Organizational learning in the age of data:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2021]
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| Schriftenreihe: | EAI/Springer Innovations in Communication and Computing
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xv, 307 Seiten Illustrationen, Diagramme |
| ISBN: | 9783030748654 |
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Datensatz im Suchindex
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| adam_text | Contents 1 Oat with the Old - In with the New.................................................... 1.1 Organizational Decision-Making.................................................... 1.1.1 Hypercompetition and Intuition.......................................... 1.1.2 To Intuit or to Infer?............................................................ 1.1.3 Learning Organizations Versus Organizational Learning.............................................................................. 1.1.4 Time for a New Perspective................................................ 1.2 Knowledge and Knowing................................................................. 1.3 The Learning with Data Framework............................................... 1.3.1 Learning Inputs and Outcomes.......................................... 1.3.2 Learning Modalities............................................................ 1.3.3 Data Analytic Literacy........................................................ 1.3.4 A Microperspective: Analytics as Search for Answers .... 1.4 Organizational Learning Transformation........................................ References................................................................................................ 1 1 2 3 6 В 14 18 19 20 27 29 36 36 2 Democratization of Organizations........................................................ 2.1 Organizations as Human Collectives.............................................. 2.1.1 A Brief History.................................................................. 2.1.2 Commercial
Organizations................................................ 2.1.3 Non-Commercial Organizations........................................ 2.1.4 Organizational Dynamics.................................................... 2.2 Organizations as Commercial and Social Units.............................. 2.2.1 Organizational Governance................................................ 2.2.2 Operating Structure............................................................ 2.2.3 Organizational Culture........................................................ 2.2.4 The Interaction Effect........................................................ 2.3 Changing Organizational Dynamics.............................................. 2.3.1 The Duty of Care and Business Judgement Rule................ 2.3.2 Stakeholder Activism.......................................................... 37 37 38 39 42 43 45 45 46 51 54 55 56 58
Contents 2.4 Changing Organizational Environment.......................................... 2.4.1 Now That Everyone Has Voice, Is Anyone Listening? ... . 2.4.2 De-Departmentalization of Innovation.............................. 2.43 The Rise of lhe Gig Economy............................................ 2.5 Inspiration or Perspiration?............................................................ 59 59 60 64 65 Organizational Dynamics and Individual Cognition.......................... 3.1 Informational Overabundance........................................................ 3.2 Institutional Influences.................................................................... 3.2.1 Organizational Form.......................................................... 3.2.2 Group Dynamics................................................................ 3.3 !ndividual-Level Factors................................................................ 3.3.1 The Mechanics of Learning andRemembering................... 3.3.2 Cognitive, Behavioural and Emotive Factors...................... 3.3.3 Learning Modes.................................................................. 3.4 Organizational Sensemaking.......................................................... 3.4.1 Searching for What Matters................................................ 3.4.2 New Knowledge.................................................................. 69 69 71 72 74 77 78 80 82 83 84 85 4 A Brief History of Learning with Data................................................ 4.1 Axial
Ages..................................................................................... 4.2 The Changing Nature of Work........................................................ 4.2.1 LearningFoci..................................................................... 4.3 From the Age of Reason to the Age of Data.................................. 4.3.1 Statistical Inference............................................................ 4.3.2 Machine Learning.............................................................. 87 87 90 94 96 99 100 5 103 103 106 Ю7 112 115 117 118 123 126 129 130 135 136 138 140 141 І44 3 Learning with Data in the Twenty-First Century.............................. 5-1 Digital Literacy............................................................................ 5.2 From Digital Nativity to Digital Productivity................................ 5.2.1 Getting to Know Data....................................................... 5.2.2 Making Sense of Data Structures........................................ 5.2.3 Analytic Know-How......................................................... 5.3 Building Data Analytic Proficiency................................................ 5.3.1 Data Preparation................................................................. 5.3.2 Derived Effects............................;..................................... 5.3.3 Data Utilization................................................................. 5.4 Statistical Data Utilization............................................................. 5.4.1 Exploratory
Analyses.......................................................... 5.4.2 Confirmatory Analyses........................................................ 5.4.3 Predictive Analyses........................................................... 5.5 Algorithmic Data Utilization......................................................... 5.5.1 Data Mining Versus Machine Learning.............................. 5.5.2 Numeric Data Mining....................................................... 5.5.3 Text Data Mining...............................................................
