A Mixed-Method Approach for Evaluating Spatial Data Sharing Partnerships for Spatial Data Infrastructure Development

KEVIN MCDOUGALL,1,2 ABBAS RAJABIFARD,2 AND IAN P. WILLIAMSON2

University of soUthern QUeensland, toowooMba,1 and University of MelboUrne, viCtoria,2 aUstralia

InrecentyearsinterjurisdictionalpartnershipshaveemergedasanimportantmechanismforestablishinganenvironmentconducivetodatasharingandhencethefacilitationofSDIdevelopment.However,unlessthepartnershiparrange-mentsarecarefullydesignedandmanagedtomeetthebusinessobjectivesofeachpartner,itisunlikelythattheywillbesuccessfulorsustainableinthelongerterm.Thepurposeofthispaperistofocusonthemethodologicalapproachesandrel-evantissuesforresearchingthesenewdatasharingpartnershipsandtheirrela-tionshipstoSDIdevelopment.Thispaperproposesaresearchmethodologyforinvestigatingboththeorganisationalcontextofdatasharingpartnershipsandthefactorsthatcontributetothesuccessofinterjurisdictionaldatasharingini-tiatives.Thepaperexaminespastresearchandtheoryinspatialdatasharingandexaminesthecharacteristicsofanumberofexistingdatasharingmodelsandframeworks.Theuseofamixed-methodapproachtoevaluatelocal-stategovernmentpartnershipsinAustraliaisdescribed.Finally,thevalidationofthemixed-methodapproachanditsgeneralisationtootherSDIanddatasharinginitiativesisdiscussed.

abstract

�� A mixed-method approach for evaluating spatial data sharing partnerships

IntrODUctIOn Spatialinformationplaysanimportantroleinmanysocial,economic,andpoliticaldecisions.Governments,business,andthegeneralcommunityrelyonspatialinformationforpracticaldecisionmakingonadailybasis(OnsrudandRushton1995).Inemergencyservicesanddisastermanagementthevalueofaccurateandrelevantinformationsuchasaddress,vehicularaccess,locationofservices,propertyownership,climate,andtopographyiscrucialfordirectingandmanagingresponseefforts.However,rarelydoallofthesedatasetsresidewithintheoneorganisationorjurisdiction,andhencecooperationanddatasharingamongsttheseorganisationsisessential.Althoughthereisahistoryofgoodcooperationbetweenlocal,state,andnationaljurisdictionsduringdisas-termanagement,atothertimesthesharingofdatahasbeenproblematic.

Withlocalgovernmentbeingacustodianofanumberofstrategicspatialdata-sets,ithasacrucialroletoplayinthedevelopmentofthestateandnationalspa-tialdatainfrastructures(SDIs),whichrelyheavilyontheverticalintegrationofspatialdatafromthelowerlevelsofgovernment(Harvey2000).Inrecentyears,anumberofcooperativepartnershipsbetweenlocalandstategovernmentshaveemerged.Thesepartnershipsarerelativelynewarrangementsthathavebeenestablishedtofacilitatetheimprovedsharingofspatialdataandtorealisethefullpotentialofaspatialdatainfrastructure(NationalResearchCouncil1994).However,inordertoachievemaximumbenefitfromsucharrangements,itisimportanttounderstandthefactorsthatcontributetothesuccessfulandsustain-ableoperationofthesepartnerships.

Organisational,technical,legal,andeconomicissuescontinuetoimpedetheintegrationofspatialinformationinheterogeneousdatasharingenvironments(Masser1998;MasserandCampbell1994;Nedović-BudićandPinto2001;OnsrudandRushton1995).Althoughresearchhasidentifiedthattheseinter-organisationalissuesremainapriority,therehavebeenfewsystematicevalua-tionsofthemechanismsandfactorsthatfacilitatetheinterorganisationalefforts(Nedović-BudićandPinto2001).Inparticular,theverticalintegrationofmulti-plelevelsofdataacrossmultiplelevelsofgovernmentcontinuestobeamajorimpedimenttoafullyrobustnationalSDI(Harveyetal.1999).Masser(2005)identifiesapressingneedformoreresearchonthenatureofdatasharinginamultilevelSDIenvironment,particularlywithrespecttotheorganisationalissues.

PartnershipsareconsideredtobeessentialforSDIdevelopmentbecausetheyprovideamechanismtoalloworganisationstoworktogethertoachieveSDIgoalsandshareimplementationresponsibilitiesandtheeventualpartnershipbenefits(WehndeMontalvo2001).Experiencesinseveralcountrieshaveiden-tifiedanumberofproblemswithestablishingpartnershipsateverylevelofgov-ernment.Theseproblemsincludethepoorstructureofpartnerships,lackofawarenessofpartnershipbenefits,poorlydefinedresponsibilitiesofeachpart-ner,fearoflosingcontrolofdata,limitedfunding,andlackofabuy-in(WehndeMontalvo2001,2003b).Althoughmanyissueshavebeenidentified,thekeyproblemof“howtopackagetheseresearchinsightsintoacoherentandeffectiveprogramorsetofguidelines”remains(Nedović-BudićandPinto2001).Kevany(1995)alsoidentifiesasoneofthemostimportantareasoffutureresearchtheestablishmentofasetoffactors(values)forbothsuccessfulandunsuccessfuldatasharingenvironmentswhichcanbeappliedtofutureinitiatives.

