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For undergraduate/graduate level courses in Management Science, Quantitative Analysis, and Decision Models. This best-selling text has long been considered one of the most student accessible texts for the management science course. The new edition retains and updates the traditional, comprehensive coverage of past editions but now adds spreadsheet-based problem solutions to most chapters of the text. In addition, the text is now packaged with free software.
- Published on: 1986-06
- Original language: English
- Number of items: 1
- Binding: Paperback
- 750 pages
From the Publisher
This easy-to-use text provides students with the skills to apply the techniques of quantitative analysis in all kinds of organizational decision-making situations. Designed for optimum teaching flexibility, it covers every major topic in the quantitative analysis/management science field, showing how each technique works, discussing the assumptions and limitations of the models, and illustrating the real-world usefulness of each technique with many applications in both profit-making and nonprofit organizations. Dramatically revised, the Sixth Edition now offers a completely new look and feel to make teaching more efficient and enhance students' learning experience.
From the Back Cover
Fully integrated with the personal computer, this easy-to-use book provides readers with the skills to necessary to apply the techniques of quantitative analysis in all kinds of organizational decision-making situations. It covers every major topic in the quantitative analysis/management science field, showing how each technique works, discussing the assumptions and limitations of the models, and illustrating the real-world usefulness of each technique with many applications and case studies in both profit-making and nonprofit organizations. A FREE CD-ROM readers can use to solve the examples presented in the book is conveniently packaged with the book providing Excel QM, Crystal Ball, TreePlan, QM for Windows and data files for examples. Probability Concepts and Applications, Decision Theory, Decision Trees with Utility Theory, Forecasting, Inventory Control Models, Linear Programming Models, Linear Programming: The Simplex Method. Transportation and Assignment Models, Integer Programming, Goal Programming, Non Linear Programming, and Branch and Bound Models, Analytic Hierarchy Process, Network Models, Project Management, Waiting Lines and Queuing Theory Models, Simulation Modeling, Markov Analysis, Using QM for Windows, Using Excel OM. Appropriate for business managers and analysts.
About the Author
Barry Render is the Charles Harwood Distinguished Professor of Management Science at the Roy E. Crummer Graduate School of Business at Rollins College in Winter Park, Florida. He received his M.S. in Operations Research and his Ph.D. in Quantitative Analysis at the University of Cincinnati. He previously taught at George Washington University, the University of New Orleans, Boston University, and George Mason University, where he held the GM Foundation Professorship in Decision Sciences and was Chair of the Decision Science Department. Dr. Render has also worked in the aerospace industry for General Electric, McDonnell Douglas, and NASA.
Professor Render has co-authored ten textbooks with Prentice-Hall, including Managerial Decision Modeling with Spreadsheets, Operations Management, Principles of Operations Management, Service Management, Introduction to Management Science, and Cases and Readings in Management Science. His more than one hundred articles on a variety of management topics have appeared in Decision Sciences, Production and Operations Management, Interfaces, Information and Management, the Journal of Management Information Systems, Socio-Economic Planning Sciences, and Operations Management Review, among others.
Dr. Render has also been honored as an AACSB Fellow and named as a Senior Fulbright Scholar in 1982 and again in 1993. He was twice vice-president of the Decision Science Institute Southeast Region and served as Software Review Editor for Decision Line from 1989 to 1995. He has also served as Editor of the New York Times Operations Management special issues from 1996 to 2001. Finally, Professor Render has been actively involved in consulting for government agencies and for many corporations, including NASA; the FBI; the U.S. Navy; Fairfax County, Virginia; and C8zP Telephone.
He teaches operations management courses in Rollins College's MBA and Executive MBA programs. In 1995 he was named as that school's Professor of the Year, and in 1996 was selected by Roosevelt University to receive the St. Claire Drake Award for Outstanding Scholarship.
Ralph Stair has been Professor of Management Science at Florida State University for twenty years and is now entering its phased retirement program. He received a B.S. in Chemical Engineering from Purdue University and an MBA from Tulane University. Under the guidance of Ken Ramsing and Alan Eliason, he received his Ph.D. in operations management from the University of Oregon.
He has taught at the University of Oregon, the University of Washington, the University of New Orleans, and Florida State University. He has twice taught in Florida State University's Study Abroad Program in London. Over the years, his teaching has been concentrated in the areas of information systems, operations research, and operations management.
Dr. Stair is a member of several academic organizations, including the Decision Sciences Institute and INFORMS, and he regularly participates at national meetings. He has published numerous articles and books, including Managerial Decision Modeling with Spreadsheets, Introduction to Management Science, Cases and Readings in Management Science, Production and Operations Management: A Self-Correction Approach, Fundamentals of Information Systems, Principles of Information Systems, Introduction to Information Systems, Computers in Today's World, Principles of Data Processing, Learning to Live with Computers, Programming in BASIC, Essentials of BASIC Programming, Essentials of FORTRAN Programming, and Essentials of COBOL Programming.
