Decision support and business intelligence systems:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Boston, Mass. [u.a.]
Pearson
2011
|
| Ausgabe: | 9. ed., Internat. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXII, 696 S. graph. Darst. |
| ISBN: | 0132453231 9780132453233 |
Internformat
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Datensatz im Suchindex
| _version_ | 1804142934710288384 |
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| adam_text | Titel: Decision support and business intelligence systems
Autor: Turban, Efraim
Jahr: 2011
BRIEF CONTENTS
PART I Decision Support and Business Intelligence 1
Chapter 1 Decision Support Systems and Business Intelligence 2
PART II Computerized Decision Support 37
Chapter 2 Decision Making, Systems, Modeling, and Support 38
Chapter 3 Decision Support Systems Concepts, Methodologies,
and Technologies: An Overview 70
Chapter 4 Modeling and Analysis 135
Part III Business Intelligence 189
Chapter 5 Data Mining for Business Intelligence 190
Chapter 6 Artificial Neural Networks for Data Mining 241
Chapter 7 Text and Web Mining 286
Chapter 8 Data Warehousing 326
Chapter 9 Business Performance Management 374
PART IV Collaboration, Communication, Group Support
Systems, and Knowledge Management 419
Chapter 10 Collaborative Computer-Supported Technologies
and Group Support Systems 420
Chapter 11 Knowledge Management 471
PARTV Intelligent Systems 529
Chapter 12 Artificial Intelligence and Expert Systems 530
Chapter 13 Advanced Intelligent Systems 580
PART VI Implementing Decision Support Systems
and Business Intelligence 633
Chapter 14 Management Support Systems: Emerging Trends
and Impacts 634
CONTENTS
Preface xvi
Part I Decision Support and Business Intelligence 1
Chapter 1 Decision Support Systems and Business Intelligence 2
1.1 Opening Vignette: Norfolk Southern Uses Business Intelligence
for Decision Support to Reach Success 3
1.2 Changing Business Environments and Computerized Decision
Support 5
1.3 Managerial Decision Making 7
1.4 Computerized Support for Decision Making 9
1.5 An Early Framework for Computerized Decision Support 11
? APPLICATION CASE 1.1 Giant Food Stores Prices the Entire Store 14
1.6 The Concept of Decision Support Systems (DSS) 16
? APPLICATION CASE 1.2 A DSS for Managing Inventory at
GlaxoSmithKline 16
1.7 A Framework for Business Intelligence (Bl) 18
? APPLICATION CASE 1.3 Location, Location, Location 21
? APPLICATION CASE 1.4 Alltel Wireless: Delivering the Right Message, to
the Right Customers, at the Right Time 23
1.8 A Work System View of Decision Support 25
1.9 The Major Tools and Techniques of Managerial Decision
Support 26
? APPLICATION CASE 1.5 United Sugars Corporation Optimizes Production,
Distribution, and Inventory Capacity with Different Decision Support Tools 27
1.10 Plan of the Book 28
? APPLICATION CASE 1.6 The Next Net 30
1.11 Resources, Links, and the Teradata University Network
Connection 30
Chapter Highlights 31 ? Key Terms 32
Questions for Discussion 32 ? Exercises 33
? END OF CHAPTER APPUCATION CASE Vodafone Uses Business Intelligence
to Improve Customer Growth and Retention Plans 34
References 35
Part II Computerized Decision Support 37
Chapter 2 Decision Making, Systems, Modeling, and Support 38
2.1 Opening Vignette: Decision Modeling at HP Using
Spreadsheets 39
2.2 Decision Making: Introduction and Definitions 41
2.3 Models 44
2.4 Phases of the Decision-Making Process 45
2.5 Decision Making: The Intelligence Phase 48
? APPLICATION CASE 2.1 Making Elevators Go Faster! 48
Contents vii
2.6 Decision Making: The Design Phase 50
¦ TECHNOLOGY INSIGHTS 2.1 The Difference Between a Criterion and a
