A Study of the Factors that Influence Engagement in ...fb4reports/2012/2012... · Prof. Dr. Petra Schubert petra.schubert@uni‐koblenz.de Institute for IS Research, University of

A Study of the Factors that Influence

Engagement in University-Industry

Collaboration Projects

Petra Schubert

Nr. 12/2012

Arbeitsberichte aus dem

Fachbereich Informatik

Die Arbeitsberichte aus dem Fachbereich Informatik dienen der Darstellung

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Arbeitsberichte des Fachbereichs Informatik

ISSN (Print): 1864-0346

ISSN (Online): 1864-0850

Herausgeber / Edited by:

Der Dekan:

Prof. Dr. Grimm

Die Professoren des Fachbereichs:

Prof. Dr. Bátori, Prof. Dr. Burkhardt, Prof. Dr. Diller, Prof. Dr. Ebert, Prof. Dr. Frey,

Prof. Dr. Furbach, Prof. Dr. Grimm, Prof. Dr. Hampe, Prof. Dr. Harbusch,

jProf. Dr. Kilian, Prof. Dr. von Korflesch, Prof. Dr. Lämmel, Prof. Dr. Lautenbach,

Prof. Dr. Müller, Prof. Dr. Oppermann, Prof. Dr. Paulus, Prof. Dr. Priese,

Prof. Dr. Rosendahl, Prof. Dr. Schubert, Prof. Dr. Sofronie-Stokkermans, Prof. Dr.

Staab, Prof. Dr. Steigner, Prof. Dr. Sure, Prof. Dr. Troitzsch, Prof. Dr. Wimmer, Prof.

Dr. Zöbel

Kontaktdaten der Verfasser Petra Schubert Institut für Wirtschafts- und Verwaltungsinformatik

Fachbereich Informatik

Universität Koblenz-Landau

Universitätsstraße 1

D-56070 Koblenz

E-Mail: [email protected]

mailto:[email protected]

WorkingPaper:BusinessSoftwareResearchGroup,UniversityofKoblenz‐LandauDate:2012‐10‐01

Author:Prof.Dr.PetraSchubert petra.schubert@uni‐koblenz.de InstituteforISResearch,UniversityofKoblenz‐Landau,Koblenz,Germany

Publicationhistory:

ThisworkingpaperisafurtherdevelopmentofapaperpublishedattheBledConference2009.Theoriginalpaperreceivedthe“OutstandingPaperAward”.http://bledconference.org/index.php/eConference/2011/about/editorialPolicies

Reference:

Schubert,P.,&Bjørn‐Andersen,N. 2012 .University‐IndustryCollaborationinISRe‐search:AnInvestigationofSuccessfulCollaborationModels.ProceedingsoftheBledCon‐ference2012,109‐126.

ThisextendedversioncontainsalargersetofdiagramsthatcouldnotbepublishedintheoriginalBledpaperduetospacelimitations.Additionally,fivemoreinterviewswerein‐cludedintheanalysis.IwasalsoaskedtoaddanexplanationoftheISResearchMethodsthatwereusedintheinterviews.

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TableofContents

Theimperativetopublish.....................................................................................................................................1

Settingthescene:attitudetowardsuniversity‐industrycollaboration............................................2

So,howisresearchwithindustryseenbyISresearchers?..................................................................4

Themesintheliteratureonuniversity‐industrycollaboration...........................................................5

ScholarshipofEngagement.............................................................................................................................6

EngagedScholarship..........................................................................................................................................6

Realengagementthroughcollaboration...................................................................................................6

Driversforengagement:successfulpublications..................................................................................7

Barrierstoengagement....................................................................................................................................8

Researchmethodsincollaborativeresearch..........................................................................................9

Design Science Research DSR :developinganartefact...............................................................................................9

ActionResearch:interventioninthecompanyproject......................................................................................................9

BehaviouralResearch:studyofhumanbehaviour..............................................................................................................9

GroundedTheory:buildingtheoryfromrawdata...............................................................................................................9

Experiment/simulation:laboratoryenvironment...............................................................................................................9

CaseStudy:derivingfindingsfromreal‐worldphenomena..........................................................................................10

Conceptualdevelopment:creationofconceptsbasedonreasoning.........................................................................10

Researchapproach...............................................................................................................................................10

InterviewGuideline.........................................................................................................................................11

Taxonomyforuniversity‐industrycollaboration...............................................................................12

Findingsfromtheinterviewsanddiscussion...........................................................................................13

Somefinalthoughts..............................................................................................................................................21

Acknowledgements..............................................................................................................................................22

References................................................................................................................................................................23

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ABSTRACTJoint collaborationprojectsbetweenUniversity and industrypartnershavealwaysbeenofparticularimportancetotheIScommunity.Themotivationtostudycurrentattitudes towardscooperationwas inspiredbyrecentdiscus‐sions on “engaged scholarship” and “successful publication strategies” inwhichwecanobserveadifference inattitudes towards industrycollabora‐tionindifferentregionsoftheworld.Theauthorofthispaperwasparticu‐larlyinterestedinexploringdriversandbarriersforengagementwithindus‐trypartnersfromthepointofviewofISacademics.Thispaperpresentsthefindingsfromaqualitativein‐depthstudy,inwhichfourteenexperiencedre‐searchersfromfourdifferentcontinentswereinterviewedinordertounder‐standthephenomenonofuniversity‐industrycollaborationinthecontextofdifferentresearchtraditions,differentuniversityenvironmentsanddifferentgeographical regions.The findings fromthe interviewsshowthatresearch‐ershaveverydifferentpreferencesregardingtheidealsetupofsuchcollabo‐rativeresearchprojects.FindingsalsoshowthatCaseStudyandDesignRe‐searcharethemostcommonresearchmethodsinsuchprojects.

Keywords: University‐industry collaboration, collaborative projects, practi‐tioners,researchprogramme,researchfunding

Papertype:Researchpaper

TheimperativetopublishThe ISresearchcommunityhasexperienceda trend inrecentyears thatseems todefine“research” as equivalent to “publication output” and that accepts the number of journalpublicationsinthebest mostcited internationaljournalsastheonly“real”measurement

FactorsthatInfluenceEngagementinUniversity‐IndustryCollaboration Schubert

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ofresearchexcellence Straub2009 .Publicationoutput isoftenthedominantmetricforresearchassessment.

There is growing concern that too stronga focuson journalpublicationsmaydivertourattention from providing value to our key stakeholders: industry, students and societyDavisetal.2005 .Asaresponseanumberofresearchershaveproposeda“revival”ofcol‐laborative research,which isnow increasingly referred toas “engagedscholarship” VanderVen2007 .

Thepurposeofthispaperistocontributetotheunderstandingofuniversity‐industrycol‐laborationwithin thedisciplineof InformationSystems IS .Theauthor investigates fac‐torsthatinfluencethedecisionofanISresearcheraboutwhetherornottoengageinjointprojectswithindustry.Theresearchdatawasdrawnfromcurrent“bestpractice”collectedfrom real‐life experiences of IS researchers. Specific focus is given to examining typicalformsofcollaborativeprojects,theappliedresearchmethodsandoutputsaswellasbarri‐ersanddrivers.ThedatawasgatheredinpersonalinterviewswithISresearcherswhohadpreviously engaged in industry collaboration and agreed to report on their experienceswithsuchprojects.

Apreliminaryversionof thisstudyreport shorterandbasedonasmallernumberof in‐terviews waspresentedatthe25thannualBledConference SchubertandBjørn‐Andersen2012 .Encouragedby the livelydiscussionand theencouraging feedback theauthorde‐cidedtoextendthedata todrawamorerepresentativepictureof the internationalcom‐munityofISresearchersandtheirattitudesandopinionstowardindustryresearch.Inthemonths that followed the conference an additional five one‐hour interviews were con‐ductedwithresearchersrepresentingfournewcountriesandthreedifferentcontinents.

Settingthescene:attitudetowardsuniversity‐industrycollaborationInpreparationforthestudyoncurrentpracticetheauthorsearchedforexistingstudiesinthetopicarea.Severalstudieswereidentifiedinwhicheithertheunitofanalysis inthisstudythe“ISresearcher” orthestudyobject inthisstudy“factorsthateitherfacilitateorimpedecollaboration” wasdifferent.Thefollowingsectionsreviewsomeofthesestudies.

Bruneeletal. 2010 performedastudyon thebarriers touniversity‐industrycollabora‐tionfromthepointofviewofcompanies:Theyfoundthat“ ... relativelyfewstudieshave


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investigatedthenatureofthebarriersandthefactorsthatmightmitigatethem” Bruneeletal.2010,p.858 .VandeVenandJohnson 2006,p.802 pointtorisingconcernsintheISdisciplinestating“thatacademicresearchhasbecomelessusefulforsolvingpracticalprob‐lemsand that thegulfbetweentheoryandpractice intheprofessions iswidening”.Theyraisespecificconcernse.g. that “findings fromacademicaswellasconsultingstudiesarenotusefultopractitionersanddonotgetimplemented”andtheyclaimthatacademicsarenotawareof the relevant i.e.practice‐oriented researchquestions.Theyconclude that,“asaresult,organizationsarenotlearningfastenoughtokeepupwiththechangingtimes.”Thekeyissueistoaddresswhattheycall,the“transferproblem”.