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TheimportanceofpartnershipsandcollaborationhasbeenpromotedandreportedbytheNationalMappingCommitteeoftheNationalResearchCouncil(NationalResearchCouncil1994,2001)andtheGeodataAlliance(Johnsonetal.2001)throughdocumentedsuccessstoriesandidentificationofkeysuccessfac-tors.However,thesedocumentsalsosuggestthatmorerigorouseffortsneedtobepursuedtoimproveourunderstandingofcollaborativeinitiatives.Abetterunderstandingoftheexistingjurisdictionalpartnershiparrangementscouldassistinthedevelopmentofamoreuniversalandsuccessfulmodelforcollaboration.Thebenefitsfromsuchamodelshouldleadtotheimproveddevelopmentofspa-tialdatainfrastructuresatalllevels,whichinturnshouldpositivelyimpactallsectorsofthegovernment,business,andcommunity.

Thispaperwillfirstlyreviewavarietyofexistingdatasharingmodelsandframe-workswithrespecttotheircharacteristics,strengths,andlimitations.Themixed-methodresearchapproachisthendescribedasasuitablemethodforexaminingexistingdatasharingpartnerships.Thismethodologywillthenbeexaminedinthecontextofevaluatinglocal-stategovernmentdatasharingpartnershipsforSDIdevelopment.Finally,theutilityofthisapproachanditsvaliditywillbediscussed.

Thesharingofspatialdataisnotnew;however,inrecenttimestheimportanceofspatialdatasharingasamechanismforbuildingandsustainingthedevelopmentofspatialdatainfrastructureshasbeenhighlighted(NationalResearchCouncil1994).Severalcontributionshavebeenmadetotheunderstandingofdatashar-ingwithinandacrossorganisations,includingthewillingnessoforganisationstosharetheirdata.Thesecontributionsrangeincomplexityanddetail,butitisuse-fultoreviewanumberofthesemodelsandframeworkstogainabetterunder-standingofexistingtheoryandpractice.

OneoftheearlyeffortstodescribeaclassificationframeworkfordatasharingwasundertakenbyCalkinsandWeatherbe(1995).Thefourprimarycompo-nentsoftheirtaxonomyincluded(1)characteristicsoftheorganisation,(2)data,(3)exchange,and(4)constraintsandimpediments.Kevany(1995)proposedamoredetailedstructuretomeasuretheeffectivenessofdatasharing.Thisstruc-tureisbasedontheauthor’sexperienceacrossarangeofprojects,particularlyatthecountyandcitylevelsintheUnitedStates.Thirtyfactorsthatinfluencedatasharingwereidentifiedunderthefollowingninebroadareas:sharingclasses,projectenvironment,needforshareddata,opportunitytosharedata,willing-nesstoshare,incentivetoshare,impedimentstosharing,technicalcapabilityforsharing,andresourcesforsharing.

Datasharingcanalsobeviewedintermsofantecedentsandconsequences.AframeworkproposedbyObermeyerandPinto(1994)andPintoandOnsrud(1995)includesanumberofantecedents—suchasincentives,superordinategoals,accessibility,qualityofrelationships,bureaucratisation,andresourcescarcity—whichprecedetheprocessofdatasharing.Theeffectsoftheseeventsandfactorsthenmediatearangeofdatasharingconsequencessuchasefficiency,effectiveness,andenhanceddecisionmaking.AzadandWiggins(1995)proposedatypologybasedoninterorganisationalrelations(IOR)anddynamics.Theauthorsarguethatspatialdatasharingacrossmanyagenciesisfundamentallyan

Data sharIng mODels anD

framewOrks

�� A mixed-method approach for evaluating spatial data sharing partnerships

organisationalaffairandthattheconceptoforganisationalautonomyisacriticalissueindatasharing.

AnotherframeworkwhichexaminesorganisationaldatasharingisputforwardbyNedović-BudićandPinto(1999)anddrawsontheKevanymodel(1995),whichwaslargelyexperiencebased.Theconceptualframeworkdrawsonabroaderliteraturebasetoderivefourtheoreticalconstructs:interorganisationalcontext,motivation,coordinationmechanisms,andoutcomes.Thetheoreti-calfoundationsofthisframeworkprovideaveryusefulbasisforfurtherdevel-opmentandassessmentofspatialdatasharinginitiatives.WehndeMontalvo(2002)suggeststhatsharing,byitsverynature,isahumanbehaviourandthere-foreitshouldbeexploredfromahumanbehaviouralperspective.Theauthorusedthetheoryof“plannedbehaviour”asanorganisingframeworkforinvestigatingthewillingnesstosharespatialdata.Themodelmapstheprocessofdatasharingusingbeliefstructuresandthepredictivepowerofintentionalbehaviour.Table1summarisesthevariousmodelsandframeworksproposedbydifferentauthors.

