Applied Soft Computing

ContentslistsavailableatSciVerseScienceDirect

Applied

Soft

Computing

jo u r n al h om e p a g e :w w w . e l s e v i e r . c o m / l o c a t e / a s o c

Website

success

comparison

in

the

context

of

e-recruitment:

An

analytic

network

process

(ANP)

approach

Abbas

Keramati

,

Mona

Salehi

a_{AssociateProfessorofIndustrialEngineeringDepartment,FacultyofEngineering,UniversityofTehran,Tehran,Iran} b_{LuleaUniversityofTechnology,Sweden}

a

r

t

i

c

l

e

i

n

f

o

Received31July2010

Receivedinrevisedform17July2012

Accepted4August2012

Availableonline23August2012

Keywords:

e-Commerce,e-Recruitment,Analytic

networkprocess(ANP),UpdatedDelone

andMcLeanISSuccessModel

a

b

s

t

r

a

c

t

Thisstudyinvestigatesrelativeimportanceofwebsitesuccessfactorsinselectingthemostpreferred website.Toidentifyrelativeimportanceofwebsitesuccessfactorsandtorankalternativewebsiteswith respecttosuccessfactors,UpdatedDeloneandMcLeanInformationSystemSuccessModelisextended throughapplyingananalyticnetworkprocess(ANP)approach.Afieldstudywith383academicinternet userswasperformed.Relativeimportanceofeachwebsitesuccessfactorwithrespecttotheirinfluence onusingthee-recruitmentwebsite,andusersatisfactionareidentified.Furthermorerelativesignificance ofusingthee-recruitmentwebsiteandusersatisfactioninachievingpositivebenefitsarediscovered. Thisstudyalsofoundtherelativepreferenceofeachwebsitewithrespecttodifferentsuccessvariable.

ResultsindicatethatANPisaneffectivetooltoprovideanaccuratesolutionforinterdependenciesthat areabletoaffectthedecisiontobemadefornetworklikemodels.Thefindingsofthisstudyprovide decisionmakersofe-commercecompanieswithusefulinsightstocomparethepreferenceoftheir web-sitewithotherswithrespecttodifferentsuccessvariables.Moreover,relativesignificanceofdifferent successvariablesinwebsitescanbecompared.

©2012ElsevierB.V.Allrightsreserved.

1. Introduction

Websitechangestheroleofaconsumerfromapassiverecipient toaproactiveone[1].Hence,e-commerceistheshiftofthepower towardtheconsumer,whichcontributestofundamentalchanges inthewaycompaniesrelatetotheircustomersandcompetewith one another[2]. Thereare almostnobarriers for customersto switchtoanalternativewebsitesifperformanceisunacceptable [3].

Somepreliminarystudies[4]indicateawidegapbetween antic-ipatedandactualachievementsfrome-commercesystems.This hasmotivatedanumberofstudiestolookforfactorsthatinhibit e-commercesuccess[5].

Onlinerecruitmentservicesareamongthemostpopular appli-cations on the internet [6]. Since employers are required to payfortheservice,theirperceptions ofthelevelof serviceare typicallytheconcernofmostrecruitmentwebsitesandthe recruit-mentservicequalitylevelforthejobseekersistypicallyignored [7]. Therefore, study of e-recruitment websites success from

∗Correspondingauthor.Tel.:+982188021067;fax:+982182084194.

E-mailaddresses:[email protected](A.Keramati),[email protected]

(M.Salehi).

jobseekers’perceptionisofprominenceforonee-recruitment web-sitetostayprofitableincompetitiveenvironment.

Recently,onlinerecruitmentwebsitesstartedworkinginIran. According to Amuzegar [8], Iran’s current active laborforce is broadlyestimatedtobelessthan32%ofthetotalpopulation.This figurecomparespoorlywiththe50–60%laborparticipationinother countries.

