知识管理是21世纪的管理趋势课件

KnowledgeManagementResearch:APersonalExperienceT.P.LiangNationalSunYat-senUniversityNovember7,2006KnowledgeManagementResearch:1ImportanceofKMResearchTheimportanceofknowledgeinbusinessManagingknowledgeisadifficultandcontinuingprocessAchallengingquestion:Howcanknowledgebemanagedproperlytoimprovefirmperformance?ImportanceofKMResearchThei2知識管理是21世紀的管理趨勢知識管理是21世紀的管理趨勢3資料、資訊、知識、智慧關係資料、資訊、知識、智慧關係4內隱知識與外顯知識的比較項目內隱知識外顯知識特點難以書面化表達難以系統化持續性強，不易被人改變例如：經驗、秘訣、信念、感覺、習慣可量化或書面化較系統化固定的資訊，其運用視人而異例如：業務手冊、企劃案、作業指導規範、物理定律儲存方式人的心智資料庫、電腦、文件分享方式由於難以表達，故分享困難度視個人表達能力而定，通常只能意會，並透過師徒制來學習可透過視覺、聲音或動作來呈現、或透過書籍、影片等來傳遞內隱知識與外顯知識的比較內隱知識外顯知識特點難以書面化5不同的知識特性個人組織內隱藝術IC設計外顯(SOP)大學生產製造不同的知識特性個人組織內隱藝術IC設計外顯大學生產製造6知識、智慧資本與企業價值企業價值員工的觀念型知識員工的經驗型知識內含於組織文化的知識內含於組織文化的知識可編碼的知識人力資本顧客資本組織資本有形資產無形資產財務性資產知識分類企業潛力內隱知識外顯知識＝知識、智慧資本與企業價值企業價值員工的觀念型員工的經驗型內含7個人知識與組織知識的轉換個人知識透過分享後，轉變為組織的知識組織的知識或經驗供個人學習、吸收後，強化個人知識個人知識創意經驗人脈組織知識作業程序

Know-How

工作手冊合作方式個人知識與組織知識的轉換個人知識透過分享後，轉變為組織的知識8Nonaka的知識成長模式

內隱知識外顯知識內隱知識社會化外部化外顯知識內部化組合Nonaka的知識成長模式

內隱知識社會化外部化外顯知識內9知識管理的基本工具創造分類/儲存索引/檢索過濾/篩選導覽使用分析知識推薦知識管理的基本工具創造10ResearchinKnowledgeManagementConceptualKnowledgemanagementcyclesFrameworkofknowledgemanagementTechnicalKMSdevelopmentKnowledgerecommendationManagerialKnowledgemanagementimplementationKMandperformanceResearchinKnowledgeManageme11MajorconstructsofKMNatureofknowledgeOrganizationalenvironmentNatureoforganizationKnowledgemanagementactivitiesandprocesses(cycles)KMplatform:infrastructureandKMSNatureofusersandintermediariesEffectofKMonorganizationsMajorconstructsofKMNatureo12SampleStudiesEffectofKnowledgeDiversityonFirmPerformanceCapabilityandTaskTechnologyFitonIndividualPerformancePersonalizationandCustomer-CentricSystemsSampleStudiesEffectofKnowle13EffectofKnowledgeDiversityonFirmPerformanceEffectofKnowledgeDiversity14ResearchProblemShouldanindustryfocusonafewkeycategoriesofknowledgeorabroadcoverageofallknowledgeinordertobecompetitive?DoestheadoptionofIThaveanyrelationshipwiththevalueofknowledgeandfirmperformance?ResearchProblemShouldanindu15EcologicalmodelinOrganizationHannonandFreeman(1989)proposedtheecologicalviewoforganizationthatseekstounderstandhowsocialconditionsaffecttheratesinwhichneworganizationsandneworganizationalformsarises,theratesatwhichorganizationschangeforms,andtheratesatwhichorganizationsdieout.EcologicalmodelinOrganizati16何謂生態學？生態學（Ecology）是研究生物與其周圍環境相互關係的科學。亦即，生態學是研究在某一特定範圍內，生物與生物之間、生物與環境之間相互影響關係的科學。生態學亦可以被視為是一種巨觀的生物學生態學以不同層次的角度觀察生物，包含：個體（Organism）物種（Species）族群（Population）群落（Community）生態系統（Ecosystem）何謂生態學？生態學（Ecology）是研究生物與其周圍環境相17生態學的DICE模式基於生態學理論的歸納，生物族群在生態系統內的關係，主要可以分成分佈、互動、競爭、演化四個階段，並形成一個循環，命名為DICE模式。生態學的DICE模式基於生態學理論的歸納，生物族群在生態系統18分佈（Distribution）在研究的本質上，生態學探討、描述生物體之間及生物體與環境之間的相互關係。如何去描繪目前生態系統的狀況便是生態研究

