Praise for the First Edition "This is the most usable decision support systems text. [i]t is far better than any other text in the field" —Computing Reviews
Computer-based systems known as decision support systems (DSS) play a vital role in helping professionals across various fields of practice understand what information is needed, when it is needed, and in what form in order to make smart and valuable business decisions. Providing a unique combination of theory, applications, and technology, Decision Support Systems for Business Intelligence, Second Edition supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS.
This new edition reflects numerous advances in the field as well as the latest related technological developments. By addressing all topics on three levels—general theory, implications for DSS design, and code development—the author presents an integrated analysis of what every DSS designer needs to know. This Second Edition features:
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Expanded coverage of data mining with new examples
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Newly added discussion of business intelligence and transnational corporations
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Discussion of the increased capabilities of databases and the significant growth of user interfaces and models
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Emphasis on analytics to encourage DSS builders to utilize sufficient modeling support in their systems
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A thoroughly updated section on data warehousing including architecture, data adjustment, and data scrubbing
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Explanations and implications of DSS differences across cultures and the challenges associated with transnational systems
Each chapter discusses various aspects of DSS that exist in real-world applications, and one main example of a DSS to facilitate car purchases is used throughout the entire book. Screenshots from JavaScript® and Adobe® ColdFusion are presented to demonstrate the use of popular software packages that carry out the discussed techniques, and a related Web site houses all of the book's figures along with demo versions of decision support packages, additional examples, and links to developments in the field.
Decision Support Systems for Business Intelligence, Second Edition is an excellent book for courses on information systems, decision support systems, and data mining at the advanced undergraduate and graduate levels. It also serves as a practical reference for professionals working in the fields of business, statistics, engineering, and computer technology.
Table of Contents:
Preface xiii
Part I Introduction to Decision Support Systems 1
1 Introduction 3
What is a DSS? 13
Uses of a Decision Support System 17
The Book 19
Suggested Readings 19
Questions 21
On the Web 22
2 Decision Making 23
Rational Decisions 25
Bounded Rationality and Muddling Through 29
Nature of Managers 31
Appropriate Decision Support 33
Electronic Memory 33
Bias in Decision Making 33
Appropriate Data Support 36
Information Processing Models 37
Tracking Experience 45
Group Decision Making 46
Intuition, Qualitative Data, and Decision Making 47
How Do We Support Intuition? 48
Virtual Experience 51
Business Intelligence and Decision Making 53
Analytics 57
Competitive Business Intelligence 58
Conclusion 60
Suggested Readings 60
Questions 65
On the Web 66
Part II DSS Components 67
3 Data Component 69
Specific View Toward Included Data 72
Characteristics of Information 73
Timeliness 73
Sufficiency 74
Level of Detail 75
Understandability 76
Freedom from Bias 77
Decision Relevance 78
Comparability 78
Reliability 80
Redundancy 80
Cost Efficiency 80
Quantifiability 81
Appropriateness of Format 82
More is Never Better! 83
Databases 85
Database Management Systems 86
Data Warehouses 87
Data Scrubbing 93
Data Adjustment 96
Architecture 97
Car Example 101
Possible Criteria 101
Data Warehouse 102
Information Uses 102
“How To” 107
Discussion 118
Suggested Readings 121
Questions 123
On the Web 124
4 Model Component 125
Models and Analytics 125
Options for Models 129
Representation 130
Time Dimension 132
Linearity of the Relationship 134
Deterministic Versus Stochastic 135
Descriptive Versus Normative 136
Causality Versus Correlation 137
Methodology Dimension 138
Problems of Models 147
Data Mining 148
Intelligent Agents 156
Model-Based Management Systems 159
Easy Access to Models 159
Understandability of Results 163
Integrating Models 166
Sensitivity of a Decision 168
Model Management Support Tools 174
Car Example 177
Brainstorming and Alternative Generation 177
Flexibility Concerns 179
Evaluating Alternatives 183
Running External Models 189
Discussion 190
Suggested Readings 190
Questions 193
On the Web 195
4S Intelligence and Decision Support Systems 197
Programming Reasoning 200
Backward-Chaining Reasoning 201
Forward-Chaining Reasoning 203
Comparison of Reasoning Processes 206
Uncertainty 206
Representing Uncertainty with Probability Theory 208
Representing Uncertainty with Certainty Factors 209
Discussion 211
Suggested Readings 211
Questions 212
On the Web 212
5 User Interface 215
Goals of the User Interface 216
Mechanisms of User Interfaces 218
User Interface Components 223
Action Language 224
Display or Presentation Language 233
Knowledge Base 251
Car Example 256
Discussion 271
Suggested Readings 271
Questions 273
On the Web 274
Part III Issues of Design 277
6 International Decision Support Systems 279
Information Availability Standards 289
Data Privacy 290
Data Availability 295
Data Flow 296
Cross-Cultural Modeling 297
Effects of Culture on Decision Support System 303
Discussion 310
Suggested Readings 310
Questions 312
On the Web 313
7 Designing a Decision Support System 315
Planning for Decision Support Systems 319
Designing a Specific DSS 320
Design Approaches 329
The Design Team 340
DSS Design and Reengineering 341
Discussion 344
Suggested Readings 344
Questions 346
On the Web 347
8 Object-Oriented Technologies and DSS Design 349
Kinds of Development Tools 350
Non-Object-Oriented Tools 350
Object-Oriented Tools 352
Benefits of Object-Oriented Technologies for DSS 365
Suggested Readings 366
Questions 367
On the Web 367
9 Implementation and Evaluation 369
Implementation Strategy 369
Ensure System Does What It is Supposed to Do the Way It is Supposed to Do It 372
Keep Solution Simple 375
Develop Satisfactory Support Base 375
Institutionalize System 380
Implementation and System Evaluation 382
Technical Appropriateness 382
Overall Usefulness 385
Implementation Success 386
Organizational Appropriateness 391
Discussion 392
Suggested Readings 392
Questions 394
On the Web 395
Part IV Extensions of Decision Support Systems 397
10 Executive Information and Dashboards 399
KPIs and Balanced Scoreboards 400
Dashboards 401
Dashboard as Driver to EIS 408
Design Requirements for Dashboard 410
Dashboard Appliances 417
Value of Dashboard and EIS 418
Discussion 423
Suggested Readings 423
Questions 425
On the Web 426
11 Group Decision Support Systems 427
Groupware 429
GDSS Definitions 432
Features of Support 434
Decision-Making Support 434
Process Support 438
GDSS and Reengineering 439
Discussion 440
Suggested Readings 440
Questions 442
On the Web 443
Index 445
