Journal of Innovation

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Journal of Innovation

& Knowledge

https://www.journals.elsevier.com/journal-of-innovation-and-knowledge

Conceptual paper

Information technology for supporting the development and maintenance of open innovation capabilities

Emmanuel Adamides, Nikos Karacapilidis

^∗

IndustrialManagementandInformationSystemsLab,MEAD,UniversityofPatras,Greece

a r t i c l e i n f o

Articlehistory:

Received6June2018 Accepted2July2018 Availableonlinexxx

Keywords:

Openinnovation ICT

Capabilities

Knowledgeengineeringandmanagement Collectiveandcollaborativeintelligence

a b s t r a c t

WediscussICTforOpenInnovation(OI)fromacapabilitiesperspective.Wedistinguishtwotypesof capabilitiesforOI:strategic,whichneedtobedevelopedsothattheorganizationcantakeadvantage ofanOIstrategyproactively,andoperationalfortheefﬁcientimplementationofOIprocesses.ICTat thestrategiclevelsupportsdynamiccapabilitiesandrelatedcognitiveprocessesofmanagerialstafffor developingandusingtheappropriatelevelofabsorptivecapacityandactivetransparency,whereasICT aspartofoperationalcapabilitiesaimsatenhancingtheday-to-dayperformanceofOIactivities.Through analysisofcapabilities,weassociatespeciﬁcICTwiththefunctionalitiesrequiredintheentireOIprocess.

Payingparticularattentiontotheissuesofcollaborationandsophisticateddataanalysis,wealsocomment ontheseamlessintegrationofthesetechnologiesandtheirembedmentinOI-relatedorganizational processes.

Introduction

Undoubtedly, Open Innovation (OI) has become an estab- lished paradigm in innovation strategy. According to its main proponent, it is “the useof purposive inflows and outflows of knowledgetoaccelerateinternalinnovation,andexpandthemar- ket for external use of innovation, respectively” (Chesbrough, 2006). The adoption of OI by an organization implies that its innovationmanagementprocess(Tidd&Bessant,2014)becomes porous,andideas,concepts,designs,products,services,etc.,flow in and out of its boundaries. At the same time, internal and externalorganizationactors,suchasmanagers,users/customers, employees,suppliers,competitors,researchersandregulatorsare interconnectedinmanydifferentways.Infact,itisthedifferent human and non-human knowledge sources that are intercon- nected, while informational and knowledge items of different formsflowbetweenthemandaretransformedinmanydifferent ways.Clearly,inlargecomplexorganizations,thisisaccomplished inacomplexwebofsocialprocesses(Anderson&Hardwick,2017), inwhichparticipateagentsofdifferentviews,interests,cultures andpowerstatus(MotaPedrosa,Välling,&Boyd,2013),usually situatedgeographicallyandcontextuallyatadistance.

It hasbeenarguedthatorganizations aimingatan OIstrat- egymust beabletomanage theserelationships, processes and

∗ Correspondingauthor.

E-mailaddresses:[email protected](E.Adamides),[email protected] (N.Karacapilidis).

agencieseffectively,inordertogainfromtheirdiversity(Sarker, Sarker,Sahaym, &Bjørn-Andersen, 2012).In other words,they need todevelop a setof capabilitiesfor making theirinterface totheexternalenvironment moretransparent,aswellastobe abletoabsorband assimilateknowledge fromdifferentsources inanefﬁcientandeffectivemanner,inadditiontodisseminating knowledge-containing artefacts of value totheir external envi- ronment(Hosseini,Kees,Manderscheid,Röglinger,&Rosemann, 2017).Thesecapabilities arebased on, aswellascontribute to thedevelopmentof,anorganisation’sabsorptive(anddesorptive) capacity that leverages its knowledge management operational processes,sothat knowledgefromtherightsource(s)arrivesat therighttime,inthemosteffectivemanner.

This suggests that, in order to embrace OI, an organization shoulddevelopcapabilitiesattwolevels:(i)atthestrategiclevel (dynamiccapabilities),bypreparingitsmemberssothattheyare abletoabsorb,utilizeandtransformtherightexternalandinternal knowledgeintovaluetobedisseminatedtotheeconomythrough thedevelopmentoftheappropriateoperationalcapabilitiesand(ii) attheoperationallevel,forconnectingknowledgesources,aswell asforsupportingthetransferandtransformationoftherequired knowledge right.Given thecomplexity ofthese tasks(Sanchez, Heene,&Thomas,1996),inthecontextofpluralisticanddistributed modernorganizations,informationandcommunicationtechnolo- gies(ICT)haveaveryimportantroletoplayinthedevelopment, maintenanceandappropriationofthesecapabilities(Majchrzak&

Malhotra,2013).

Theuseof ICTinOIimplementationshasbeenstudiedfrom differentperspectives(e.g.Bengtsson&Ryzhkova,2013;Bugshan,

https://doi.org/10.1016/j.jik.2018.07.001

2444-569X/© 2018 Journal of Innovation & Knowledge. Published by Elsevier Espa?a, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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2015;Corvello,Gitto,Carlsson,&Migliarese,2013;Cui,Ye,Teo,&

Li,2015;Dodgson,Gann,&Salter,2006;Hrastinski,Kviselius,Ozan,

&Edenius,2010),andanumberofOIplatformsarenowavailable (Bieler,2016).Nevertheless,sofar,researchhasnotconsideredthe importanceandstructureofICTinfrastructureforOIoperational capabilitiesinaholisticmanner:themajorityoftheseeffortsasym- metricallyconcernpredominatelythefront-endoftheinnovation process,i.e.concentrateontheinteraction/interfacingoftheorgan- isationwithexternalparties,andpaylittleattentiontoknowledge integrationand(re)generation(Malhotra&Majchrzak,2016).They considerindividualfront-endOIprocesses,mainlyfromafunctional simpliﬁcationperspective,i.e.howtoreducethecomplexityofreal processesbyimposingstructure(orderedproceduralsequences), tosealoffprocessesfromtheirmessyandambiguousenvironment, and tomake them “transferable” bydetachingthem fromtheir socialcontext(Kallinikos,2011).Thisfragmentedandstylisedfocus toindividualOIprocessesandstakeholders(Corvelloetal.,2013) isdesirableonlywhentheobjectiveistodevelopstaticstrategies of(knowledge)depth/intensity,asfarasexternalknowledgeman- agementisconcerned(Cuietal.,2015),throughintegrationofan organisation’sinformationsystemswithspeciﬁcexternalknowl- edgesources(Barua,Konana,Whinston,&Yin,2004;Rai&Tang, 2010).LimitedresearchhasaddressedtheroleofICTinthedevel- opmentandmaintenanceofthedynamiccapabilitiesrequiredfor thedeploymentofmoredynamicOIstrategies(Cuietal.,2015).

AholisticconsiderationofICTforopeninnovationcanbefacili- tatedbyadoptingacapability-basedperspective.ICTartefactsof various forms are assets engaged in capability-deﬁning knowl- edgeandsocialprocesses/routinesatdifferentlevelsandmodes.

