Upload
others
View
5
Download
0
Embed Size (px)
Citation preview
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.
McDougall et al. �7
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.
McDougall et al. ��
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.)
Azad,B.,andL.L.Wiggins.1995.Dynamicsofinter-organizationaldatasharing:Aconceptualframeworkforresearch.InSharing geographic information.H.J.OnsrudandG.Rushtoneds.,22–43.CentreforUrbanPolicyResearch,NewBrunswick,NJ.
Benbasat,I.,D.K.Goldstein,andM.Mead.1987.Thecaseresearchstrategyinstudiesofinformationsystems.MIS Quarterly11(3):369–89.
Benbasat,I.,ed.1984.The information systems research challenge2.Experimentalresearchmethods,HarvardBusinessSchoolPress,Boston.
Bonoma,T.V.1985.Caseresearchinmarketing:Opportunities,problems,andaprocess.Journal of Marketing Research22(2):199–208.
Brannen,J.1992.Combiningqualitativeandquantitativeapproaches:Anoverview.InMixing Methods: qualitative and quantitative research,ed.J.Brannen.Avebury,Aldershot,England.3–37.
Bryman,A.1992.Quantitativeandqualitativeresearch:Furtherreflectionsontheirintegration.InMixing Methods: Qualitative and quantitative research,ed.J.Brannen,57–78.Avebury,Aldershot,England.
Bryman,A.1998.Quantity and quality in social research.UnwinHyman,London.
Calkins,H.W.,andR.Weatherbe.1995.Taxonomyonspatialdatasharing.InSharing geographic information,eds.H.J.OnsrudandG.Rushton,67–75.CentreforUrbanPolicyResearch,NewBrunswick,NJ.
Child,J.,D.Faulkner,andS.B.Tallman.2005.Cooperative strategy.OxfordUniversityPress,Oxford.
references
acknOwleDgments
McDougall et al. 71
Coleman,D.J.,andJ.McLaughlin.1998.Definingglobalgeospatialdatainfrastructure(GGDI):Components,stakeholdersandinterfaces.Geomatica52(2):129–43.
Creswell,J.W.2003.Research design: Qualitative, quantitative, and mixed method approaches,2nded.SagePublications,ThousandOaks,CA.
Creswell,J.W.,V.L.PlanoClark,M.L.Gutmann,andW.E.Hanson.2003.Advancedmixedmethodsresearchdesigns.InHandbook of mixed methods in social and behavioral research,eds.A.TashakkoriandC.Teddlie,209–40.ThousandOaks,CA:SagePublications.
Gray,B.1985.Conditionsfacilitatinginterorganizationalcollaboration.Human Relations 38(10):911–36.
Groot,R.1997.Spatialdatainfrastructure(SDI)forsustainablelandmanagement.ITC Journal1997(3/4):287–93.
Harvey,F.J.2000.PotentialsandpitfallsforverticalintegrationfortheNSDI.Finalreportofasurveyoflocalgovernmentperspectives.
Harvey,F.J.,B.P.Buttenfield,andS.C.Lambert.1999.Integratinggeodatainfrastructuresfromthegroundup.Photogrammetric Engineering and Remote Sensing65(11):1287–91.
Johnson,R.,Z.Nedovic-Budic,andK.Covert.2001.Lessonsfrompractice:Aguidebooktoorganizingandsustaininggeodatacollaboratives.GeodataAlliance,June20,2002.
Johnson,R.B.,andA.J.Onwuegbuzie.2004.Mixedmethodsresearch:Aresearchparadigmwhosetimehascome.Educational Researcher33(7):14–26.
Kevany,M.J.1995.Aproposedstructureforobservingdatasharing.InSharing geographic information,eds.H.J.OnsrudandG.Rushton.CentreforUrbanPolicyResearch,NewBrunswick,NJ.76–100.
Lee,A.S.1989.AscientificmethodologyforMIScasestudies.MIS Quarterly8(1):33–50.
Lincoln,Y.S.,andE.G.Guba.2000.Paradigmaticcontroversies,contradictions,andemergingconfluences.InHandbook of qualitative research,2nded.,eds.N.K.DenzinandY.S.Lincoln,163–88.ThousandOaks,CA:SagePublications.
Masser,I.1998.Governments and geographic information.London:Taylor&Francis.
Masser,I.2005.GIS worlds: Creating spatial data infrastructures.Redlands,CA:ESRIPress.
Masser,I.,andH.Campbell.1994.InformationsharingandtheimplementationofGIS:Somekeyissues.InInnovations in GIS1:217–27,ed.M.F.Worboys.London:Taylor&Francis.
Maxwell,J.A.1996.Qualitative research design: an iterative approach41.Appliedsocialresearchmethodsseries.ThousandOaks,CA:SagePublications.
