeneitybetweenstudies,asmentionedabove.

Itisnoteworthythatthearticleswereanalyzedandthecoding of datacarried out bytwo researchers fromthe fieldof mar-keting.Precedingthisactivity, theanalysis criteriahavebeen widelydiscussed,inordernot tohavedivergenceinthe pro-cess.Nevertheless,wherethereweredoubtsaboutthedatatobe extractedfromsomeworks,meetingswereheldwiththe partici-pationofthetwoevaluatorstomeetaconsensusonthecriterium used.

Inthedataanalysis,itwasusedthePearson’srcorrelation coefficientasametricvariabletomeasuretheeffectsizeonthe variablesofthestudiedscope.Forthestudiesthatdidnotreport the rcorrelation, the statisticsshown, for example, χ2,f-test, t-test,z-test,β-valueandp-value,wereconvertedtocorrelation coefficient,aprocedurerecommendbyRosenthal(1991)1and carried outinstudiesofthe samenature(Santini,Ladeira, & Araujo,2014;Vieira,2010).

Inrelationtothesizeeffectandtheheterogeneityofthe stud-ies,theproceduresrecommendedbyHedgesandOlkin(1985)

andRosenthal(1995)wereused.Whenthemagnitudeofthe cor-rectedeffectsizeissignificant,itisnecessarytocalculatethe failsafenumber(FSN=k((r/.05)−1));thisestimatesthe num-berofnon-significantand/orunpublishedstudiesthatwouldbe required for the size of the totalcumulative effectof a rela-tionship to be false (Rosenthal,1991). Yet the heterogeneity test(Cochran’sQtest(Q=_wiES_i2−(_wiES_I)2/_wi))is usedtodetectthe effectsofoutliers(Hedges&Olkin,1985). The confirmation of the null hypothesis confirms the hetero-geneitybetweenstudies,indicatingthatthedifferencebetween theeffectsizemaybeattributedtodifferentsamplingerrors,and thecharacteristicsofthestudiesmayberelatedasmoderating variablesofthatrelationship(Hunter&Schmidt,2004).

1 _{Conversioncalculationoftheeffectsizesstandardstatisticswasusedfor}

eachstudy.Pearson’srwasusedasthemeasureofeffectsize.Theformulas usedtocalculatetheeffectsizeswerederivedfromthestudiesofRosenthal (1991),beingtforr:r=√(t2_/(t2_{+df))wheredf=n}

1+n2−2;Fforr:r=√

(F/(F+dfError)),whereFindicatesanyFwithdf=1inthenumerator;andx2

forr:r=√(x2_{(1)/N).Whenmeansandstandarddeviationswereprovided,}

thesewereprocessed,Cohendiscalculatedbyd=(M1−M2)/σpooledandthen

convertedtor,calculatedr=d/(√(d2+4)).

Analysisoftheresults

78 workswere analyzed,asstated previously.Amongthis universe, thereare works dated from 1991to2014. Through

Fig.2,onecanseethegrowinginterestinthesubjectinrecent years. Thisfinding reinforcestheimportance ofthisresearch. Studieswithdifferentsamplesizeswereobserved,thesmallest had55respondentsandthelargesthad2972.Theaccumulated totalsamplewas40,641.RegardingtheCronbach’salpha reli-ability of the DSIconstruct, the datashowed that the lowest value wasα=0.600,andthelargerwasα=0.980, makingan averageofα=0.824.

To better understand the results of the meta-analysis, the results session wasdivided into two parts: (i)analysis of the relationshipshypothesizedinthemodeland(ii)analysisofthe moderatingeffects.

Analysisoftherelationshipshypothesizedinthemodel Table1presentsthesynthesisoftheresultsobtainedinthe meta-analysis,directlyexpressingtherelationshipbetweenthe DSIandtheconsequents.Itisnoteworthythattheeffectsfound inthestudiesanalyzedwerecodedandturnedintoeffectsize, Pearson’sr.Afterthat,theeffectsizewasadjustedbythe sam-plesizeandthereliabilityindicesofthescalesused,following theproceduresrecommendedbyHunterandSchmidt(2004).In addition,itwasverifiedtheconfidenceintervaloftheweighted effectsizeandtheheterogeneityofthestudies(Hedges&Olkin, 1985).Itwerealsocalculatedthefailsafenumberthatrefersto the amountof studiesnecessary for therejection of the find-ings inthis study (Rosenthal, 1991) and the binomial effect size display(BESD).TheBESDisaproceduredevelopedby