Constraint 51
¦ TECHNOLOGY INSIGHTS 2.2 Are Decision Makers Really Rational? 52
2.7 Decision Making: The Choice Phase 58
2.8 Decision Making: The Implementation Phase 58
2.9 How Decisions Are Supported 59
¦ TECHNOLOGY INSIGHTS 2.3 Decision Making in the Digital Age 61
? APPLICATION CASE 2.2 Advanced Technology for Museums: RFID Makes
Art Come Alive 63
2.10 Resources, Links, and the Teradata University Network
Connection 64
Chapter Highlights 65 ? Key Terms 65
Questions for Discussion 65 ? Exercises 66
? End of Chapter Application Case Decisions and Risk Management (!) That
Led to the Subprime Mortgage Crisis 67
References 68
Chapter 3 Decision Support Systems Concepts, Methodologies,
and Technologies: An Overview 70
3.1 Opening Vignette: Decision Support System Cures for Health
Care 71
3.2 Decision Support System Configurations 74
3.3 Decision Support System Description 75
? APPLICATION CASE 3.1 A Spreadsheet-Based DSS Enables Ammunition
Requirements Planning for the Canadian Army 76
3.4 Decision Support System Characteristics and Capabilities 77
3.5 Decision Support System Classifications 79
? APPLICATION CASE 3.2 Expertise Transfer System to Train Future Army
Personnel 81
3.6 Components of Decision Support Systems 85
3.7 The Data Management Subsystem 89
? APPLICATION CASE 3.3 Pacific Sunwear Tracks Business Performance 90
¦ TECHNOLOGY INSIGHTS 3.1 The Capabilities of a Relational DBMS in a
DSS 92
¦ TECHNOLOGY INSIGHTS 3.2 The 10 Essential Ingredients of Data
(Information) Quality Management 94
3.8 The Model Management Subsystem 96
? APPLICATION CASE 3.4 SNAP DSS Helps OneNet Make Telecommunications
Rate Decisions 98
¦ TECHNOLOGY INSIGHTS 3.3 Major Functions of an MBMS 100
3.9 The User Interface (Dialog) Subsystem 100
¦ TECHNOLOGY INSIGHTS 3.4 Next Generation of Input Devices 104
3.10 The Knowledge-Based Management Subsystem 105
? APPLICATION CASE 3.5 IAP Systems Intelligent DSS Determines the
Success of Overseas Assignments and Learns from the Experience 106
3.11 The Decision Support System User 106
3.12 Decision Support System Hardware 107
3.13 A DSS Modeling Language: Planners Lab 108
viii Contents
? APPLICATION CASE 3.6 Nonprofits Use Planners Lab as a Decision-Making
Tool 109
3.14 Resources, Links, and the Teradata University Network
Connection 125
Chapter Highlights 126 ? Key Terms 127
Questions for Discussion 128 ? Exercises 128
? END OF CHAPTER APPLICATION CASE Spreadsheet Model-Based
Decision Support for Inventory Target Setting at Procter Gamble 132
References 133
Chapter 4 Modeling and Analysis 135
4.1 Opening Vignette: Model-Based Auctions Serve More
Lunches in Chile 136
4.2 Management Support Systems Modeling 139
? APPLICATION CASE 4.1 Lockheed Martin Space Systems Company
Optimizes Infrastructure Project-Portfolio Selection 140
? APPLICATION CASE 4.2 Forecasting/Predictive Analytics Proves to be a
Good Gamble for Harrah s Cherokee Casino and Hotel 142
4.3 Structure of Mathematical Models for Decision Support 145
4.4 Certainty, Uncertainty, and Risk 147
4.5 Management Support Systems Modeling with Spreadsheets 149
? APPLICATION CASE 4.3 Showcase Scheduling at Fred Astaire East Side
Dance Studio 150
4.6 Mathematical Programming Optimization 152
? APPLICATION CASE 4.4 Spreadsheet Model Helps Assign Medical
Residents 152
¦ TECHNOLOGY INSIGHTS 4.1 Linear Programming 154
4.7 Multiple Goals, Sensitivity Analysis, What-lf Analysis, and
Goal Seeking 157
4.8 Decision Analysis with Decision Tables and Decision Trees 161
? APPLICATION CASE 4.5 Decision Analysis Assists Doctor in Weighing
Treatment Options for Cancer Suspects and Patients 164
4.9 Multicriteria Decision Making with Pairwise Comparisons 165