It canbeobserved that the IS research community appearsdividedover thequestionofwhethercollaborationwithindustryissomethingthatISresearchersshouldembraceasavaluablewayofknowledgeco‐creation,orifithastoomanydistractingfacetsthatitshouldbeavoided. Itcanbearguedwehavetoprovidevaluetoourkeystakeholders industry,studentsandsocietyatlarge iftheISfieldistosurviveinthelongrun.Inotherwords,weneedtobecomeengagedscholars.Itcanalsobearguedthatthereareformsofuniversity‐industryresearchcollaborationthatarehighlyrewardingfortheresearchersinvolvedandthatsuchresearchcanleadto“valueco‐creation” Sarkeretal.2012 .

Theauthorbelievesthattheprevailingrelationshipbetweenacademiaandindustryisanimportantaspect in thediscussionaround thenatureand fundamentalunderstandingoftheISdiscipline.Providedthatthescientificcommunityunderstandstheconceptof“rele‐vance”toa largeextentas“relevanttopractitioners” itbecomesclearthataresearcher’sattitude towardsanengagementwith industryhas tobeadefining characteristicofhis/herresearchstance.Thisquestionisisolatedfromthequestionofhowtocommunicatetheresearchfindingstopractitioners.Academicoutletsarenotsuitedforthiscommunicationbecause they are directed towards academic researchers and largely not relevant to theconcerns of practitioners. This is emphasised by Straub andAng 2008, p. v who state:“Anyacademic journalwrittenbyresearchers forresearchersas theprimaryaudience issimplynot targeted forpractitioners.” In the studyquestions regardingoutputswere in‐cludedthataresuitabletoacademic e.g.papers,articles aswellaspractitioners e.g.pro‐jectreports,slides .


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So,howisresearchwithindustryseenbyISresearchers?Themotivationforthe long‐termstudyonISresearchers’engagementwith industrywasfurtherspurredbyanumberofdiscussionstreamsinrecentIS journalsandatISconfer‐ences.Amongthesearethefollowingacademicdiscourses:

The provocative opinion piece “Why the old world cannot publish?” Lyytinen et al.2007 ,

thedebate about thepublication chancesof design science articles in journal publica‐tions Österleetal.2011;Baskervilleetal.2011 ,

thevalue fromresearch fundingthatstakeholdersandsocietyasawholearederivingDaviset.al.2005;GibbonsandJohnston1974;Halletal.2003 ,

the streamabout the conceptof “EngagedScholarship”which ismeant toaddress theallegedgapbetweentheoryandpractice “knowledgeproductionproblem”,VandeVenandJohnson2006,p.802 ,

the Scholarship of Engagement, amovement reacting to the disconnect between aca‐demicsandthepublic Boyer1996;Pettigrew2001;Barker2004 ,

theprosandconsofcollaborativeresearchendeavourssuchasinteractivesocialscienceOrme 2000; Simmons and Walker 2000; Caswill and Shove 2000; Van Buuren andEdelenbos2004;HardyandWilliams2011 orCo‐operativeInquiry HeronandReason2001 .

Itcanbearguedthat inprinciple,university‐industrycollaborationcanaddressallof theabove thematic challenges, but it differs substantially depending on academic traditionsandsocio‐economicsettingsduetodifferentsetsof internalandexternalchallenges.Theauthorbelievesthatwecanlearnfromexamplesof“excellent”collaborationprojectswithindustryandthatthesemayhelpacademicstowriterelevant andatthesametimerigor‐ous journalpublicationsandcontribute tohighquality teaching. It canbeassumed thatresearchculturesthatfavouralternativeresearchapproaches Frank2006 andmorespe‐cificallyDesignScience Hevneretal.2004 aremorelikelytoactivelyseekoutopportuni‐tiesforuniversity‐industrycollaboration.


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Thispaperaddressesthefollowingresearchquestions:

Whatareforms or“models” ofsuccessfuluniversity‐industrycollaborationwithinIS?

Additionalquestionsthatareaddressedinthispaper:

What is a typical setup of collaboration projects between IS researchers and industryfundingsourcesandnumberofpartners ?

Whatarebarriersanddriversofsuchprojects?

Whatresearchmethodsareusedintheseprojectsandwhatisthetypical formofout‐put?

Theremainingpaperisstructuredasfollows:Inthenextsection,theliteraturewhichledtotheresearchquestionandtheinterviewguidelineisreviewed.Driversandbarrierstoen‐gagementarediscussedanddifferentformsandmethodsofcollaborationareintroduced.Theresearchstepsandthedevelopmentofthesurveyinstrumentarethenexplained.Themainsectionpresentsthefindingsfromthepreliminarystudy.Theauthorconcludeswithsomethoughtsonthecurrentfindingsandsuggestionsforfurtherstudies.

Themesintheliteratureonuniversity‐industrycollaborationBeforeengaginginastudyofuniversity‐industrycollaborationitisnecessarytodefinethetermmore clearly. In the author’s understanding “university‐industry collaboration” de‐scribesaresearchactivityperformedbyagroupofpeoplecontainingacademicsandprac‐titioners. The research is carriedout together collaboratively or, asHeron andReason2001 aptlyputit,asresearch“with”ratherthan“on”people.Indoingso,academicsandpractitionersareco‐constructingknowledge HardyandWilliams2011 .Thepractitionersin a companyor government agency are engaged in the researchprocess– they arenotmerestudyobjects.Accordingly,astudyoftheimpactofaparticulartechnologyinanor‐ganisationcommontobehaviouralstudieswouldnotqualifyasresearchcollaboration inthedefinitionofthispaper.Thefocusisonresearchprojectsthatarecarriedoutasajointworkbetween researchers inuniversitiesandpractitioners in companiesorgovernmentagencies.

Theengagement canoccuratall stages, fromthedefinitionof the researchquestionandthedevelopmentoftheresearchdesign,totheactualresearchworkandtheinterpretation


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ofthefindings.Pettigrewpointsoutthatit isessentialthatthepractitionersareinvolvedearly in the researchprocess in saying “Theaction steps toresolve theolddichotomyoftheoryandpracticewereoftenportrayedwiththeminimalistrequestformanagementre‐searchers to engage with practitioners through more accessible dissemination. But dis‐seminationistoolateifthewrongquestionshavebeenasked.” Pettigrew2001,p.67 .

The following sectionspresent anddiscuss someof the themes in the literature that arerelatedtouniversity‐industrycollaboration.

ScholarshipofEngagementTheideaofcollaborationbetweenuniversityandindustryisnotanewone.Boyer 1996 coined the term “Scholarship of Engagement” also seeBarker 2004 .While the currenttraditionalmeasuresofresearcharethenumberofacademic journalpublications,andtosomeextentthenumberofcitations,thereisagrowingdemandinindustryandsocietyforresearchmetricsofbenefitstokeystakeholders,students,industryandsocietyatlarge.Inlinewiththis,inthenextResearchAssessmentExercise RAE intheUKin2014,research‐erswillalsobeevaluatedonwhethertheirresearchhashadanimpactonsocietyandin‐dustry Ref2012 .

EngagedScholarshipVandeVen tookup theBoyer ideaandpublishedabookentitled “EngagedScholarship”VandeVen2007 .Inhisbookhedescribesaresearchmethodologyforparticipatoryre‐searchwithstakeholders.Thecontentisconcernedwithbridgingtheknowledgegapandengagingpractitioners inpartsof the researchprocess.However,hisworkdoesnot talkaboutacademic‐industrycollaborationassuch,anditdoesnotprovidepracticalguidanceonthenecessaryorganisationalframeworkforsuchprojects.

RealengagementthroughcollaborationHowever,whilstVandeVen 2007 acknowledgestheengagementofpractitionerstoen‐sureacertaindegreeofrelevanceandpracticabilityintheresearchhedoesnotexplicitlyargueforcollaborationwithanindustrypartnerovertheperiodofaresearchprojectwithadefinedoutcome.Thereare,however,successfulformsofcollaborationwhichhavebeendescribedintheliterature,e.g.CollaborativeBasicResearch SchubertandFisher2009 orConsortiumResearch ÖsterleandOtto2010 .Suchformsofdirectcollaborationcanvarydepending on scope number of parties involved, project amount , length time inmonths/years ,initiator researchinitiatedbyuniversityorindustry ,researchobject ar‐


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tefact, process, data/information, behaviour, attitudes and research outcome software,technologycomponent,method,report .

Theseinfluential issueswereaddedtothedesignofthe interviewguidelineusedforthisstudy.Itcanbearguedthatcollaborationcanaddressmanyofthebefore‐mentionedprob‐lemsbyengagingthepractitionerintheresearchprocessasalsoarguedbyproponentsoffieldworksuchasSchein 1987 andWhyte 1984 .

