The Spiral of Knowledge according to Nonaka - ResearchGate

The spiral of knowledge consists of four processes which are bound to two types of knowledge implicit (hidden, latent, delitescent) and explicit (evident, ... Figure1-uploadedbyMarkusSchattenContentmaybesubjecttocopyright.DownloadViewpublicationCopyreferenceCopycaptionEmbedfigureTheSpiralofKnowledgeaccordingtoNonaka SourcepublicationSmartResidentialBuildingsasLearningAgentOrganizationsintheInternetofThingsArticleFull-textavailableMar2014MarkusSchattenSmartbuildingsareoneofthemajorapplicationareasoftechnologiesboundtoembeddedsystemsandtheInternetofthings.Suchsystemshavetobeadaptableandflexibleinordertoprovidebetterservicestoitsresidents.Modellingsuchsystemsisanopenresearchquestion.Herein,thequestionisapproachedusinganorganizationalmodellingme...ContextinsourcepublicationContext1...insightsintotheprocessesbehindlearningandknowledgecreationcanbefoundinthenotionoftheknowledgecreatingcompanyasdescribedbyNonakaandTakeuchi(1995).Theybasedtheirconceptualizationontheknowledgespiralshownonfigure1(Barlow,2000).Thespiralofknowledgeconsistsoffourprocesseswhichareboundtotwotypesofknowledgeimplicit(hidden,latent,delitescent)andexplicit(evident,external,andwritten):Socialization.Thefirstprocess,socialization,isthetranspositionofimplicitknowledgeagainintoimplicitknowledge.Thisisachievedbyobservingforeignbehaviourandadoptingit.Humans,forexample,learnhowtospeakandsurviveintheircommunitysolelybythisprocess.Externalization.Thesecondprocess,externalization,istheprocessoftransformingimplicitintoexplicitknowledge.Itisachievedbyformalizing(“writingdown”)internalknowledgetobeobservablebyothers.Forexample,askilledprogrammermightwritedownhisexperienceingoodprogrammingtechniques.Internalization.Internalizationrepresentsthetransformationofexplicitintoimplicitknowledge.Itistheprocessinwhichsomethingwelearnedbecomesanautomatedbehaviour.Forexample,whenapersonlearnshowtodrive,itthinksaboutallthemanualstepsfullyaware(whentobrake,whentolookatthemirrors,whentochangethegearetc.).Oncelearned,thepersonbecomesunawareofitsactions;theactionsbecomeanautomatedprocess.Combination.Inthecombinationprocess,explicitisagaintransformedintoexplicitknowledge.Itisachievedbycombiningexplicitknowledgeintonewfindings.Mostacademicinstitutionsrelymostlyonthisprocess.Nonakafurtherexplainsthat,evenifmanagersoftenthinkthatknowledgeiscreatedexclusivelyinthecombinationprocess,itismuchmoreeffectiveandcreativetocreateknowledgebygoingthroughallfourquadrants.Inthiswayvariouscreativeprocesseslikegroupbasedproblemsolving,newproductorservicedesignandprojectmanagementcanhavebetteroutcomes.Forsomeprojects,itwillbenecessarytovisitallquadrantsmultipletimes,whichishowaknowledgespiralemerges(Barlow,2000).AccordingtoNonaka,combinationandinternalizationarebetteradjustedtobureaucraticorganizations,whilesocializationandexternalizationapplypreferablytoteambasedstructures.Thisissummarizedintheideaofthehypertextorganizationinwhichemployeesshould(asdohyperlinksonWebPages)delineatebureaucracyandconnectsteambasedprojectswithhierarchicalorganizedunits(Barlow,2000;Žugaj&Schatten,2008).Thushisorganizationalmodelconsistsofthreelayers:Businesssystemlayer-representstheperformanceofday-to-daybusinessprocessesintheorganization.Sinceahierarchicalorganizedbureaucracyismostefficientforroutineactivities,thislayerhasapyramidal...Viewinfull-textCitations...IoTdenotesnetworkedanduniqueaddressedobjectswhichcanbeapplicatedinfactories,cars,house,electricaldevices,furnitureandcellphone(Schatten,2014).IoTwasfirstinventedin1999todefine"internet-connecteddeviceswithRFIDinasupplychain",andnowadays,itisacriticalconceptinIT....Simulationofstakeholders’consensusonorganizationaltechnologyacceptance(casestudy:InternetofThings)ArticleNov2020KYBERNETESAliSarkeshikianMohhamadaliShafiaAmirZakeryAlirezaAliahmadiPurpose