Thisstudyhastwoobjectives:thefirstistofindrelative impor-tanceofe-recruitmentwebsitesuccessfactorsandthesecondisto findrelativepreferenceofe-recruitmentwebsiteswithrespectto eachwebsitesuccessfactorinIran.

2. Background

2.1. Evaluatinge-recruitmentwebsitesuccess

Several modelshave beendeveloped from 1980s for inves-tigating Information System (IS)success and the broader term websitesuccess.However,fewstudiesconsideredthecombination ofinformationsystemqualityandonlineservicequalityvariables ascomponentsofwebsitesuccess.UpdatedDeloneandMcLean IS SuccessModel[9] (Fig.1)isone ofthehighly citedmodels; whichconcernsbothISandServicequalityasantecedentsof web-sitesuccess.Thismodelcanbeadaptedtomeasurementchallenges ofnewe-commerceworld[9].DeloneandMcLean[10]classified

1568-4946/$–seefrontmatter©2012ElsevierB.V.Allrightsreserved.

174 A.Keramati,M.Salehi/AppliedSoftComputing13(2013)173–180 Table1

e-Commercesuccessmeasures[10].

Reference DimensionsofUpdatedDelone

andMcLeanISSuccessModel (2003)

e-Commercesuccess measures

Definition

Daughtrey[11] Servicequality Assurance Reportofexperienceofothercustomers

Iwaardenetal.[12] Empathy Virtualassistant,offeringproductand

servicestoonlinecustomers

Iwaardenetal.[12] Responsiveness Givingpromptservice,amountoftime

ittakestodownloadaWebpage

Friedmanetal.[13] SystemQuality Privacy Protectionofpersonalinformation

Palmer[14];Mollaetal.[15] Easeofnavigation

Palmer[14] Customization Interactionwithwebsiteusers

Mollaetal.[15] InformationQuality Dynamiccontent Preparedfreshinformationforeach

individualviewing

Baruaetal.[16],Mollaetal.[15] Contentpersonalization Deliveredcontentinreal-timespecific

totheindividual

Palmer[14] Varietyofinformation Diversityofinformationonthewebsite

D’Ambraetal.[17];Mollaetal.[15] Use Numberofapplications

sentthroughe-recruitment

website

Numberofpurchasescompleted

ReichheldandSchefter’s[18] Usersatisfaction Repeatvisits e-Loyalty

D’Ambraetal.[17] Netbenefits Betterdecision Tomakebetterdecisionbecauseof

informationonthewebsite

newlydevelopedmeasuresine-commerceenvironment,intosix dimensionsofUpdatedDeloneandMcLeanISSuccessModel[9] (Table1).

2.2. ANPstructureofe-commercewebsitesuccess

Saaty[19]statesthatbecauseoftheinteractionandfeedbacks betweendifferentlevelsofthestructure,manydecisionscannot bestructuredhierarchically,becausetheyinvolvetheinteraction anddependenceofhigherlevelelementsonlowerlevelelements. AccordingtoSaaty[20],ANPisthefirstmathematicaltheorythat makesitpossibletodealsystematicallywithallkindsof depend-enceandfeedback.

UpdatedDeloneandMcLeanISSuccessModel[9]doesnothave alineartoptobottomformofahierarchybutlooksmorelikea networkwithcyclesconnectingitsclusterofelements.Therefore toidentifyrelative importanceofdifferentsuccessvariableand torankalternativewebsites,UpdatedDeloneandMcLeanIS Suc-cessModel[9]willbedevelopedthroughanalyticnetworkprocess (ANP)approach[21].

Leeet al., [22],investigated theeffect ofwebsite qualityon e-businesssuccess. They extended original Delone and McLean ISSuccessModel[23]byapplyingananalytichierarchyprocess approach.DeloneandMcLeanISSuccessModel[23]hasalineartop tobottomformofahierarchy.ByadoptingDeLoneandMcLean’s ISSuccessModel[23]andapplyinganAHPmethod,Leeetal.,[22] investigatedrelativeimportanceofeachsuccessfactorinranking thealternativewebsites.