的基礎。生物分佈狀況或空間塑模（SpatialModeling）：以數學方法對生態系統進行描述，包含對於各個生物族群數量的計數、地理區域的分佈狀況。生態研究的第一步工作。分佈（Distribution）在研究的本質上，生態學探討19分佈構面的子構面族群的強度族群強度在衡量不同族群之間的相對強度，藉以分析族群間的強弱關係並可定義它們之間的行為關係。一般而言，族群的強度可以利用族群的種類、族群內生物體的個數、分佈區域、及在食物鏈上的關係等構面來衡量，可用來描繪群落內族群的分佈輪廓。物種的多樣性衡量群落內物種的豐富程度，生態系統的一個重要觀察

指標。多樣性與穩定性關係法則（Diversity-stabilityprinciple）分佈構面的子構面族群的強度20AKnowledgeEcologyBasicspeciesinaknowledgeecologyisdifferenttypesofknowledgethatbelongtotheorganization.ThegoalofKMistobuildamechanismbywhichahealthybalanceofknowledgecanbemaintainedforachievingsuperiorperformance.AKnowledgeEcologyBasicspeci21Diversityvs.StabilityInecologicalrules,thediversity-stabilityrelationshipisamajorprincipal,whichsaysanecologyismorestableifitmaintainsacertainlevelofdiversity.Similarly,wewouldliketoexaminewhetherthesameruleholdsinaknowledgeecology,ie,organizationswithmorediversifiedknowledgearemorestableinperformance.Diversityvs.StabilityInecol22ResearchFrameworkResearchFramework23Hypotheses(1)H1:RelationshipBetweenITandKnowledgeEcologyH11:HigherITcapabilitiessupporthigherknowledgeecologyH12:HigherITcapabilitiessupporthigherknowledgediversityHypotheses(1)H1:Relationship24Hypotheses(2)RelationshipbetweenKnowledgediversityandfirmperformanceH21:HigherknowledgeintensityresultsinhigheraverageperformanceH22:HigherknowledgeintensityresultsinlowerperformancevariationsHypotheses(2)Relationshipbet25Hypotheses(3)RelationshipbetweenknowledgediversityandfirmperformanceHigherknowledgediversityresultsinloweraverageperformanceHigherknowledgediversityresultsinlowerperformancevariationsHypotheses(3)Relationshipbet26CriteriaforChoosingIndustriesFourindustrieswerechosenbasedontheirknowledgeintensityandenvironmentaluncertainty.Knowledgeintensityismeasuredastheratioofproductpricebythetangiblecosts(includingmaterialcostsanddepreciationoffixedassets).Environmentaluncertaintyismeasuredbythechangesintechnology(measuredbythenumberandimportanceofpatents)andproductlifecycle.CriteriaforChoosingIndustri27TheChosenIndustriesEnv.UncertaintyKnowledgeIntensityLowHighHighBankingICDesignLowSteelSemi-conductorFoundryTheChosenIndustriesEnv.Unce28TwelveKnowledgeTypesTwentycompanieswerechosen(fiveineachcategory)forstudy.Valuechainactivitiesareusedtodifferentiate12categoriesofknowledge,suchasrawmaterialacquisition,productmanufacturing,distribution,marketing,customerservices,strategicplanning,generalmanagement,financialmanagement,qualitymanagement,humanresourcemanagement,R&D,andISmanagement.TwelveKnowledgeTypesTwentyc29DataCollectionAgroupofexpertswasinvitedtofilloutthequestionnaireforassessingtherelativeimportanceofaparticularknowledgeinanindustryandtherelativestrengthofthetwelvetypesofknowledgeamongthecompaniesAtotalof58responseswerecollected,amongwhich17forsemiconductor,16forICDesign,15forbanks,and10forsteel.DataCollectionAgroupofexpe30DatameasurementITcapabilities:meanscoreontheITcapabilityquestionfromexpertsKnowledgeintensity:meanscoreoftheother11typesofknowledgeKnowledgediversity:usingtheentropytomeasureitFirmperformance:Earningspershareinthepastfiveyears(meansandvariance)DatameasurementITcapabilitie31RelativeImportancesK.TypeICDesignSemiconductorBankSteelMeanRankMeanRankMeanRankMeanRankR&D6.6916.7116.2716.401Acquisition6.5625.41105.7355.909Strategy6.5036.0645.6075.8011Production6.4446.3526.1326.203Marketing6.1955.4785.8035.8012Qualitymgt6.1965.8855.2096.302Distribution5.9474.71124.87116.204ITappl.5.6985.8265.5385.8010Service5.6986.1835.8046.007Generalmgt5.63105.6575.6766.106HRM5.63104.82114.53126.008Finance5.44125.4195.20106.205RelativeImportancesK.TypeIC32DataReliability