Comenfs 5.6 6 7 Visual Data Learning............................................................................. 5.6.1 Design and Storytelling Considerations................................. 5.6.2 Informational Visualization..................................................... 5.6.3 Scientific Visualization ............................................................ 5.6.4 Graph Data Structures.............................................................. 150 151 156 158 159 Managing by (he Numbers........................................................................... 6.1 The Evolution of the Art and Science of Managing........................... 6.1.1 By the Numbers......................................................................... 6.1.2 To the Numbers......................................................................... 6.1.3 To Versus by the Numbers and Top-Down Versus Bottom-Up.................................................................................. 6.2 The Latency Tiers.................................................................................. 6.2.1 Latency Tiers Case Study: Customer Loyalty...................... 6.3 Analytically Enabled Management..................................................... 6.3Л Learning Modalities and Performance of Tasks................. 6.3.2 Data Analytic Outcome Utilization........................................ 6.3.3 Assessment of Data Analytic Adeptness............................... 6.4 Rights and Responsibilities................................................................. 6.4.1 Unauthorized Data
Access........................................................ 6.4.2 Improper Data Access.............................................................. 6.4.3 Publication of Dc-anonymizable Data.................................... 6.5 Learning to Learn.................................................................................... References........................................................................................................... 161 161 162 165 Decision Automation....................................................................................... 7.1 From Decision Support to Decision Automation............................... 7.Í.1 Decision Support Systems Case: Buyer Loyally Classification.............................................................................. 7.1.2 Decision Automation Case: Social Credit Scoring............. 7.1.3 Autonomous Decision Systems Case: Self-Driving Cars............................................................................................. 7.1.4 ADM Adoption Hurdles............................................................ 7.2 The Heart of ADM: Machine Learning............................................... 7.2.1 The Key Modalities................................................................... 7.3 The Soul oi ADM: Human-Computer Interaction............................. 7.3.1 The Question of Accountability............................................... 7.3.2 Human Versus Machine Mental Models............................... 7.3.3 Right Tool lor the
Task.............................................................. 7.4 Data-Enabled Creativity......................................................................... 7.4.1 Reason-Algorithm Collaboration............................................. 7.4.2 The New Frontier of Imagination.......................................... References........................................................................................................... 189 189 167 169 171 174 П5 177 179 183 184 185 185 187 187 190 192 194 197 200 202 205 209 210 213 214 216 217 221
xiv Contents 8 In Machine We Trust............................................................................. 8.1 Algocracy Anyone?......................................................................... 8.1.1 Algorithmic Bias................................................................. 8.1.2 Decision Logic Transparency............................................. 8.1.3 Accountability..................................................................... 8.1.4 Concentration of Power....................................................... 8.2 The Internet of Things..................................................................... 8.2.1 Applications and Implications............................................ 8.3 Informational Automation and Organizational Learning................ 8.3.1 Variable Associations........................................................... 8.3.2 Data Reimagined................................................................. 8.4 Algorithmic Decision-Making and Organizational Value.............. 8.4.1 Analytics·. From Edge to Augmented.................................. Reference................................................................................................. 223 223 224 226 228 230 231 233 236 238 243 250 251 254 9 255 255 257 261 263 263 265 267 269 270 223 274 225 226 277 278 279 Letting Go: Knowing W hen and How.................................................. 9-і Brain as a Computer........................................................................ 9.1.1 The Decision-Making