? APPLICATION CASE 4.6 Multicriteria Decision Support for European
Radiation Emergency Support System 166
4.10 Problem-Solving Search Methods 168
? APPUCATION CASE 4.7 Heuristic-Based DSS Moves Milk in New Zealand 170
4.11 Simulation 171
? APPLICATION CASE 4.8 Improving Maintenance Decision Making in the
Finnish Air Force Through Simulation 171
? APPLICATION CASE 4.9 Simulation Applications 176
4.12 Visual Interactive Simulation 177
4.13 Quantitative Software Packages and Model Base
Management 179
4.14 Resources, Links, and the Teradata University Network
Connection 180
Chapter Highlights 181 ? Key Terms 182
Questions for Discussion 182 ? Exercises 183
Contents ix
? END OF CHAPTER APPLICATION CASE HP Applies Management Science
Modeling to Optimize Its Supply Chain and Wins a Major Award 185
References 187
Part III Business Intelligence 189
Chapter 5 Data Mining for Business Intelligence 190
5.1 Opening Vignette: Data Mining Goes to Hollywood! 191
5.2 Data Mining Concepts and Applications 194
? APPLICATION CASE 5.1 Business Analytics and Data Mining Help 1-800-
Flowers Excel in Business 195
¦ TECHNOLOGY INSIGHTS 5.1 Data in Data Mining 197
? APPLICATION CASE 5.2 Law Enforcement Organizations Use Data Mining to
Better Fight Crime 199
? APPLICATION CASE 5.3 Motor Vehicle Accidents and Driver
Distractions 203
5.3 Data Mining Applications 204
? APPLICATION CASE 5.4 A Mine on Terrorist Funding 206
5.4 Data Mining Process 207
? APPLICATION CASE 5.5 Data Mining in Cancer Research 213
5.5 Data Mining Methods 216
? APPLICATION CASE 5.6 Highmark, Inc., Employs Data Mining to Manage
Insurance Costs 222
5.6 Data Mining Software Tools 228
? APPLICATION CASE 5.7 Predicting Customer Churn?A Competition of
Different Tools 231
5.7 Data Mining Myths and Blunders 233
Chapter Highlights 234 ? Key Terms 235
Questions for Discussion 235 ? Exercises 236
? END OF CHAPTER APPUCATION CASE Data Mining Helps Develop Custom-
Tailored Product Portfolios for Telecommunication Companies 238
References 239
Chapter 6 Artificial Neural Networks for Data Mining 241
6.1 Opening Vignette: Predicting Gambling Referenda with Neural
Networks 242
6.2 Basic Concepts of Neural Networks 245
¦ TECHNOLOGY INSIGHTS 6.1 The Relationship Between Biological and
Artificial Neural Networks 247
? APPLICATION CASE 6.1 Neural Networks Help Reduce Telecommunications
Fraud 248
6.3 Learning in Artificial Neural Networks 253
? APPUCATION CASE 6.2 Neural Networks Help Deliver Microsoft s Mail to
the Intended Audience 254
6.4 Developing Neural Network-Based Systems 259
¦ TECHNOLOGY INSIGHTS 6.2 ANN Software 263
6.5 Illuminating the Black Box of ANN with Sensitivity Analysis 264
? APPUCATION CASE 6.3 Sensitivity Analysis Reveals Injury Severity Factors
in Traffic Accidents 266
6.6 A Sample Neural Network Project 267
Contents
6.7 Other Popular Neural Network Paradigms 270
6.8 Applications of Artificial Neural Networks 274
? APPLICATION CASE 6.4 Neural Networks for Breast Cancer Diagnosis 276
Chapter Highlights 277 ? Key Terms 277
Questions for Discussion 278 ? Exercises 278
? END OF CHAPTER APPLICATION CASE Coors Improves Beer Flavors with
Neural Networks 282
References 284
Chapter 7 Text and Web Mining 286
7.1 Opening Vignette: Mining Text for Security
and Counterterrorism 287
7.2 Text Mining Concepts and Definitions 289
¦ TECHNOLOGY INSIGHTS 7.1 Text Mining Lingo 290
? APPLICATION CASE 7.1 Text Mining for Patent Analysis 291
7.3 Natural Language Processing 292
? APPLICATION CASE 7.2 Text Mining Helps Merck to Better Understand and
Serve Its Customers 294
7.4 Text Mining Applications 296
? APPLICATION CASE 7.3 Mining for Lies 297
? APPLICATION CASE 7.4 Flying Through Text 301