Intheorganizationaltechnologyacceptance(TA)decision-makingprocess,stakeholdershavemanydivergenceopinions.Sometimes,anopposingstakeholderofadecisioncanstopthewholeprocessofdecision-making.Insuchacase,consensusmaytakealongtimefollowedbyahighrisk.Thepurposeofthisstudyistwofold.First,tofindthebestmodelwiththeleastpredictionerrorforthesimulationoftheconsensusprocessinTAdecisions.Second,toinvestigatethetimerequiredfortheconsensusprocesstoyieldtheTAdecisionindifferentscenariosandtoproposesolutionstoreducetherequiredtimeinacasestudy. Design/methodology/approach Thisstudyusesreal-worlddatacontaining1,186actualobservations.Stakeholdersaredecision-makeragents,andtheobservationsarederivedfromsurveydataandusedforsimulation.Datawereobtainedfrom126expertsintheIranianrailfreightindustry.Opiniondynamicstheorywasusedforagent-basedsimulationofstakeholders’behavior.Theagentsinteractedovertimeandtheireffectsonotheragents’opinionswereinvestigated. Findings Theresultsillustrateanappropriateopinionchangingmodel,adata-gatheringmethodandasimulationscenarioforTAconsensus.Thesuitablemodelwasselectedafterexaminingtheadvantagesanddisadvantagesofandcomparingthepredictionresultsfordifferentmodelswiththerealdatabaseofopinions.Toreducetheconsensusprocesstime,theresultssuggestgatheringtheteammembersandnetworkingwithsomeleadersasadvocators.Alargenumberofadvocatorswithhighacceptabilityandcontinuousexchangingmessageswithotheragentscanimprovetheacceptancerateandhavethemostsignificantimpactonotherstakeholders’opinions. Originality/value Tothebestoftheauthors’knowledge,previousstudiessimulateindividualTAprocesses.However,thereisadifferencebetweentheindividualTAandtheorganizationalTA.TheorganizationalTArequiresthesimultaneousdecision-makingofdifferentstakeholders.Inthisresearch,theorganizationalTAwasinvestigated....Keyfieldsandapplications(ThiscanbeportrayedinFig.1)forapplyingIoTsolutionsencompass[5]:smartcities,smartpowernetworks,smarttransportandsmartbuildings(intelligentsolutionsforliving).Thislistalsoincludessmarthealthcare,oneofthemainsubjectsofthisarticle....UncertaintyinIoTforSmartHealthcare:Challenges,andOpportunitiesChapterFull-textavailableJun2020AnisTissaouiMalakSaidiAccordingtoKnight,uncertaintysignifiesdeviationsfromtheexpectedstates,whichpreventusfromtheuseofanyprobabilityforthedeterminationofaresultforagivenactionordecision[1].Thispaperdescribesthephenomenonofuncertaintyinthefaceoftechnologicalmegatrendsandchallengesassociatedwiththem.Thearticlefocusesontheanalysisoftheuncertaintyinoneofthemostimportanttechnologytrends–theInternetofThings(IoT)–ontheexampleofHealthcare.Therightdecisionsarenotalwaysequivalenttogoodresults.Sometimes,thedecisiontakeninaccordancewithgeneralrulesbringsworseresultsthantheonewhobreaksthem.Suchasituationispossibleasaresultoftheuncertaintyaccompanyingthepredictionsofthefuture.InthisarticletheconceptoftheIoTistreatedasabig,complex,dynamicsystemwithspecificcharacteristics,dimensions.structuresandbehaviors.TheaimofthearticleistoanalyzethefactorsthatmaydeterminetheuncertaintyandambiguityofsuchsystemsinthecontextofthedevelopmentofHealthcare,andrecommendationsaremadeforfutureresearchdirections....