Business Analytics Principles, Concepts, and Applications with SAS

Marc J. Schniederjans is the C. Wheaton Battey Distinguished Professor of Business in the College of Business Administration at the University of Nebraska-Lincoln and has served on the faculty of three other universities. Professor Schniederjans is a Fellow of the Decision Sciences Institute (DSI) and in 2014-2015 will serve as DSI’s president. His prior experience includes owning and operating his own truck leasing business. He is currently a member of the Institute of Supply Management (ISM), the Production and Operations Management Society (POMS), and Decision Sciences Institute (DSI). Professor Schniederjans has taught extensively in operations management and management science. He has won numerous teaching awards and is an honorary member of the Golden Key honor society and the Alpha Kappa Psi business honor society. He has published more than a hundred journal articles and has authored or coauthored twenty books in the field of management. The title of his most recent book is Reinventing the Supply Chain Life Cycle, and his research has encompassed a wide range of operations management and decision science topics. He has also presented more than one hundred research papers at academic meetings. Professor Schniederjans is serving on five journal editorial review boards, including Computers & Operations Research, International Journal of Information & Decision Sciences, International Journal of Information Systems in the Service Sector, Journal of Operations Management, and Production and Operations Management. He is also serving as an area editor for the journal Operations Management Research and as an associate editor for the International Journal of Strategic Decision Sciences and International Journal of the Society Systems Science and Management Review: An International Journal (Korea). In addition, Professor Schniederjans has served as a consultant and trainer to various business and government agencies. Dara G. Schniederjans is an assistant professor of Supply Chain Management at the University of Rhode Island, College of Business Administration. She has published articles in journals such as Decision Support Systems, Journal of the Operational Research Society, and Business Process Management Journal. She has also coauthored two text books and coedited a readings book. She has contributed chapters to readings utilizing quantitative and statistical methods. Dara has served as a guest coeditor for a special issue on Business Ethics in Social Sciences in the International Journal of Society Systems Science. She has also served as a website coordinator for Decisions Sciences Institute. She currently teaches courses in Supplier Relationship Management and Operations Management. Christopher M. Starkey is an economics student at the University of Connecticut-Storrs. He has presented papers at the Academy of Management and Production and Operations Management Society meetings. He currently teaches courses in Principles of Microeconomics and has taught Principles of Macroeconomics. His current research interests include macroeconomic and monetary policy, as well as other decision-making methodologies.

Preface    xvi
PART I: What Is Business Analytics? 1
Chapter 1: What Is Business Analytics? 3
PART II: Why Is Business Analytics Important? 15
Chapter 2: Why Is Business Analytics Important? 17
Chapter 3: What Resource Considerations Are Important to Support Business Analytics? 29
PART III: How Can Business Analytics Be Applied? 43
Chapter 4: How Do We Align Resources to Support Business Analytics within an Organization? 45
Chapter 5: What Is Descriptive Analytics? 63
Chapter 6: What Is Predictive Analytics? 95
Chapter 7: What Is Prescriptive Analytics? 117
Chapter 8: A Final Business Analytics Case Problem    137
PART IV: Appendixes    161
Appendix A: Statistical Tools    163
Appendix B: Linear Programming    195
Appendix C: Duality and Sensitivity Analysis in Linear Programming    229
Appendix D: Integer Programming    249
Appendix E: Forecasting    257
Appendix F: Simulation    281
Appendix G: Decision Theory    289
Index    321