Thedatasharingmodelsintable1relyonarangeoftheoreticalandexperien-tialapproaches.Increasingly,theimportanceoforganisationalandbehaviouralissuesisrecognised,andthereisgrowingsupportforempiricalmodels.Therecentassessmentsofthesemodelsandtheories(Nedović-BudićandPinto1999;WehndeMontalvo2003a)haveidentifiedtheadvantagesofutilisingbothqual-itativeandquantitativeapproachestobetterunderstandandevaluatedatashar-ingarrangements.Tounderstandtheissuesassociatedwithdatasharingwithin

Model/framework Characteristics Strengths Limitations

Calkins and Weatherbe (1995)

Taxonomy based on characteristics of organisation, data, exchange process, and constraints/impediments

Framework recognises organisational issues and nature of exchange

Limited with respect to motivations, policy, and capacity of organisations

Kevany (1995) Factor- and measure-based model

Very comprehensive list of factors that can be rated based on existing exchanges

Based on personal experience and not supported by theoretical foundations

Obermeyer and Pinto (1994), Pinto and Onsrud (1995)

Conceptual model based on antecedents and consequences

Based on exchange and organisational theory; basis for further research

Mainly conceptual and has limited depth or justification of factors

Azad and Wiggins (1995) Typology based on IOR and dynamics

Attempts to classify organisation dynamics and behaviour (Oliver 1990)

Lack of justification for the initial premise that data sharing leads to the loss of autonomy and independence and lack of empirical evidence

Nedović-Budić and Pinto (1999)

Based on the theoretical constructs of context, motivation, mechanisms, and outcomes

Broad theoretical basis supported by quantitative validation in later studies

May not predict potential willingness to share data

Wehn de Montalvo (2003) Based on theory of planned behaviour

Strong theoretical basis that is strengthened by a mixed-method approach

Model is predictive (by design) and may not be directly applicable to the analysis of existing initiatives

Table 1. Data sharing models.

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thecontextofadatasharingpartnership,thefollowingresearchquestionsneedtobeaddressed:1. Howcanourunderstandingofexistinginterjurisdictionaldatasharingmodels

beutilisedtoimprovetheiroperationandsustainabilityinthecontextofSDIdevelopment?

2. Howcanthesepartnershipmodelsbemorerigorouslydescribedandclassified?3. Whatarethemotivationsfor,andbarriersto,theparticipationofgovern-

mentsinspatialdatasharingpartnerships?4. Whatarethefactorsthatcontributetothesuccessofthesedatasharing

partnerships?5. Canthesefactorsbeusedtoidentifythecapacityofeachpartnertosuccess-

fullyparticipateinthesepartnerships?6. Canagenericframeworkormodelbedevelopedtoguidefuturespatialdata

sharingpartnerships?

Thefirstandsecondquestionsareprimarilyqualitativeinnatureandseektoexplainthenatureofinterjurisdictionalpartnerships.Thenextthreequestionsaremorequantitativeandseektoidentifyandmeasureanumberofissuesorfactors.Thefinalquestionrequirestheblendingofbothqualitativeandquan-titativeapproachestobetterguidethedevelopmentofagenericframeworkormodel.Toinvestigatethesequestionsmorefully,weproposeamixed-methodapproachwhichintegratesbothqualitativeandquantitativestrategies.Thethe-oryofmixedmethodsisdiscussedindetailbelowtodemonstrateitsapplicabilitytotheclassificationandevaluationofspatialdatasharingpartnerships.

Thedebateoverthebenefitsofqualitativeversusquantitativemethodscontin-ues,withtheproponentsineachcampvigorouslydefendingthebenefitsandrigorofeachapproach(TashakkoriandTeddlie2003).Newmethodsinthe-oryandpracticesuchasparticipatoryapproaches,advocacyperspectives,crit-icalappraisal,andpragmaticideashavecontinuedtoemerge(LincolnandGuba2000).However,inrecenttimesresearchershavebeguntoreexaminethesepreviouslyisolatedstrategies(Creswell2003).Thefieldofmixedmethodshasdevelopedasapragmaticapproachtoutilisethestrengthsofbothqualitativeandquantitativemethods.

Mixed-methodresearchisnotnewbutalogicalextensionofthecurrentreexam-inationandexplorationofnewpractices.AsCreswell(2003)putsit,

Mixedmethodsresearchhascomeofage.Toincludeonlyquantitativeorqualitativemethodsfallsshortofthemajorapproachesbeingusedtodayinthesocialandhumansciences....Thesituationtodayislessquantitativeversusqualitativeandmorehowresearchpracticesliesome-whereonthecontinuumbetweenthetwo....Thebestthatcanbesaidisstudiestendtobemorequantitativeorqualitativeinnature.

Thedefinitionsforqualitativeandquantitativemethodsvarywithindividualresearchers(Thomas2003).Mixed-methoddesigncanincorporatetechniquesfromboththequalitativeandthequantitativeresearchtraditionsinauniqueapproachtoanswerresearchquestionsthatcouldnotbeansweredinanother

mIxeD-methOD apprOach

�0 A mixed-method approach for evaluating spatial data sharing partnerships

way(TashakkoriandTeddlie2003).However,themixed-methodapproachdiffersfromqualitativeandquantitativeresearchparadigms(Brannen1992)andcanprovideanumberofadvantages.TeddlieandTashakkori(2003)identifythreereasonsthatmixed-methodresearchmaybesuperiortosingle-approachdesigns:1. Mixed-methodresearchcananswerresearchquestionsthatothermethodologies

cannot2. Mixed-methodresearchprovidesbetter(stronger)inferences3. Mixedmethodsprovidetheopportunityforpresentingagreaterdiversity

ofviews

Theabovereasonsprovideasoundbasisforjustifyingtheapplicationofthemixed-methodapproachtoSDIpartnershipresearch.Firstly,themixed-methodapproachnotonlyenabledtheexplorationanddescriptionofexistingpartner-shiparrangements,particularlythe“why”and“how”ofthearrangements,butalsofacilitatedthemeasurementorquantificationofthevalueofthesearrange-ments.Theresearchquestionsidentifiedpreviouslyarealsodifficulttoanswerthroughanysingleapproach.Acasestudyapproachwasdeemedsuitableforaddressingthe“why”and“how”questions.However,toevaluatelargemulti-participantdatasharingpartnerships,aquantitativeapproachwasconsideredmoreappropriate.