Dr. Stair divides his time between Florida and Colorado. He enjoys skiing, biking, kayaking, and other outdoor activities.
Michael E. Hanna is Professor of Decision Sciences at the University of Houston-Clear Lake (UHCL).
Most helpful customer reviews
12 of 12 people found the following review helpful.
REQUIRED FOR MGMT 524 MANAGEMENT SCIENCE
By D. Comer
This book is required for the MGMT 524 Management Science course at Embtry-Riddle Aeronautical University. It does not come with a CD, but the programs associated with it are available for free at the companion website.
20 of 22 people found the following review helpful.
Software Corrected for the 11th Edition-- ignore old reviews!
By Let's Compare Options Preptorial
I've taught both MBA and Master's in Management classes online and physically at MIT, Harvard (GE Crotonville) and Phoenix State University. There are a group of about 3-5 texts that are now the most popular for graduate Quantitative Analysis (QA). These include the Swift text (most popular in Europe) at from $40 to $80 US (Quantitative Methods: For Business, Management and Finance), the Render Quantitative Analysis for Management text (Quantitative Analysis for Management (11th Edition)), $175 for the 11th edition, and the very thorough but NOT for self study Anderson text (Quantitative Methods for Business (with Printed Access Card)) for $250.
QA is a really tough course for people with less math background such as liberal arts, nursing, etc. students going for an MBA, and a bit easier for math and engineering majors in undergrad, because it involves modeling, using a lot of fairly advanced math. Typical QA courses include linear programming (not really linear, and not really programming-- it is about objectives and constraints stated algebraically to find "optimal" graphic or corner solutions to problems such as mixing, profit maximization, or cost minimization); queueing problems; statement analysis; Decision analysis; Project Management; Forecasting; Inventory Control; Logistics; Markov Analysis; Stats; Integer/ nonlinear/ goal programming; regression modeling; simulation; probability, and possibly some econometrics. Most grad (MBA) courses don't go as far as differential equation modeling (frequent models in physics, biosciences, ecology, etc).
The Swift and Render texts are the most popular, and the Anderson text a distant third according to publisher's (QA!) data on course use and sales. Both Swift and Render are frequently zinged in reviews for broken or less useful software and models, but this is an unfair criticism. Swift gives numerous (although London oriented) model examples, and Render has their own internet models available. The reason both of these criticisms are unfair is that there are numerous plug ins for Excel that do all the analysis, statistics, programming solutions, etc. you will need regardless of which text you use. The Library Picks team chose Render as the top pick, but due to expense, if you're doing self study, Swift is also a good bet.
If the included websites, plug ins, templates and downloads aren't working for you from a software/ modeling viewpoint, here is a brief list of outstanding Excel options that will do the same thing, many for free:
-- Statistical Analysis: Microsoft Excel 2010
-- Business Analysis: Microsoft Excel 2010 (MrExcel Library)
-- Predictive Analytics: Microsoft Excel
-- Microsoft Excel 2010: Data Analysis and Business Modeling
-- Charts and Graphs: Microsoft Excel 2010 (MrExcel Library)
These will take care of the problems metioned by some reviewers that it is hard to stay up to date on models. In particular, Microsoft has now migrated their SQL server business analysis package to a new language called DAX in the FREE Excel plug in PowerPivot. These plug ins, many free on the web, will work perfectly with the examples in Swift and Render so you don't have to sweat the included QA software if it crashes.
One caveat: many reviews complain about QA software with "bugs" when in fact it is the reviewer's computer at fault. To run modern QA programs with lots of modeling, you need a modern dual core processor with at LEAST 8 gig of ram, preferably 12 or 16. The reason for this is that with pipelining, the old "math coprocessor" hardware has given way to sharing between CPU and GPU for floating point, and recent software-- even SPSS -- will crash older machines or appear to be buggy. Excel with a plug in also is a great answer to this, because you can get away with much less power if your machine is already doing well with Excel. PowerPivot is intensive, but only if you have huge amounts of data. The typical mixing problem is no problem even with a computer that's say, post 2009.
0 of 0 people found the following review helpful.
The contents of the textbook I received were great. However the actual book was in horrible condition
By Amazon Customer
The contents of the textbook I received were great. However the actual book was in horrible condition. When I opened the box, the back portion of the book fell out, it wasn't even attached. I was not impressed. I have always used Amazon for textbooks but this particular book was in horrible condition.
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