Driversforengagement:successfulpublicationsIthasbeenarguedthatengagementwithindustrycanleadtosuccessfulacademicpublica‐tions ifwellpresentedandcarriedout ina rigorousway Baskervilleetal.2011;StraubandAng2008 .Researchwith industry,whenusingasuitableresearchmethod,canbeaveryvaluablebasisforevidence‐basedresearchfollowingwellacceptedparadigmsforhowtodealwithdata,measurements,observations,testing,andvalidation.Thisperceptionisinaccordancewithstatementsfromtheprovocativeopinionpiece“Whytheoldworldcannotpublish?” Lyytinenet al.2007 inwhich theauthorsacknowledgea strong industryen‐gagement of European Ph.D. students but criticise their lack of rigour in their academicwriting.They say: “Many times,Ph.D. thesesareproduced to addresspracticalproblemswithin industry; forexample, innovativeworkflowdesignsormodelingmethods.” Lyyti‐nenetal.2007,p.323 Theyfurtherarguethattheseprojectsoftenendwhentheindustrypartnerissatisfiedwiththeresearchoutcome,whichisoftenaproduct,somesoftwareoramethodwithoutscientificallyreportingtheresultsinjournalarticles.

Theanalysisoftheinterviewsforthispapershowedthatcollaborativeresearchcanindeedleadtohigh‐qualityarticles if theacademicrequirementsarepartof theresearchdesign.Rigourandrelevancecanbeimprovedbyraisingsubstantiveevidencedataandmonitoringtheresearchprocessonameta‐level,whichmightseemsuperfluousfortheindustrypart‐nerbut is essential forhigh‐quality researchpublications. It is aprevailingcriticism thatdesignresearchprojectsoftenfallshortofthe lastphase, thevalidationoftheartefact inactualpractice Hevnerelal.2004 anditcanbearguedthatthisisexactlywhereuniver‐sity‐industry cooperation can help filling the gap. One interview partner stresses thechancetolookbehindthescenesandseewhatisreallygoingoninbusinessesbysaying:“Researchwithindustrypartnersgivesusaccesstopracticalproblemsthatwedonotseefrom‘outsidethecompany’.” respondent#7


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BarrierstoengagementSchubert and Fisher 2009 identify a number of factors that impede collaboration be‐tweenpractitionersandacademicsfrombothoftheirrespectivepointsofview.

Amongthebarriersforindustrytheymention 1 unclearrelevanceofresearchfindingstoindustry Kabins2011 , 2 lackingknowledgeand interest indesigning theresearch in‐struments Amabileetal.2001 , 3 lackofaccesstoresearchresults academicjournalsnot attractive for practitioners , 4 different timescales, 5 different expectations fromtheresearchoutcomesaswellas 6 disagreementonintellectualpropertyrights.

For the academics theymention a belief that 1 industry is not interested orwilling toworkwithuniversities Hall etal. 2003 , the 2 rather long timeframe foracademic re‐searchproducts Pettigrew2001 and the 3 tediousmaintenanceof relationshipswithindustrypartnersover a longperiodof time Amabile et al. 2001 .Thebarriers foraca‐demicsweretestedintheinterviewsandfoundsomeofthemconfirmed.Aspectthree,thetediousbuildingupoftrustwasconfirmedbymultiplerespondents,oneoftheme.g.say‐ing: “Research collaboration takes a lot of time and themutual understanding and trustincreasesover time. It isan investment thatyouhave tomake.” respondent#7 .Anex‐periencedEUprojectparticipantremarked:“Therearepathdependenciesduetodifferentexpectations in different countries. You have to identify overlapping interestswith yourresearchpartnersandbuildupsocialcapitalovertime.” respondent#9 .ThisassessmentissharedbyVandeVenandJohnson” 2006,p.812 whosay:“Timeiscriticalforbuildingrelationshipsoftrust,candour,andlearningamongresearchersandpractitioners”.

ArelatedbarrierthatemergedfromtheinterviewswasthetimeandenergythathastobeinvestedbytheseniorresearcherifPh.D.studentsareinvolvedintheproject.Exemplaryquotesare:”Industryprojectsarelabour‐intensefortheseniorresearcher theprofessor becausehehasto leadandguidetheproject.” respondent#9 .Theseremarksare inac‐cordancewith theobservationmadebyLyytinenetal.whoargue: “ ... intenseresearch‐industryengagementssaptimeandenergyawayfrompublicationanddecreasesEurope‐ans’motivation topublish inelite journals” 2007,p.324 .Their conclusion,however, isnot shared by the respondents. Most of them agree with the following assessment: “Igainedaccesstovaluableempiricaldataandwasabletowriteahighqualitypaperwithit.”respondent#9 .Thisisalsoconfirmedbythehighnumberofpublicationsintopjournalsaswillbeshowninthefindingssectionbelow .


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ResearchmethodsincollaborativeresearchPartoftheinvestigationwasthestudyofresearchmethodsthataretypicallyusedforcol‐laborationwith industry. The author assumed that approaches that call for an industrypartner, suchasDesignResearchorActionResearchwouldscorehighest in the list.Thefollowingchoiceofresearchmethodswasderivedfromtheliteratureandpresentedtotheinterviewpartners.Although interviewpartnerswereactivelyencouraged tonameaddi‐tionalmethods,nofurthermethodswereaddedbytheinterviewees.

Design Science Research DSR :developinganartefactDesign Science Research DSR representsthedevelopmentofanITartefact e.g.asoft‐ware programme ormethod as themain objective of the joint project. DSR has been atopicofconsiderableinterestintheISliteratureinrecentyears Hevneretal.2004,Österleetal.2011,Gregor2006,LeeandHubona2009 .

ActionResearch:interventioninthecompanyprojectActionResearchisusedtodescribeasituation,inwhicharesearcherisactivelyengagedina company projectand,insteadofjustbeingamereobserver,intervenesinitovertimeBaskervilleandWood‐Harper1996,Gregor2006,LeeandHubona2009 .

BehaviouralResearch:studyofhumanbehaviourThe term Behavioural Research is used to indicate the study of human behaviour withquantitativemethods. Research projects in this categorymake use of statistical analysisoften in the form of hypotheses models showing causal relations e.g. Lee and Hubona2009,Österleetal.2011 .

GroundedTheory:buildingtheoryfromrawdataGrounded Theory is an inductive method for theory‐building. This kind of research isaimedatdevelopingtheoryfromdataraisedduringtheproject“fromscratch”i.e.withouttheexistenceofapriormodelortheory GlaserandStrauss1999,Urquhartetal.2009 .

Experiment/simulation:laboratoryenvironmentThetermexperiment/simulationreferstotheuseofspecialsimulationsoftwareoralabo‐ratorysetting to testorpredictcertainoutcomes Hartmann1996 .Simulation is typicalforproblemsituationsinwhichthealgorithmsareverycomplex e.g.dynamicsystembe‐haviour .


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CaseStudy:derivingfindingsfromreal‐worldphenomenaCaseStudyisusedwhenanobjectiseitherstudiedin‐depth singlecase,e.g.acompanyororganisationalunit orwhenmultiplecases multiple‐casestudy arecomparedtoderivegenerisable conclusions Eisenhardt 1989, Yin 2009 . Case studies follow a holistic ap‐proach,targetmultipleperspectivesanddescribereal‐worldphenomena.Theyareusuallyseenasdescriptiveandexploratoryandideallyincludeanexplanatoryanalysis.

Conceptualdevelopment:creationofconceptsbasedonreasoningThedevelopmentofideasandconceptscanbebuiltona“mere”formalorconceptualde‐ductiveanalysis hermeneutics .Thisformofresearchismostlyfact‐basedandmakesuseofreasoningwithastrongfocusontheexplanationofsemanticsandtheinterpretationofcorrelationswhichresultsintothedevelopmentofideasandconcepts.

Theauthorexpectedthatsomeresearchersworkwithmere formalorconceptualdeduc‐tive analysis hermeneutics but none of the participants selected this as an applied re‐searchmethod.

ResearchapproachThis section describes the steps thatwere followed in order to develop the research in‐strument.Inthefirststepaninductive,qualitativeresearchapproachwasdeployedinor‐dertounderstandthefactorssurroundingsuccessfulcollaborationwithindustryfromthepoint of view of IS researchers. A semi‐structured interview guideline a questionnairewithclosedandopenquestions basedonthethemesidentifiedabovewasdeveloped.

Interviewswereusedinordertogivetheinterviewpartnerstheopportunitytoraiseim‐portant aspects and identify issues and factors during the conversation. The interviewswerealsousedtoidentifycategoriesandterminology.Uncertaintyaboutterminologyandsemanticscoulddirectlybesolvedduringtheinterview.