ICdesignSemiconductorfoundryBankingSteelRawmaterialacquisition0.89770.86080.72740.7401Production0.71800.76860.79210.8023Distribution0.79010.94890.74070.9265Marketing0.66000.83570.70960.8247Customerservices0.80080.74460.10270.7342Strategicplanning0.67040.63900.83880.8106Generalmgmt0.78660.86250.84150.7020Financemgmt0.50800.78690.87110.7803Qualitymgmt0.79610.58220.92490.8780Humanresourcesmgmt0.77500.73340.91200.8691R&D0.77090.84710.80130.6753ITapplications0.93920.76170.91300.8231Allconstructs0.95760.94590.95080.9627DataReliability

ICdesignSemi33ResultsfromPathAnalysisResultsfromPathAnalysis34IndustrialDifferencesHypothesesIndustryH11H12H21H22H31H32ICDesign0.675***0.326**0.630***0.565***ns-0.25*Semiconductor0.718***0.375***0.732***ns-0.375***-0.195Banking0.621***0.436**nsns-0.283*-0.272Steel0.724***0.364***0.502***-0.351*-0.429**nsIndustrialDifferences35EffectofKnowledgeBreadthWechoosedifferentnumberofknowledgetypesandseehowknowledgebreadthwouldaffectthehypothesesStepwiseanalysisthatremovedoneknowledgecategoryrankedtheleastimportantbyexpertsatatime,andrepeatedthepathanalysisfor9times.EffectofKnowledgeBreadthWe36ModelswithDifferentKnowledgeSpread

HypothesesKnowledgeH11H12H21H22H31H32Top100.740***0.414***0.619***0.502***-0.204***-0.127**Top90.719***0.387***0.617***0.505***-0.195***-0.137**Top80.743***0.422***0.603***0.499***-0.192***-0.155*Top70.700***0.365***0.602***0.514***-0.183**-0.170**Top60.711***0.368***0.635***0.511***-0.196***-0.157*Top50.699***0.338***0.636***0.510***-0.163**-0.145**Top40.697***0.339***0.608***0.477***-0.162**-0.142*Top30.705***0.322***0.535***0.433***nsnsTop20.669***0.184**0.491***0.392***ns-0.154**ModelswithDifferentKnowledg37EffectsofKnowledgeBreadthbyIndustry