Secondly,theweaknessesofasingleapproachareminimisedthroughthecom-plementaryutilisationofothermethods.Thequalitativecasestudyapproachprovidedtheopportunitytoinvestigatetheorganisationalaspectsofthepartner-shipsingreaterdepth,whileaquantitativesurveyofalargernumberofpartner-shipparticipantsfacilitatedagreaterbreadthofviews.Finally,theopportunitytoinvestigateandpresentagreaterdiversityofviewswasconsideredimportantinvalidatingtheresearchfindings.Thiswasvaluablebecauseitledtothereex-aminationoftheconceptualframeworkandunderlyingassumptionsofeachofthetwomethods(TeddlieandTashakkori2003).Thediversityanddivergenceofperspectivesbetweendifferentlevelsofjurisdictionssuchasstateandlocalgovernmentsiswellknown.Importantly,thisreflectstherealityoftherelation-shipsandhencethehealthofthepartnershiparrangements.

Animportantconsiderationinusingamixed-methodapproachisthewayinwhichthequalitativeandquantitativemethodsarecombined(Brannen1992).ThetwostrategiescanbecombinedinthreewaysaccordingtoBryman(1998):1. Preeminenceofquantitativeoverqualitative2. Preeminenceofqualitativeoverquantitative3. Qualitativeandquantitativearegivenequalweight

Inthefirstapproach,thequalitativeworkmaybeundertakenpriortothemainquantitativestudyandmaybeusedasabasisforhypothesistesting,devel-opingtheresearchinstrument,orclarifyingquantitativedata.Thequalita-tiveworkmaybeperformedatanearlystagebutcanalsoberevisitedlater.Inthesecondapproach,thequantitativestudycanbeconductedbeforethemainstudyorattheendofthemainstudy.Itcanprovidebackgrounddatatocon-textualisesmallintensivestudies,testhypothesesderivedthroughqualitativemethods,orprovideabasisforsamplingandcomparison.Thefinalapproachpro-videsequalweightingtoeachmethod.Thetwostudiesareconsideredseparatebut

McDougall et al. �1

linkedandcanbeperformedsimultaneouslyorconsecutively.Theprocessesmaybelinkedatvariousstagesintheresearchprocessandthenintegratedtoformulatefinaloutcomes.

Priority,implementationtiming,stageofintegration,andtheoreticalperspectivescanassistinclassifyingthemixed-methodapproach.Creswelletal.(2003)pro-posesixdesigntypesbasedonthesefourcriteria.Thesedesigntypescanbeusedtoassistresearchersinidentifyingthemostsuitablemixed-methodapproachforaparticularstudy,particularlywhenandhowtointegratethetwomethods.ThedesigntypesproposedbyCreswelletal.areclassifiedprimarilyaseithersequen-tialorconcurrent.Forthesequentialdesign,theorderofthequantitativeandqualitativestudiesmaybedictatedbytheresearchproblemandwhetheramoreexploratoryorexplanatoryapproachisrequired.Alternatively,thetwostudiescouldbeconductedconcurrently,withtheresultsofeachstudybeinginterpretedduringtheanalysisstage.

Themixed-methodapproachisnotwithoutproblems,andcaremustbetakenintheintegrationandinterpretationphasesoftheresearch(Bryman1992).However,whenproperlybalancedandguidedbyanunderstandingoftheresearchpur-posesandproblems,themixed-methodapproachisapowerfulresearchstrat-egy.Tomoreclearlyillustratethemixed-methodapproach,weexamineitsusefortheclassificationandevaluationoflocal-stategovernmentspatialdatashar-ingpartnershipsfromamethodologicalperspective.

Localgovernmentisarichsourceofaccurateanddetailedspatialinformation,whichisutilisednotonlyatthelocallevelbutalsoincreasinglyatotherlev-elsofgovernment.Incountriesthathaveasystemoffederatedstates,suchasAustralia,thebuildingofstateandnationalSDIsincreasinglyreliesontheinvolvementoflocalgovernment.AlthoughinstitutionalproblemsstillpresentsomeofthegreatestchallengesinbuildingmultijurisdictionalSDIs,thetechnicalandphysicalcapacityofthesmallerjurisdictionscanaffecttheirabilitytopartic-ipatewithlarger,bigger-budgetjurisdictions.

Themixed-methodresearchdesignillustratedinfigure1consistsofafour-stageprocesswhichculminatesinthesynthesisanddevelopmentofanewmodelforlocal-stategovernmentSDIpartnerships.Thisdesigndrawstogetheragener-aliseddesignframeworkforcasestudyapproachesproposedbyYin(1994),Onsrudetal.(1992),Lee(1989),andWilliamsonandFourie(1998).Thethree-stageprocessofWilliamsonandFourie(1998)isexpandedtoincludequanti-tativemethodsusedtoidentifyandmeasuretheimpactandeffectivenessofthedatasharingpartnershipmodels.Thedesignalsoincludestheintegrationofbothqualitativeandquantitativeresultsandaprocessofmodelvalidation.