In total, fourteen personal interviewswere conducted in the years 2010 to 2012 of be‐tween30and60minutesinlengthwithresearcherswhohadcarriedoutcollaborativere‐search projects. The interviewswere recorded and partly transcribed. In the interviewsrespondentswereaskedtoindicatetheirlevelofagreementwiththeproposedstatementscontained in the interviewguideline.These itemsweredeveloped from the literatureondriversandbarrierstouniversity‐industrycollaborationdiscussedabove.


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InterviewGuidelineThecontentofthe interviewguideline is listedbelow cf. Table1 .Somequestionsaresimple selections from a list of items. Questions on opinions or attitude are phrased instatementsandresponsesaremeasuredonafivepointLikertscalefrom“Ifullyagree”to“Ifullydisagree” or“noresponse” .Thecompleteinterviewguideline isavailablefromtheauthoronrequest.

1.DemographicinformationPosition,role,sizeofgroup,academicage,country

2.TypesofindustrycollaborationEngagementinthepast

3.OnesuccessfulprojectDemographicsofthesuccessfulprojectInitiatingpartyMotivationtostartprojectResearchmethodsusedPublicationoutputOutputforpractitionersSuccessfactors

4.ProjectexperienceingeneralOverheadSatisfactionofindustrypartnersDriversforengagementBarrierstoengagementProblems/challengesencounteredinthepastExperiencewithofPh.D.studentsPerceived trend towards more or less industryresearch

Table1:Contentsoftheinterviewguideline

Demographic informationwas collected inorder to identify correlationsbetweenprojectcharacteristics and the outcome/attitude of the researcher. Previous experiences of theintervieweewereinvestigatedtounderstandtherangeofprojectsheorshehadbeenen‐gagedin.

Themainsectionofthequestionnaireexplorestherespondent’sexperienceswitha“suc‐cessful project”. The author believes that the motivation/output for the practitionerslargelydefinestheresearchdesignandthusthechoiceoftheresearchmethod.ThispartoftheresearchdrawsonpreviousworkbyPerkmanandWalsh 2009 ,whoperformedaninductivestudyandidentifiedfourtypicalgoalsofcollaborationfrominterviewswithaca‐demics.Thefindingsshowedthatcompanieshadapproachedtheresearcherswithissuesregarding 1 problem solving, 2 technology development, 3 ideas testing and4 knowledge generation. Accordingly, this classification of motivations was used. Thereasonswhytheselectedprojectwasconsideredsuccessful “success factors” werealsoexplored.The“generalexperience”sectionexploresthedriversandbarriersforcollabora‐tionasdiscussedintheliteraturereviewaboveandtheroleofPh.D.students inresponsetothecriticismvoicedinLyytinenetal.2007 .


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Taxonomyforuniversity‐industrycollaborationTheinitialsearchintheliteratureforausefulclassificationschemeforcollaborationpro‐jects remained largely unsuccessful. As a consequence, the author used a self‐developedtaxonomyinordertobeabletoidentifyarchetypes SchubertandBjørn‐Andersen2012 .Thefollowingmatrixwasdevelopedtoclassifyresearchprojects cf.Figure1 .Duringtheworkondevelopingthetaxonomy,itbecameapparentthatintheacademicliteraturesomeauthorsfocusonthefundingaspect Halletal.2001,2003;Cohenetal.2002;D’Este2007 ,while others focussed on the parties involved in the project Schubert and Fisher 2009;ÖsterleandOtto2010 .Asaconsequence,thestartingpointwasputonthedevelopmentofaclassificationschemeforpartiesinvolvedandexternalfundingsources.Itwasdecidedtoonlyincludeexternalfunding industrypartnerorgovernmentagency althoughtheUni‐versity, inmostcases,contributestotheoverallcosteitheras“inkindcontribution” e.g.theiralreadyemployedstaff orintheformofadditionalfinancialresources.Intheendthetaxonomycontainedthreedimensions:

1. Numberofuniversitiesinvolved

2. Numberofcompaniesinvolved

3. Industryfunded,governmentfundedorco‐funded

Inordertoillustratethematrix,examplesoftypicalprojectsareprovidedthatwouldfallwithineachcategory.

Figure1:TaxonomyforUniversity‐IndustryResearch partiesandexternalfunding

Many companies (m)

One University (1)

Industry-fundedConsortium Research (1:m)

EU Integrated Projects (n:m)

Nationally-funded Research Projects (n:m)

One company (1)

Many Universities (n)

Nationally-funded Collaborative Research (n:1)

Co-funded

Contract Research (1:1)

Collaborative Contract Research (n:1)

Nationally-funded Research Projects (1:m)

Nationally-funded Research Projects (1:1)

Government-funded

Collaborative Contract Research (n:m) Industry-funded

Co-funded

Government-funded


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Informationabouthowoftenthedifferenttypeswereencounteredandwhichfieldsofthematrixwereseenasthe“mostsuccessful”projectsetupswillbepresentedbelow.

FindingsfromtheinterviewsanddiscussionThefollowingsectionpresentsthefindingsfromthestudy.Thefiguresinroundbracketsn indicatethenumberofresponsesinthiscategory.

Allrespondentsareeithertheheadoftheirresearchunit 13 ortheheadoftheirownre‐searchgroup 1 .Themajorityoftheirresearchgroupsinclude6to15researchers 10 .Theyareexperiencedresearchers; theaveragenumberofyearssincetheirPh.D.gradua‐tion is21years.Thesample includesresearchers fromEurope,Australia,AsiaandNorthAmerica,i.e.Finland 2 ,Germany 3 ,Switzerland 1 ,TheNetherlands 1 ,Australia 1 ,SouthKorea 2 ,Singapore 1 andTaiwan 1 ,Canada 1 andUSA 1 .Thetypicalprojectbudgethasanaverageof437’195rangingfrom7’718to1’500’000Euros.Mostacademicinstitutionsdeductoverheadcostfromtheprojectfunding,i.e.theychargetheprojectforcostssuchasstaffworkplace,rentofrooms,telephone,stamps, library,maintenance,etc.Theoverheadraterangesbetweenzeroand43%withanaverageof23% 9 .

The classification for collaboration projects revealed typical combinations cf. Figure 2 .The “1:1, industry funded” emerged as themost frequentlyused type 7 .Generally, therespondentshadbeenengagedinallfundingformsof“1:1projects” totalof14 .Thecol‐laboration type “n:m, government‐funded”was placed second 6 . The n:1 combinationswithonecompanyandmultipleUniversitieswerethemostuncommon 2 .

Thesuccessfulprojectshadanaverageof1.7universities minimum:1,maximum:4 and3industrypartners minimum:1,maximum:10 .Thissuggests thatmostprojects thatarerankedas“successful”arerunbyonlyoneuniversity 9 butmaywellincludemorethanoneindustrypartner.


14

Figure2:Experiences:typesofindustryengagement

Theinterviewsshowedthattherespondentswerenotparticularlydrivenbythefinancialprospectofthejointproject.Onlytwointerviewpartnersnamedfundingofstafforequip‐mentasanimportantmotivationtoengagewiththeindustrypartner.In60%ofthecasestheresearchchallenge i.e.theresearchtopic wasthemaindriverfortheengagement.

The funding sources varied according to the different forms of collaboration Figure 3 .41%of the funding came fromgovernment sources, 43% from industry andonly 17%werepaidbytheUniversityitself.

Figure3:Experiences:typesofindustryengagement

0

0

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0 1 2 3 4 5 6 7 8

n:1, government‐funded

n:m, co‐funded

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n:m, industry‐funded

1:m, industry‐funded

1:m, co‐funded

1:1, government‐funded

1:m, government‐funded

1:1, co‐funded

n:m, government‐funded

1:1, industry‐funded

What type of industry collaboration have you been

personally engaged in over the last 10 years? (N=14)

4143

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0

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10

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25

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40

45

Government funding Industry funding University funding

Which funding did you have for the project – please

indicate approximate in % (N=14)


15

ThedominantresearchapproachwasCaseStudy 8 followedbyDesignResearch 7 ,Be‐havioural Research 6 and Action Research 3 . Experiments/simulations 2 andGroundedTheory 1 wereonlynamedintworespectivelyonecase.Meredeductiveanaly‐siswasnotusedatall.

Thefindingsconfirmthatprojectswithindustrypartnersarebestsuitedtolookatonepar‐ticularcaseindetailanddevelopartefactsandevaluatetheminpractice cf.Figure4 .ThesingleCaseStudyallowsacademicstotransferthequalitativeresultsoftheprojectsintoanaccessible form. Industry projects are also a source for empirical data, as the company/governmentagencycanalsobeseenasastudyobjectforBehaviouralResearch Positivist Research. As expected we also see the application of Action Research in which the re‐searcherispartoftheresearchprocessandactivelyinfluencestheoutcome.