7.5 Text Mining Process 302
? APPLICATION CASE 7.5 Research Literature Survey with Text Mining 309
7.6 Text Mining Tools 312
7.7 Web Mining Overview 312
7.8 Web Content Mining and Web Structure Mining 314
? APPLICATION CASE 7.6 Caught in a Web 315
7.9 Web Usage Mining 316
7.10 Web Mining Success Stories 318
? APPLICATION CASE 7.7 Web Site Optimization Ecosystem 319
Chapter Highlights 321 ? Key Terms 322
Questions for Discussion 322 ? Exercises 323
? END OF CHAPTER APPUCATION CASE HP and Text Mining 323
References 325
Chapter 8 Data Warehousing 326
8.1 Opening Vignette: DirecTV Thrives with Active Data
Warehousing 327
8.2 Data Warehousing Definitions and Concepts 328
? APPUCATION CASE 8.1 Enterprise Data Warehouse Delivers Cost Savings
and Process Efficiencies 331
83 Data Warehousing Process Overview 333
? APPUCATION CASE 8.2 Data Warehousing Supports First American
Corporation s Corporate Strategy 333
8.4 Data Warehousing Architectures 335
8.5 Data Integration and the Extraction, Transformation, and Load
(ETL) Processes 342
? APPUCATION CASE 8.3 BP Lubricants Achieves BIGS Success 342
Contents
8.6 Data Warehouse Development 346
? APPLICATION CASE 8.4 Things Go Better with Coke s Data Warehouse 347
? APPLICATION CASE 8.5 HP Consolidates Hundreds of Data Marts into a
Single EDW 350
¦ TECHNOLOGY INSIGHTS 8.1 Hosted Data Warehouses 352
? APPLICATION CASE 8.6 A Large Insurance Company Integrates Its
Enterprise Data with AXIS 357
8.7 Real-Time Data Warehousing 359
? APPLICATION CASE 8.7 Egg Pic Fries the Competition in Near-Real-Time 360
¦ TECHNOLOGY INSIGHTS 8.2 The Real-Time Realities of Active Data
Warehousing 363
8.8 Data Warehouse Administration and Security Issues 364
¦ TECHNOLOGY INSIGHTS 8.3 Ambeo Delivers Proven Data Access Auditing
Solution 365
8.9 Resources, Links, and the Teradata University Network
Connection 365
Chapter Highlights 367 ? Key Terms 367
Questions for Discussion 367 ? Exercises 367
? END OF CHAPTER APPLICATION CASE Continental Airlines Flies High
with Its Real-Time Data Warehouse 369
References 371
Chapter 9 Business Performance Management 374
9.1 Opening Vignette: Double Down at Harrah s 375
9.2 Business Performance Management (BPM) Overview 377
9.3 Strategize: Where Do We Want to Go? 379
9.4 Plan: How Do We Get There? 382
9.5 Monitor: How Are We Doing? 383
? APPLICATION CASE 9.1 Discovery-Driven Planning: The Coffee Wars 385
9.6 Act and Adjust: What Do We Need to Do Differently? 387
9.7 Performance Measurement 390
? APPLICATION CASE 9.2 Expedia.com s Customer Satisfaction Scorecard 393
9.8 BPM Methodologies 395
¦ TECHNOLOGY INSIGHTS 9.1 BSC Meets Six Sigma 402
9.9 BPM Technologies and Applications 404
9.10 Performance Dashboards and Scorecards 408
Chapter Highlights 411 ? Key Terms 412
Questions for Discussion 412 ? Exercises 413
? END OF CHAPTER APPUCATION CASE Tracking Citywide Performance 414
References 416
Part IV Collaboration, Communication, Group Support
Systems, and Knowledge Management 419
Chapter 10 Collaborative Computer-Supported Technologies and Group
Support Systems 420
10.1 Opening Vignette: Procter Gamble Drives Ideation with
Group Support Systems 421
10.2 Making Decisions in Groups: Characteristics, Process, Benefits,
and Dysfunctions 423
xii Contents
¦ TECHNOLOGY INSIGHTS 10.1 Benefits of Working in Groups and
Dysfunctions of the Group Process 425
10.3 Supporting Groupwork with Computerized Systems 426
? APPLICATION CASE 10.1 GSS Boosts Innovation in Crime Prevention 427
¦ TECHNOLOGY INSIGHTS 10.2 Unsupported Aspects of Communication 430
10.4 Tools for Indirect Support of Decision Making 431
? APPLICATION CASE 10.2 Catalyst Maintains an Edge with WebEx 433