Anumberofmixed-methoddesignframeworkshaveemergedinrecenttimes(Creswelletal.2003;JohnsonandOnwuegbuzie2004;Nedović-Budićunpub-lished;TashakkoriandTeddlie1998;WehndeMontalvo2003a).Thedesigninfigure1startswiththeidentificationofresearchquestionsandproceedstoorganisationalcasestudies,aquantitativesurvey,andsynthesisofresults.Thefourstagesarediscussedindetailbelow.

Use Of the mIxeD-methOD apprOach tO assess Data sharIng

partnershIps In aUstralIa

�� A mixed-method approach for evaluating spatial data sharing partnerships

Figure 1. Mixed-method research design.

McDougall et al. ��

Stage1:Reviewoftheoryandframeworkdevelopment.Thefirststageoftheresearchprovidesthefoundationfordevelopmentofasuitableconceptualframe-workfortheinitialdatacollectionandassessment.Fortheorganisationalcasestudiesofthestategovernments,theconceptualframeworkwasdevelopedfromorganisationalandcollaborationtheories.Avarietyofresearchers(Childetal.2005;Gray1985;MulfordandRogers1982;Oliver1990;Prefontaineetal.2003)haveidentifiedanumberofimportantdimensionsofcollaborationincludingthecollaborativeenvironment,thedeterminantsforcollaboration,thecollaborativeprocess,andtheperformanceofcollaborativeinitiatives.Thetheoryenabledthedevelopmentofabasicframeworkforexploringtheinitiation,development,andoperationofthestategovernmentpartnerships.OneoftheprimarypurposeswastoinvestigatethecontributionofdatasharingpartnershipstoSDIdevelop-mentatlocalandstatelevels.Therefore,theconceptualframeworkforthelocal-governmentquestionnaireswasdevelopedaroundtheSDIelementsidentifiedbyarangeofauthors(ColemanandMcLaughlin1998;Groot1997;NationalResearchCouncil1993;RajabifardandWilliamson2001).Thesecomponentsincludedata,people,standards,institutionalframework/policies,andtechnol-ogy/accessarrangements.

Case study selection.Thecasestudiesinvestigatedexistingdatasharingpartner-shipsbetweenstateandlocalgovernmentsinAustraliawhichhadbeenestab-lishedtofacilitatethesharingofproperty-relateddata.ThethreeAustralianstatesofQueensland,Victoria,andTasmaniawerechosenforthestudy.Thestateswereselectedonthebasisofalreadyestablisheddatasharingarrange-mentsandavarietyofcharacteristicsincludinggeographicarea,population,andthenumberoflocalgovernments.ThestateofQueenslandisthesecondlargeststateinAustraliabyarea.ItscapitalcityofBrisbanerepresentsoneofthelarg-estlocalgovernmentjurisdictionsintheworld.Queenslandalsohasarelativelylargenumberoflocalgovernments,125intotal,includingmanyinremoteruralcommunitieswithverysmallpopulations.

Attheotherendofthespectrum,thestateofTasmaniaisacompactislandstatethathasonly29localgovernmentsandapproximatelyhalfamillionpeo-ple.Itprovidedacontrastingstudyofasmallerjurisdictionbothinareaandinthenumberofpartnershipparticipants.ThethirdcaseselectedwasthestateofVictoria,with79localgovernments.VictoriaisoneofthemostpopulatedstatesinAustraliaandisalsowelladvancedinitspartnershiparrangements.Itfallsinbetweentheothertwostatesingeographicareaandnumberoflocalgovernments.The3statesrepresentalmost50percentofAustralia’spopulation,approximately35percentofthetotalnumberoflocalgovernments,andabout25percentofthelandarea.Thestatesrepresentcontrastingmixturesoflocalgovernments,geography,andinstitutionalarrangements.

Stage2:Organisationalcasestudiesofpartnerships(qualitativecomponent).Akeyobjectiveofthequalitativecomponentofthecasestudieswastoexaminetheorganisationalframeworksofeachofthestate-government-initiatedpartnerships.AstructuredcasestudymethodologyasrecommendedbyYin(1994)wasutilised.AnSDIframeworkconsistingofthekeyareasofpolicy,data,people,accessarrangements,andtechnology/standardsprovidedthebasisfortheinvestigation.

Case study data collection.Forthisqualitativecomponent,themethodsofdatacollectionfocusedontwoprimaryformsofevidence:interviewsandexisting

�� A mixed-method approach for evaluating spatial data sharing partnerships

documentation.Asemistructuredinterviewtechniquewasutilisedtocollectdatafromstaffwithineachstategovernmentagencythatwaschargedwiththemanage-mentofthepartnershiparrangement.Theinterviewscoveredthefollowingtopics: • Organisationoverviewandroleofpartnership • Historicaldevelopmentswithinthepartnership • Existingpolicyarrangements • Understandingofthedataanddatasharingprocesses • Operationalandresourceaspectsofthepartnership • Organisationalandinstitutionalarrangements • Barriersandissues(legal,technical,economic,institutional)

Thepeopleinterviewedincludedthepartnershipinitiators,partnershipmanagers,andstaffinvolvedinvariousdatasharingactivities.