Brain.............................................. 9.1.2 Objective Evidence VersusSubjective Beliefs..................... 9.2 Informational Literacy.................................................................... 9.2.1 The Digital Dimension......................................................... 9.2.2 The Data Dimension.......................................................... 9.2.3 The Analytic Dimension..................................................... 9.2.4 The Communication Dimension........................................ 9.3 In Data We Trust.................................................. .......................... 9.4 Probabilistic Thinking.................................................................... 9.4.1 Understanding Probability.................................................. 9.4.2 Probabilistic Evidence........................................................ 9.5 Organizational Change.................................................................... 9.5.1 Understanding Organizational Change.............................. 9.5.2 Managing Organizational Change...................................... References................................................................................................ 10 The Future?............................................................................................ 281 10.1 Human-Machine Interweaving...................................................... 281 10.1.1 Emulation. Simulation and Virtualization........................ 282 10.1.2 From Doing to Thinking to
Being.................................... 285 10.2 Transcendent Creativity.................................................................. 287 10.3 Liberal and Digital Arts.................................................................. 289 10.3.1 Managing Organizational Know-How.............................. 291 10.3.2 The Evolution of Learning................................................ 293 10.4 Up to the Challenge?...................................................................... 295 Index................................................................................................................ 299
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| adam_txt |
Contents 1 Oat with the Old - In with the New. 1.1 Organizational Decision-Making. 1.1.1 Hypercompetition and Intuition. 1.1.2 To Intuit or to Infer?. 1.1.3 Learning Organizations Versus Organizational Learning. 1.1.4 Time for a New Perspective. 1.2 Knowledge and Knowing. 1.3 The Learning with Data Framework. 1.3.1 Learning Inputs and Outcomes. 1.3.2 Learning Modalities. 1.3.3 Data Analytic Literacy. 1.3.4 A Microperspective: Analytics as Search for Answers . 1.4 Organizational Learning Transformation. References. 1 1 2 3 6 В 14 18 19 20 27 29 36 36 2 Democratization of Organizations. 2.1 Organizations as Human Collectives. 2.1.1 A Brief History. 2.1.2 Commercial
Organizations. 2.1.3 Non-Commercial Organizations. 2.1.4 Organizational Dynamics. 2.2 Organizations as Commercial and Social Units. 2.2.1 Organizational Governance. 2.2.2 Operating Structure. 2.2.3 Organizational Culture. 2.2.4 The Interaction Effect. 2.3 Changing Organizational Dynamics. 2.3.1 The Duty of Care and Business Judgement Rule. 2.3.2 Stakeholder Activism. 37 37 38 39 42 43 45 45 46 51 54 55 56 58
Contents 2.4 Changing Organizational Environment. 2.4.1 Now That Everyone Has Voice, Is Anyone Listening? . . 2.4.2 De-Departmentalization of Innovation. 2.43 The Rise of lhe Gig Economy. 2.5 Inspiration or Perspiration?. 59 59 60 64 65 Organizational Dynamics and Individual Cognition. 3.1 Informational Overabundance. 3.2 Institutional Influences. 3.2.1 Organizational Form. 3.2.2 Group Dynamics. 3.3 !ndividual-Level Factors. 3.3.1 The Mechanics of Learning andRemembering. 3.3.2 Cognitive, Behavioural and Emotive Factors. 3.3.3 Learning Modes. 3.4 Organizational Sensemaking. 3.4.1 Searching for What Matters. 3.4.2 New Knowledge. 69 69 71 72 74 77 78 80 82 83 84 85 4 A Brief History of Learning with Data. 4.1 Axial
Ages. 4.2 The Changing Nature of Work. 4.2.1 LearningFoci. 4.3 From the Age of Reason to the Age of Data. 4.3.1 Statistical Inference. 4.3.2 Machine Learning. 87 87 90 94 96 99 100 5 103 103 106 Ю7 112 115 117 118 123 126 129 130 135 136 138 140 141 І44 3 Learning with Data in the Twenty-First Century. 5-1 Digital Literacy. 5.2 From Digital Nativity to Digital Productivity. 5.2.1 Getting to Know Data. 5.2.2 Making Sense of Data Structures. 5.2.3 Analytic Know-How. 5.3 Building Data Analytic Proficiency. 5.3.1 Data Preparation. 5.3.2 Derived Effects.;. 5.3.3 Data Utilization. 5.4 Statistical Data Utilization. 5.4.1 Exploratory
Analyses. 5.4.2 Confirmatory Analyses. 5.4.3 Predictive Analyses. 5.5 Algorithmic Data Utilization. 5.5.1 Data Mining Versus Machine Learning. 5.5.2 Numeric Data Mining. 5.5.3 Text Data Mining.