Hypotheses

KnowledgecategoryICdesignSemiconductorBankingSteelTop11---0.502***Top100.594***0.535***ns0.496**Top90.599***0.543***ns0.510***Top80.587***0.573***ns0.503***Top70.612***0.571***ns0.505**Top60.612***0.600***ns0.539***Top50.620***0.601***ns0.565***Top40.550***0.604***ns0.587***Top30.541***0.659***ns0.540***Top20.412***0.627***nsnsH21:knowledgeintensityonperformanceEffectsofKnowledgeBreadthb38MajorObservationsITaffectstheintensityanddiversityoforganizationalknowledgeHigherknowledgeintensityimprovestheaveragefirmperformancebutreducesthestability(increasesvariance)Higherknowledgediversityreducesfirmperformance,butincreasesperformancestabilityMajorObservationsITaffectst39知识管理是21世纪的管理趋势40KnowledgeManagementResearch:APersonalExperienceT.P.LiangNationalSunYat-senUniversityNovember7,2006KnowledgeManagementResearch:41ImportanceofKMResearchTheimportanceofknowledgeinbusinessManagingknowledgeisadifficultandcontinuingprocessAchallengingquestion:Howcanknowledgebemanagedproperlytoimprovefirmperformance?ImportanceofKMResearchThei42知識管理是21世紀的管理趨勢知識管理是21世紀的管理趨勢43資料、資訊、知識、智慧關係資料、資訊、知識、智慧關係44內隱知識與外顯知識的比較項目內隱知識外顯知識特點難以書面化表達難以系統化持續性強，不易被人改變例如：經驗、秘訣、信念、感覺、習慣可量化或書面化較系統化固定的資訊，其運用視人而異例如：業務手冊、企劃案、作業指導規範、物理定律儲存方式人的心智資料庫、電腦、文件分享方式由於難以表達，故分享困難度視個人表達能力而定，通常只能意會，並透過師徒制來學習可透過視覺、聲音或動作來呈現、或透過書籍、影片等來傳遞內隱知識與外顯知識的比較內隱知識外顯知識特點難以書面化45不同的知識特性個人組織內隱藝術IC設計外顯(SOP)大學生產製造不同的知識特性個人組織內隱藝術IC設計外顯大學生產製造46知識、智慧資本與企業價值企業價值員工的觀念型知識員工的經驗型知識內含於組織文化的知識內含於組織文化的知識可編碼的知識人力資本顧客資本組織資本有形資產無形資產財務性資產知識分類企業潛力內隱知識外顯知識＝知識、智慧資本與企業價值企業價值員工的觀念型員工的經驗型內含47個人知識與組織知識的轉換個人知識透過分享後，轉變為組織的知識組織的知識或經驗供個人學習、吸收後，強化個人知識個人知識創意經驗人脈組織知識作業程序