Theotherkeysourceofevidenceforthecasestudiesconsistedofhistoricaldoc-umentationwhichhadbeeninexistencesincethedesignanddevelopmentofthepartnerships.Thedocumentationvariedfromstatetostatebutincludedsomeofthefollowing: • Initialproposaldocumentsforthepartnership • DescriptivedocumentationsuchasthatavailableonWebsites • Examplesofindividualpartnershipagreements • Internalreviewdocumentsofthearrangements • Externalconsultancyreports • Conferenceandjournalpapersdescribingthearrangements

Intheevaluationofeachofthedocuments,carewastakentorecognisethestrengthsandweaknessesofthevariousformsofdocumentation,particularlywithrespecttoanybias.Incasestudies,oneofthemostimportantusesfordoc-umentationistocorroborateandaugmentevidencefromothersourcestomini-misepossiblebias.

Animportantobjectiveoftheresearchwastocompareandclassifythedifferentpartnershiparrangementsinexistence.Basiccomparatorsincluded: • Lengthofpartnership • Extentofdatasharing • Quantificationofresources • Communicationmechanismsandfrequency • Numberofpartners • Geographicextent • Environmentalcontext

TofurtherexplorethenatureandsustainabilityoftheSDIpartnershipsincom-parisontopartnershipsoperatinginotherdisciplines,atypologyforclassify-ingthepartnershipmodelswasdeveloped.Thetypologyincludedthefollowingdimensions:

case stUDy cOmparIsOn anD

classIfIcatIOn

McDougall et al. ��

• Natureofpartnership • Partnershipgoals • Negotiationprocesses • Resourceorfundingmodel • Governancemodel • Projectmanagement • Performancemeasurement • Maturityandorganisationallearning

Stage3:Multiparticipantquestionnaire(quantitativecomponent).Inordertoassessthemotivatingfactors,constraints,andeffectivenessoflocal-stategovernmentdatasharingpartnerships,aquestionnairewasadministeredtothelocalgovernmentsinthethreestates.Thepurposeofthequestionnairewastoassessarangeoffac-torsthatmightinfluencethesuccessorfailureofthedatasharingpartnerships,particularlyfromalocalgovernmentperspective.Thequestionnairewascon-structedaroundtheexistingknowledgeofSDIframeworks,especiallythepar-ticipants’understandingofpolicies,dataholdings,people,accessarrangements,andstandards/technology.InadditiontotheSDIframework,thequestionnaireinvestigatedtheorganisationalsetting,partnerships,andcollaborationsandtheparticipants’perspectivesontheexistingpartnershiparrangements.

Thequestionnaireconsistedofeightsections:1. TheOrganisationsectionquantifiedthesizeofthelocalgovernmentinterms

ofthenumberofpropertiesandstaffandprovidedanassessmentofitsgen-eralICTcapacityincludingspecificGISandspatialdatacapacities.

2. ThePolicyonUseofSpatialDatasectionexploredexistingpolicieswithinthelocalgovernmentforaccessandpricingofspatialinformationincludingissuesoflegalliability,copyright,andprivacy.

3. TheAccessingSpatialDatasectionexaminedtheorganisation’sarrangementsforaccessingandpricingofspatialinformationfromtheperspectivesofbothinternalandexternalusers.

4. TheAboutSpatialDatasectionexaminedthesourcesofspatialdata,thekeyproviders,andthestatusoftheirdataholdings.

5. TheSpatialDataStandardsandIntegrationsectioninvestigatedtheuseofstandardsandthedegreeofintegrationoftheorganisation’sspatialdatasys-temswithothercoresystems,providinganindicationofthelevelofmaturityofspatialinformationsystemswithintheorganisation.

6. TheAboutPeoplesectionexploredthehumanresourcesoftheorganisationincludingstaffturnoverandaccesstotraining.

7. ThePartnershipsandCollaborationsectionexploredtheperceivedstrengthoftheorganisation’srelationshipwitharangeoforganisations,thebarrierstocollaboration,thedriversforcollaboration,andthetypesofexistingcol-laborations.

8. TheSpecificDataSharingPartnershipssectionexaminedtheorganisation’sspecificattitudestowardandexperienceswithanexistingSDIpartnership.

�� A mixed-method approach for evaluating spatial data sharing partnerships

Forthemajorityofquestionstheresponseswerestandardisedandcategorisedonafive-pointLikertscale.Somequestionsaskedfornumericdatasuchasnumberofstafforlandparcels.Participantscouldalsoprovidecommentsoneachareaofthequestionnaire.Adraftquestionnairewasdistributedtothreelocalgovern-mentstocheckforterminologyandunderstandingofthequestions.Theques-tionnairewasthenconvertedintoaWebformtoenabledigitalcollectionofthedataandfacilitateahigherreturnrate.TheWeb-basedquestionnairewasthentestedinternallyandexternallybytwolocalgovernmentstoensurethattheURLprovidedwasaccessibleandalsothatresponseswerebeingrecordedontheWebserver.

Thedistributionofthequestionnairewasundertakenafterconsultationwitheachofthestateagencies.Thequestionnairesoughtresponsesfromlocalgovernmentsinanumberofareasthatcouldreflectpoorlyonthestategovernmentagency,soadegreeofsensitivitywasrequired.Privacyofcustomerorpartnerinforma-tionalsobecameanissue.Understateandfederalgovernmentprivacylegislation,permissionmustbesoughtfromindividualsbeforetheircontactdetailscanbedisclosed.Thisbecameasignificantissue,asitwascriticalthatthequestionnairebesenttothecorrectpartnershipcontactpersonratherthanrandomlytargetedlocalgovernmentstaff.Theprivacyissuewasaddressedbythestategovernmentagencymakingtheinitialcontactwiththelocalgovernmentagencyandseek-ingtheirconsenttobeinvolvedwiththestudy.Onceconsentwasobtained,thedetailswerepassedontotheresearcher.Thequestionnaireresponseratewas56percent,whichwasconsideredextremelysatisfactory,giventhediversityoflocalgovernmentsbeinginvestigated.