Mulford,C.L.,andD.L.Rogers.1982.Chapter2DefinitionsandModels.InInterorganizational coordination: Theory, research and implementation,eds.D.A.RogersandD.A.Whettons,9–31.IowaStateUniversityPress,Ames,Iowa.
NationalResearchCouncil.1993.Toward a coordinated spatial data infrastructure for the nation.Washington,DC:NationalAcademyPress.
NationalResearchCouncil.1994.Promoting the national spatial data infrastructure through partnerships.Washington,DC:NationalAcademyPress.
NationalResearchCouncil.2001.National spatial data infrastructure partnership programs: Rethinking the focus.Washington,DC:NationalAcademyPress.
7� A mixed-method approach for evaluating spatial data sharing partnerships
Nedović-Budić,Z.ExploringtheutilityofmixedmethodresearchinGIS.(Inprogress.)
Nedović-Budić,Z.,andJ.K.Pinto.1999.UnderstandinginterorganizationalGISactivities:aconceptualframework.Journal of Urban and Regional Information Systems Association11(1):53–64.
Nedović-Budić,Z.,andJ.K.Pinto.2001.Organizational(soft)GISinteroperability:LessonsfromtheU.S.International Journal of Applied Earth Observation and Geoinformation3(3):290–98.
Obermeyer,N.J.,andJ.K.Pinto.1994.Managing geographic information systems.NewYork:TheGuildfordPress.
Oliver,C.1990.Determinantsofinter-organizationalrelationships:integrationandfuturedirections.Academy of Management Review15(2):241–65.
Onsrud,H.J.,andG.Rushton.1995.Sharinggeographicinformation:Anintroduction.InSharing geographic information.H.J.OnsrudandG.Rushtoneds.CentreforUrbanPolicyResearch,NewBrunswick,NewJersey.xiii–xviii.
Onsrud,H.J.,J.K.Pinto,andB.Azad.1992.Casestudyresearchmethodsforgeographicinformationsystems.URISA Journal1(4):32–43.
Pinto,J.K.,andH.J.Onsrud.1995.Sharinggeographicinformationacrossorganisationalboundaries:Aresearchframework.InSharing geographic information,eds.H.J.OnsrudandG.Rushton,45–64.NewBrunswick,NJ:CentreforUrbanPolicyResearch.
Prefontaine,L.,L.Ricard,H.Sicotte,D.Turcotte,andS.S.Dawes.2003.Newmodelsofcollaborationforpublicservicedelivery:Criticalsuccessfactorsofcollaborationforpublicservicedelivery.CTG.http://www.ctg.albany.edu(May1,2006).
Rajabifard,A.,andI.P.Williamson.2001.Spatialdatainfrastructures:Concept,SDIhierarchyandfuturedirections.ProceedingsofGeomatics’80,Tehran,Iran.
Tashakkori,A.,andC.Teddlie.1998.Mixed methodology: Combining qualitative and quantitative approaches46.Appliedsocialresearchmethodsseries.ThousandOaks,CA:SagePublications.
Tashakkori,A.,andC.Teddlie,eds.2003.Handbook of mixed methods in social and behavioral research.ThousandOaks,CA:SagePublications.
Teddlie,C.,andA.Tashakkori.2003.Majorissuesandcontroversiesintheuseofmixedmethodsinthesocialandbehavioralsciences.InHandbook of mixed methods in social and behavioral research,eds.A.TashakkoriandC.Teddlie,3–50.ThousandOaks,CA:SagePublications.
Thomas,R.M.2003.Blending qualitative and quantitative research methods in theses and dissertations.ThousandOaks,CA:CorwinPress.
WehndeMontalvo,U.2001.StrategiesforSDIimplementation:Asurveyofnationalexperiences.Proceedingsof5thGlobalSpatialDataInfrastructureConference,CartagenadeIndias,Colombia,May21–25,2001.
WehndeMontalvo,U.2002.Mappingthedeterminantsofspatialdatasharing.Proceedingsof8thEC-GIandGISWorkshop,Dublin,Ireland,July3–5,2002.
WehndeMontalvo,U.2003a.Insearchofrigorousmodelsforpolicy-orientatedresearch:Abehaviouralapproachtospatialdatasharing.URISA Journal15(1):19–28.
McDougall et al. 7�
WehndeMontalvo,U.2003b.Mapping the determinants of spatial data sharing.Aldershot,England:AshgatePublishingLtd.
Williamson,I.P.,andC.Fourie.1998.Usingthecasestudymethodologyforcadastralreform.Geomatica52(3):283–95.
Yin,R.K.1994.Case study research: Design and methods,2nded.,vol.5.Appliedsocialresearchmethodsseries.ThousandOaks,CA:SagePublications.