Decision Support and Business Intelligence Systems 9e provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making.
The 9th edition focuses on Business Intelligence (BI) and analytics for enterprise decision support in a more streamlined book.
Efraim Turban (M.B.A., Ph.D., University of California Berkeley) is a visiting scholar at the Pacific Institute for Information System Management, University of Hawaii. Prior to this he was on the staff of several universities including City University of Hong Kong, Lehigh University, Florida International University, California State University Long Beach, Eastern Illinois University, and the University of Southern California. Dr. Turban is the author of over 100 refereed papers published in leading journals such as Management Science, MIS Quarterly, and Decision Support Systems. He also the author of 20 books including Electronic Commerce: A Managerial Perspective and Information Technology for Management. He is also a consultant to major corporations world wide. Dr. Turban’s current areas of interest are Web-based decision support systems, using intelligent agents in electronic commerce systems, and collaboration issues in global electronic commerce.
Jay E. Aronson (M.S., M.S., Ph.D., Carnegie Mellon University) is a professor of Management Information Systems in the Terry College of Business at The University of Georgia. Prior to this he was on the faculty at Southern Methodist University. Dr. Aronson is the author of about 50 refereed papers that have appeared in leading journals including Management Science, Information Systems Research, and MIS Quarterly. He is the author of three books, and contributes to several professional encyclopedias. He is also a consultant to major international corporations and organizations. Dr. Aronson’s current areas of research include knowledge management, collaborative computing, and parallel computing.
Ting-Peng Liang (MA, Ph.D., University of Pennsylvania) is a National Chair Professor of Information Systems at National Sun Yat-sen University in Taiwan and a visiting professor at Chinese University of Hong Kong. Prior to this, he had been on the faculties of University of Illinois (Urbana-Champaign) and Purdue University. Dr. Liang has published more than 50 referred research papers in leading journals such as Management Science, MIS Quarterly, Decision Support Systems, and Journal of MIS. He is also the author of three books and a consultant to several major companies in the United States and Taiwan. Dr. Liang’s current areas for research and teaching include Web-based intelligent systems, electronic commerce, knowledge management, and strategic applications of information technologies.
Ramesh Sharda (MBA, Ph.D, University of Wisconsin-Madison) is Director of the Institute for Research in Information Systems (IRIS), ConocoPhillips Chair of Management of Technology, and a Regents Professor of Management Science and Information Systems in the Spears School of Business Administration at Oklahoma State University. He started and served as the Director of the MS in Telecommunications Management Program at OSU. Over 100 papers describing his research have been published in major journals including Management Science, Information Systems Research, Decision Support Systems, Journal of Management Information Systems, and many others. Dr. Sharda serves on several editorial boards including INFORMS Journal on Computing, Decision Support Systems, and Information Systems Frontiers. His current research interests are in decision support systems, collaborative applications, and technologies for managing information overload. Dr. Sharda is also a co-founder of a company that produces virtual trade fairs, iTradeFair.com.
Part I: Decision Support and Business Intelligence Chapter 1: Decision Support Systems and Business Intelligence
Part II: Computerized Decision Support Chapter 2: Decision Making, Systems, Modeling, and Support Chapter 3: Decision Support Systems Concepts, Methodologies, and Technologies: An Overview Chapter 4: Modeling and Analysis
Part III: Business Intelligence Chapter 5: Data Mining for Business Intelligence Chapter 6: Artificial Neural Networks for Data Mining Chapter 7: Text and Web Mining Chapter 8: Data Warehousing Chapter 9: Business Performance Management
Part IV: Collaboration, Communication, Group Support Systems, and Knowledge Management Chapter 10: Collaborative Computer-Supported Technologies and Group Support Systems Chapter 11: Knowledge Management
Part V: Intelligent Systems Chapter 12: Artificial Intelligence and Expert Systems Chapter 13: Advanced Intelligent Systems Chapter 14: Management Support Systems: Emerging Trends and Impacts
Online Files: Online File W2 W2.1: The MMS Running Case Online File W3 W3.1: Databases W3.2: Major Capabilities of the UIMS Online File W4 W4.1: Influence Diagrams W4.2: Linear Programming Optimization: The Blending Problem W4.3: Lindo Example: The Product-Mix Model W4.4: Lingo Example: The Product-Mix Model W4.5: Links to Excel Files of Section 4.9 Online File W5 W5.1: CreditRisk.xlsx W5.2: MovieTrain.xlsx W5.3: MovieTest.xlsx Online File W6 W6.1: The Forest CoverType Dataset Online File W9 W9.1: Portfolio of Options W9.2: Effective Performance Measurement W9.3: Influence Problems with Dashboard Displays