Know-How

工作手冊合作方式個人知識與組織知識的轉換個人知識透過分享後，轉變為組織的知識48Nonaka的知識成長模式

內隱知識外顯知識內隱知識社會化外部化外顯知識內部化組合Nonaka的知識成長模式

內隱知識社會化外部化外顯知識內49知識管理的基本工具創造分類/儲存索引/檢索過濾/篩選導覽使用分析知識推薦知識管理的基本工具創造50ResearchinKnowledgeManagementConceptualKnowledgemanagementcyclesFrameworkofknowledgemanagementTechnicalKMSdevelopmentKnowledgerecommendationManagerialKnowledgemanagementimplementationKMandperformanceResearchinKnowledgeManageme51MajorconstructsofKMNatureofknowledgeOrganizationalenvironmentNatureoforganizationKnowledgemanagementactivitiesandprocesses(cycles)KMplatform:infrastructureandKMSNatureofusersandintermediariesEffectofKMonorganizationsMajorconstructsofKMNatureo52SampleStudiesEffectofKnowledgeDiversityonFirmPerformanceCapabilityandTaskTechnologyFitonIndividualPerformancePersonalizationandCustomer-CentricSystemsSampleStudiesEffectofKnowle53EffectofKnowledgeDiversityonFirmPerformanceEffectofKnowledgeDiversity54ResearchProblemShouldanindustryfocusonafewkeycategoriesofknowledgeorabroadcoverageofallknowledgeinordertobecompetitive?DoestheadoptionofIThaveanyrelationshipwiththevalueofknowledgeandfirmperformance?ResearchProblemShouldanindu55EcologicalmodelinOrganizationHannonandFreeman(1989)proposedtheecologicalviewoforganizationthatseekstounderstandhowsocialconditionsaffecttheratesinwhichneworganizationsandneworganizationalformsarises,theratesatwhichorganizationschangeforms,andtheratesatwhichorganizationsdieout.EcologicalmodelinOrganizati56何謂生態學？生態學（Ecology）是研究生物與其周圍環境相互關係的科學。亦即，生態學是研究在某一特定範圍內，生物與生物之間、生物與環境之間相互影響關係的科學。生態學亦可以被視為是一種巨觀的生物學生態學以不同層次的角度觀察生物，包含：個體（Organism）物種（Species）族群（Population）群落（Community）生態系統（Ecosystem）何謂生態學？生態學（Ecology）是研究生物與其周圍環境相57生態學的DICE模式基於生態學理論的歸納，生物族群在生態系統內的關係，主要可以分成分佈、互動、競爭、演化四個階段，並形成一個循環，命名為DICE模式。生態學的DICE模式基於生態學理論的歸納，生物族群在生態系統58分佈（Distribution）在研究的本質上，生態學探討、描述生物體之間及生物體與環境之間的相互關係。如何去描繪目前生態系統的狀況便是生態研究

的基礎。生物分佈狀況或空間塑模（SpatialModeling）：以數學方法對生態系統進行描述，包含對於各個生物族群數量的計數、地理區域的分佈狀況。生態研究的第一步工作。分佈（Distribution）在研究的本質上，生態學探討59分佈構面的子構面族群的強度族群強度在衡量不同族群之間的相對強度，藉以分析族群間的強弱關係並可定義它們之間的行為關係。一般而言，族群的強度可以利用族群的種類、族群內生物體的個數、分佈區域、及在食物鏈上的關係等構面來衡量，可用來描繪群落內族群的分佈輪廓。物種的多樣性衡量群落內物種的豐富程度，生態系統的一個重要觀察