Figure4:Researchmethodsused

Peer reviewed conferencepublications 44% are themost frequentacademicoutputofprojectswithindustry.ThehighnumberofarticlesintheAISseniorscholarbasketofeight18% followedbyotherpeer‐reviewedjournalarticles 17% demonstratesclearlythatfindingsfromindustryprojectscanbeusedtoproducehighqualitypublications cf.Figure5 .WherePh.D. studentswere involved in theprojects the senior researchermade surethattherewasahighsynergybetweentheprojectoutcomesandthefindingsofthePh.D.

0

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2

3

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8

0 1 2 3 4 5 6 7 8 9

Deductive analysis

Grounded Theory

Experiment/simulation

Action Research

Behavioural research

Design Research

Case Study

Research methods/approaches used in this project (N=14)


16

theses 15% .“Otherpublications” 6% aremostlybookswhichwereauthoredoreditedbytheresearchconsortium.

It is remarkable that basket‐of‐eight journal articles are in second place even ahead of“other” peer‐reviewed journals. This could confirm the increasing importance of journalrankingsandthechangedawarenessforaneedtopublishinhighlyrankedoutlets.

Figure5:Typeofpublicationin%oftotalamountofresultingpublications

Thefindingsofthestudyshowthatthereisawidespectrumofoutputsthatarerelevantfor the industry partner cf. Figure6 .Themost important outputs for practitioners arereports i.e.theactualfindings,artefactdocumentation,figures,interpretationandadviceforaction andcomplementarysessionsinwhichthefindingsarepresentedtoseniorman‐agement. Direct support in the formof consulting 10 and presentations 10 was alsohighlywelcomeinthemajorityoftheprojects.

6

15

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18

44

0 10 20 30 40 50

Other publications

Ph.D. theses

Other peer‐reviewed journal

Top 8 journal

Peer‐reviewed conference

Type of resulting publications in % (N=14)


17

Figure6:Outputforpractitioners totalnumbers

Theperceived value to the industry partners from collaborative projects varies substan‐tially cf.Figure7 .Almosthalfoftherespondentsfeltthat thepartnersreceivedavaluethatwasmuchgreater thanwhat theyhad invested 6 .Another four classified theper‐ceivedvaluestillhigherthantheinput 4 .Intwocases,however,therespondentsfeltthattheresultingvaluewasmuchlessthantheindustrypartnershadexpected.Bothresearch‐ers said in the interview that such researchprojects carry the risk of failure and that inmany cases the industry partnermight pay for the development of an artefact thatwillneverbesuccessfulinthemarket respondent#5and#6 .

Figure7:Perceivedvalueforindustrypartners

However,aseparatequestiononthesatisfactionoftheindustrypartnersdepictsanevenmorepositivepicture.Withonlyoneexception 1 therespondentsagreed that their in‐

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Training material

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Sessions with senior manager(s)

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Output for practitioners (N=14)

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much less

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equal

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Value compared to input (N=14)


18

dustrypartnersareverysatisfied 7 orsatisfied 6 andare likely toengage inanotherindustryprojectwiththisuniversitygroupagain 13 .

Figure8showsthemostimportantdriversforacademicstoengageinindustrycollabora‐tion.Themostimportantoneisto“getaccesstoempiricaldata”followedby“getaccesstorelevantproblems/researchquestions”.Theresponsestothisquestionconfirmthelackoffinancial orientation regarding funding for “academic staff for your group”. Not surpris‐ingly,academicsseemtoberatherdrivenbytheirindividualcareerthanbythemanagerialurgetoenlargetheexistingresearchgroup.

Otherdriversthatcameupintheinterviewsbutwerenotincludedintheoriginallistare“theprestigethatsuchprojectsgivetotheUniversity”,“competitiveadvantageoverotherresearchers”, that “findings are an important input for teaching” and that “such projectsprovideevaluationopportunities totryartefactsinpractice ”.

Figure8:Mostimportantdriversforacademics sortedbyimportance

Figure9shows themost importantbarriers foracademics.The first twobarriersarere‐latedtoexternalfactorsandarehardtoinfluencebytheresearcher.Theseare“Scepticisminindustrytowardsacademics”whichscoresasthenumberonebarrierfollowedby“Ac‐quisitioncostofgettingprojectsistoohighortakestoolongtimeandeffort”.Therespon‐dents also see difficulties in obtaining funding for their work from external or publicsources.

Possibleunfavourableconditionsforacquiringcollaborationprojectsarepositionedinthemid‐field.Theyare: “Fewopportunities in theenvironmentofwheremyuniversity is lo‐cated”,“Lackofrecognitionfromcolleagues/deans”and“Unfavourable ornegative repu‐

0 2 4 6 8 10 12 14 16

Get more academic faculty / staff for your group

Contribute to effectiveness and growth & development in

industry / society

Get research funds for your own personal use

Get access to relevant problems / research questions

Get access to empirical data

Most important drivers for academics involving themselves in industry collaborative projects (N=14)

important rather important neutral rather unimportant unimportant


19

tation of industry research for personal promotion”. Especially in the German speakingcountries, apositivegeneral attitude towards cooperationcanbe identified.One respon‐dentdescribesthisas:“Ithinkyouonlygetanunfavourablereputationwhenyouengageexclusivelyinresearchwithindustrypartners.Theportfoliohastobemixed.Universitiesarenotmeanttobeconsultingcompaniesbutjointprojectswithindustrypartnerscanleadtohighqualityfindingsandthisishighlyrespectedinourplace.” respondent#8

Itisinterestingtonotethattherespondentsdidnotfeelthattheylackexpertise.Thethreequestions that contain a self‐assessment of the researcher’s skills, i.e. “Lack of propermethods/ideasforhowtodoit”,“Lackofnecessarypracticalknowledge”and“Inabilitytospeak the practitioners’ language”were rated as unimportant. The one respondentwhorated them“important” laterexplained thathewasreferring toother ISresearchersandnot tohimself.All inall, the findingsshowthat there isnoperceptionof lackofpersonalskills toworkwith industry but that collaboration is rather impededby external factorssuchasattitudeofcolleagues/practitionersandfunding/acquisitioncosts.

Additionalbarriersthatwerementionedintheinterviewsare:“BoardofUniversityisnowcareful about direct collaborationwith industry due to the risk of researchersbecomingconsultantsandnotdoingresearch”;“Itistootimeconsuming”;“Tooshorttimeperspec‐tivefromthecompany'sside.Companieswanttooconcreteresults.”; “Universityadmini‐strationmakesitdifficulttorunsuchprojects tooexpensive .”;“Overheadcostsonindus‐tryprojectstoohigh”.

Thereisnoagreementonatrendtowardsmoreorlessresearchcollaborationwithindus‐try.Sixrespondentsperceivea trendtowards less, five towardsmorecollaboration.Tworespondentsdonotperceiveatrendatall.Theinterviewpartnerswereunanimousintheirassessment toan increase inmeasuringandassessingof researchoutput.Onesays: “Weobserveadrivetoametric‐basedworld.Thismakesithardertosucceedasaresearcher,itremindsme of a tennismatch” respondent #14 . Another researcher comments on thetrendquestion:“WithworriesIperceiveatrendtocounting,weighingandmeasuringandanobligationtopublish inA‐journals.Thiscould leadtoatrendof lessengagementwithindustry” respondent#6 .


20

Figure 9: Most important barriers for academics sorted by the sum of important andratherimportant

In the study of the “most successful setup for a collaboration”, the “1:1, industry fundedcollaboration”cameoutas“themostsuccessfultype”.Itwasfavouredbyfiveofthe13re‐searchers that responded to this question cf. Figure 10 . Two researchers favoured the“n:m,co‐fundedmodel”andtwoothersthe“1:m,industry‐funded”.Fourtypesweremen‐tionedonlyonce.Theninthrespondentstatedthatonlyamixoftypescouldsustainasuc‐cessfulresearchgroupandthusclaimedthattherewasnouniquemostsuccessfultype re‐spondent#9 .

Exactlyhalfof the respondentsselectedan industry‐fundedmodel either1:1or1:m astheirmostsuccessfulapproach.Theprobleminacquiringpublicfundingwasunanimouslyexpressed by all participants during the interview. It is not surprising that the findings

0 2 4 6 8 10 12 14 16

Lack in‐ability to speak practitioners’ language

Lack of practical knowledge

Lack of proper methods / ideas for how to do it

Unfavourable (or negative) reputation of industry research for personal promotion

Lack of recognition from colleagues/deans

Few opportunities in the environment of where my university is located

Lack of access to industry partners

Difficulty in obtaining supporting external funds from public sources (e.g. low acceptance rate)

Acquisition cost of getting projects is too high or takes too long time and effort

Scepticism in industry towards academics

What do you consider the most important barriers for academics involving themselves in industry collaborative projects in general (N = maximal 14)

important rather important neutral rather unimportant unimportant


21

showthatresearchersvalueprojectsinwhichtheindustrycoversthefullcost.Suchpro‐jectscanstart immediatelyafterthedecisionhasbeentakenbythe industrypartnerandthereisnoneedtogothroughtheawkwardgrantapplicationprocessthatisinmostcasesconnectedwith a longwaiting time for an uncertain outcome. The 1:1 approach can, inthese cases, beused for small, agileprojectswhere confidential topics are researchedornewinnovationsaredevelopedthatcannotbesharedwithcompetitors.