Forinstance,thereareanumberofICTtoolsthatcanbeusedon thesideofactualOIoperationalprocessestodevelopandexploit organizationalabsorptive(anddesorptive)capacityina cooper- ativemanner for enhancingOI-related dynamic capabilities (in therestofthepaper,withoutlossofgenerality,weusetheterm absorptivecapacitytoincludetheintangibleassetofdesorptive capacity).These,togetherwithabouquetofICTtechnologiesfor supportingoperationallevelcapabilities,canprovidethebasisofa technologyinfrastructureforOI.Towardsthisend,inthispaper,by adoptinganinboundOIperspective(Gassmann&Enkel,2004),and byjuxtaposingOIcapabilities’requirementswithbasicinforma- tionsystemfunctionalitiesandassociatedtechnologyandsystems characteristics,wediscuss,for theentireOIprocess,theassoci- ationofknowledgemanagementcapabilitiestoICTsastheyare moderatedbyspeciﬁcOImodels/strategies.Theaimis tofacili- tatedmanagementdecisionsontheemploymentoftechnologyfor OpenInnovationstrategies.Theresearchanddiscussionarebased onsecondarysources,aswellasontheﬁndingsandtheexperi- encefromthedevelopmentanduseofrelatedcollaborativeand knowledge-managementinformationsystemsintheframeworkof asetofprivateandpublic,nationalandmulti-nationalprojects.

Thepaperalsodiscussestechnologiesfortheseamlessintegration oftheabovementioned ICTsand theirembedment inthe orga- nizationalprocesses,payingparticularattentiontotheissuesof collaborationandsophisticateddataanalysis.

OpenInnovation,organisationalcapabilitiesandICT requirements

StrategiccapabilitiesforOI

In the resource-based view (RBV) of strategy, competitive advantage is a function of the availability of certain resources and capabilities (Grant, 1997). Capabilities are constituted by assets/resources,suchasICTartefacts,androutines/processesfor deployingtheseassets (Amit&Schoemaker,1993).Ina generic capabilitiesperspective,strategiclevelcapabilitiesforOIarelinked

tothenotionofdynamiccapabilities(Teece,Peteraf,&Leih,2016), i.e.totheabilitytoselectorchangeoperational/ordinarycapabil- itiesandswitchstrategiesbetweenbreadth(diversity)anddepth (intensity)intheeffectiveuseofknowledgesources(Laursen&

Salter,2006).More speciﬁcally,theyarelinkedtoan organization’sability toinnovatethroughtheappropriationof theright knowledgebysensingtheenvironment,seizingopportunitiesand transformingitsinnovationprocess(es)andvalueofferings.Sensing isassociatedwithexploration,whereasseizingwithbothexploita- tion of the internalized environmental signals, ideas, concepts, technologies,etc.,aswellaswiththeexplorationoftheexternal environmentforgainingeconomicvaluefromtheinnovativeprod- uctsand/orservicesdevelopedthroughtransformingactivities.In theinboundopeninnovationapproach,alltheseactivitieswillhave acertaindegreeofopennesstoo(Tavakoli,Schlagwein,&Schoder, 2017),whiletheireffectivenesswilldependonthelevelofabsorp- tivecapacity(ACAP)oftheorganization(Cohen&Levinthal,1990), aswellasonitslevelof“activetransparency”,whichmaybedeﬁned asaformof“generativesensing”(Cuietal.,2015;Dong,Garbuio,

&Lovallo,2016).

Activetransparencyallowsanorganisationtocontrolproac- tivelyandeffectivelyitsinterfacewiththeexternalenvironment, asfarasknowledgeinflowsandoutflowsareconcerned.Boththe activetransparencyandACAPofanorganisationdependonthe correspondingqualitiesofitsindividualmembers.Activetrans- parencyreferstoanactiveorganisationalinterfacethathasthe abilitytodevelophypothesesonthepossibleuseand effectsof incomingand outgoingknowledge items, and to test them for theirvalidity(Dongetal.,2016).ACAPdeterminesanorganiza- tion’scapabilitytorecognizethevalueofnewexternalinformation, assimilateit,andapplyittocommercialends(Cohen&Levinthal, 1990).Recentresearchdirectlyassociatesabsorptivecapacityto thedynamic capabilitiesframeworkandstressesitsimportance asadegrees-of-freedomprovidertowardsinnovationandchange (Teeceet al., 2016;Zahra&George,2002).Absorptive capacity isafunctionoftherichness/diversityofthepre-existingknowl- edgestructure,personalized(tacit)andimpersonalized(codified).

Hence,althoughsomeauthorsconsiderACAPasdynamiccapabil- ity(e.g.Lichtenthaler&Lichtenthaler,2009),inourviewitmore appropriateforOI,andclosertotheactualdeﬁnitionofcapabilities, toconsideritasanintangibleaccumulatinganddepletingstrategic assetemployed/usedinorganisationalprocesses/routines.

Understanding dynamic capabilities requires understanding theirmicrofoundations(Dongetal.,2016;Helfat&Martin,2015).

Atthatlevel,theimportanceofthediversityofpriorknowledge inlearning(Cohen&Levinthal,1990)canbebetterunderstoodby consideringtwokeyattributesofmentalmodelsthataredirectly relatedtoabsorptivecapacity:complexityandcentrality(Nadkarni

& Narayanan,2005). Complexity is the result of the degree of differentiation(therange/diversityofinternalandexternalorga- nizationalconceptsincludedinthementalmodel)andintegration (degree ofconnectedness among concepts) ofthemodel. Com- plexchange-andinnovation-related mentalmodelsallowﬁrms tonoticeandrespondtoalargernumberofdifferentstimuli,thus increasingtheirinnovationcapacity.Theyallowmanagerstoscan theenvironmentandrespondtoincomingstimulimoreeffectively byassociatingenvironmentaleventswithelementsoftheexisting organizationalknowledgebase.Centrality,ontheotherhand,refers tothefocusandhierarchyofmentalmodels.Acentralizedmodel isfocusedaroundalimitednumberofcoreconcepts.Asaresult, it is complexmental models thatare responsible forincreased absorptivecapacityandactivetransparency,makingtheorgani- zationmoreresponsivetoexternalsignals,andbetterpositioned asfarasexploitationofthebeneﬁtsofOIareconcerned(Doz,2013).