10.5 Integrated Groupware Suites 436
? APPLICATION CASE 10.3 Wimba Extends Classrooms at CSU, Chico 440
10.6 Direct Computerized Support for Decision Making:
From Group Decision Support Systems to Group
Support Systems 441
¦ TECHNOLOGY INSIGHTS 10.3 Modeling in Group Decision Making: EC11 for
Groups 443
? APPLICATION CASE 10.4 Collaborative Problem Solving at KUKA 444
? APPLICATION CASE 10.5 Eastman Chemical Boosts Creative Processes and
Saves $500,000 with Groupware 445
10.7 Products and Tools for GDSS/GSS and Successful
Implementation 448
¦ TECHNOLOGY INSIGHTS 10.4 The Standard GSS Process 449
10.8 Emerging Collaboration Tools: From VoIP to Wikis 453
¦ TECHNOLOGY INSIGHTS 10.5 VoIP System Helps Increase Productivity and
Enhance Learning Experiences at the State University of New York 453
10.9 Collaborative Efforts in Design, Planning, and Project
Management 456
? APPLICATION CASE 10.6 CPFR Initiatives at Ace Hardware and Sears 461
10.10 Creativity, Idea Generation, and Computerized Support 462
Chapter Highlights 465 ? Key Terms 466
Questions for Discussion 466 ? Exercises 467
? END OF CHAPTER APPLICATION CASE Dresdner Kleinwort Wasserstein
Uses Wiki for Collaboration 468
References 469
Chapter 11 Knowledge Management 471
11.1 Opening Vignette: MITRE Knows What It Knows Through
Knowledge Management 472
11.2 Introduction to Knowledge Management 474
? APPLICATION CASE 11.1 KM at Consultancy Firms 477
? APPLICATION CASE 11.2 Cingular Calls on Knowledge 480
11.3 Organizational Learning and Transformation 481
? APPLICATION CASE 11.3 NASA Blends KM with Risk Management 483
11.4 Knowledge Management Activities 485
11.5 Approaches to Knowledge Management 486
? APPUCATION CASE 11.4 Texaco Drills for Knowledge 488
¦ TECHNOLOGY INSIGHTS 11.1 KM: A Demand-Led Business Activity 490
11.6 Information Technology (IT) In Knowledge Management 493
11.7 Knowledge Management Systems Implementation 498
? APPUCATION CASE 11.5 Knowledge Management: You Can Bank on It at
Commerce Bank 501
Contents xiii
11.8 Roles of People in Knowledge Management 504
? APPLICATION CASE 11.6 Online Knowledge Sharing at Xerox 506
¦ TECHNOLOGY INSIGHTS 11.2 Seven Principles for Designing Successful
COP 508
11.9 Ensuring the Success of Knowledge Management
Efforts 509
¦ TECHNOLOGY INSIGHTS 11.3 MAKE: Most Admired Knowledge
Enterprises 510
? APPLICATION CASE 11.7 The British Broadcasting Corporation Knowledge
Management Success 511
? APPLICATION CASE 11.8 How the U.S. Department of Commerce Uses an
Expert Location System 512
¦ TECHNOLOGY INSIGHTS 11.4 Six Keys to KM Success for Customer
Service 513
¦ TECHNOLOGY INSIGHTS 11.5 KM Myths 516
? APPLICATION CASE 11.9 When KMS Fail, They Can Fail in a Big Way 517
¦ TECHNOLOGY INSIGHTS 11.6 Knowledge Management Traps 518
Chapter Highlights 520 ? Key Terms 521
Questions for Discussion 521 ? Exercises 522
? END OF CHAPTER APPLICATION CASE Siemens Keeps Knowledge
Management Blooming with ShareNet 523
References 524
Part V Intelligent Systems 529
Chapter 12 Artificial Intelligence and Expert Systems 530
12.1 Opening Vignette: A Web-Based Expert System for Wine
Selection 531
12.2 Concepts and Definitions of Artificial Intelligence 532
? APPLICATION CASE 12.1 Intelligent System Beats the Chess Grand
Master 533
12.3 The Artificial Intelligence Field 535
¦ TECHNOLOGY INSIGHTS 12.1 Artificial Intelligence Versus Natural
Intelligence 537
? APPLICATION CASE 12.2 Automatic Speech Recognition in Call Centers 539
? APPLICATION CASE 12.3 Agents for Travel Planning at USC 541
12.4 Basic Concepts of Expert Systems 542
¦ TECHNOLOGY INSIGHTS 12.2 Sample Session of a Rule-Based ES 545
? APPLICATION CASE 12.4 Expert System Helps in Identifying Sport