Itisinterestingtonotethatofthethreerespondentsofn:mprojectstwostemfromFinlandco‐funded andonefromSingapore government‐funded .Then:mparadigmisatypicalEUprojectprofilewhichwillmost likely lead to large, complexprojectswitha lotof ex‐changeofideas,possiblyinterdisciplinarygroupsandtheneedtoopenlydiscussideasandsharethoughts.

Figure10:Mostsuccessfultypeofcollaboration

Thesefindingswereunderlinedbyarespondentwhoarguedforconsortiumprojectsasthebestformbecause“researcherteamscanachieveahigherefficiencyandmoreinterestingoutputwithmultiplepartners” respondent#7 .Theresearchersrespondedunanimouslytothelastquestion:Theywouldallengageinanindustrycollaborationprojectagain.

SomefinalthoughtsThisstudyinvestigatesattitudesandexperiencesofISresearchersfromfourdifferentcon‐tinents NorthAmerica,Europe,AsiaandAustralia regardingcollaborationwithindustry.

1

1

1

1

2

2

5

0 1 2 3 4 5 6

1:1, government‐funded

1:m, co‐funded

n:1, co‐funded

n:m, government‐funded

1:m, industry‐funded

n:m, co‐funded

1:1, industry‐funded

Which type of collaboration was the most successful for you? (N=13)


22

Thefindingsshowthattheattitudeofresearchersislargelydeterminedbytheprevailingresearchcultureanddependentonthepersonalexperiencesthatanindividualresearcherhasgainedfromsuchprojects.AsBaskervilleetal. 2011 argue,topjournalsonlyaccepttop publications characterized by contribution to theory and novel findings based on arigorous analysisofdata evidence .Itcanbearguedthatwiththerightsetofmethods,researchers can derive findings that are highly relevant for academics and practice aswellashighlyrigorousatthesametime.

It istheauthor’sfirmbelievethatthepursuitofrelevanceconstitutesaconditiosinequanonforISresearch.WithoutitindustrywillloseinterestinresearchfindingsandthepublicspendingonISresearchwillbewasted.

A second implication of engaging in university‐industry collaboration is that we mightavoid themanyarticles/projects,where the researcher isusinga convenience sampleofstudentsfromhis/herclass,whichareoftenproblematicproxiesforrealusers/managers.

Thirdly andmost importantly, university‐industry projects aremuchmore likely to pro‐ducevaluetoourkeystakeholders industryandstudents thanresearchcarriedoutex‐clusivelyatthedesk.Incollaborativeprojectswithpractitionersinindustry,valuewillal‐mostautomaticallybecomecentrestage.Valuetostudentsisalsolikelytobehigher.Itisarguedthatinmostsituations,themarginalvaluetostudentsoflearningaboutonemoretaxonomy and/oronemore theoretical perspective is likely to be substantially less thanworkingwithrealcases/data/persons.Inthatway,studentswillbebetterpreparedfortherealityawaitingthemaftergraduation,andtheywillbebetterabletosurvive,developandcontributevalueindirectlyjustifyingourroleasteachers/co‐learners.

AcknowledgementsThestudyofattitudesandexperiencesrequiredtocollectalotofprimarydatawhichwasquitelabour‐intensiveandalsorequiredalotoftravellingduetotheinternationalnatureoftheresearch.Theauthorofthisworkingreportwouldliketogiveherthankstoanum‐berofpeoplewhocontributedtothiswork.Firstly,IwouldliketothanktheinterviewersNiels Bjørn‐Andersen, Norbert Frick,Matthias Bertram andmyself who conducted theinterviewsandturnedintherecordings.Iamalsoindebtedtotheresearchpersonnelwhotranscribedtheinterviewsandmadethemreadyforcodingandanalysis.Myspecialthanksgo totheresearchparticipants, thepeoplewhoagreedtobe interviewedandsharetheirvaluableexperiencesandattitudes.


23

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Martin Surrey, Roland Diehl, DOCHOUSE: Opportunity Management im Partnerkanal (IBM Lotus Quickr), Arbeitsberichte aus dem Fachbereich Informatik 2/2012

Mark Schneider, Ansgar Scherp, Comparing a Grid-based vs. List-based Approach for Faceted Search of Social Media Data on Mobile Devices, Arbeitsberichte aus dem Fachbereich Informatik 1/2012 Petra Schubert, Femi Adisa, Cloud Computing for Standard ERP Systems: Reference Framework and Research Agenda, Arbeitsberichte aus dem Fachbereich Informatik 16/2011 Oleg V. Kryuchin, Alexander A. Arzamastsev, Klaus G. Troitzsch, Natalia A. Zenkova, Simulating social objects with an artificial network using a computer cluster, Arbeitsberichte aus dem Fachbereich Informatik 15/2011 Oleg V. Kryuchin, Alexander A. Arzamastsev, Klaus G. Troitzsch, Simulating medical objects using an artificial network whose structure is based on adaptive resonance theory, Arbeitsberichte aus dem Fachbereich Informatik 14/2011

Oleg V. Kryuchin, Alexander A. Arzamastsev, Klaus G. Troitzsch, Comparing the efficiency of serial and parallel algorithms for training artificial neural networks using computer clusters, Arbeitsberichte aus dem Fachbereich Informatik, 13/2011 Oleg V. Kryuchin, Alexander A. Arzamastsev, Klaus G. Troitzsch, A parallel algorithm for selecting activation functions of an artificial network, Arbeitsberichte aus dem Fachbereich Informatik 12/2011 Katharina Bräunlich, Rüdiger Grimm, Andreas Kasten, Sven Vowé, Nico Jahn, Der neue Personalausweis zur Authentifizierung von Wählern bei Onlinewahlen, Arbeitsberichte aus dem Fachbereich Informatik 11/2011 Daniel Eißing, Ansgar Scherp, Steffen Staab, Formal Integration of Individual Knowledge Work and Organizational Knowledge Work with the Core Ontology strukt, Arbeitsberichte aus dem Fachbereich Informatik 10/2011 Bernhard Reinert, Martin Schumann, Stefan Müller, Combined Non-Linear Pose Estimation from Points and Lines, Arbeitsberichte aus dem Fachbereich Informatik 9/2011 Tina Walber, Ansgar Scherp, Steffen Staab, Towards the Understanding of Image Semantics by Gaze-based Tag-to-Region Assignments, Arbeitsberichte aus dem Fachbereich Informatik 8/2011 Alexander Kleinen, Ansgar Scherp, Steffen Staab, Mobile Facets – Faceted Search and Exploration of Open Social Media Data on a Touchscreen Mobile Phone, Arbeitsberichte aus dem Fachbereich Informatik 7/2011 Anna Lantsberg, Klaus G. Troitzsch, Towards A Methodology of Developing Models of E-Service Quality Assessment in Healthcare, Arbeitsberichte aus dem Fachbereich Informatik 6/2011 Ansgar Scherp, Carsten Saathoff, Thomas Franz, Steffen Staab, Designing Core Ontologies, Arbeitsberichte aus dem Fachbereich Informatik 5/2011 Oleg V. Kryuchin, Alexander A. Arzamastsev, Klaus G. Troitzsch, The prediction of currency exchange rates using artificial neural networks, Arbeitsberichte aus dem Fachbereich Informatik 4/2011 Klaus G. Troitzsch, Anna Lantsberg, Requirements for Health Care Related Websites in Russia: Results from an Analysis of American, British and German Examples, Arbeitsberichte aus dem Fachbereich Informatik 3/2011 Klaus G. Troitzsch, Oleg Kryuchin, Alexander Arzamastsev, A universal simulator based on artificial neural networks for computer clusters, Arbeitsberichte aus dem Fachbereich Informatik 2/2011 Klaus G. Troitzsch, Natalia Zenkova, Alexander Arzamastsev, Development of a technology of designing intelligent information systems for the estimation of social objects, Arbeitsberichte aus dem Fachbereich Informatik 1/2011 Kurt Lautenbach, A Petri Net Approach for Propagating Probabilities and Mass Functions, Arbeitsberichte aus dem Fachbereich Informatik 13/2010 Claudia Schon, Linkless Normal Form for ALC Concepts, Arbeitsberichte aus dem Fachbereich Informatik 12/2010 Alexander Hug, Informatik hautnah erleben, Arbeitsberichte aus dem Fachbereich Informatik 11/2010