Knowledge creation is largely associated with interaction and socialisation (Nonaka & Takeuchi, 1995). So, a knowledge

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management strategy for OI that aims at the efficient and effectivecreation ofknowledge fromdifferentintra-and inter- organizationalsources,aswellasataugmentinglearningcapacity, shouldbeprimarilytargetedontheuseofICT forthedevelop- mentofsocialcapital,ratherthanontheinstallationoftechnology systemsforthestorage,transformation anddistributionofcod- ified knowledge (Lichtenthaler &Lichtenthaler, 2009).Towards thisobjective,threemainareasofinterventionareofparticular importance:(i)interveningonthewaymentalmodelcharacteris- ticsinfluencetheaccumulationoflearningcapacity,(ii)improving managerialparticipationinthedevelopmentofinnovationstrate- gies and in the deployment of required operational processes, and(iii)improvingtheprocesses,methodsandtoolsforassessingthefutureenvironment.Inotherwords,theobjectiveofopen innovationand flexible learning asstrategic capabilitysuggests a personalization rather than a codification knowledge management meta-strategy (Scheepers,Venkitachalam, &Gibbs, 2004), payingparticularattentiontoidentifyinglearninggaps,ratherthan knowledgeones.Informationandcommunicationtechnologyhas animportantroletoplayinthisstrategicchoice.Thereisawide rangeoftechnologiesthatcanbeusedforaugmentinglearningpro- cessesandbuildingACAPandactivetransparency.In“Technologies forstrategicOIcapabilities”section,wediscussthesetechnologies inthecontextoftheirusefordevelopingandsupportingdynamic capabilitiesforOI.

OperationalcapabilitiesforOI

Inadditiontothestrategic(dynamic)OIcapabilitiesthatare associated with the development of an infrastructure for aug- mentingorganisationallearning,thedevelopmentofoperational levelcapabilitiesisnecessarysothatOIprocessesaresupported appropriatelyintermsofefﬁciencyandeffectiveness(Chen,Wang, Nevo,Benitez-Amado,&Kou,2015).ThestructureofOIprocesses dependsonthemodelofOIadopted.Ingeneral,therearefouroper- ationsmodelsassociatedwiththeinboundOIapproach(Möslein, 2013).Ininnovationmarkets,organizationsandindividualsactas seekersofinnovationsolutionsandsolversofinnovationproblems.

Thismodelis usuallyimplementedthrough intermediariesthat facilitatethematchingofproblemstosolutions.Inthemodelof firm-sponsoredinnovationcommunitiesagentsofdifferentsizeand complexitydevelopideas,discussconceptsandpromoteinnova- tion.Crowdsourcingisaparticularstrategyintheframeworkof thismodel.Ininnovationcontests,afirmgetsideasforproducts, services,solution,orevenbusinessmodelsfromdifferentsources (customers,suppliers,etc.)whicharealsoinvolved,inassociation withpanelsof experts,intheirevaluationand selection. When innovationtoolkitsareused,usersdevelopsolutionsinprescribed steps,sometimesusing standardcomponentsand modulesin a predefinedsolutionspace,andinteractingwiththecompanyto getfeedback.Theformertwoapproachesarebasedonadyadic (1:1),whereas thelattertwo ina network collaborationmodel (1:n/n:n).Innovationmarketsandtherelatedsocialproductdevel- opmentforums,aswellastheideascontests,providesolutionspaces witha highnumber ofdegreesof freedom,whereasinnovation andco-designtoolkitsandinnovationcommunities,throughpre- definedprocedures,restrictthesolutionspaceandprocesses(Piller

&Ihl,2013).

Regardingthe capabilitiesrequired to supportopeninnova- tion,afterreviewingrelatedliteratureanddistillingitsaggregate formulations (e.g. in Hosseini et al., 2017 and Lichtenthaler &

Lichtenthaler,2009),wecanconcludethat,inadditiontocollabora- tion(COLB),themostimportantcapabilitiesfortheimplementation of OI are: knowledge exploration (KXPL), knowledge exploitation (KXPT),knowledgeretention(KRTN),decisionmaking(DMKG),partnerrelationshipmanagement(PREM),socialintegration(SINT),and

intellectualpropertymanagement(IPMA).Clearly,theimportance ofthesecapabilitiesvariesacrossthespectrumoftheabovemod- elsofOI,especiallyasfarastheupstreamstagesoftheinnovation processareconcerned.Acoarse-graininnovationprocessconsists ofthesequenceofactivities:ideageneration,selectionandcon- ceptualizationofproduct/service/process,technicaldevelopment, product/servicelaunch,and(possibly)improvementoftheconcept (Tidd&Bessant,2014).

Knowledge exploration (KXPL) is a capability needed in all modelsofOIfortheideagenerationphasetosupportthesourc- ing,internallyandexternally,ofasmanyaspossibleanddiverse ideasforproducts,concepts,etc.KXPLmayconcerntheexperi- enceavailable in theorganisation, experimentationcarried out withconceptsandideasintheorganisation,ortheacquisitionof externalknowledge(Tidd&Bessant,2014).Itisdirectlylinkedto absorptivecapacity,andifthereisnotavailableatasufﬁcientlevel, intermediariescanactascompensators.Inaddition,intheinno- vation communitymodel, inthe samephase, social integration (SINT)capability (capabilitytofacilitateinteractionand coordi- nateindividualsbuildingrelationswithexternalentities,suchas universitiesandresearchinstitutes,orprojectsandprojectman- agersinotherorganisations)isrequiredtostrengthenrelationships inthecommunityandtodevelopsocialcapital(trustandqual- ity communications) and commonunderstanding.Moreover,in theinnovationtoolkitsmodelthat offersa morerestrictiveand structuredinteractionprocess,closerrelationshipswithexternal agenciesrequirehigherpartnerrelationshipmanagement(PREM) capability(capabilitytoidentify,assessandselecttherightpart- ners, as well as to motivate them so that they contribute to innovation).

In thesamemodel, PREM isnecessary fortheselection and conceptualizationphase,asexternalpartnersareactivelyengaged.

InallOImodels,thisphaserequiresacertainlevelofknowledge exploitationcapability(KXPT)tocombineexternalknowledgewith existinginternalone,motivateinternalsourcestocontribute,make tacit knowledgeexplicitandcommercializeit throughproducts andservices.Italsorequiresdecisionmakingcapability(DMKG) forconstructingandmanagingaportfolioofprojects(principally investment and resource allocation decisions) for the selected ideas/conceptsandformakingdecisionsonissuesrelatedtoIntel- lectualPropertyRights.DMKGandKXPTcapabilitiesarenecessary forthetechnicaldevelopmentstagetoo.Inaddition,organizations havetohaveeffectivemechanismsformaintainingtheirknowl- edge (knowledge retention capability (KRTN))that is produced duringthe technicaldevelopmentof theconcept/producttobe usedinconsecutiveprojectstoshortenthedevelopingtimeand thetimetomarket(marketlaunchphase).Knowledgeretention isalsoachieved,indirectly,byretainingrelationshipswithimpor- tantpartners-holdersofknowledge.Tohaveaneffectivemarket launchphasewithtimelyproduct/serviceintroductions,useofpre- viousknowledgeisnecessary(KXPT),aswellaseffectivepartner management(PREM).Before,oratthesametime,activitiesforthe managementofintellectualpropertymustbeundertakenbydecid- ingwhattodiscloseandwhatnot(needforintellectualproperty managementcapability,IPMA).IPMAcapabilityisrequiredinmost innovationprocessstagestoassessIPheldintheorganisation,to identifyIPneededandpossiblyheldbypartners,tovalueIPexposed tootherparties(importantininnovationcommunitiesmodel)and tosearchforIPforsourcing.