Rosenthal and Rubin (1991) that is used to demonstrate the practicalapplicationsofaneffectsize,fromtheobservedeffects. TheanalysisofthedirectrelationshipsbetweenDSIandits consequentsinvolvedthecodingofallexistingrelationsinthe constructs and an assessment of their effects. Regarding the hypothesisH1,itwasexpectedapositiveandsignificant

relation-shipbetweenDSIandadoptionofinnovation.Theresultsarein linewithstudiesfromRogers(1995)anddemonstratesupport for the aforementioned hypothesis,since therewas a signifi-cantandpositiveeffect(r=0.340,p<0.001)betweenthetwo behaviors.Academically,thisdatumbringsconsolidationtothe

9 8 7 6 5 4 3 2 1 0 1995 2000 2005 Year of publication Domain-Specific Innovativeness 2010 2015 Number of ar ticles pub lished

Table1

Synthesisofthemeta-analysisresults.

Relationship k o N ESrange ES ESN ESrN CI Q FSN BESD

Consequents H1–Innovationadoption 9 10 7423 −0.04to0.49 0.28 0.27 0.34*** 0.210.46 191.24*** 2565 0.65 H2–Attitude 9 12 4665 0.08to0.43 0.27 0.26 0.32*** 0.240.41 64.27*** 1904 0.66 H3–Behavioralint. 24 36 17,820 0.00to0.76 0.31 0.33 0.40*** 0.330.48 814.57*** 35,345 0.70 H4–Productusage 8 9 2726 0.15to0.57 0.37 0.34 0.40*** 0.270.53 77.04*** 1855 0.70 H5–Opinionleader 15 16 3413 0.18to0.73 0.50 0.49 0.61*** 0.500.72 158.78*** 11,259 0.80 H6–Opiniomseeking 10 10 3283 −0.56to0.81 0.10 0.13 0.16† −0.580.91 353.55*** N/C N/C H7–Riskperception 3 5 1311 −0.33to−0.16 −0.23 −0.23 −0.28*** −0.39–0.19 10.96* 143 0.35 Sum 78 98 40,641

Notes:k,numberofstudiesusedforanalysis;o,numberofobservationstakenfromstudiesforanalysis;N,numberofaccumulatedsamplesoftheevaluatedstudies;

ESrange,minimumandmaximumsimplecorrelationfoundinthestudies;ES,simpleaverageoftheeffectsizesfoundinstudies;ESN,weightedandadjustedaverage

oftheeffectsizesextractedfromstudies;ESr,weightedaverage,adjustedfromthesample,andreliabilityobtainedinthestudies;CI,minimumandmaximum

confidenceinterval;Q,heterogeneitytestatindividualandaggregatelevel;FSN,failsafenumber,numberofitemsneededfortheresulttobefalse;BESD,percentage ofthepracticalapplicationofthefinding.

† _{p>0.05(significancelevel).}

* _{p<0.05(significancelevel).}

**p<0.01(significancelevel).

***_{p<0.001(significancelevel).}

theoreticallinethatsuggestsapositiveassociationbetweenthe DSIandthepropensitytoadoptnewproducts(Citrinetal.,2000; Huotilainen,Pirttilä-Backman,&Tuorila,2006).Managerially, andthroughBESDanalysis,onecansaythat65%ofconsumers withDSIfeatureswouldchoosetoadoptanewproduct.This datumstrengthenstheimportancethatmanagersshouldgiveon identifyingthecharacteristicsoftheirtargetaudience,sincethe largeportionofinnovationadoptersinaparticularareawould presentapredispositiontotrynewproducts.

The hypothesis H2 predicted a positive and significant

relationship between DSI and attitude. The results sup-ported the hypothesis H2 (r=0.329, p<0.001; FSN=1,904;

BESD=0.66). This finding brings greater consistencyto the line of research that suggests the productionof favorable or unfavorablebehaviors on aproductor service from the con-sumercharacteristics linkedtoDSI(Caroetal.,2011;Gefen, Karahanna,&Straub,2003;Karahanna, Straub,&Chervany, 1999).Inpractical terms,it isobservedthat 66%of the con-sumerswiththeaforementionedcharacteristics wouldtendto generate opinions resulting from the contact with a good or service.