Marc Santos, Harald F.O. von Kortzfleisch, Shared Annotation Model – Ein Datenmodell für kollaborative Annotationen, Arbeitsberichte aus dem Fachbereich Informatik 10/2010 Gerd Gröner, Steffen Staab, Categorization and Recognition of Ontology Refactoring Pattern, Arbeitsberichte aus dem Fachbereich Informatik 9/2010 Daniel Eißing, Ansgar Scherp, Carsten Saathoff, Integration of Existing Multimedia Metadata Formats and Metadata Standards in the M3O, Arbeitsberichte aus dem Fachbereich Informatik 8/2010 Stefan Scheglmann, Ansgar Scherp, Steffen Staab, Model-driven Generation of APIs for OWL-based Ontologies, Arbeitsberichte aus dem Fachbereich Informatik 7/2010 Daniel Schmeiß, Ansgar Scherp, Steffen Staab, Integrated Mobile Visualization and Interaction of Events and POIs, Arbeitsberichte aus dem Fachbereich Informatik 6/2010 Rüdiger Grimm, Daniel Pähler, E-Mail-Forensik – IP-Adressen und ihre Zuordnung zu Internet-Teilnehmern und ihren Standorten, Arbeitsberichte aus dem Fachbereich Informatik 5/2010 Christoph Ringelstein, Steffen Staab, PAPEL: Syntax and Semantics for Provenance-Aware Policy Definition, Arbeitsberichte aus dem Fachbereich Informatik 4/2010 Nadine Lindermann, Sylvia Valcárcel, Harald F.O. von Kortzfleisch, Ein Stufenmodell für kollaborative offene Innovationsprozesse in Netzwerken kleiner und mittlerer Unternehmen mit Web 2.0, Arbeitsberichte aus dem Fachbereich Informatik 3/2010 Maria Wimmer, Dagmar Lück-Schneider, Uwe Brinkhoff, Erich Schweighofer, Siegfried Kaiser, Andreas Wieber, Fachtagung Verwaltungsinformatik FTVI Fachtagung Rechtsinformatik FTRI 2010, Arbeitsberichte aus dem Fachbereich Informatik 2/2010 Max Braun, Ansgar Scherp, Steffen Staab, Collaborative Creation of Semantic Points of Interest as Linked Data on the Mobile Phone, Arbeitsberichte aus dem Fachbereich Informatik 1/2010 Marc Santos, Einsatz von „Shared In-situ Problem Solving“ Annotationen in kollaborativen Lern- und Arbeitsszenarien, Arbeitsberichte aus dem Fachbereich Informatik 20/2009 Carsten Saathoff, Ansgar Scherp, Unlocking the Semantics of Multimedia Presentations in the Web with the Multimedia Metadata Ontology, Arbeitsberichte aus dem Fachbereich Informatik 19/2009 Christoph Kahle, Mario Schaarschmidt, Harald F.O. von Kortzfleisch, Open Innovation: Kundenintegration am Beispiel von IPTV, Arbeitsberichte aus dem Fachbereich Informatik 18/2009 Dietrich Paulus, Lutz Priese, Peter Decker, Frank Schmitt, Pose-Tracking Forschungsbericht, Arbeitsberichte aus dem Fachbereich Informatik 17/2009 Andreas Fuhr, Tassilo Horn, Andreas Winter, Model-Driven Software Migration Extending SOMA, Arbeitsberichte aus dem Fachbereich Informatik 16/2009 Eckhard Großmann, Sascha Strauß, Tassilo Horn, Volker Riediger, Abbildung von grUML nach XSD soamig, Arbeitsberichte aus dem Fachbereich Informatik 15/2009 Kerstin Falkowski, Jürgen Ebert, The STOR Component System Interim Report, Arbeitsberichte aus dem Fachbereicht Informatik 14/2009

Sebastian Magnus, Markus Maron, An Empirical Study to Evaluate the Location of Advertisement Panels by Using a Mobile Marketing Tool, Arbeitsberichte aus dem Fachbereich Informatik 13/2009 Sebastian Magnus, Markus Maron, Konzept einer Public Key Infrastruktur in iCity, Arbeitsberichte aus dem Fachbereich Informatik 12/2009 Sebastian Magnus, Markus Maron, A Public Key Infrastructure in Ambient Information and Transaction Systems, Arbeitsberichte aus dem Fachbereich Informatik 11/2009 Ammar Mohammed, Ulrich Furbach, Multi-agent systems: Modeling and Virification using Hybrid Automata, Arbeitsberichte aus dem Fachbereich Informatik 10/2009 Andreas Sprotte, Performance Measurement auf der Basis von Kennzahlen aus betrieblichen Anwendungssystemen: Entwurf eines kennzahlengestützten Informationssystems für einen Logistikdienstleister, Arbeitsberichte aus dem Fachbereich Informatik 9/2009 Gwendolin Garbe, Tobias Hausen, Process Commodities: Entwicklung eines Reifegradmodells als Basis für Outsourcingentscheidungen, Arbeitsberichte aus dem Fachbereich Informatik 8/2009 Petra Schubert et. al., Open-Source-Software für das Enterprise Resource Planning, Arbeitsberichte aus dem Fachbereich Informatik 7/2009 Ammar Mohammed, Frieder Stolzenburg, Using Constraint Logic Programming for Modeling and Verifying Hierarchical Hybrid Automata, Arbeitsberichte aus dem Fachbereich Informatik 6/2009 Tobias Kippert, Anastasia Meletiadou, Rüdiger Grimm, Entwurf eines Common Criteria-Schutzprofils für Router zur Abwehr von Online-Überwachung, Arbeitsberichte aus dem Fachbereich Informatik 5/2009 Hannes Schwarz, Jürgen Ebert, Andreas Winter, Graph-based Traceability – A Comprehensive Approach. Arbeitsberichte aus dem Fachbereich Informatik 4/2009 Anastasia Meletiadou, Simone Müller, Rüdiger Grimm, Anforderungsanalyse für Risk-Management-Informationssysteme (RMIS), Arbeitsberichte aus dem Fachbereich Informatik 3/2009 Ansgar Scherp, Thomas Franz, Carsten Saathoff, Steffen Staab, A Model of Events based on a Foundational Ontology, Arbeitsberichte aus dem Fachbereich Informatik 2/2009 Frank Bohdanovicz, Harald Dickel, Christoph Steigner, Avoidance of Routing Loops, Arbeitsberichte aus dem Fachbereich Informatik 1/2009 Stefan Ameling, Stephan Wirth, Dietrich Paulus, Methods for Polyp Detection in Colonoscopy Videos: A Review, Arbeitsberichte aus dem Fachbereich Informatik 14/2008 Tassilo Horn, Jürgen Ebert, Ein Referenzschema für die Sprachen der IEC 61131-3, Arbeitsberichte aus dem Fachbereich Informatik 13/2008 Thomas Franz, Ansgar Scherp, Steffen Staab, Does a Semantic Web Facilitate Your Daily Tasks?, Arbeitsberichte aus dem Fachbereich Informatik 12/2008 Norbert Frick, Künftige Anfordeungen an ERP-Systeme: Deutsche Anbieter im Fokus, Arbeitsberichte aus dem Fachbereicht Informatik 11/2008 Jürgen Ebert, Rüdiger Grimm, Alexander Hug, Lehramtsbezogene Bachelor- und Masterstudiengänge im Fach Informatik an der Universität Koblenz-Landau, Campus Koblenz, Arbeitsberichte aus dem Fachbereich Informatik 10/2008

Mario Schaarschmidt, Harald von Kortzfleisch, Social Networking Platforms as Creativity Fostering Systems: Research Model and Exploratory Study, Arbeitsberichte aus dem Fachbereich Informatik 9/2008 Bernhard Schueler, Sergej Sizov, Steffen Staab, Querying for Meta Knowledge, Arbeitsberichte aus dem Fachbereich Informatik 8/2008 Stefan Stein, Entwicklung einer Architektur für komplexe kontextbezogene Dienste im mobilen Umfeld, Arbeitsberichte aus dem Fachbereich Informatik 7/2008 Matthias Bohnen, Lina Brühl, Sebastian Bzdak, RoboCup 2008 Mixed Reality League Team Description, Arbeitsberichte aus dem Fachbereich Informatik 6/2008 Bernhard Beckert, Reiner Hähnle, Tests and Proofs: Papers Presented at the Second International Conference, TAP 2008, Prato, Italy, April 2008, Arbeitsberichte aus dem Fachbereich Informatik 5/2008 Klaas Dellschaft, Steffen Staab, Unterstützung und Dokumentation kollaborativer Entwurfs- und Entscheidungsprozesse, Arbeitsberichte aus dem Fachbereich Informatik 4/2008 Rüdiger Grimm: IT-Sicherheitsmodelle, Arbeitsberichte aus dem Fachbereich Informatik 3/2008 Rüdiger Grimm, Helge Hundacker, Anastasia Meletiadou: Anwendungsbeispiele für Kryptographie, Arbeitsberichte aus dem Fachbereich Informatik 2/2008 Markus Maron, Kevin Read, Michael Schulze: CAMPUS NEWS – Artificial Intelligence Methods Combined for an Intelligent Information Network, Arbeitsberichte aus dem Fachbereich Informatik 1/2008 Lutz Priese,Frank Schmitt, Patrick Sturm, Haojun Wang: BMBF-Verbundprojekt 3D-RETISEG Abschlussbericht des Labors Bilderkennen der Universität Koblenz-Landau, Arbeitsberichte aus dem Fachbereich Informatik 26/2007 Stephan Philippi, Alexander Pinl: Proceedings 14. Workshop 20.-21. September 2007 Algorithmen und Werkzeuge für Petrinetze, Arbeitsberichte aus dem Fachbereich Informatik 25/2007 Ulrich Furbach, Markus Maron, Kevin Read: CAMPUS NEWS – an Intelligent Bluetooth-based Mobile Information Network, Arbeitsberichte aus dem Fachbereich Informatik 24/2007 Ulrich Furbach, Markus Maron, Kevin Read: CAMPUS NEWS - an Information Network for Pervasive Universities, Arbeitsberichte aus dem Fachbereich Informatik 23/2007 Lutz Priese: Finite Automata on Unranked and Unordered DAGs Extented Version, Arbeitsberichte aus dem Fachbereich Informatik 22/2007 Mario Schaarschmidt, Harald F.O. von Kortzfleisch: Modularität als alternative Technologie- und Innovationsstrategie, Arbeitsberichte aus dem Fachbereich Informatik 21/2007 Kurt Lautenbach, Alexander Pinl: Probability Propagation Nets, Arbeitsberichte aus dem Fachbereich Informatik 20/2007 Rüdiger Grimm, Farid Mehr, Anastasia Meletiadou, Daniel Pähler, Ilka Uerz: SOA-Security, Arbeitsberichte aus dem Fachbereich Informatik 19/2007 Christoph Wernhard: Tableaux Between Proving, Projection and Compilation, Arbeitsberichte aus dem Fachbereich Informatik 18/2007