Operationalcapabilitiesarereifiedinorganizationalprocesses thatusespecificassets.Forinstance,theknowledgeexploration capabilityistypicallyreifiedina“knowledgeseekingandfinding”

organisationalprocesses.Infact,alltheaforementionedcapabili- tiesareassociatedwithprocessesthataredominatedbyactivities of collaborative interaction (between information sources) and transformation/processing(ofdata/informationitems).Inthecom-

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Fig.1.Theproposedcapability-basedframeworkforOpenInnovationanditsassociationwithICT.

plex and pluralistic context of modern organizations, efﬁcient deploymentoftheseactivitiesrequiresthesupportofICT(Cuietal., 2015).Intermsofbasicinformation systemsfunctionalities and operationstheserequirementscorrespondtoencodingtheuser(s) willandemotions,theautomaticorhuman-assistedaggregation of the encoded data, the computability of the data/information forconstructingmeaning(Alaimo&Kallinikos,2017),aswellas exchangeandtransformation,andstorageandretrievalofdatain variousformats.Morecomplexoperations/functionalities,suchas experimentation,dialoguing,processrepresentation,etc.arebased onthesebasicoperations.Technologiesfor implementingthese functionalitiesarediscussedin “TechnologiesforoperationalOI capabilities”section.Someofthesetechnologiescanbeassetsto both strategicand operationallevel capabilities. Ourdiscussion hasacriticalperspectivetowardsisolated/fragmentedadoption, arguingfor theirintegrationintheframework of a ﬂexible ICT infrastructure.Fig.1depictstheentirecapability-basedframework forOpenInnovationdiscussedaboveanditsassociationwithICT.

ThespeciﬁcICTdepictedintheﬁgureforbothlevelcapabilitiesare discussedinSections“Technologiesfor strategicOIcapabilities”

and“TechnologiesforoperationalOIcapabilities”.

TechnologiesforstrategicOIcapabilities

Onthebasisofthethreeabovementioned(see“Strategiccapa- bilitiesforOI”section)areasofinterventionforbuildingstrategic dynamic OI capabilities for scanning, seizing and transform- ingknowledge, three knowledge-management-related practices (boundaryspanning,collaborativeproblemsolvingandparticipa- tivescenarioplanning)withtheirassociatedprocesses(routines) andICTtoolsets(assets)arepresentedbelow.Table1presentsthem inacompactform.

Boundaryspannersandboundaryobjects

Inmodernorganizationswithmodularanddistributed characteristics,there isaninherenttendencytolocalizeand embed knowledgeandlearningpracticeswithintheboundariesofindi- vidualmodules.Interfacing withothermodules isby meansof pre-deﬁned,standardizedinterfaces.Clearly,thislogicincreases mental model centrality and fragments knowledge and know- ing,and theircreativeinterplay in strategicprocesses (Amin&

Cohendet,2004).However,OIrequiresthecreationof“hotspots”of

creativityandinnovationwherepeople“workingacrossfunction, nationalandorganizationalboundaries”areenergeticallyinvolved (Gratton,2013).Therequirementforcrossingboundariesisnotjust tofacilitatecommunication,butprincipallytoresolvethenegative consequencesoftheattitudesoftheindividualsfromeachorgani- zationandmoduleagainstalteringtheirownknowledge,aswell astoleveragetheircapabilitiesofinﬂuencingortransformingthe knowledgeusedbyothers.Knowledgeboundarieslimitnotonly organisationalprocessesforrespondingtoenvironmentalsignals whenchangesattheinterior,exteriorandarchitecturallevelofpro- cessesandproductsneedtotakeplace,butalsotheplanningforthe futurewhenknowledgegeneratedisbeingexploited.Twointerre- latedconceptshavebeendevelopedforovercomingtheproblems ofknowledgeboundariesandfacilitatingdistributedcoordination:

boundaryspannersandboundaryobjects.

Boundaryspannersareorganizationmembersassignedthespe- ciﬁcroleoffacilitatingthecollaborationofindividualsindifferent organizationsordifferentorganizationmodules.Theycoordinate activitiesacrossandontheedgeofboundariestheycrossoroverlap.

BoundaryspannerscanbecomplementedbyICTboundaryobjects, whichareartefactsusedtocreatesharedcontextamongdifferent partiesincross-moduleactivities.Carlile(2002)formedaclassi- ﬁcationofboundaryobjectsintorepositories,standardizedforms andmethods,andobjects,modelsandmaps.Thislastcategoryis theonlyonethatdirectlysupportsthetransformationofknowl- edge,inadditiontorepresentationandlearning,andthereforeis suitableforovercomingknowledgeboundaries.

Boundaryobjectssuchasprocessmaps,strategymaps,process andsystemdynamicssimulationmodels,collaborativelymanipu- lated/drawn2Dand3Dobjects,aswellascomputer-basedlearning environments, can trigger and support learning-by-adaptation, eliminating,probablywiththehelpofaboundaryspanner,knowledge boundaries. From a different perspective, theyconstitute

“transitionalobjects”(Morecroft,2004)foraligningin theshort term,andexpanding,inthelongterm,mentalmodelsofindivid- ualsindifferentfunctionsandorganisations,thusincreasingthe effectivenessofcollaboration.Graphicalmodellingandsimulation environmentsin which models arebuilt include discrete-event simulations systems such as Arena, Extend, ProModel, etc., sys- temdynamicsmodellingsystems,suchasVensin,Powersimand ithink,aswellasagent-basedsimulationenvironments(AnyLogic, etc.).Allcanbeintegrated,technicallyandoperationally,inwider enterprise-levelinformationsystems,suchasERP.

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Table1

MethodsforthedevelopmentofOIstrategiccapabilitiesandtheirsupportingICT.

Requiredstrategiclevelcapabilitiesdevelopmentactivities(processes) MethodsandsupportingICT(assets) Activities:

Interveneonthewaymentalmodelcharacteristicsinﬂuencethe accumulationoflearningcapacity

Requirements:

Developmentoftheconditionsforboundaryspanningthroughboundary objects

• Graphicalmodellingandsimulationenvironments(discrete-event:Arena, Extend,ProModel,etc.,systemdynamics:Vensin,Powersim,ithink,etc.,as agent-based:AnyLogic,etc.

• Integrated,technicallyandoperationally,inwiderenterprise-level informationsystems,suchasSAP

Activities:

Improvemanagerialparticipationinthedevelopmentofinnovation strategiesandinthedeploymentofrequiredoperationalprocesses Requirements:

Supportcollaborationforissueresolutionandstrategicthinking

• Participativesystemsmethodologies(problem-structuringmethodologies, suchasSSM,SODA,etc.)