InhypothesysisH3,apositiverelationshipbetweenDSIand

behavioralintentionwasexpected.Thisassumptionwasbased onthepreceptthatconsumerswithinnovativefeaturestendto havetheintentiontoadoptmoreinnovations(Caroetal.,2011), sincethepriorknowledgeofacertainclassofproductsincreases theabilitytodetectnewtopproducts(Hirschman,1980).The resultsfoundandshowninTable1 corroboratethisacademic prerogative(r=0.404, p<0.001;FSN=35,345).Furthermore, itisobservedaninterestingmanagementapplicabilitysincethe BESDanalysisindicatesthat70%oftheconsumerswithDSI characteristics tendtohaveapositiveintentiontopurchase a newproduct.

ThehypothesisH4predictedapositiverelationshipbetween

theDSIandtheconsequent,usinganewproduct.The propo-sitionwasbasedontheoriesthatstatethatthemoreinnovative

the consumer profilethe largestis the propensity tousenew products (Goldsmith, 2001;Wong, 2012).The findings show significantrelationshipswithrforce=0.409(p<0.001),being necessary1,855studieswithconflictingresultsforrejectingthis hypothesis.TheBESDtestshowedthat70%ofDSIconsumers haveapropensitytouseanewproduct.Managerscanmapthe characteristicsoftheircustomerstoidentifypotentialbuyersin launchingnewgoodsandservices.

Hypothesis H5 anticipated asignificant and positive

asso-ciation between the DSI and the construct opinion leader. From the analysis performed, it was detected a very strong correlation(r=0.613,p<0.001;FSN=11,259),which consol-idatesthetheorythatinnovativeconsumersaremoreinvolved, and are connoisseurs of newproducts (Midgley & Dowling, 1978;Roehrich,2004).Inpractice,averysignificantportionis observed(BESD=80%)amongconsumerswithDSIfeatures thathavethepropensitytoplaytheroleofopinionleader.The relationshipbetweenDSIandopinionseekingwastestedfrom theH6.Inthiscase,itisobservedthatrelationshipwasnot

sig-nificant,asitisobservedzerobetweenitsconfidenceinterval (r=0.166,p=ns).

Finally,itwasexpectedanegativerelationshipbetweenDSI andriskperception(H7).Theresultsconfirmedtheassumption

(r=−0.289, p<0.001; FSN=143). Thus,it is reinforced the ideathatthemoreinnovativetheconsumer,thelowerhis/herrisk perceptioninrelationtoadoptnewproducts(Conchar,Zinkhan, Peters,&Olavarrieta,2004).Itisverifiedthat,inpracticalterms, theprobabilityofthisoccurringisin35%oftheDSIconsumers. To endthe dataanalysis chapter,andinordertoillustrate the hypothesizedresults betweenDSI andits consequents,is presented,throughFig.3,theforestplotgraphwhereonecansee themagnitudeoftheeffectsizesandtheirconfidenceintervals foreachofthehypothesesraised.Inthisgraph,theweightgiven toeachstudyisweightedinthesizeofthebox(morespecifically, bythearea)andtheconfidenceintervalsize–highandlow(95%) –intheparallellines.

–1.0 –0.5 0.0 Effect size Consequents H1 – Innovation Adoption H2 – Attitude H3 – Behavioral Intention H4 – Product Usage H6 – Opinion Seeking H7 – Risk Perception H5 – Opinion Leadership 0.5 1.0

Fig.3.Forestplot.

BasedonFig.3,itisseenahighervariabilityofeffectssize betweentheDSIandtheopinionseeking.Itisnotedthatthe con-fidence intervals were substantiallydistinct, −0.58and 0.91, whichis characterizedas aheterogeneity of theeffects sizes producedinthestudiesthatinvestigatedtherelationship.In con-trast, whenobserving thedimensions of behavioralintention, opinionleaderandriskperception,despitehavingalow confi-denceinterval,Qtestshowedheterogeneityamongthestudies thatmakeuptheserelationships.Completedtheanalysisofthe hypothesizedrelationships,thestudygoesonanalyzingpossible methodologicalmoderatorsoftheserelationship.