Ulrich Furbach, Claudia Obermaier: Knowledge Compilation for Description Logics, Arbeitsberichte aus dem Fachbereich Informatik 17/2007

Fernando Silva Parreiras, Steffen Staab, Andreas Winter: TwoUse: Integrating UML Models and OWL Ontologies, Arbeitsberichte aus dem Fachbereich Informatik 16/2007

Rüdiger Grimm, Anastasia Meletiadou: Rollenbasierte Zugriffskontrolle (RBAC) im Gesundheitswesen, Arbeitsberichte aud dem Fachbereich Informatik 15/2007

Ulrich Furbach, Jan Murray, Falk Schmidsberger, Frieder Stolzenburg: Hybrid Multiagent Systems with Timed Synchronization-Specification and Model Checking, Arbeitsberichte aus dem Fachbereich Informatik 14/2007

Björn Pelzer, Christoph Wernhard: System Description:“E-KRHyper“, Arbeitsberichte aus dem Fachbereich Informatik, 13/2007

Ulrich Furbach, Peter Baumgartner, Björn Pelzer: Hyper Tableaux with Equality, Arbeitsberichte aus dem Fachbereich Informatik, 12/2007

Ulrich Furbach, Markus Maron, Kevin Read: Location based Informationsystems, Arbeitsberichte aus dem Fachbereich Informatik, 11/2007

Philipp Schaer, Marco Thum: State-of-the-Art: Interaktion in erweiterten Realitäten, Arbeitsberichte aus dem Fachbereich Informatik, 10/2007

Ulrich Furbach, Claudia Obermaier: Applications of Automated Reasoning, Arbeitsberichte aus dem Fachbereich Informatik, 9/2007

Jürgen Ebert, Kerstin Falkowski: A First Proposal for an Overall Structure of an Enhanced Reality Framework, Arbeitsberichte aus dem Fachbereich Informatik, 8/2007

Lutz Priese, Frank Schmitt, Paul Lemke: Automatische See-Through Kalibrierung, Arbeitsberichte aus dem Fachbereich Informatik, 7/2007

Rüdiger Grimm, Robert Krimmer, Nils Meißner, Kai Reinhard, Melanie Volkamer, Marcel Weinand, Jörg Helbach: Security Requirements for Non-political Internet Voting, Arbeitsberichte aus dem Fachbereich Informatik, 6/2007

Daniel Bildhauer, Volker Riediger, Hannes Schwarz, Sascha Strauß, „grUML – Eine UML-basierte Modellierungssprache für T-Graphen“, Arbeitsberichte aus dem Fachbereich Informatik, 5/2007

Richard Arndt, Steffen Staab, Raphaël Troncy, Lynda Hardman: Adding Formal Semantics to MPEG-7: Designing a Well Founded Multimedia Ontology for the Web, Arbeitsberichte aus dem Fachbereich Informatik, 4/2007

Simon Schenk, Steffen Staab: Networked RDF Graphs, Arbeitsberichte aus dem Fachbereich Informatik, 3/2007

Rüdiger Grimm, Helge Hundacker, Anastasia Meletiadou: Anwendungsbeispiele für Kryptographie, Arbeitsberichte aus dem Fachbereich Informatik, 2/2007

Anastasia Meletiadou, J. Felix Hampe: Begriffsbestimmung und erwartete Trends im IT-Risk-Management, Arbeitsberichte aus dem Fachbereich Informatik, 1/2007

„Gelbe Reihe“ (http://www.uni-koblenz.de/fb4/publikationen/gelbereihe) Lutz Priese: Some Examples of Semi-rational and Non-semi-rational DAG Languages. Extended Version, Fachberichte Informatik 3-2006

Kurt Lautenbach, Stephan Philippi, and Alexander Pinl: Bayesian Networks and Petri Nets, Fachberichte Informatik 2-2006

Rainer Gimnich and Andreas Winter: Workshop Software-Reengineering und Services, Fachberichte Informatik 1-2006

Kurt Lautenbach and Alexander Pinl: Probability Propagation in Petri Nets, Fachberichte Informatik 16-2005

http://www.uni-koblenz.de/~ag-pn/html/mitarbeiter/mitarbeiter.html

http://www.uni-koblenz.de/~ag-pn/html/mitarbeiter/apinl.html

Rainer Gimnich, Uwe Kaiser, and Andreas Winter: 2. Workshop ''Reengineering Prozesse'' – Software Migration, Fachberichte Informatik 15-2005

Jan Murray, Frieder Stolzenburg, and Toshiaki Arai: Hybrid State Machines with Timed Synchronization for Multi-Robot System Specification, Fachberichte Informatik 14-2005

Reinhold Letz: FTP 2005 – Fifth International Workshop on First-Order Theorem Proving, Fachberichte Informatik 13-2005

Bernhard Beckert: TABLEAUX 2005 – Position Papers and Tutorial Descriptions, Fachberichte Informatik 12-2005

Dietrich Paulus and Detlev Droege: Mixed-reality as a challenge to image understanding and artificial intelligence, Fachberichte Informatik 11-2005

Jürgen Sauer: 19. Workshop Planen, Scheduling und Konfigurieren / Entwerfen, Fachberichte Informatik 10-2005

Pascal Hitzler, Carsten Lutz, and Gerd Stumme: Foundational Aspects of Ontologies, Fachberichte Informatik 9-2005

Joachim Baumeister and Dietmar Seipel: Knowledge Engineering and Software Engineering, Fachberichte Informatik 8-2005

Benno Stein and Sven Meier zu Eißen: Proceedings of the Second International Workshop on Text-Based Information Retrieval, Fachberichte Informatik 7-2005

Andreas Winter and Jürgen Ebert: Metamodel-driven Service Interoperability, Fachberichte Informatik 6-2005

Joschka Boedecker, Norbert Michael Mayer, Masaki Ogino, Rodrigo da Silva Guerra, Masaaki Kikuchi, and Minoru Asada: Getting closer: How Simulation and Humanoid League can benefit from each other, Fachberichte Informatik 5-2005

Torsten Gipp and Jürgen Ebert: Web Engineering does profit from a Functional Approach, Fachberichte Informatik 4-2005

Oliver Obst, Anita Maas, and Joschka Boedecker: HTN Planning for Flexible Coordination Of Multiagent Team Behavior, Fachberichte Informatik 3-2005

Andreas von Hessling, Thomas Kleemann, and Alex Sinner: Semantic User Profiles and their Applications in a Mobile Environment, Fachberichte Informatik 2-2005

Heni Ben Amor and Achim Rettinger: Intelligent Exploration for Genetic Algorithms – Using Self-Organizing Maps in Evolutionary Computation, Fachberichte Informatik 1-2005

http://www.uni-koblenz.de/~winter/

http://www.uni-koblenz.de/~murray/

http://fstolzenburg.hs-harz.de/

http://www.uni-koblenz.de/~beckert/

http://www.uni-koblenz.de/FB4/Institutes/ICV/AGPaulus/Members/paulus

http://www.uni-koblenz.de/~droege/

http://www.uni-koblenz.de/~winter/

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http://www.uni-koblenz.de/~ebert/

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Documents

A Study of the Factors that Influence Engagement in ...fb4reports/2012/2012... · Prof. Dr. Petra Schubert petra.schubert@uni‐koblenz.de Institute for IS Research, University of