Talents 546
12.5 Applications of Expert Systems 546
? APPLICATION CASE 12.5 Sample Applications of ES 547
12.6 Structure of Expert Systems 550
? APPLICATION CASE 12.6 A Fashion Mix-and-Match Expert System 552
12.7 Knowledge Engineering 553
¦ TECHNOLOGY INSIGHTS 12.3 Difficulties in Knowledge Acquisition 555
12.8 Problem Areas Suitable for Expert Systems 564
? APPUCATION CASE 12.7 Monitoring Water Quality with Sensor-Driven
Expert Systems 565
1Z9 Development of Expert Systems 566
xiv Contents
12.10 Benefits, Limitations, and Critical Success Factors of Expert
Systems 569
12.11 Expert Systems on the Web 572
? APPLICATION CASE 12.8 Banner with Brains: Web-Based ES for Restaurant
Selection 573
? APPLICATION CASE 12.9 Rule-Based System for Online Consultation 573
¦ TECHNOLOGY INSIGHTS 12.4 Automated and Real-Time Decision
Systems 574
Chapter Highlights 575 ? Key Terms 576
Questions for Discussion 576 ? Exercises 577
? END OF CHAPTER APPLICATION CASE Business Rule Automation at Farm
Bureau Financial Services 577
References 578
Chapter 13 Advanced Intelligent Systems 580
13.1 Opening Vignette: Machine Learning Helps Develop an
Automated Reading Tutoring Tool 581
13.2 Machine-Learning Techniques 582
13.3 Case-Based Reasoning 585
? APPLICATION CASE 13.1 A CBR System for Optimal Selection and
Sequencing of Songs 590
13.4 Genetic Algorithms and Developing GA Applications 593
? APPLICATION CASE 13.2 Genetic Algorithms Schedule Assembly Lines at
Volvo Trucks North America 600
¦ TECHNOLOGY INSIGHTS 13.1 Genetic Algorithm Software 600
13.5 Fuzzy Logic and Fuzzy Inference Systems 601
13.6 Support Vector Machines 606
13.7 Intelligent Agents 613
¦ TECHNOLOGY INSIGHTS 13.2 Intelligent Agents, Objects, and ES 617
13.8 Developing Integrated Advanced Systems 622
? APPLICATION CASE 13.3 International Stock Selection 623
? APPLICATION CASE 13.4 Hybrid ES and Fuzzy Logic System Dispatches
Trains 625
Chapter Highlights 625 ? Key Terms 626
Questions for Discussion 627 ? £xerc/ses 627
? END OF CHAPTER APPLICATION CASE Improving Urban Infrastructure
Management with Case-Based Reasoning 628
References 629
Part VI Implementing Decision Support Systems and
Business Intelligence 633
Chapter 14 Management Support Systems: Emerging Trends and
Impacts 634
14.1 Opening Vignette: Coca-Cola s RFID-Based Dispenser Serves a
New Type of Business Intelligence 635
14.2 RFID and New Bl Application Opportunities 636
14.3 Reality Mining 641
14.4 Virtual Worlds 644
¦ TECHNOLOGY INSIGHTS 14.1 Second Life as a Decision Support Tool 645
Contents XV
14.5 The Web 2.0 Revolution 649
14.6 Virtual Communities 650
14.7 Online Social Networking: Basics and Examples 653
? APPLICATION CASE 14.1 Using Intelligent Software and Social
Networking to Improve Recruiting Processes 656
14.8 Cloud Computing and Bl 658
14.9 The Impacts of Management Support Systems: An
Overview 659
14.10 Management Support Systems Impacts on Organizations 661
14.11 Management Support Systems Impacts on Individuals 664
14.12 Automating Decision Making and the Manager s Job 665
14.13 Issues of Legality, Privacy, and Ethics 667
14.14 Resources, Links, and the Teradata University Network
Connection 671
Chapter Highlights 671 ? Key Terms 672
Questions for Discussion 672 ? Exercises 672
? END OF CHAPTER APPLICATION CASE Continental Continues to Score
with Data Warehouse 674
References 675
Glossary 678
Index 691
Online Chapters
Chapter 2 Online Files
W2.1 The MMS Running Case
Chapter 3 Online Files
W3.1 Databases
W3.2 Major Capabilities of the UIMS
Chapter 4 Online Files
W4.1 Influence Diagrams
W4.2 Linear Programming Optimization: The Blending Problem