Meta-regressionofthemethodologicalmoderators

Acommonproceduretotestwhetherthecharacteristicsof thestudiesmayexplainthevariabilityineffectsizesisthe meta-regression. This analysis uses the effects sizes as dependent variablesandthemoderatingvariablesasindependentvariables (Hedges& Olkin,1985; SzymanskiandHenard, 2001). It is emphasizedthatforthisanalysistobeapplied,itmustfollow thenextconditions:(i)whentheQstatistic, correspondingto theheterogeneityoftheeffectsizes,isgreaterthan25%(Hunter &Schmidt,2004);(ii)whenthenumberofobservationsisequal toorgreaterthan14,sincelowernumberswouldbeinsufficient tonoticechangesinbehaviorthroughmoderators,becausethe lowstatisticalpowerofthesamplethreatenstheconfidencein theresults(Hunter&Schmidt,2004).

Guidedontheabovereasons,itwasheldthetestofthe mod-erating effectof the methodological applications only inthe relations betweenDSIandbehavioralintention and;DSIand opinionleader.Intotal,fiveequationsforeachrelationshipwere examinedinordertoverify themethodologicalvariablesthat couldmoderatetherelationshipbetweentheDSIconsequents: research method (survey vs. experimental); subject (students vs.non-students);environment(fieldvs.laboratory);objectof study(productvs.service);countryofapplication(Westernvs. Eastern).

Table2 shows the resultsof the moderation analysis.The relationshipbetweenDSIandbehavioralintentionshowed mod-eration effect on the object of the study (rproduct=0.34 vs rservice=0.14;f(1.34)=6.061;p=0.01).Academically,itis

rein-forced the proposition of Parasuraman, Zeithaml, and Berry (1985),wherein products are characterizedas more homoge-neous than services and, consequently, may produce greater effectsize (Fern andMonroe, 1996).Managerially, it canbe assumed that innovativeproducts will tendtoinfluencemore

strongly the purchase intent of consumers with DSI features thantheservices.Fortheotherrelationstherewasnosignificant differenceinthemoderatingeffect.

IntherelationshipDSIandopinionleaderitisnotedthatthe researchmethodexertedasignificantmethodological moderat-ingrole.Theeffectsizeinthisrelationshipisstrongerwhenits application occursthrough survey (β=−0.610,p<0.01)than when theexperimentalmethodisperformed(rsurvey=0.53vs. rexperimental=0.17;f(1.14)=8.315;p=0.01).Theresultfoundin

thisresearchiscontrarytotheassumptionthat in experimen-talstudiesitiscommontofindgreaterexplanatorypowerofthe effectsizes,sincethefeatureofthisresearchallowsthe random-izationofrespondentstodifferentgroupsandthecontroloverthe interveningvariables(AugustodeMatosetal.,2009).Moreover, itwasobservedthattheremainingvariableshavenomoderating effectontherelationshipsbetweenDSIandbehavioralintention andopinionleader.

Finalconsiderations

Thispaperproposedameta-analyticstudyoftheconstructs associated with DSI introduced by Goldsmith and Hofacker (1991).Theperformanceofthemeta-analysisallowedto inves-tigate quantitatively the main findings associated with the analyzedconstruct.Thesynthesisofthedatastatisticspresented herewasbasedonmathematicalcriteria,asproposedbyHedges andOlkin (1985)andHunterandSchmidt(2004),unlike the conventionalliteraturereviews,inwhichtheauthorsimplicitly assignalevelofimportanceforeachstudy,makinginferences onthefindings(Bartels&Reinders,2011).Suchfactleadsthis worktoshowimportantcontributionsfor researcharound the constructsstudiedhere.

Thisstudyprovidesimportantcontributionsforresearchers andscholarsofthesubject.First,itworksinconjunctionwith constructswhicharealoneinseveralarticlespublishedinthelast twodecades.Second,itallowsidentifyingrelationshipsbetween theDSIanditsmainconsequents.Basedontheresults,ithas been possible todetectasignificant relationshipbetween the DSIandallinvestigatedconsequents(innovationadoption, atti-tude, behavioralintention, productusage, opinionleaderand riskperception),exceptopinionseeking.

