Intended for business professionals, and managers who would like to have a better conceptual understanding of the role management science in the decision-making process. Rather than giving instruction in just solving problems and models, this textbook focuses on the process of modeling and the use of models to aid in analyzing various managerial situations. The emphasis of this text will be on the integration and development of modeling skills including problem recognition, data collection, model formulation, analysis, and communicating and implementing the results.
"synopsis" may belong to another edition of this title.
Jack Meredith is Professor of Management and Broyhill Distinguished Scholar and Chair in Operations at the Babcock Graduate School of Management at Wake Forest University. He received his undergraduate degrees in engineering and mathematics from Oregon State University and his PhD and MBA from University of California, Berkeley. During his undergraduate studies he worked for Ampex Corporation and Hewlett-Packard Company as a mechanical engineer. Following the award of his undergraduate degrees he worked as an astrodynamicist for Douglas Aircraft Company, and then TRW Systems Group on the Apollo Space Program.
His current research interests are in the areas of research methodology and the strategic planning, justification, and implementation of advanced manufacturing technologies. His recent articles in these areas have been published in Decision Sciences, Journal of Operations Management, Sloan Management Review, Strategic Management Journal, and others. He has two textbooks that are currently popular for college classes: Operations Management for MBAs (John Wiley & Sons) and Project Management: A Managerial Approach (John Wiley & Sons). He is currently the Editor-in-Chief of the Journal of Operations Management, an area editor for Production and Operations Management, was the founding editor of Operations Management Review, and was the production/operations management series editor for John Wiley & Sons, Inc.
The sequence of topics, as evidenced by the very detailed table of contents, is one of the strengths of this text. Integration of the statistical data analysis tools with the management science modeling and analysis topics within a problem-solving framework is quite appealing.
I tried to read the manuscript from two perspectives: (1) a university professor considering the book for adoption, and (2) an undergraduate taking the course. I believe this book will do well, as it emphasizes utility of the topics without overwhelming the student with soporific mathematical proofs. The examples are "real world", and are supplemented with figures which delineate the materials. A student who is taught from this textbook will have the tools to use quantitative business models for their career.
For every chapter I reviewed, the influence diagrams were excellent. These are a major strength of the text and are great learning tools for the students.
We are currently teaching these two subjects in two different courses. I teach Business Statistics and another professor teaches MS. My opinion is that this book can be used by both classes. I would adopt this book for the following two reasons. First, I like its writing style. The materials are presented in a quite understandable way. Second, the topics in this book are those exactly what I teach in my classes.
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