According toSaaty [20], ANP is the first mathematical the-orythat makesit possibletodealsystematically withallkinds ofdependenceandfeedback.Althoughseveralquantitative tech-niqueshave beenapplied,this studyhaspresentedtheANP as a decision analysistool ininvestigating websitesuccessfactors andcapturinginterdependenciesamongvariouscriteriawhichhas rarelybeenappliedininvestigationofwebsitesuccess.

Eliciting preferences of various components and attributes requires a series of pair-wise comparisons where the decision makerwillcomparetwocomponentsat atime withrespectto sourceorparentcriterion.Nodesthataretobepair-wisecompared arealwaysallinthesameclusterandarecomparedwithrespectto theirparent(source)element,thenodefromwhichtheyare con-nected.Thisresultsinlocalprioritiesofthenodeswithrespectto thesourcenode.Saaty[24]hassuggestedascaleof1to9when comparingtwocomponents,withascoreof1representing indif-ferencebetweenthetwocomponentsand9beingoverwhelming dominanceofthecomponentunderconsiderationoverthe com-parisoncomponent(AppendixA).UpdatedDeloneandMcLeanIS SuccessModelisshown inFig.1.In Fig.2,Deloneand McLean UpdatedISSuccessModelisextendedthroughANPinthisstudy.

A. Keramati, M. Salehi / Applied Soft Computing 13 (2013) 173–180 175 Unweightedsupermatrix.

Alternatives Informationquality Servicequality Systemquality Use User

satisfaction

Netbenefits

Agahjobs Irantalent Content personal-ization Dynamic content Varietyof information

Assurance Empathy Responsi-veness Customi-zation Easeof navigation Privacy Numberof transactions executed Repeat visits Better decision Time saving Alternatives Agahjobs 0 0 0.111 0.125 0.143 0.099 0.111 0.167 0.125 0.125 0.111 0.143 0.099 0.111 0.125 Irantalent 0 0 0.889 0.874 0.857 0.9 0.889 0.833 0.875 0.875 0.889 0.857 0.9 0.889 0.875 Information quality Content personalization 0.35 0.35 0 0 0 0 0 0 0 0 0 0.325 0.358 0 0 Dynamiccontent 0.341 0.398 0 0 0 0 0 0 0 0 0 0.462 0.341 0 0 Varietyof information 0.309 0.252 0 0 0 0 0 0 0 0 0 0.212 0.301 0 0

Servicequality Assurance 0.322 0.333 0 0 0 0 0 0 0 0 0 0.386 0.312 0 0

Empathy 0.369 0.398 0 0 0 0 0 0 0 0 0 0.272 0.372 0 0

Responsiveness 0.308 0.268 0 0 0 0 0 0 0 0 0 0.342 0.316 0 0

Systemquality Customization 0.332 0.397 0 0 0 0 0 0 0 0 0 0.361 0.298 0 0

Easeofnavigation 0.317 0.304 0 0 0 0 0 0 0 0 0 0.314 0.324 0 0 Privacy 0.351 0.298 0 0 0 0 0 0 0 0 0 0.325 0.377 0 0 Use Numberof transactions executed 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 User satisfaction Repeatvisits 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1

Netbenefits Betterdecision 0.472 0.099 0 0 0 0 0 0 0 0 0 0.111 0.143 0 0

176 A.Keramati,M.Salehi/AppliedSoftComputing13(2013)173–180

Table3 ClusterMatrix.

Alternatives Informationquality Servicequality Systemquality Use Usersatisfaction Netbenefits

Alternatives 0 1 1 1 0.157 0.241 0.352 Informationquality 0.179 0 0 0 0.164 0.143 0 Servicequality 0.179 0 0 0 0.174 0.154 0 Systemquality 0.145 0 0 0 0.161 0.159 0 Use 0.169 0 0 0 0 0.154 0.356 Usersatisfaction 0.162 0 0 0 0.172 0 0.291 Netbenefits 0.166 0 0 0 0.171 0.149 0

Overallresearchquestionsareformulatedas:“Whatisthe rel-ativeimportanceofwebsitesuccessfactorsinselectingthemost preferrede-recruitmentwebsite?”and“whatistherelative

pref-erence of e-recruitment websites withrespect to each success

factor?”