• Simulation-basedparticipativemodelling,methodologies

• Informationsystemssupportingcollaborationandargumentation Activities:

Improveprocesses,methodsandtoolsforassessingthefutureenvironment Requirements:

Establishpracticesforparticipativescenarioplanning

• Methodsofintuitivelogics(qualitative)

• MethodsthatbelongtotheareaofProbabilisticModiﬁedTrends(PMT)(IFS (InteractiveFuturesSimulations),INTERAX(InteractiveCrossImpact Simulation),SMIC(CrossImpactSystemsandMatrices)withtheir correspondingsupportsoftwaretools

• Methodof“LaProspective”(Micmac,ProbExpert,ScenaringTools,etc.)

Methodsandsystemsforcollaborativeproblemsolving

Whenusedatcross-functionalandcross-organizationallevel, collaboration supporting methods and systems can be consid- ered as a particular class of boundary objects that promote diverseparticipation and facilitate theactivation of the micro- instantiationoftheorganizationalknowledgecycleoverparticular cross-organisational/functionalissuesandproblems(Adamides&

Karacapilidis,2006).Asindicatedin“Web2.0collaboration”and

“Argumentative knowledge construction”, computer-based collaboration and argumentation systems can actively supportOI operational processes. Similar methods and artefacts can also beusedatthestrategiclevel tostructureproblem-solving/issue- resolvingprocessesandtherelateddialoguing.Bythecollaborative developmentand manipulationofstructuredmodels,aswellas bytheembedmentofdialecticlogicintheformofargumentation schemesinthecollaborationprocesses(dialecticlogicfacilitates synthesis of perceptions), they can increase the organization’s problem-solvingand planningcapability.Informationand com- municationtechnologiesareusedtosupporttheknowledgeﬂows amongtherelevantactorsandartefacts,inawaythatenhancesthe creationofnewknowledge(theprocessofknowing).Thesearethe maintasksofaclassofComputer-basedKnowledgeManagement Systems(CKMS),whicharesystemsthatprovideacorporatemem- ory,i.e.anexplicit,disembodiedpersistentrepresentationofthe knowledgeandinformationinanorganisation(asortofknowledge base)andmechanismsthatimprovethesharinganddissemina- tion of knowledge by facilitating interaction and collaboration.

Moreover,theprovisionof anassociatedICTinfrastructure that supportsvirtuality(dispersedgroups,asynchronouscollaboration) attractswidermembershipandhenceincreasesthediversityand richnessofknowledge,promotesactiveparticipation,andfurther increasestheproductivityofstrategicissueresolution(Adamides

&Karacapilidis,2006;Adamides&Pomonis,2008).

Themethodsandsystemsdevelopedoverthelasttwodecades forsupportingcollaborationinissueresolutionincludeparticipa- tivesystemsmethodologies(problem-structuringmethodologies, such as SSM, SODA, etc.), methodologies that rely on simula- tionmodelling,methodologiesthatusecollaborativeinformation technology,andinformationsystemssupportingcollaborationand argumentation(Adamides&Karacapilidis,2006).Thesesystems haveasigniﬁcantroletoplayasfarasthedemocratizationofinno- vationisconcerned(vonHippel,2006),whichgoesbeyondmere gatheringideas/conceptsfromdiversesources.Whilesomeofthe availablenetworkingandcollaborationsupportingsoftwarepack- ages,suchasLotusNotes,contributetofunctionalspeciﬁcationand

homogenisationininformationdistributionandtotheconserva- tionofpowerstructures(Lilley,Lightfoot,&Amaral,2004),thus limitingpluralisminactualinnovation,moresophisticatedtools, asthosementionedin“Web2.0collaboration”and“Argumentative knowledgeconstruction”,reachingwiderparticipationandimple- mentingmoredemocraticrationalesinargumentationandconﬂict resolution,embeddedinspeciﬁcorganisationalcontextsappropri- ately, canactas enablersoftheenlargement oftheinnovation discourse,andasarbitratorsthatfacilitatethere-distributionof power.

Participativescenarioplanning

Scenario planning is the most frequently used tool of the

“prosessualistic”, or learning, school of strategic management (Schoemaker,1995)thathaspenetratedtheﬁeldofstrategicinno- vationmanagement(Tidd&Bessant,2014)andthedevelopmentof dynamiccapabilities(Teeceetal.,2016).Thevalueofscenarioplan- ningdoesnotstemfromtheoutcomesitproducesbutratherfrom theprocessofscenarioconstruction,whichthroughthedynamic interactionbetweentheorganizationandtheenvironment,stim- ulates learning byconsidering possibleand “impossible”future eventsandtheirconsequences.Writtenscenarios,frequentlycom- plemented by computer simulations, are used to explore the concurrentimpactofvariousuncertaintiesbymodifyingmultiple variablesatatimeandbyspeculatingontheiroutcomes.Inthis way,theprocessofscenarioconstructionstimulatesandfacilitates thesharingandrecombinationofpersonalknowledgetobuilda holisticunderstandingoftheinternalandexternalenvironment oftheorganization.Scenarioplanningmakesexplicittheimplicit assumptionsofindividualsaboutthefuture,stimulatingcreative andinnovativethinking(Karacapilidis&Gordon,1995;Meissner&

Wulf,2013).

Scenarioplanningconstitutesoneofthemostpopularandeffec- tiveexercisesforknowledgecreationandlearninginknowledge management initiatives suchas communities of practice (CoP).

Managersfromdifferentdepartments,aswellasexternalactors, participateinatypicalscenarioconstructionprocess,whichisusu- allycomprisedbyanumberofdistinctstages(Schoemaker,1995) usingICTthatcomprisesdatabaseswithspecialisedoptimisation and simulation methods. A largenumber of publicand private organizationsusesscenarioplanninginconnectionwithadvanced informationsystems (corporatedataand knowledgebases,eco- nomicintelligencedatabases,GIS,technologydatabases,etc.)for mentallyvisitingthefutureinordertobuildtherequiredﬂexibility intheirtangibleandintangiblestrategicresources.

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Scenariomethodsandtoolsincludemethodsofintuitivelogics, whichdonotapplyquantitativeassessmentandrequirelimitedIS support,methodsthatbelongtotheareaofProbabilisticModiﬁed Trends(PMT)andincludemethods,suchas,IFS(InteractiveFutures Simulations),INTERAX(InteractiveCrossImpactSimulation),SMIC (CrossImpactSystemsandMatrices)withtheircorrespondingsup- portsoftwaretools,andtheFrenchmethodof “LaProspective”, supportedbyanumberofsoftwaresystems(Micmac,ProbExpert, ScenaringTools,etc.)(Amer,Daim,&Jetter,2013).

TechnologiesforoperationalOIcapabilities

Asithasalreadybeenmentioned,collaborationisthedominant characteristicofOIprocesses.Fromthetechnologypointofview, comparedtotraditionalgroupwareapplicationsforbrainstorming, argumentationandgroupdecisionsupport,thediversetypesof ICT-basedopeninnovationsystemsdifferintermsofthenumber ofusers(scale)andgoalofthesystem,inthatopeninnovationsys- temsassume,bydesign,alargernumberofusersandanarrower goal(Klein&Convertino,2015).Thisgoalislargelysupportedby Web2.0technologies(O’Reilly,2008), whichledtonewknowl- edgesharingparadigms due totheirinherentuser-friendliness, intuitivecharacterandﬂexibility.Atthesametime,asdiscussed intheprevioussections,ithasbeenbroadlyadmittedthatknowl- edgemanagementplaysaninvaluableroleininnovation,inthat itfostersaknowledge-drivencultureandassistsincreatingtools, platformsandprocessesfortacitknowledgecreation,sharingand leverage,whichplayanimportantroleintheinnovationprocess (Adamides&Karacapilidis,2006;duPlessis,2007).