ThedatafromthequestionnaireswasautomaticallyrecordedintoanExcelspreadsheetviatheWebserver.Thisprocesswasextremelyeffective,asitelim-inatedencodingandtranscriptionerrorsandfacilitateddirecttransfertotheanalysissoftware(SPSS).Initialdescriptivestatisticsidentifiedanumberofearlytrendsintheresponsesfromthedifferentstatejurisdictions,particularlyintheareasofinformationpolicyandoutcomesdeliveredthroughthepartnerships.Factoranalysiswasthenutilisedtoidentifyclustersofvariables(components),whichwerethencorrelatedwiththeoutcomevariablesusingaregressionmodel.Throughthismodelling,componentswhichhadcontributedsignificantlytothesuccessofthepartnershipoutcomeswereidentified.

Stage4:Integration,modeldevelopment,andvalidation.Afterthecompletionofthecasestudiesandquestionnaireanalysistheresultswereintegratedtodevelopanewdatasharingpartnershipmodel.Thecasestudyresultsassistedinclarify-ingtheinitialconceptualframeworkandtypologyoftheexistingpartnershipsineachofthethreestategovernmentjurisdictions.Thedescriptiveandcomparativeanalysisenabledaclearerunderstandingoftheorganisationalstructures,pol-icyobjectivesandgoals,partnershipstructure,progressandoutcomes,resourcerequirements,andsustainability.Theperspectivesgainedfromthesecasesassistedinansweringsomeoftheresearchquestionsrelatedtohowandwhythespatialdatasharinginitiativeswereputinplaceandidentifiedsomeofthemajorissuesrelatedtotheirimplementation.Importantly,itshouldbenotedthatthe

QUestIOnnaIre DIstrIbUtIOn anD

analysIs

McDougall et al. �7

descriptivecasestudiesprimarilyprovidedtheperspectiveofthepartnershipinitiatorandmanagerratherthanpartnershipparticipants.

Thedevelopmentofagenericmodelrequiredtheperspectivesoflocalgovern-mentsforamorebalancedviewofthesuccessofthedatasharingarrangements.Theresultsofthequestionnaireidentifiedthecapacitiesandmotivationsoflocalgovernmentstoparticipateindatasharingpartnerships.Thequantitativeanalysisenabledthesefactorstobeidentifiedandmodelledagainstpartnershipoutcomes.

Interjurisdictional(localandstate)partnershipsinevitablycreatechallengesforeachlevelofgovernment.Theresearchfoundthatstate–localgovernmentdatasharingpartnershipsdifferinanumberofwaysfromotherinterjurisdictionaldatasharing.Firstly,foracomprehensivesolutiontodatasharingbetweenstateandlocalgovernmentsthepartnershiparrangementsneedtobeestablishedonaone-to-manybasis.Thequalitativecasestudiesshowedthatasystemisedapproachtopartnershipnegotiation,datalicensing,datamaintenance,partnercommunication,dataexchange,andprojectmanagementiscriticaltothesuccessoftheseendeavours.

Table2identifiessomeofthedifferencesamongthethreestatejurisdictions.BoththeVictorianandtheTasmaniandatasharingpartnershipsfromtheout-sethadappropriateresources,cleargoals,andstrongleadership.However,theQueenslandpartnershipstruggledtogainthesupportoflocalgovernmentsbecauseofpoorinitialfundingandarestrictivepolicyframeworkthatlimitedthelocalgovernmentsinconductingtheirbusinessactivitiesusingstategovern-mentdata.

Thefindingsofthestategovernmentlevelinvestigationsweresupportedbythequantitativestatisticsofthelocalgovernmentsurvey(figure2).Theareasof

Collaborative stage

Victorian Property Information Project

(PIP)

Queensland Property Location Index (PLI)

Project

Land Information System Tasmania

(LIST)

Establishment and direction setting Goal setting Negotiation Agreements

A clear common goal for the project. Well-managed process of negotiation and development of policy and institutional structures.

Business case for the project was limited. Goals unclear, and policy framework worked against data-sharing agreements.

High-level strategy and clear overall goals. Policy and negotiation strategy well-structured. Agreements very detailed.

Operation and maintenance Project management Maintenance Resources Communication

Project management has been good since inception, maintenance infrastructure developed progressively, some resource limitations. Communication with stakeholders and partners has been positive.

Poor institutional arrangements led to resource limitations and poor project support. Culture of interjurisdictional sharing emerging only now. Confused channels of communication due to dispersed organisational structure.

LIST started with strong overall leadership and project support. Project generally had strong resources and was technology focused. Issues of local government communication and data maintenance now starting to emerge.

Governance Governance structures Reporting Performance management

Early project efforts focused on negotiation and data exchange. Performance management now part of the process. Improved governance arrangements emerging.

There appears to have been little performance management or reporting. No governance structure in place which includes the key stakeholders.

Initial governance and reporting structures were appropriate, but as project matures new governance models are required.

Table 2. Qualitative assessments of the performance of state partnerships.