3. Researchmethodology

Inordertoinvestigatetherelativeimportanceofwebsite suc-cessfactorsinselectingthemostpreferredwebsite,aninternet

mediated questionnaire based field survey was conducted on

commonusers ofthe onlytwo Iranian e-recruitment websites,

www.irantalent.comandwww.agahjobs.com.

Tochooseasamplingframefrome-recruitmentusers,anonline academicunionisused.Samplingframeconsistsof100,000 uni-versity graduated individuals in Iran. According to selecting a probabilitysample[25],simplerandomsamplingisselectedasthe mostappropriatesamplingtechnique.Theminimumsamplesize requiredforthepopulationof100,000,withconfidencelevelof 95%,andconfidenceintervalof5hasbeencalculatedandisequal to383.

Inthequestionnairecoverletteritismentionedthatthe objec-tiveofthisresearchiscomparingtwoe-recruitmentwebsites,and only themembers of both websites are eligible toanswer the questionnaire.55responseswerereceived,andtheportionofthe unansweredquestionnaireswasduetoineligibilityofrespondents, accordingtonotusingbothe-recruitmentwebsites.

Inordertoachievecredibilityoftheresultsseveralprecautions weretaken.AfterestablishingaquestionnaireaccordingtoSaaty [26],areviewonthequestionnairewasmadebyindependent indi-viduals.First,expertswereconsultedtoensurethatquestionswere properlyphrased.Successvariablesweredefinedbrieflyina glos-sarysectionofthequestionnaire toinsurethatthemeaning of UpdatedDeloneandMcLeanISSuccessvariablesisnot misunder-stoodbyrespondents.Afterthat,ANPexpertsconductedareview onquestionnairetomakecertainthatpairwisecomparisonsare establishedproperly.

Due to inevitable inconsistency among the judgments, it is necessarytomeasuretheinconsistencyindextoeliminate incon-sistentjudgmentsforeachgroupofpairwisecomparisonsforeach respondent.Therefore,priortotheanalyzingphaseofthisstudy, inconsistencyratioformatricesbiggerthat2×2wascalculatedto ensurethatratioisinanacceptablelevelofinconsistency. 4. Dataanalysis

comparisonsthroughoutthenetworkthatshowninFig.2.Allthe localprioritiescanbereaddirectlyfromtheunweighted superma-trix(Table2).

Theclusterthemselvesmustbecomparedtoestablishtheir rel-ativeimportanceandusetheirprioritiestoweightthesupermatrix [19](Table3).

Theweightedsupermatrix(Table4)isobtainedbymultiplying alltheelementsinacomponentoftheunweightedsupermatrixby thecorrespondingclusterweight[19].

AccordingtoSaaty[19],limitsupermatrixisgainedfromthe weightedsupermatrixbyraisingittopowersuntilallcolumnsare identicaltowithinacertaindecimalplace.

Therelativewebsitesuccessofthealternatives,Irantalentand Agahjobs,fromthelimitsupermatrixis:0.33,and0.05(Table5). Theprioritiesofallnodescanbereadfromthelimitsupermatrix.

Thesynthesized prioritiesfor each alternative are shown in Table6.AccordingtosynthesizedprioritiesIrantalent.com web-sitehasthe87.75%ofwebsitesuccess,andAgahjobs.comwebsite has12.24%.

5. Results

Themajorcontributionofthisstudyliesinthedevelopmentof aframeofreference,whichincorporatesinterrelatedsuccess fac-torsinUpdatedDeloneandMcLeanISSuccessModel[9]forthe selectionofasuccessfule-recruitmentwebsiteandfinding rela-tiveimportanceofsuccessfactors.ByadoptingUpdatedDeloneand McLeanISSuccessModel[9],andapplyingANPapproach,thisstudy investigatedfactorsaffectingwebsitesuccess,theirrelative impor-tance,interdependenciesamongsuccessfactors,andthepriorityof alternativewebsites.