Keyknowledgemanagement(micro)processes(i.e.retrieving, sharing and developing knowledge) ensure informed decisionmaking and stimulate organizational learning. Recent research suggeststhattheICTtoolsforfacilitatingsuchprocessesshould(i) attractwideparticipation,howeverinacontrolledmanner,(ii)sim- plifycollaborationtowardsknowledgeco-creation,(iii)enablea formalknowledgestructureforre-useandreasoningpurposes,and (iv)supportasophisticatedcollectionandanalysisofassociated bigdatamostlycomingfromrelatedsocialmedia(delGiudice&

dellaPeruta,2016;Hrastinskietal.,2010;Mount&Martinez,2014).

BelowwepresentandcommentonthemainICT-basedpractices andassociatedtoolsforbuildingthistypeofOIcapabilities.

Web2.0collaboration

TheemergenceoftheWeb2.0eraintroducedaplethoraofcol- laborationtools,whichenableengagementatamassivescaleand featurenovelparadigms.Thesetoolscovera broadspectrumof needsrangingfromknowledgeexchange,sharingandtagging,to socialnetworking,groupauthoring,mindmappinganddiscussing.

FacebookandLinkedInarerepresentativeexamplesofsocialnet- workingtoolsthatfacilitatetheformationofonlinecommunities amongpeoplewithsimilarinterests; toolssuchasMindMeister and Mindomo aimto collectively organize, visualize and struc- tureconceptsviamapstoaidbrainstormingandproblemsolving;

DebatepediaandCohere(http://cohere.open.ac.uk)aretypicaltools aimingtosupportonlinediscussions over theWeb;phpBB and bbPressareWeb2.0applicationsenablingtheexchangeofopin- ions,focusing especiallyonproviding anenvironmentin which userscanexpresstheirthoughtswithoutpayingmuchattention tothestructureofthediscussion.

Generallyspeaking, theabove technologiesenable themas- siveandunconstraintcollaborationofusers;however,this very feature is the source of the information overloadproblem. The amountofinformationproducedandexchangedandthenumber ofeventsgenerated withinthesetoolsexceeds byfarthemen-

talabilities ofusersto: (i)keep pacewiththeevolution ofthe collaborationinwhichtheyengageand(ii)keeptrackoftheout- comeofpastsessions.CurrentWeb2.0collaborationtoolsexhibit two important shortcomings making them proneto the prob- lemsofinformationoverloadandcognitivecomplexity.First,these toolsare“informationislands”,thusprovidingonlylimitedsupport forinteroperation,integrationandsynergywiththirdpartytools.

WhilesomeprovidespecializedAPIswithwhichintegrationcanbe achieved,theseareprimarilyaimedatdevelopersandnotatend users.Second,Web2.0collaborationtoolsareratherpassivemedia, i.e.theylackreasoningserviceswithwhichtheycouldactivelyand meaningfullysupportcollaboration.Inotherwords,theyconcen- tratemoreonencodingtheuserandexchangeoperationsthanon informationaggregationandcomputability.

Overall, Web 2.0 collaboration support tools can contribute directly to the development and support of processes associ- atedwith thecollaboration(COLB) capability, and indirectlyto thoseassociatedwithknowledgeexploration(KXPL),knowledge exploitation(KXPT),knowledgeretention(KRTN),andsocialinte- gration(SINT).Inmanycases,throughsophisticatedmechanisms foruserproﬁlingandnetworking,theycanalsosupportthedevel- opmentofthepartnerrelationshipmanagement(PREM)capability.

Argumentativeknowledgeconstruction

Collaborativeknowledgeco-creationandlearningprocessesare oftenbasedonwrittenargumentativediscourseofvariousstake- holders,who discuss theirperspectives ona problemwiththe goaltoresolveitandacquireknowledge(Weinberger&Fischer, 2006).Asfarasargumentationrelatedprocessesareconcerned, varioustechnologiesfocusingonthesharingandexchangeofargu- ments, diverse knowledge representations and visualization of argumentationhavebeendeveloped.ToolssuchasAraucaria(Reed

&Rowe,2001),Reason!Able(vanGelder,2002)andCompendium (http://compendium.open.ac.uk)allowuserstocreateissues,take positionsontheseissues, and makeproand contraarguments.

Theycancapturekeyissuesandideas,andcreatesharedunder- standingin a teamof knowledge workers;in somecases, they canbeusedtogatherasemanticgroupmemory.However,these argumentationsupporttoolsexhibitthesameproblemswiththe aforementionedWeb2.0collaborationtools.Theyarestandalone applications,lackingsupportforinteroperabilityandintegration withothertools(e.g.withdataminingservicesforagingtheWeb todiscover interesting patterns or trends) limiting information aggregation,computabilityandexchange.Theyalsocopepoorly withvoluminousandcomplexdataastheyprovideonlyprimi- tivereasoningservices.Thismakesthemalsopronetotheproblem ofinformationoverload.Argumentationsupportservicesrecently developedinthecontextoftheDicodeproject(Karacapilidis,2014) addressthe majorityof theseshortcomings through innovative virtualworkspacesofferingalternativevisualizationschemasthat helpstakeholderscontroltheimpactofvoluminousandcomplex data,while also accommodatingthe outcomesof external web services,thusaugmentingindividualandcollectivesense-making (Lau,Yang-Turner,&Karacapilidis,2014).

Armedwiththelatterfunctionalities,argumentativeknowledge constructionsupporttoolscontributesignificantlytothesupport ofknowledgeexploration(KXPL),knowledgeexploitation(KXPT), andknowledgeretention(KRTN)capabilities.However,theyhavea fewshortcomingsthatmakethemmoresuitableforuseprincipally in“OItoolkits”strategies.Theiremphasisonprovidingfixedand prescribedwaysofinteractionwithincollaborationspacesmake themdifficulttouseinmore“open”modelsastheyconstrainthe expressivenessofusers,whichinturnresultsinmakingthesesys- temsbeingusedonlyinnichetool-proficientcommunities.