Therelationshipsweresignificantandpositiveforallraised relationships, exceptfor the risk perception, whichshoweda negativerelationshipwithDSI(ES=−0.289).Theeffectofthe relationshipbetweenDSIandopinionleadershowedastrong effectsize(ES=0.613).Therelationswiththeadoptionof inno-vation,attitude,behavioralintentionanduseofanewproduct hadan averagemagnitudeof theeffects (0.329<ES<0.409). Animportantfindingforthismeta-analysiswastheeffectsize foundfortherelationshipestablishedbetweenDSIandopinion seeking;wichcanbeverifiedthatthereisnon-significanteffect size(ES=0.166;p>0.50),wichshowsnulleffectsize.

In addition, the meta-regression was performed to test whetherthecharacteristicsofthestudiesinterferewiththe vari-ability ofthe effectssize (Hedges&Olkin,1985;Szymanski andHenard,2001).Themoderatingeffectofthe methodologi-cal applicationswasconductedonlyinrelationsbetweenDSI

Table2

Methodologicalmoderatoreffect.

Moderatingvariable Behavioralintention Opinionleader

β t-Value β t-Value

Method(surveyvs.experimental) −0.038 −0.099+ _{−0.610 −2.884}**

Subject(studentsvs.non-students) −0.015 −0.029+ _{0.248 1.114}+

Environment(laboratoryvs.field) −0.026 −0.056+ _{−0.248 −1.114}+

Object(productvs.service) −0.449 −2.338* _{−0.288 1.395}+

Country(Westernvs.Eastern) 0.106 0.539+ _{−0.174 0.797}+

R2adjusted _{2% 32%}

Note:β,standardizedadjustedbeta.

+ _p=ns.

* _p=0.05. ** _p=0.01.

andbehavioralintentionandopinionleader.Ascanbeseen,the meta-regressionshowedthattheresearchmethodhasa moder-atingeffectontherelationshipbetweenDSIandopinionleader. YetintherelationshipbetweenDSIandbehavioralintention, asignificant difference is observed tothe objectof study, in thisparticularcase,productorservice.Itishighlighted,inthis case,thatthestrongesteffectssizearepresentedmorefor prod-ucts withinnovative features thanfor innovation inservices. Moreover,theremainingvariablesshowednon-significanteffect sizes.

Thismeta-analysisshowstobepromisingfor managersof companiesworkingwithinnovativeproducts,sinceitshowsthe impactofDSIinsevendirectconsequents.Thesemanagerscan bestdeveloptheirstrategies,buildingandmaintainingstronger relationswiththeircustomers,oncetheyknowthatthestrongest relationshipswithDSIfollowthisorder:opinionleader,useofa newproduct,behavioralintention,innovationadoption,attitude andriskperception.

Thelimitationspresentedinthisstudypertaintotheproblems inherentinexecutingameta-analysisinafieldofknowledge, guidedbasicallyontheamountofdatacollected,samplesize andstudydesign.Theamountofdatacollectedisdirectlyrelated totheaccuracywithwhichtheeffectsizeis estimated. Rela-tionshipsthathaveasignificant numberof observations(e.g., behavioralintentionsandopinionleader)willtendtoprovide morepreciseestimatesoftheeffectsizesinrelationtotheothers. As a suggestion for future research, it is recommended toinvestigatepossibleconsequentsthat were notinvestigated in this meta-analysis, such as: mouth-to-mouth, satisfaction, loyalty, commitment, among others. The analysis of these constructs was not performed in this study, in virtue of the few relationships found in the literature, which shows a possibility of future investigations. It is also suggested a meta-analysis with possible antecedents or correlates of the DSI.

Anotherimportantpointtohighlightinfuturestudiesisthe analysisofnewmoderators.Theheterogeneitybetweenalmost everyrelationship requires further investigation to determine othermoderatorsthatmayinfluencetheeffectivenessoftheDSI. Finally,thisarticleproposedtogenerateatheoreticalmodeland thereforetocreateanopportunityofinsightstoresearchersand academicstobetterbuildtheirresearchintheDSIapproach.

Conflictsofinterest

Theauthorsdeclarenoconflictsofinterest.