ThisstudysuggeststhatANPisaneffectivetooltoprovide solu-tionforinterdependenciesthatareabletoaffectthedecisiontobe madefornetworklikemodels.ThisstudypresentsANPfor measur-ingtherelativeimportancethatcapturesinteractionandfeedback inUpdatedDeloneandMcLeanISSuccessModel[9].

5.1. Relativeimportanceofsuccessfactors

Resultsoflocalprioritiesderivedfrompairwisecomparisons canbereadfromweightedsupermatrix(Table4).

HighestpreferenceofIrantalent(0.9)toAgahjobs(0.1)iswith respecttoassurance.Incontrast,preferenceofIrantalent(0.13)to Agahjobs(0.022)withrespecttonumberofapplicationsexecuted throughthewebsitewasthelowest.

A. Keramati, M. Salehi / Applied Soft Computing 13 (2013) 173–180 177 WeightedSupermatrixes.

Alternatives Informationquality Servicequality Systemquality Use Usersatisfaction Netbenefits

Agahjobs Irantalent Content personal-ization Dynamic content Varietyof informa-tion

Assurance Empathy Responsiveness Customization Easeof naviga-tion

Privacy Numberof transactions executed

Repeatvisits Better decision Time saving Alternatives Agahjobs 0 0 0.111 0.125 0.143 0.1 0.111 0.167 0.125 0.125 0.111 0.022 0.024 0.039 0.044 Irantalent 0 0 0.889 0.875 0.857 0.9 0.889 0.833 0.875 0.875 0.889 0.13 0.219 0.313 0.308 Information quality Content personalization 0.063 0.063 0 0 0 0 0 0 0 0 0 0.053 0.051 0 0 Dynamic content 0.061 0.071 0 0 0 0 0 0 0 0 0 0.076 0.049 0 0 Varietyof information 0.055 0.045 0 0 0 0 0 0 0 0 0 0.035 0.043 0 0

Servicequality Assurance 0.058 0.059 0 0 0 0 0 0 0 0 0 0.067 0.048 0 0

Empathy 0.066 0.071 0 0 0 0 0 0 0 0 0 0.047 0.057 0 0

Responsiveness 0.055 0.048 0 0 0 0 0 0 0 0 0 0.059 0.049 0 0

Systemquality Customization 0.048 0.058 0 0 0 0 0 0 0 0 0 0.058 0.047 0 0

Easeof navigation 0.046 0.044 0 0 0 0 0 0 0 0 0 0.05 0.052 0 0 Privacy 0.051 0.043 0 0 0 0 0 0 0 0 0 0.052 0.06 0 0 Use Numberof transactions executed 0.169 0.169 0 0 0 0 0 0 0 0 0 0 0.154 0.356 0.356

Usersatisfaction Repeatvisits 0.162 0.162 0 0 0 0 0 0 0 0 0 0.172 0 0.291 0.291

Netbenefits Betterdecision 0.078 0.016 0 0 0 0 0 0 0 0 0 0.019 0.021 0 0

178 A. Keramati, M. Salehi / Applied Soft Computing 13 (2013) 173–180 Table5 LimitSupermatrix.

Alternatives Informationquality Servicequality Systemquality Use User

satisfaction Net benefits Agahjobs Irantalent Content

personal-ization

Dynamiccontent Varietyof informa-tion

Assurance Empathy Responsiveness Customization Easeof naviga-tion Privacy Numberof transac-tions executed Repeat visits Better decision Time saving Alternatives Agahjobs 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 Irantalent 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 0.331 Information quality Content per-sonalization 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 Dynamic content 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 Varietyof information 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026 0.026

Servicequality Assurance 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035

Empathy 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038 0.038

Responsiveness0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031 0.031

Systemquality Customization0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033 0.033

Easeof navigation 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 0.028 Privacy 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 Use Numberof transactions executed 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116

Usersatisfaction Repeatvisits 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109 0.109

Netbenefits Better decision

0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014 0.014

Table6

Thesynthesizedresultsforthealternatives.