W4.3 Undo Example: The Product-mix Model
W4.4 Lingo Example: The Product-mix Model
W4.5 Links to Excel Files of Section 4.9
Chapter 5 Online Files
W5.1 Credit Risk
W5.2 Movie Train
W5.3 Movie Test
Chapter 6 Online Files
W6.1 The Forest CoverType Dataset
Chapter 9 Online Files
W9.1 Portfolio of Options
W9.2 Effective Performance Measurement
W9.3 Influence Problems with Dashboard Displays
|
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| ctrlnum | (OCoLC)604824048 (DE-599)HBZHT016283526 |
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| discipline | Informatik Wirtschaftswissenschaften |
| edition | 9. ed., Internat. ed. |
| format | Book |
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| id | DE-604.BV036448752 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:39:39Z |
| institution | BVB |
| isbn | 0132453231 9780132453233 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020320945 |
| oclc_num | 604824048 |
| open_access_boolean | |
| owner | DE-634 DE-20 DE-91G DE-BY-TUM DE-11 DE-355 DE-BY-UBR DE-2070s |
| owner_facet | DE-634 DE-20 DE-91G DE-BY-TUM DE-11 DE-355 DE-BY-UBR DE-2070s |
| physical | XXII, 696 S. graph. Darst. |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Pearson |
| record_format | marc |
| spelling | Decision support and business intelligence systems Efraim Turban ... 9. ed., Internat. ed. Boston, Mass. [u.a.] Pearson 2011 XXII, 696 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Managementinformationssystem (DE-588)4074518-1 gnd rswk-swf Entscheidungsunterstützung (DE-588)4202171-6 gnd rswk-swf Expertensystem (DE-588)4113491-6 gnd rswk-swf Unternehmen (DE-588)4061963-1 gnd rswk-swf Entscheidungsunterstützungssystem (DE-588)4191815-0 gnd rswk-swf Expertensystem (DE-588)4113491-6 s Entscheidungsunterstützung (DE-588)4202171-6 s Managementinformationssystem (DE-588)4074518-1 s Unternehmen (DE-588)4061963-1 s DE-604 Entscheidungsunterstützungssystem (DE-588)4191815-0 s 1\p DE-604 Turban, Efraim 1930- Sonstige (DE-588)13563024X oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020320945&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Decision support and business intelligence systems Managementinformationssystem (DE-588)4074518-1 gnd Entscheidungsunterstützung (DE-588)4202171-6 gnd Expertensystem (DE-588)4113491-6 gnd Unternehmen (DE-588)4061963-1 gnd Entscheidungsunterstützungssystem (DE-588)4191815-0 gnd |
| subject_GND | (DE-588)4074518-1 (DE-588)4202171-6 (DE-588)4113491-6 (DE-588)4061963-1 (DE-588)4191815-0 |
| title | Decision support and business intelligence systems |
| title_auth | Decision support and business intelligence systems |
| title_exact_search | Decision support and business intelligence systems |
| title_full | Decision support and business intelligence systems Efraim Turban ... |
| title_fullStr | Decision support and business intelligence systems Efraim Turban ... |
| title_full_unstemmed | Decision support and business intelligence systems Efraim Turban ... |
| title_short | Decision support and business intelligence systems |
| title_sort | decision support and business intelligence systems |
| topic | Managementinformationssystem (DE-588)4074518-1 gnd Entscheidungsunterstützung (DE-588)4202171-6 gnd Expertensystem (DE-588)4113491-6 gnd Unternehmen (DE-588)4061963-1 gnd Entscheidungsunterstützungssystem (DE-588)4191815-0 gnd |
| topic_facet | Managementinformationssystem Entscheidungsunterstützung Expertensystem Unternehmen Entscheidungsunterstützungssystem |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020320945&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT turbanefraim decisionsupportandbusinessintelligencesystems |