Comenfs 5.6 6 7 Visual Data Learning. 5.6.1 Design and Storytelling Considerations. 5.6.2 Informational Visualization. 5.6.3 Scientific Visualization . 5.6.4 Graph Data Structures. 150 151 156 158 159 Managing by (he Numbers. 6.1 The Evolution of the Art and Science of Managing. 6.1.1 By the Numbers. 6.1.2 To the Numbers. 6.1.3 To Versus by the Numbers and Top-Down Versus Bottom-Up. 6.2 The Latency Tiers. 6.2.1 Latency Tiers Case Study: Customer Loyalty. 6.3 Analytically Enabled Management. 6.3Л Learning Modalities and Performance of Tasks. 6.3.2 Data Analytic Outcome Utilization. 6.3.3 Assessment of Data Analytic Adeptness. 6.4 Rights and Responsibilities. 6.4.1 Unauthorized Data
Access. 6.4.2 Improper Data Access. 6.4.3 Publication of Dc-anonymizable Data. 6.5 Learning to Learn. References. 161 161 162 165 Decision Automation. 7.1 From Decision Support to Decision Automation. 7.Í.1 Decision Support Systems Case: Buyer Loyally Classification. 7.1.2 Decision Automation Case: Social Credit Scoring. 7.1.3 Autonomous Decision Systems Case: Self-Driving Cars. 7.1.4 ADM Adoption Hurdles. 7.2 The Heart of ADM: Machine Learning. 7.2.1 The Key Modalities. 7.3 The Soul oi'ADM: Human-Computer Interaction. 7.3.1 The Question of Accountability. 7.3.2 Human Versus Machine Mental Models. 7.3.3 Right Tool lor the
Task. 7.4 Data-Enabled Creativity. 7.4.1 Reason-Algorithm Collaboration. 7.4.2 The New Frontier of Imagination. References. 189 189 167 169 171 174 П5 177 179 183 184 185 185 187 187 190 192 194 197 200 202 205 209 210 213 214 216 217 221
xiv Contents 8 In Machine We Trust. 8.1 Algocracy Anyone?. 8.1.1 Algorithmic Bias. 8.1.2 Decision Logic Transparency. 8.1.3 Accountability. 8.1.4 Concentration of Power. 8.2 The Internet of Things. 8.2.1 Applications and Implications. 8.3 Informational Automation and Organizational Learning. 8.3.1 Variable Associations. 8.3.2 Data Reimagined. 8.4 Algorithmic Decision-Making and Organizational Value. 8.4.1 Analytics·. From Edge to Augmented. Reference. 223 223 224 226 228 230 231 233 236 238 243 250 251 254 9 255 255 257 261 263 263 265 267 269 270 223 274 225 226 277 278 279 Letting Go: Knowing W'hen and How. 9-і Brain as a Computer. 9.1.1 The Decision-Making
Brain. 9.1.2 Objective Evidence VersusSubjective Beliefs. 9.2 Informational Literacy. 9.2.1 The Digital Dimension. 9.2.2 The Data Dimension. 9.2.3 The Analytic Dimension. 9.2.4 The Communication Dimension. 9.3 In Data We Trust. . 9.4 Probabilistic Thinking. 9.4.1 Understanding Probability. 9.4.2 Probabilistic Evidence. 9.5 Organizational Change. 9.5.1 Understanding Organizational Change. 9.5.2 Managing Organizational Change. References. 10 The Future?. 281 10.1 Human-Machine Interweaving. 281 10.1.1 Emulation. Simulation and Virtualization. 282 10.1.2 From Doing to Thinking to
Being. 285 10.2 Transcendent Creativity. 287 10.3 Liberal and Digital Arts. 289 10.3.1 Managing Organizational Know-How. 291 10.3.2 The Evolution of Learning. 293 10.4 Up to the Challenge?. 295 Index. 299 |
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| spelling | Banasiewicz, Andrew D. Verfasser (DE-588)1184815836 aut Organizational learning in the age of data Andrew Banasiewicz Cham Springer [2021] xv, 307 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier EAI/Springer Innovations in Communication and Computing Erscheint auch als Online-Ausgabe 978-3-030-74866-1 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032783137&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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