Alternatives Raw Normals Ideals

Agahjobs 0.05 0.12 0.14

Irantalent 0.33 0.88 1

Consideringsystemquality,Agahjobs’sabilityinproviding pri-vacy(0.051)isrelativelymoreincomparisonwithothertwosystem qualitymeasures.However,customization(0.058)isrelativelymore significantinIrantalent.

Regardingservicequality,empathyismentioned asrelatively

most significant measure in Irantalent (0.071) and Agahjobs

(0.066).Unlike,responsivenessisregardedastheless significant measure in both Irantalent (0.048)and Agahjobs(0.055). Since responsivenessisregardedastheamountoftimeittakesto

down-loadawebpage, onereasoncouldbethelow internetspeed in

Iran.

Inaddition,timesavingmeasureisrelativelymoreconsequential inbothIrantalent(0.149)andAgahjobs(0.087)thanbetterdecision becauseofinformationonthewebsite.

Regarding information quality, dynamic content (0.076) is

remarkedasthemostimportant factorwhich affects usingthe

e-recruitmentwebsite,whereascontentpersonalization(0.051)is consideredtobethemostsignificantcontributortouser satisfac-tion.

While assurance (0.067) is mentioned as relatively most

important service quality measure which influences using the

e-recruitmentwebsite,empathy(0.047)is relativelyless signifi-cantmeasure.Unlike, usersbelievethatempathy(0.057)affects theirsatisfactionrelativelythemostincomparisonwithassurance

(0.048)andresponsiveness(0.049).

Customizationis consideredasrelatively moreconsequential systemqualitymeasurethataffectsusingthewebsite(0.058),but thismeasurebecomeslesssignificantinusersatisfaction(0.047). Meanwhile,privacy(0.06)measureaffectsusers’satisfaction rela-tivelythemost.

e-Recruitmentwebsites’usersconsidertimesavingasrelatively morebeneficialfactorwhichleadstousingthee-recruitment web-site(0.152)andalsosatisfactionfromthewebsite(0.127).

5.2. Relativeinfluenceofsuccessfactorsonwebsitesuccess

Accordingtolimitsupermatrix(Table5)thepriorityand impor-tanceofeachsuccessfactorisachievedwithrespecttoitsinfluence onwebsitesuccess.

Dynamic content (0.04) has the highest influence on e-recruitmentwebsitesuccess,whilstvarietyofinformation(0.026) hastherelativelesscontributiontoe-recruitmentwebsitesuccess. Itissurprisingthatbothofdynamiccontentandvarietyof informa-tionarethemeasuresofinformationqualitycategoryinUpdated DeloneandMcLeanISSuccessModel[9].

Withrespecttosystemqualitycategory,customization(0.033) is highlyranked,indicating that companiesshouldspend more efforttomakeadesignthatcanbepersonalizedbytheusers,so thattheycanhavetheirownversionofthewebsite.Meanwhile,

easeofnavigation(0.028)influenceisrelativelylesssignificantin e-recruitmentwebsitesuccess.

Considering service quality category, empathy (0.033) com-parativelyhasgot mostattentionfromonlineusers,notingthat companiesshoulddeployavirtualassistantonthewebsite.The relativeunimportanceofresponsiveness(0.028)incomparisonto otherservicequalitymeasuresisapparentinthelimitsupermatrix.

Timesavingisfoundtobemorebeneficialsuccessfactor(0.085) incomparisontobetterdecisionsbecauseofinformationonthe web-site(0.014).

Synthesizedresults(Table6)supportthatIrantalentischosenas thepriore-recruitmentwebsitewithhigherweightedscore(0.88) againstAgahjobs(0.12).