Acknowledgments

The authors thank CAPES/CNPqfor founding, the editor, associateeditorandthereviewersfortheirinvaluablefeedback andguidanceatvariousstagesofthisproject.

References

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

Agarwal,R.,&Prasad,J.(1998).Aconceptualandoperationaldefinitionof per-sonalinnovativenessinthedomainofinformationtechnology.Information SystemResearch,9(2),204–215.

Aldás-Manzano,J.,Lassala-Navarré,K.,Ruiz-Mafé,C.,&Sanz-Blas,S.(2009).

Theroleofconsumerinnovativenessandperceivedriskinonlinebanking usage.InternationalJournalofBankMarketing,27(1),53–75.

AugustodeMatos,C.,VargasRossi,C.A.,TeixeiraVeiga,R.,&AfonsoVieira, V.(2009).Consumerreactiontoservicefailureandrecovery:themoderating roleofattitudetowardcomplaining.JournalofServicesMarketing,23(7),

462–475.

Bartels,J.,&Reinders,M.J.(2011).Consumerinnovativenessanditscorrelates: Apropositionalinventoryforfutureresearch.JournalofBusinessResearch, 64(6),601–609.

Black,J.S.(1982).Opinion leaders:Isanyonefollowing?Public Opinion Quarterly,46(2),169–176.

Caro,A.,Mazzon,J.,Caemmerer,B.,&Wessling,M.(2011).Inovatividade, envolvimento,atitudeeexperiêncianaadoc¸ãodecompraon-line.RAE– RevistadeAdministra¸cãodeEmpresas,SãoPaulo,52(6).

Citrin,A.V.,Sprott,D.E.,Silverman,S.N.,&Stem,D.E.,Jr.(2000). Adop-tionofinternetshopping:Theroleofconsumerinnovativeness.Industry ManagementDataSystem,100(7),294–300.

Conchar,M.P.,Zinkhan,G.M.,Peters,C.,&Olavarrieta,S.(2004).An inte-gratedframeworkfortheconceptualizationofconsumers’perceived-risk processing.JournaloftheAcademyofMarketingScience,32(4),418–436.

Crespo,H.A.,&DelBosque,I.R.(2008).Theeffectofinnovativenesson theadoptionofB2Ce-commerce:Amodelbasedonthetheoryofplanned behaviour.ComputersinHumanBehavior,24(6),2830–2847.

DelVecchio,D.,&Smith,D.C.(2005).Brand-extensionpricepremiums:The effectsofperceivedfitandextensionproductcategoryrisk.Journalofthe AcademyofMarketingScience,33(2),184–196.

Eastlick,M.A.,&Lotz,S.(1999).Profilingpotentialadoptersandnon-adopters ofaninteractiveelectronicshoppingmedium.InternationalJournalofRetail &DistributionManagement,27(6),209–223.

Farley, J.U.,Lehmann,D.R.,& Sawyer, A.(1995).Empiricalmarketing generalizationusingmeta-analysis.MarketingScience,14(3supplement), G36–G46.

Feick,L.F.,&Price,L.L.(1987).Themarketmaven:Adiffuserofmarketplace information.JournalofMarketing,51(1),83–97.

Fern,E.F.,&Monroe,K.B.(1996).Effect-sizeestimates:Issuesandproblems ininterpretation.JournalofConsumerResearch,89–105.

Flynn,L.R.,&Goldsmith,R.E.(1993).AvalidationoftheGoldsmithand Hofackerinnovativenessscale.EducationalandPsychological Measure-ment,53,1105–1116.

Gao,T.T.,Rohm,A.J.,Sultan,F.,&Pagani,M.(2013).Consumersun-tethered: Athree-marketempiricalstudyofconsumers’mobilemarketingacceptance.

JournalofBusinessResearch,66(12),2536–2544.

Gao,T.,Rohm,A.J.,Sultan,F.,&Huang,S.(2012).Antecedentsofconsumer attitudestowardmobilemarketing:Acomparativestudyofyouthmarkets intheUnitedStatesandChina.ThunderbirdInternationalBusinessReview, 54(2),211–224.