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Informeddecisionmaking

Datawarehouses,on-lineanalyticalprocessing,anddatamining havebeen broadlyrecognizedastechnologiesplayinga promi- nent role in the development of current and future Decision Support Systems. They may aid users make better, faster and informeddecisions,andconsequentlydevelopthedesiredorgani- zationaldecisionmaking(DMKG)capability.However,thereisstill roomforfurtherdevelopingtheconceptual,methodologicaland application-orientedaspectsofcomputer-supporteddecisionmaking.Aholisticperspectiveoncomputer-supporteddecisionmaking isstillmissing,andthereisagrowingneedtodevelopapplications byfollowingamorehuman-centric(andnotproblem-centric)view (Karacapilidis,2006).Decisionmakinghastobeconsideredasa socialprocesswherehumaninteractionisofprimaryimportance (Smoliar,2003).Thestructuringandmanagementofthisinterac- tion,especiallyinnetworkorganizations,requirestheappropriate technologicalsupportand hastobeexplicitlyembeddedinthe solutionoffered.Atthesametime,muchoftheavailabledatais oftenunderutilizedinthedecisionmakingprocessduetoalack ofproﬁciencyindataanalysis;thereismuchprogresstobemade whenitcomestoanalysingdatatodriveinnovation.

Theaboverequirementsdelineateasetofchallengesforfurther decisionsupporttechnologydevelopment.Suchchallengescanbe addressedbyadoptingaknowledge-baseddecision-makingview, whilealsoenablingthemeaningfulaccommodationoftheresults of the social knowledge and related mining processes (Tsiliki, Karacapilidis,Christodoulou,&Tzagarakis,2014).Accordingtothis view,whichbuildsonbottom-upinnovationmodels,decisionsare consideredaspiecesofdescriptiveorproceduralknowledgerefer- ringtoanactioncommitment.Insuchaway,thedecisionmaking processisabletoproducenewknowledge,suchasevidencejus- tifyingorchallenginganalternativeorpracticestobefollowedor avoidedaftertheevaluationofadecision,thusprovidingareﬁned understandingof theproblem. Ontheotherhand,ina decision makingcontexttheknowledgebaseoffactsandroutinesalters, sinceithastoreﬂecttheever-changingexternalenvironmentand internalstructuresoftheorganization.

An effective decision making toolset for OI should be able tointegrate(aggregate) and manage(store/retrieve) in asingle repository allthe relevant data,metrics, and objectives; moreover,toproperlysharethemacrossandbeyondtheorganization andusethemasbasisofend-to-enddecisionmakingprocesses (exchange/transformationoperations);inaddition,toembedcog- nitivecapabilitiessothatuserswillbeaidedintheirdatasearch, collectionandanalysis.Itisstressedthatknowledgemanagement activitiessuchasknowledgeelicitation,representationanddistri- butioninﬂuencethecreationofthedecisionmodelstobeadopted, thusenhancingthedecisionmakingprocess,whileevaluationof contributionsinthedecisionmakingprocessmayactasareputa- tionmechanismandprovideincentivesforengagement(Anadiotis, Kafentzis,Pavlopoulos,&Westerski,2012).

Socialmediamonitoringandanalytics

Socialmediamonitoringandanalyticsisanevolvingmarketing researchﬁeldthatreferstothetrackingorcrawlingofvarioussocial mediacontentasawaytodeterminethevolumeandsentimentof onlineconversationaboutabrandortopic(Bekkers,Edwards,&

deKool,2013).Theiraddedvalueliesonthefactthatsuchpro- cessescanbeperformedatrealtimeandinahighlyscalableway (highaggregationandcomputabilityfunctionality).Representative toolsofthiscategoryincludeSocialMention,Sysomos,Hootsuite, and Trackur.Such toolsare abletoreveal theissues, ideasand argumentsthatcanbestcontributeinanopeninnovationprocess.

Inaddition,theycansupporttherequired“attentionmediation”

(Klein&Convertino,2015),byprovidingastructuredwaytorep- resentthe“bigpicture”.

Theemploymentofthesetoolssupportstheknowledgeexplo- ration(KXPL)anddecisionmaking(DMKG)capabilities.However, despitetheirenormouspotential,sofar,theyhavenotbeenwidely –andmeaningfully–adopted,basicallydueto:(i)thepoorqual- ityandreliabilityoftheexistingsolutions,and(ii)thedifﬁculty ofintegrationintotheexistingcompanystructuresandmarketing procedures.IntheOIsettings,datasourcesareassociatedwithvar- ioustypesofinformation,eachofthemcoveringdistinctaspects.

Asystematicwayisneededtogeneratedifferentpointsofviewfor suchkindofdata.Contemporaryapproachesneedtohelpusersuti- lizingcomplexmulti-sourcedatainareasonablewaybysupporting theminﬁndingrelevantinformationandbyprovidingpersonalized recommendations(Bugshan,2015).

Another category of requirementsconcerns theexploration, delivery and visualization of the pertinent information. These shouldbebasedon:(i)anintelligentsemanticannotation,struc- turingandaggregationofvoluminousandcomplexdata,(ii)the meaningfulanalysisandexploitationofdatapatternsandinterre- lations,(iii)thecapturingofstakeholders’tacitknowledge,asfaras informationanalysisandproblemsolvingareconcerned,througha socialwebapproach,and(iv)theexploitationofparticularuserand groupcharacteristicstoproperlydirectoradaptdata(Karacapilidis, Loefﬂer,Maassen,&Tzagarakis,2012;Karacapilidis,Tzagarakis,&

Christodoulou,2013).

Opinionmining

Opinionmining(orsentiment analysis)technologiesemploy naturallanguageprocessing,machinelearning,textanalysisand computationallinguisticstoextractrelevantinformationfromthe hugeamountsofhumancommunicationovertheInternetorother (ofﬂine)sources.Hence,theyexhibitahighdegreeofcomputabil- ity.In fact,thepropagationof opinionateddatahascaused the developmentofwebopinionmining(MarreseTaylor,Rodríguez Opazo, Velásquez, Ghosh, &Banerjee, 2013) as a new concept in Web Intelligence, which deals with the issue of extracting, analyzing and aggregating data aboutopinions.The analysisof users’opinions,knownassentimentanalysis,isimportantbecause throughthemitispossibletodeterminehowpeoplefeelabouta productorserviceandknowhowitwasreceivedbythemarket.

Wecandistinguishbetweentwotypesoftoolsinthiscategory:

thosethatprovideaframeworkfordataminingalgorithms,e.g.

Rapidminer,WEKA,andKNIME,andonlineplatformsthatcanvisu- alize(inrealtime)opinionmininganalyticsonpredeﬁnedWeb2.0 Sources,e.g.sentimentvizandSocialmention.

Opinionminingmethodsandtoolsmakepossiblefororgani- zationstoreachcrowd’sopinionsaboutdiversetopicsofinterest.

Asholdsforsocialmediamonitoringandanalytics,theysupport thedevelopmentoftheknowledgeexploration(KXPL)anddecisionmaking(DMKG)capabilities.Generallyspeaking,traditional opinionminingtechniquesapplytosocialmediacontentaswell.

However,therearecertainfactorsthatmakeWeb2.0datamore complicatedanddifficulttobeparsed.Aninterestingstudyabout theidentificationofsuchfactorswasmadebyMaynard,Bontcheva, andRout,2012,inwhichtheyexposedimportantfeaturesthatpose certaindifficulties totraditional approaches whendealing with social mediastreams,suchastheshortlengthofmessages, the existenceofnoisycontent,andthedisambiguationinthesubject ofreference.