指標。多樣性與穩定性關係法則（Diversity-stabilityprinciple）分佈構面的子構面族群的強度60AKnowledgeEcologyBasicspeciesinaknowledgeecologyisdifferenttypesofknowledgethatbelongtotheorganization.ThegoalofKMistobuildamechanismbywhichahealthybalanceofknowledgecanbemaintainedforachievingsuperiorperformance.AKnowledgeEcologyBasicspeci61Diversityvs.StabilityInecologicalrules,thediversity-stabilityrelationshipisamajorprincipal,whichsaysanecologyismorestableifitmaintainsacertainlevelofdiversity.Similarly,wewouldliketoexaminewhetherthesameruleholdsinaknowledgeecology,ie,organizationswithmorediversifiedknowledgearemorestableinperformance.Diversityvs.StabilityInecol62ResearchFrameworkResearchFramework63Hypotheses(1)H1:RelationshipBetweenITandKnowledgeEcologyH11:HigherITcapabilitiessupporthigherknowledgeecologyH12:HigherITcapabilitiessupporthigherknowledgediversityHypotheses(1)H1:Relationship64Hypotheses(2)RelationshipbetweenKnowledgediversityandfirmperformanceH21:HigherknowledgeintensityresultsinhigheraverageperformanceH22:HigherknowledgeintensityresultsinlowerperformancevariationsHypotheses(2)Relationshipbet65Hypotheses(3)RelationshipbetweenknowledgediversityandfirmperformanceHigherknowledgediversityresultsinloweraverageperformanceHigherknowledgediversityresultsinlowerperformancevariationsHypotheses(3)Relationshipbet66CriteriaforChoosingIndustriesFourindustrieswerechosenbasedontheirknowledgeintensityandenvironmentaluncertainty.Knowledgeintensityismeasuredastheratioofproductpricebythetangiblecosts(includingmaterialcostsanddepreciationoffixedassets).Environmentaluncertaintyismeasuredbythechangesintechnology(measuredbythenumberandimportanceofpatents)andproductlifecycle.CriteriaforChoosingIndustri67TheChosenIndustriesEnv.UncertaintyKnowledgeIntensityLowHighHighBankingICDesignLowSteelSemi-conductorFoundryTheChosenIndustriesEnv.Unce68TwelveKnowledgeTypesTwentycompanieswerechosen(fiveineachcategory)forstudy.Valuechainactivitiesareusedtodifferentiate12categoriesofknowledge,suchasrawmaterialacquisition,productmanufacturing,distribution,marketing,customerservices,strategicplanning,generalmanagement,financialmanagement,qualitymanagement,humanresourcemanagement,R&D,andISmanagement.TwelveKnowledgeTypesTwentyc69DataCollectionAgroupofexpertswasinvitedtofilloutthequestionnaireforassessingtherelativeimportanceofaparticularknowledgeinanindustryandtherelativestrengthofthetwelvetypesofknowledgeamongthecompaniesAtotalof58responseswerecollected,amongwhich17forsemiconductor,16forICDesign,15forbanks,and10forsteel.DataCollectionAgroupofexpe70DatameasurementITcapabilities:meanscoreontheITcapabilityquestionfromexpertsKnowledgeintensity:meanscoreoftheother11typesofknowledgeKnowledgediversity:usingtheentropytomeasureitFirmperformance:Earningspershareinthepastfiveyears(meansandvariance)DatameasurementITcapabilitie71RelativeImportancesK.TypeICDesignSemiconductorBankSteelMeanRankMeanRankMeanRankMeanRankR&D6.6916.7116.2716.401Acquisition6.5625.41105.7355.909Strategy6.5036.0645.6075.8011Production6.4446.3526.1326.203Marketing6.1955.4785.8035.8012Qualitymgt6.1965.8855.2096.302Distribution5.9474.71124.87116.204ITappl.5.6985.8265.5385.8010Service5.6986.1835.8046.007Generalmgt5.63105.6575.6766.106HRM5.63104.82114.53126.008Finance5.44125.4195.20106.205RelativeImportancesK.TypeIC72DataReliability

ICdesignSemiconductorfoundryBankingSteelRawmaterialacquisition0.89770.86080.72740.7401Production0.71800.76860.79210.8023Distribution0.79010.94890.74070.9265Marketing0.66000.83570.70960.8247Customerservices0.80080.74460.10270.7342Strategicplanning0.67040.63900.83880.8106Generalmgmt0.78660.86250.84150.7020Financemgmt0.50800.78690.87110.7803Qualitymgmt0.79610.58220.92490.8780Humanresourcesmgmt0.77500.73340.91200.8691R&D0.77090.84710.80130.6753ITapplications0.93920.76170.91300.8231Allconstructs0.95760.94590.95080.9627DataReliability

ICdesignSemi73ResultsfromPathAnalysisResultsfromPathAnalysis74IndustrialDifferencesHypothesesIndustryH11H12H21H22H31H32ICDesign0.675***0.326**0.630***0.565***ns-0.25*Se