Gatignon,H.,&Robertson,T.S.(1991).Innovativedecisionprocesses.InT. S.Robertson,&H.H.Kassarjian(Eds.),Handbookofconsumerbehavior

(pp.316–324).EnglewoodCliffs,NJ:Prentice-Hall.

Gefen,D.,Karahanna,E.,&Straub,D.W.(2003).TrustandTAMinonline shopping:Anintegratedmodel.MISQuarterly,27(1),51–90.

Goldsmith,R.E.(2001).Usingthedomainspecificinnovativenessscaleto identifyinnovativeinternetconsumers.InternetResearch,11(2),149–158.

Goldsmith,R.E.,d’Hauteville,R.E.,&Flynn,L.R.(1998).Theoryand mea-surementofconsumerinnovativeness:Atransnationalevaluation.European JournalofMarketing,32(3/4),340–353.

Goldsmith,R.E.,Eastman,J.,&Freiden,J.(1996).Thegenerality/specificity issueinconsumerinnovativenessresearch.Technovation,15(10),601–612.

Goldsmith,R.E.,&Flynn,L.R.(1995).Thedomainspecificinnovativeness scale:Theoreticalandpracticaldimensions.AssociationforMarketing The-oryandPracticeProceedings,4(1995),177–182.

Goldsmith,R.E.,&Flynn,L.R.(1992).Identifyinginnovatorsinconsumer productmarkets.EuropeanJournalofInnovationManagement, 26(12),

42–55.

Goldsmith,R.E.,&Goldsmith,E.B.(1996).Anempiricalstudyofoverlapof innovativeness.PsychologicalReports,79,1113–1114.

Goldsmith,R.E.,&Hofacker,C.F.(1991).Measuringconsumerinnovativeness.

JournaloftheAcademyofMarketingScience,19,209–221.

Goldsmith,R.E.,Kim,D.,Flynn,L.R.,&Kim,W.M.(2005).Pricesensitivity andinnovativenessforfashionamongKoreanconsumers.JournalofSocial Psychology,145(5),501–508.

Grewal,R.,Mehta,R.,&Kardes,F.R.(2000).Theroleofthesocial-identity functionofattitudesinconsumerinnovativenessandopinionleadership.

JournalofEconomicPsychology,21(3),233–252.

Hedges,L.V.,&Olkin,I.(1985).Statisticalmethodsformeta-analysis.Orlando, FL:AcademicPress.

Hirschman,E.C.(1980).Innovativeness,noveltyseeking,andconsumer cre-ativity.JournalofConsumerResearch,283–295.

Hirunyawipada,T., &Paswan,A.K.(2006).Consumerinnovativenessand perceivedrisk:Implicationsforhightechnologyproductadoption.Journal ofConsumerMarketing,23(4),182–198.

Hunter,J.E.,&Schmidt,F.L.(2004).Methodsofmeta-analysis:Correcting errorandbiasinresearchfindings(2nded.).NewburyPark,CA:Sage.

Huotilainen,A.,Pirttilä-Backman,A.M.,&Tuorila,H.(2006).How innova-tivenessrelatestosocialrepresentationofnewfoodsandtothewillingness totryandusesuchfoods.FoodQualityandPreference,17(5),353–361.

Karahanna,E.,Straub,D.W.,&Chervany,N.L.(1999).Informationtechnology adoptionacrosstime:Across-sectionalcomparisonofpre-adoptionand post-adoptionbeliefs.MISQuarterly,183–213.

Kim,W.,DiBenedetto,C.A.,&Lancioni,R.A.(2011).Theeffectsofcountry andgenderdifferencesonconsumerinnovativenessanddecisionprocesses inahighlyglobalizedhigh-techproductmarket.AsiaPacificJournalof MarketingandLogistics,23(5),714–744.

Santini,F.O.,Ladeira,W.J.,&Araujo,C.F.(2014).Antecedentese Conse-quentesdaInfluênciaInterpessoal:UmaMeta-AnálisedaEscalaSUSCEP. InVIEncontrodeMarketingdaANPAD,Gramado-RS.

Lazarsfeld,P.F.,Berelson,B.,&Gaudet,H.(1944).Thepeople’schoice.New York:Duell,Sloan,andPearce.