�� A mixed-method approach for evaluating spatial data sharing partnerships

weaknessinthepartnershipprocessesidentifiedatthestategovernmentlevelwerereflectedintheoveralllevelofsatisfactioninthelocalgovernmentsur-vey.Areassuchaspolicyformulationatthestategovernmentlevelhaveastronginfluenceonthecorrespondingpolicydevelopmentsatthelocallevel.Clearpart-nershipgoals,continuousandopencommunication,andadequatefundingalsohaveastronginfluenceonpartnershipoutcomes.

TheresearchmethodologydescribedabovebuildsonsimilarmodelsproposedbyYin(1994),Onsrudetal.(1992),Lee(1989),andWilliamsonandFourie(1998)forcasestudyapproacheswiththeadditionofquantitativemethods.Themixed-methodapproachhasalreadybeenutilisedsuccessfullybyanumberofresearchersstudyingspatialdatasharing(e.g.,byWehndeMontalvo[2003a]forassessingthewillingnesstosharespatialdataandbyNedović-Budić[unpub-lished]forassessingadoptionofGIStechnology).However,thepossibleutilityandvalidityoftheapproachdeservefurthercomment.

Qualitativeapproachessuchascasestudieshaveoftenbeenviewedasinferiortoquantitativeapproaches,suitableprimarilyforstand-alonedescriptionsofphenomenaorasexploratoryresearchpreliminarytotherealresearchofgen-eratinghypothesesandtestingthemstatistically(Benbasat1984).Althoughsuchcommentsonearlierstudieswerecommon,rigorous(Yin1994)andscien-tific(Lee1989)casestudyframeworksnowexist.

Forresearchreportedinthisarticle,thecasestudymethodwasselectedastheprimaryqualitativestrategyforexamininganumberofspatial-data-sharingpartnershipmodelsindifferentjurisdictions,particularlyfromanorganisationalperspective.Thecasestudyapproachwasdeemedsuitableforexaminingthesepartnershipmodelsforseveralreasons.Firstly,datasharingpartnershipmodelscanbestudiedintheirnaturalsettingsandprovidetheopportunitytolearnfromstate-of-the-artapproachesandpractice(Benbasatetal.1987;Maxwell1996).Secondly,thecasestudyapproachallowstheaskingofthe“how”and“why”researchquestionsandinvestigationofthenatureandcomplexityofspatialdatasharingpartnerships(Benbasatetal.1987;Yin1994).Thirdly,thecasestudy

DIscUssIOn anD cOnclUsIOns

Figure 2. Levels of satisfaction reported by local governments (Likert scale).

McDougall et al. ��

approachcanprovideasuitableframeworkforanalysisandclassificationofpartnershipmodels(Lee1989;Yin1994).Finally,thecasestudyapproachpro-videsahighlevelofdatacurrencyaswellasdataintegrity(Bonoma1985).

Theincorporationofthequantitativedimensionwiththeuseofaquestionnairestrengthensthecasestudyapproachbyfacilitatingefficientinclusionofalargenumberofparticipantperspectivesandcomprehensiveandquickanalysisofthisdata.Itcanalsoassistinidentificationofkeyfactors,correlations,andpossibletrendsfordevelopinganimprovedpartnershipmodel.

Inthestudythequalitativeandquantitativecomponentsweregenerallycom-pletedconcurrently.Thequalitativeorganisationalcaseswereevolvingduringthecourseofthestudy,withsomeperiodicupdatesoftheorganisationalenvi-ronment.Thequestionnaireswerecompletedoverasix-tonine-monthperiodandreviewedastheneedarose.Theevidencefromeachcomponentwasgivenequalweight,althoughthiswasoftendifficulttoconfirm.Finally,theintegrationofthetwostrategieswasachievedattheanalysisstage.Thisprocessfacilitatedthecorroborationofresultsandconfirmationoftheimportanceofissues.

Thetriangulationofexistingtheory,casestudies,andsurveyresultsinformsthefinalmodel(figure3).Theinternalvalidityofthemodelshould,intheory,besuperiortoeachofthesingularapproaches.However,caremustalwaysbeexer-cisedinearlyconceptualdevelopmentanddesign,asinadditiontothepotentialforcomplementarity,theriskofconflictingresultsexists.

Figure 3. Method triangulation model.

70 A mixed-method approach for evaluating spatial data sharing partnerships

Thedifficultyingeneralisingthefindingsfromthesmallnumberofcasesbeinganalysedisoftenidentifiedastheweaknessofthecasestudyapproach.Byundertakingamorewide-rangingsurveyofpartnershipparticipants,thefindingsofthecasestudieswerestrengthened.

Thepurposeofthispaperwastoexaminethemethodologicalapproachesandissueswhichariseinresearchingspatialdatasharingpartnershipsandtheirrela-tionshipstoSDIdevelopment.Aspartnershipscontinuetoemerge,itisimpor-tanttounderstandtheirsuccessandcontributiontobuildingSDIs.Inthepast,discreteresearchapproachesandmodelshaveprovidedvaluablestartingpointsformeasuringandclassifyingdatasharingefforts.However,amixed-methodapproachprovidesausefulstrategytobuildontheexistingtheoryandtomorerigorouslyevaluatetheresultsofthesepartnershipefforts.

WeacknowledgethesupportofthestateandlocalgovernmentsinQueensland,Victoria,andTasmania,theUniversityofSouthernQueensland,andthemem-bersoftheCentreforSDIandLandAdministrationintheDepartmentofGeomaticsattheUniversityofMelbourne.(However,theviewsexpressedinthepaperdonotnecessarilyreflecttheviewsofthesegroups.)

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