6. Recommendations

Accordingtothe empiricalfindings, it is recommendedthat Agahjobs.comfurtherenhanceitsassurancesuccessmeasureby providing previouscustomers’ experienceonthe website.Asit wasdiscussedearlier,thismeasurewasfoundtobefarstrongerin Irantalent.com.Furthermore,thismeasureisthemostimportant servicequality measurethatinfluencesusingthee-recruitment website.Alsofromthesystemqualitypointofview,itissuggested thatAgahjobs.comimproveeaseofnavigationbyproviding func-tionsthathelpcustomersfindingwhattheyneedwithoutdifficulty andpossessingagoodsearchengine.

ItishighlysuggestedtoIrantalent.comtoimproveprivacythat makesusers’identityconfidential.Sinceprivacyisconsideredas keyevaluativecriteriainonlineservices.

Moreover, with respect to information quality, it is recom-mended that both Irantalent.com and Agahjobs.com provide varietyofinformationontheirwebsitestoincreasetheinformation quality.

AppendixA.

Thisappendixincludesacondensedversionofthesurvey instru-ment. Due to its considerable length, the entire survey is not included.

Onthecoverletter,itismentionedthatforonething,theaim oftheresearchistocomparerelativeimportanceoftwowebsites’ successfactors.Moreover,theresearchistofindoutrelative pref-erenceofeachwebsitewithrespecttodifferentsuccessvariables fromusers’perception.Therefore, jobseekerswho arethe com-monusersofbothe-recruitmentwebsitesareeligibletoanswer thequestionnaire.

Aglossaryofliteraturetermsisalsoincludedinthis question-naireforusers’information.

For survey questions, we included thefollowing table. It is mentionedthatScaleof1–9isusedfortwocomponents,witha scoreof1representingindifferencebetweenthetwocomponents and 9beingoverwhelmingdominanceofthecomponentunder consideration.

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9

Variable1 Variable2

1.Comparetherelativeimportanceofinformationquality, sys-temquality,andservicequalityinchoosingthemostpreferred website.

2.Throughwhichwebsiteyousentmoreapplications? 3.Whichwebsitedoyouvisitmoreregularly?

4.Whichwebsitedoyoupreferbasedonbetterdecisionsbecause ofinformationontheweb?

5.Whichwebsitehelpsyouwithsavingyourtimemore? 6.Comparetherelativeimportanceofassurance,empathy,and

responsivenessinsendingmoreapplicationsthroughthe web-site.

7.Comparetherelativeimportanceofdynamiccontent,content personalization,andvarietyinformationinmoreregularvisits towebsite.

8.Comparetherelativeimpactofbetterperformancein compar-isonwithcompetitorsandsatisfactionwithwebsiteonusing thee-recruitmentwebsite.

9. Comparethe relativeimpact ofsystemquality, information quality,andservicequalityonusersatisfaction.

180 A.Keramati,M.Salehi/AppliedSoftComputing13(2013)173–180 10.Comparetherelativeimpactofuseandusersatisfactiononnet

benefits. References

[1] D.Chaffey,e-Businessande-CommerceManagement,fourthed.,PrenticeHall,

2009.

[2]A.J.Slywotzky,Thefutureofcommerce,HarvardBusinessReviewMagazine

(2000)39–47.

[3]N.Bhatti,A.Bouch,A.Kuchinsky,Integratinguser-perceivedqualityintoweb

serverdesign,ComputerNetworks33(2000)1–16.

[4] P.Marshall,R.Sor,J.Mckay,Anindustrycasestudyoftheimpactsof

elec-troniccommerceoncardealershipinWesternAustralia,JournalofElectronic

CommerceResearch1(2000)1–16.

[5]E.Turban,Gehrke,Determinantsofe-commercewebsite,HumanSystem

Man-agement19(2000)111–120.

[6]B.Smyth,K.Bradley,R.Rafter,Personalizationtechniquesforonline

recruit-mentservices,CommunicationsoftheAssociationforComputingMachinery

45(2002)39–40.