Flynn,L.R.,Goldsmith,R.E.,&Eastman,J.K.(1996).Opinionleadersand opinionseekers:Twonewmeasurementscales.JournaloftheAcademyof MarketingScience,24(2),137–147.

Midgley,D.F.,&Dowling,G.R.(1993).Alongitudinalstudyofproductform innovation:Theinteractionbetweenpre-dipositionsandsocialmessages.

JournalofConsumerResearch,19,611–625.

Midgley,D.F.,&Dowling,G.R.(1978).Innovativeness:Theconceptandits measurement.JournalofConsumerResearch,4(2),229–242.

Mitchell, V. W., & Harris, G. (2005). The importance of consumers’ perceivedriskinretailstrategy.EuropeanJournalofMarketing,39(7/8),

821–837.

Moher,D.,Liberati,A.,Tetzlaff,J.,&Altman,D.G.(2009).Preferredreporting itemsforsystematicreviewsandmeta-analyses:ThePRISMAstatement.

AnnalsofInternalMedicine,151(4),264–269.

Nakata, C., & Sivakumar, K. (1996). National culture and new prod-uct development: An integrative review. Journal of Marketing, 60(1),

61–72.

Parasuraman,A.,Zeithaml,V.A.,&Berry,L.L.(1985).Aconceptualmodelof servicequalityanditsimplicationsforfutureresearch.JournalofMarketing, 49,41–50.

Punj, G. N., & Staelin, R. (1983). A model of consumer information search behavior for new automobiles. Journal of Consumer Research,

366–380.

Robertson,T.S.(1971).Innovativebehaviorandcommunication.NewYork, NY:Holt,RhinehartandWinston.

Roehrich,G.(2004).Consumerinnovativenessconceptsandmeasurements.

JournalofBusinessResearch,57,671–677.

Rogers,E.M.(1995).Diffusionofinnovations(4thed.).NewYork,NY:The FreePress.

Rogers,E.M.(2003).Elementsofdiffusion.Diffusionofinnovations(5thed., pp.1–38).

Rosenthal,R.(1991).Meta-analyticproceduresforsocialresearch(rev.ed.). NewburyPark,CA:Sage.

Rosenthal,R.(1995).Writingmeta-analyticreviews.Psychologicalbulletin, 118(2),183–197.

Rosenthal,R.,&Rubin,D.B.(1991).Furtherissuesineffectsizeestimation forone-samplemultiple-choice-typedata.PsychologicalBulletin,109(2),

351–352.

Ruvio,A.,&Shoham,A.(2007).Innovativeness,exploratorybehavior,market mavenship,andopinionleadership:AnempiricalexaminationintheAsian context.Psychology&Marketing,24(8),703–722.

Shoham,A.,&Ruvio,A.(2008).Opinionleadersandfollowers:Areplication andextension.Psychology&Marketing,25(3),280–297.

Steenkamp,J.-B.E.M.,Hofstede,F.,&Wedel,M.(1999).Across-national investigationintotheindividualandnationalculturalantecedentsof con-sumerinnovativeness.JournalofMarketing,63,55.

Sun,T.,Youn,S.,Wu,G.,&Kuntaraporn,M.(2006).Onlineword-of-mouth (ormouse):Anexplorationofitsantecedentsandconsequences.Journalof ComputerMediatedCommunication,11(4),1104–1127.

Szymanski,D.M.,&Henard,D.H.(2001).Customersatisfaction:A meta-analysisoftheempiricalevidence.JournaloftheAcademyofMarketing Science,29(1),16–35.

Truong,Y.(2013).Across-countrystudyofconsumerinnovativenessand tech-nologicalserviceinnovation.JournalofRetailingandConsumerServices, 20(1),130–137.

Vieira,V.A.(2010).Antecedentsandconsequencesofmarketingorientation:A Brazilianmeta-analysisandaninternationalmega-analysis.BAR–Brazilian AdministrationReview,7(1),40–58.

Zhang,B.,&Kim,J.H.(2013).LuxuryfashionconsumptioninChina:Factors affectingattitudeandpurchaseintent.JournalofRetailingandConsumer Services,20(1),68–79.

Wong,C.B.(2012).Facebookusagebysmallandmedium-sizedenterprise:The roleofdomain-specificinnovativeness.GlobalJournalofComputerScience andTechnology,12(4).