Intellectualpropertymanagement

Theintellectualpropertymanagement(IPMA)capabilitycon- cernsthetrackingof trademarks,patents,copyrights,and other

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Table2

OImodelsandassociatedoperationalcapabilities.

ModelofOpenInnovation Mainoperationalcapabilitiesrequired Innovationmarkets • Collaboration(COLB)

• Knowledgeexploration(KXPL)

• Knowledgeexploitation(KXPT)

• Decisionmaking(DMKG)

• Knowledgeretention(KRTN) Innovationcommunities • Collaboration(COLB)

• Socialintegration(SINT)

• Intellectualpropertymanagement(IPMA)

• Knowledgeretention(KRTN) Innovationcontests • Collaboration(COLB)

• Decisionmaking(DMKG) Innovationtoolkits • Collaboration(COLB)

• Partnerrelationshipmanagement(PREM)

• Intellectualpropertymanagement(IPMA)

• Knowledgeretention(KRTN)

intellectualproperty, as wellas to decide what to disclose. In additionto decision-support tools,organizations utilizediverse ICT-basedtoolstomanagetherelateddatabases,automateforms and correspondence for new and ongoing intellectual property ownership, and track potentialviolations of legal rights. These tools, which are often integrated with case management tools tostreamlinethelifecycle of intellectualpropertyprocurement andlitigation,aidorganizationsinmaintainingup-to-dateclient information,licenseagreements,anddiverseintellectualproperty materialinasinglerepository.Representativetoolsofthiscategory includeInteum,AnaquaandFoundationIP.

Table 2 summarises the above discussed capabilities with respecttoopeninnovationmodels.

Integrationissues

ThevastmajorityofICTtoolspresentedabovehavebeenorig- inallydesigned toworkasstandaloneapplications.However,in complexcontextssuchasthatofOIprocesses,thesetoolsneedto beintegratedandmeaningfullyorchestrated. Inmostcases,this isahardandchallengingissue,whichdependsonmanyfactors, suchasthetypeoftheresourcestobeintegrated,performance requirements,dataheterogeneityandsemantics,userinterfaces, andmiddleware(Ziegler&Dittrich,2007).Atthesametime,OI stakeholdersare confronted with therapidly growingproblem ofinformationoverload; theyneedtoefﬁcientlyandeffectively collaborateandmakedecisionsbyappropriatelyassemblingand analysingenormousvolumesofcomplexmulti-faceteddataresid- ingindifferentsources.Admittedly,whenthingsgetcomplex,we needtoaggregatebigvolumesofdata,andthenmineitforinsights thatwouldneveremergefrommanualinspectionoranalysisofany singledatasource(Karacapilidis,2014).

Theaboverequirementscanbefullyaddressedbyaninnova- tiveweb-basedplatformthatensurestheseamlessinteroperability andintegrationofdiversecomponentsandservices.Theproposed solutionshouldbeabletoloosely combinewebservicestopro- videanall-inclusiveinfrastructure(‘single-access-point’)forthe effectiveandefﬁcientsupportofdiverseOIstakeholders.Itwillnot

onlyprovideaworkingenvironmentforhostingandindexingof services,seamlessretrievalandanalysisoflarge-scaledatasets;it willalsoleverageWebtechnologiesandsocialnetworkingsolu- tionstoprovidestakeholderswithasimpleandscalablesolution fortargetedcollaboration,resourcediscoveryandexploitation,ina waythatfacilitatesandboostsOIactivities.Muchattentionneeds tobepaidtostandardizationtomakeexistingdataandsoftware reusablewiththeminimumeffortandwithoutintroducingnew standards.Interoperabilityissuesshouldbeconsideredfromatech- nical,conceptualanduserinterfacepointofview.Whennecessary, theforeseenplatformshouldexploitrichsemantics atmachine level toenable themeaningful incorporation and orchestration ofinteroperablewebservicesincustomizedOI-relatedworkﬂow settings,aimingtoreducethedata-intensivenessandsmooththe associatedworkloadstoamanageablelevel.

Theproposedintegrationcanbebasedonestablishedtechnolo- giesandstandardsofaservice-orientedarchitecture.Application ProgrammingInterfaces(APIs)allowdifferentapplicationstocon- nectand interactwith each other, while web servicesprovide astandardized wayof integratingweb-basedapplicationsusing openstandards suchas XML, SOAP, WSDL and UDDI. Such an integration approach has been fully adopted in the context of theDicodeEUproject(http://dicode-project.eu/),whereawidget- basedsolutionwasconceivedtodeliverdiversewebservicesto end-users,adedicatedregistryofservicesservedlocationandrec- ommendationpurposes,andalternativeserviceintegrationmodes wereproposedandthoroughlytested intheproject’susecases.

Ithasbeenshownthatthis approach,namelytheDicodeWork- bench(de laCalle,Alonso-Martinez, Tzagarakis, &Karacapilidis, 2012),ensuresaﬂexible,adaptableandscalableinformationand computationinfrastructure,andexploitsthecompetencesofstake- holderstoproperlyconfrontinformationmanagementissues,such asinformationcharacterization,classiﬁcationandinterpretation, thusgivingaddedvaluetotheunderlyingcollectiveintelligence.

Moreover, it facilitates knowledge sharing and knowledge co- creation,andassuresbetter-informedcollaboration.Atthesame time,suchanapproachpaysmuchattentiontotheissuesofusabil- ity and ease-of-use, not requiring any particular programming expertisefromtheendusers.

Conclusions

In this paper, based on an organisational capabilities perspective, we discussed ICT as enhancer of strategic- and operational-level processes ofOI. Asit hasbeen madeclear in theprevioussections,ICTsupportforthetwolevelsdifferssig- niﬁcantly,asfarasthehuman–machinerelationshipisconcerned.

Strategic processesare creative,complex,and highlysubjective processesthatcannotbeautomatedandobjectiﬁed.Hence,ICTsup- portisfocusedonthemicrofoundationsofdynamiccapabilities:

“opening”mentalmodelsandonthedevelopmentofsocialcapital throughcollaborationandknowledgemanagement.ICTartefacts, suchascomputersimulationmodels,playtheimportantroleof

“transitionalobjects”.Ontheotherhand,supportforencodingthe user,aggregationandcomputabilitythroughmachine-reasoning and dataprocessing is required inOI operationalprocesses for supportingthecorrespondingcapabilities.Nevertheless,evenat this level, for exploiting knowledge from diverse sources, for switchingfastbetweenexternalpartners,andmostofall,fordevel- opingabsorptivecapacityandactivetransparency,ﬂexibilityand

“breadth”aremoreimportantthanrigidintegrationand“depth”.

Thetechnologiesandtoolsdiscussedinthispaperaddressthese requirements;throughtheirﬂexibleandmeaningful integration foraggregatingandtransferringinformationtoconstructmeaning, theycanactasenablersoftheentireOIprocess.Theextenttowhich thisistrueinsuccessfulOIimplementationsisunderinvestigation