[7]J.P.C.Tong,Evaluatingtheindustrialergonomicsofservicequalityforonline

recruitmentwebsites,InternationalJournalofIndustrialErgonomics35(2005)

697–711.

[8]J.Amuzegar,Iran’sunemploymentcrisis,MiddleEastEconomicSurvey47(7)

(2004).

[9] W.H.DeLone,E.R.McLean,TheDeLoneMcLeanmodelofinformationsystems

success:aten-yearupdate,JournalofManagementInformationSystems19(4)

(2003)9–30.

[10]W.H. Delone, E.R. McLean,Measuringe-commerce success:applying the

DeloneandMcLeaninformationsystemmodel,InternationalJournalof

Elec-tronicCommerce9(1)(2004)31–47.

[11]T.Daughtrey,Costsoftrustfore-business:riskanalysiscanhelpe-businesses

decidewhereinvestmentsinqualityandsecurityshouldbedirected,Quality

Progress10(2001)38–43.

[12]J.V.Iwaarden,T.V.DerWiele,ApplyingSERVQUALtoWebsites:anexploratory

study,InternationalJournalofQualityandReliabilityManagement 20(8)

(2003)919–935.

[13]B.Friedman,H.Peter,J.R.Kahn,C.H.Daniel,Trustonline,Communicationsof

theAssociationforComputingMachinery43(2000)34–40.

[14]J.W.Palmer,Websiteusability,design,andperformancemetrics,Information

SystemsResearch13(2)(2002)151–167.

[15]A.Molla,P.S.Licker,e-Commercesystemssuccess:anattempttoextendand

respecifytheDeLoneandMcLeanmodelofISsuccess,JournalofElectronic

CommerceResearch2(4)(2001)1–11.

[16] A.Barua,P.Konana,A.Whinston,F.Yin,Measuresfore-businessvalue

assess-ment,ITProfessional3(1)(2001)47–51.

[17] J.D’Ambra,R.E.Rice,EmergingfactorsinuserevaluationoftheWorldWide

Web,InformationandManagement38(6)(2001)373–384.

[18] F.Reicheld,P.Schefter,e-Loyalty,yoursecretweaponontheweb,Harvard

BusinessReview78(4)(2000)105–113.

[19] T.L.Saaty,Decisionmakingwiththeanalytichierarchyprocess,International

JournalServicesSciences1(1)(2008)83–98.

[20] R.W.Saaty,DecisionMakinginComplexEnvironment:TheAnalyticHierarchy

Process(AHP)forDecisionMakingandtheAnalyticNetworkProcess(ANP)for

DecisionMakingwithDependenceandFeedback,SuperDecisions,Pittsburgh,

2003.

[21] M.Salehi,A.Keramati,H.Didehkhani,Aproposalframeworkfor

investigat-ingmobilewebsuccessinthecontextofe-commerce:ananalyticnetwork

processapproach,JournalofComputingScienceandEngineering3(4)(2009)

53–79.

[22]Y.Lee,A.K.Kozar,Investigatingtheeffectofwebsitequalityone-business

suc-cess:ananalytichierarchyprocess(AHP)approach,DecisionSupportSystems

42(2006)1383–1401.

[23]W.Delone,E.McLean,Informationsystemssuccess:thequestforthe

depend-entvariable,InformationSystemsResearch3(1)(1992)60–95.

[24]T.L.Saaty,Prioritysettingincomplexproblems,IEEETransactionson

Engineer-ingManagement30(1983)140–155.

[25]M.Saunders,P.Lewis,A.Thornhill,ResearchMethodsforBusinessStudents,

PrenticeHall,Paris,2007.

[26]T.L.Saaty,Howtomakeadecision:theanalytichierarchyprocess,Interfaces

24(6)(2004)19–43.

[27]M.L.Meade,P.Adrien,R&Dprojectselectionusingtheanalyticnetworkprocess,