[5]ASmartCityControlAuthority(SCCA)modelhasbeensuggestedbyresearchersforthemanagementofallofthefacilitiesofsmartcitiesandcontrollingitsrelatedservicesaccordingtocertainprivilegesgiventotheauthorityunit,thisauthorityunithastheabilitytoholdtheSCCAandhasspecificandstandardizedprinciplesandguidelineswhicharewell-definedunderthelawwiththepreservationofsecurityandprivacy.[6]Smartresidentbuildingsweredescribedbytheauthorsin[7]byquotingtheorganizationtheoryideas,andmostly,theideaofalearningorganization....SmartCommunityChallenges:EnablingIoT/M2MTechnologyCaseStudyArticleFull-textavailableJun2019NorahFarooqiAdnanGutubOsamaKhoziumWiththegreatinnovationsandthefastimprovementsintechnology,peopletendtoleavethecountrysideandstartedoccupyingthecities,andtherefore,thepopulationincitiesdramaticallyincreasedtotheextentthatit'spredictedby2050,theurbanspopulationwillreach70%oftheworldpopulationforthefirsttimeinthehistoryofmankind,knowingthatcitiesusearound75%oftheresourcesoftheworldanditsenergy.Thisleadstothefearfromdeficiencyintheearthresources.Theproblemisofgreatconcern,andresearcherstrytoproposemanyideastoovercomethisdilemma.TheideaofSmartcitieshasbeenoneofthemostefficientsolutionsbecauseofwhatithasfromadvantagesthatcouldhelpinovercomingthehurdlesofoverpopulationandlackofresources.Andforconstructingasmartcity,agreatamountofdataandinformationisneededwhichcanbegatheredfromdifferentresourcessuchas:people,sensors,buildings,TV,transportations,Wi-Fi,etc.Theseresourceshavetobesecured,availableandaccurate.Andsincethesmartcommunityistheintermediategearbetweensmartcityandsmarthomes,wherethefeaturesofthesmarthomeswillbecarriedtothesmartcitiesandviceversa,thereforeinthispaperweshowsmartcommunityconceptandproposedit'sidealcomponents,howtoharnesstheIoTandICTforglobaldevelopment,showingthedifferentchallengeswhicharisethatarerelatedtoICTandIoTattheleveloftechniquesandpolicy....Main[2].Thepopularityofsmartbuildingshasbeenontheriseforthelast25years....AnAdaptiveWeightedFuzzyControllerAppliedonQualityofServiceofIntelligent5GEnvironmentsArticleFull-textavailableJan2019ArefSafari...Improveddatacollectionandcommunicationscansupportdecisionmakingandinturnimprovetheoverallefficiencyofthegrid.IoTisalsoanintegraltechnologyinfuturesmarthomes,smartbuildingsandsmartcities[15,46,65,66]whereIoTdevicesareexpectedtocooperate,activelyshareenergy,andparticipateinenergymanagement[31,39].Inadditiontoobject-objectinteraction,theIoTdesignmustalsoconsiderhuman-object,human-environmentandhuman-humaninteractions[20,21]....EmbeddingInternet-of-ThingsinLarge-ScaleSocio-technicalSystems:ACommunity-OrientedDesigninFutureSmartGrids:Technology,CommunicationsandComputingChapterFull-textavailableJan2019YilinHuangGiacomoPoderiSanjaŠćepanovićHannaHasselqvistFrancesBrazierIntraditionalengineering,technologiesareviewedasthecoreoftheengineeringdesign,inaphysicalworldwithalargenumberofdiversetechnologicalartefacts.Therealworld,however,alsoincludesahugenumberofsocialcomponents—people,communities,institutions,regulationsandeverythingthatexistsinthehumanmind—thathaveshapedandbeenshapedbythetechnologicalcomponents.Smarturbanecosystemsareexamplesoflarge-scaleSocio-TechnicalSystems(STS)thatrelyontechnologies,inparticularontheInternet-of-Things(IoT),withinacomplexsocialcontextwherethetechnologiesareembedded.DesigningapplicationsthatembedbothsocialcomplexityandIoTinlarge-scaleSTSrequiresaSocio-Technical(ST)approach,whichhasnotyetenteredthemainstreamofdesignpractice.ThischapterreviewstheliteratureandpresentsourexperienceofadoptinganSTapproachtothedesignofacommunity-orientedsmartgridapplication.Itdiscussesthechallenges,processandoutcomesofthisapporach,andprovidesasetoflessonslearnedderivedfromthisexperiencethatarealsodeemedrelevanttothedesignofothersmarturbanecosystems....Asanimplicationofthisresearch,itisexpectedthattheresultsofthisquantitativeanalysiswillserveascriteriaforevaluationbymanagersofcompaniesconsideringR&DstrategyintheIoTfield,whichisinlinewithnumerouspreviousresearch[26][27][28].Intermsofthelimitationsofthisresearch,thereisnotellingwhetherthetraitsofthebirthandgrowthphasesofsuchfirmswillbeappropriateinlaterphases....NetworkAnalysisofInnovationintheInternetofThingsArticleFull-textavailableJun2018FumihikoIsadaYurikoIsadaBackground:IntheInternetofThings(IoT)firms,innovationbeyondtheborderofacompanyisimportant.Furthermore,advantageouspositioningintheinnovationnetworkisthoughttoenhancetheresultofinnovationandultimatelycontributetoprofit.Objectives:TheobjectiveofthisresearchistoclarifyempiricallytheinfluenceofthenetworkstructureamongcompaniesoninnovationintheIoTfield.Method:Inthisresearch,therelationshipbetweenthenetworkstructureandtheresultofinnovationwasanalysedthroughsocialnetworkanalysis.JointapplicationpatentsrelatedtotheIoTcompanieswereextractedfromtheintellectualpropertydatabase.Results:Asaresult,thedifferenceinthenetworkstructureofacompanywasrelatedtotheresultofresearchandprofitability.Inparticular,acompanywithaplatformtypeofbusinessmodelisconsideredhighlyprofitableintheIoTbusinessfield.Conclusion:Drawingonanintellectualpropertydatabaseandemployingsocialnetworkanalysis,thisresearchquantifiesthestructureofinnovationnetworksintermsoftheresultsandoperationalefficiencyofR&D....Agent-basedmodelingapproachesprovedtobeadequateformodelingtheIoTdomain[4,19,25,26],especiallywhenconsideringthepotentialinteroperabilityissuesthatmaybederivedfromheterogeneoussetofdevices,communicationprotocols,networks,dataformats,etc.IoTsystemsare,bydefinition,distributedandintelligent,whichisequivalenttomostdefinitionsofMAS.Inthedomainofsmartcities,whichcanbeviewedaslarge-scaleIoTsystems,theuseofagent-basedmodelingandimplementationtechniquesbecomesanevengreaternecessity.......Furtherconstraintofthecurrentmodelisthatmodelingofothertypesofinteractions,beyondresourcemanagement,hasnotbeenincludedintoitexplicitly.Whilethishierarchicalstructuremightfunctioninsometypesofinteractions,forothertypesofinteractions,whichrequiregreaterdynamics,likeadaptivesmartflatswithambientintelligence[19],itmightbetoorigid.Nevertheless,suchinteractionscanbemodeledusingdifferenttypesoforganizationalforms(likethelearningorganization,forexample),whichcanfunctioninparalleltothecurrentdefinedmodel,sinceagentsonlygetadditionalrolestoenact.......Ourfutureresearchwillfocusonfurtherenrichmentoftheprovidedmodelsthroughtheintroductionoftheproposedfeasibilityzones,aswellaslarge-scalesimulationsofvariousscenariostoidentifypossibleadditionalbottlenecksandproblemswiththemodel.learningtechniquesforsmartdevicesinresidentialbuildingsasoutlinedin[19],throughpossibleinclusionofadditionalorganizationaldesigntechniques....ModelingSmartSelf-sustainableCitiesasLarge-ScaleAgentOrganizationsintheIoTEnvironmentChapterApr2018IgorTomičićBogdanOkrešaĐurićMarkusSchattenThischapterprovidesanoverviewofmodelingtechniquesforlarge-scalesystemsintheInternetofThings(IoT)environmentwithaspecialaccentonsmartself-sustainablecities.TheauthorspresentaframeworkformodelingLarge-ScaleMulti-AgentSystems(LSMASs)includingagraphicalmodelinglanguage,andatool,thataimtofacilitatedevelopmentofsuchsystemsinarecursivefashion.Smartself-sustainablecitiesinthischapteraremodeledusingthislanguagethatformsthebasisfortheSmartSelf-SustainableHumanSettlements(SSSHS)frameworkdevelopedbytheauthors.TheSSSHSframeworkconsistsofseveralsustainabilitymechanismswhichattempttofacilitatetheself-sustainabilityofahumansettlementbymanagingresourcessuchaswater,electricity,andheating,basedonthecurrentneeds,production,andstorageusingadetailedagent-basedmethodology.Byintegratingthesetwoframeworks(LSMASandSSSHS),theauthorsshowarecursiveandlayeredapproachthatisabletomodellarge-scaleresourcemanagementsystemsinahierarchicalmannerbyusingIoTtechnologies....Inanotherstudy,Schatten(2014)appliedlearningbyobservingtosmartresidentialbuildings.Theauthorequippedtheagentstolearnbyobservingtheactionsofotheragentsaswellashuman-beingsintheresidentialbuilding....InvestigatingDiversityinOpenMultiagentTeamFormationArticleJul2017PoojaAhujaTeamformationisthemostrudimentaryformofinteractionsindistributedAIandmultiagentsystemsasitallowscoherentcollectionsofagentstoworktogetherinabeneficialmannertowardsacommongoalofinterest.Basically,individualexpertiseareassembledtogetherinanadditivefashionforaccomplishingtaskstogether.Aplethoraoftherelatedstudiesfoundintheliteratureoftenmakeseveralunrealisticassumptionssuchascoordinationamongsttheagents,oragentshavingknowledgeofthewholeenvironment,oragentsand/ortasksareofthesamekind,orastaticenvironmentsetting.Againstthisbackground,wearguethattherearereal-worldcharacteristicsthatmaketeamformationmorechallenging:(1)Thereisnoorminimalpre-coordinationsincestorageandretrievalisacostlyaffair,(2)Thereisdiversityamongsttypesofagents(Apprentices,Generalists,andSpecialists)andtasks(Low,Medium,andHigh),(3)Theenvironmentisopeni.e.,agentsandtaskscanleaveandentertheenvironment,and(4)Agentsarecontinuouslylearningandimprovingtheircapabilities.Themaincontributionofthisresearchistostudyingreatdepthstheimpactsofvariouspermutationsofopenanddiverseenvironmentsonteamformationandhowagentslearntoformtheseteams.Basedonthefindingsofthesestudies,wedemonstratethatbothdiversityandopennesshaveimpactsontheteamformation.Havingevaluatedtheresultsoftheimpactsofopennessanddiversityontheenvironmentwe,tostrengthentherobustnessoftheoriginalmodel,weintroduceanenhancedversionofthismodel.Thenextcontributionofthisthesisisputtingforthanenhancedprobabilisticmodellingsolution.Tobeabletocarryoutnewinvestigationsandintroducethenewmodel,wehaverestructuredandcleanedupthesimulationsoftwareusedforbuildingtheoriginalmodel.Havingimplementedtheenhancedmodel,wethenshowhowthisnewmodelperformsbetterthantheoriginalmodel.Thefinalcontributionofthisthesiswastoshowwhythenewmodelperformedbetterthantheoriginalmodel.Advisor:Leen-KiatSoh...Scientistsin[17]havedesignedaMulti-AgentHomeAutomationsystem(MAHAS)andhaveconcentratedintheusercomfortwithoutachievingasignificationreductioninenergyconsumption.DevelopingMASisnotrestrictedtomodellingintelligentbuilding,butmustcontainalearningability[24],anddynamicallylearningnewbehaviours[29],tosuittheresidentialpreferences.Moreover,someotherstudiesaredonebasedMAStoprovetheimportanceofenergyeconomyinabuildingside....AnagentbasedfuzzycontrolforsmarthomeenergymanagementinsmartgridenvironmentArticleJan2017A.GarrabA.BouallegueR.BouallegueEnergymanagementinSmartHomeenvironmentisoneofthemaintopicsadoptedinSmartGridresearchfield.Inthispaper,wepresentaMulti-AgentSystem(MAS)foraSmartHomeintelligentcontrol.Suchasolutionwasintegratedinasmartmeterinordertoaltertheshapeoftheresidentialloadcurve.TheMASisstrongappropriatetosolvecomplexdistributedproblemsashomeautomationsystem.Ourcontributionconsistsinperforminganalgorithmforschedulingappliancestasks,anddesigningamodelforadirectloadcontrolwhichmayaccommodatecustomerpreferences.ThedirectloadcontrolisbasedonFuzzyLogicControl(FLC)usingnewfuzzypowerindicator.Inordertosuccessfullyimplementoursolution,customeracceptanceofthedirectloadcontrolisvital.Weaimtoreachacompromiseamonghabitantcomfortandelectricbillsinadditionofsatisfyingtechnologicalconstraintsofappliances.Simulationresultshaveprovedtheeffectivenessoftheproposedsolutioninenergysavings....Thesethingsincludenumerousdierent(oftenembedded)devicesincludingbutnotlimitedtovarioussensorsandactuators;mobiledevices;TVsets;carandvehiclecomputers;butalsonon-ICTapplianceslikemicrowaveovens,refrigerators,dishwashers,anddriers;electricalenergysources;andbuilding'scomponents[3].SomeofthekeyapplicationareasofIoEaresmartpowergrids[4],smarthealth[5],smarttransport[6],smartcities[7]includingsmartbuildings[8,9]andsmartlivingsolutions[10].Havingthiscomplexsocio-technicalcontextinmind,suchsystemsrepresentmajorchallengesforplanning,modeling,development,implementation,engineeringandadministration.......(2)allowformodelingofallperspectivesoforganizationalarchitecture(e.g.13See[9]foramoredetailedexplanationofthisexample.byusingviewsandzooming),(3)includeorganizationaldesign(includingchangeanddynamics)notonlydescriptivemethods,(4)takeinterorganizationalaspectsintoaccount,(5)provideabest-practicesknowledgebasegroundedinextensivetestingandbenchmarkingofallknownorganizationalmethodsavailable,and(6)becompatiblewithavailableindustrystandardsandotherinitiativesregardingMASsonthesemanticweb....ARoadmapforScalableAgentOrganizationsintheInternetofEverythingArticleJan2016JSYSTSOFTWAREMarkusSchattenJuricaŠevaIgorTomičićComputingisincreasinglyubiquitous,witheverydayitemsincludingsmartphones,cars,clothesandhouseholdappliancesgainingincreasinglysophisticatedcomputingandcommunicationcapacities.WiththedevelopmentoftheInternetofThings,itisjustamatteroftimebeforedeviceshavetocollaborateandcompetewitheachother,inordertoprovidebetterservicestomankind. Theseembeddedsoftwaresystemsareincreasinglyautonomousandconnected,andcanthusbemodeledasmultiagentsystems(MAS).Only30yearsagoitwassciencefictionthatoverabillionpeoplewillexchangebillionsofe-mailsonadailybasis.Todayascenarioofmillionsofcollaboratingagentssometimesembeddedingadgetsandappliances,sometimesinformofnetworkedandbigdataservices,mayalsosoundfuturistic.Howevergiventhecurrentrateofdevelopmentinelectronics,wewillsoonhavetomanagelargescaleMASwheremillionsofagentsexist,collaborateandcompete.Organizationtheoryprovidesthenecessarymethodologytoapproachcomplexsystemsinordertodesign,implementandstrategicallymanagethemtowardssuccess. Inthispaperastate-of-the-artonorganizationaldesigntechniquesforlarge-scaleMASwillbepresented,missingadvancementswillbeidentifiedandaroadmapforfuturedevelopmentsandapplicationscenarioswillbeprovided.ShowmoreGetaccessto30millionfiguresJoinResearchGatetoaccessover30millionfiguresand135+millionpublications–allinoneplace.Joinforfree