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An Introduction to Management Science: Quantitative Approaches to Decision Making, 14th Edition

David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann

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Starting At $77.95 See pricing and ISBN options
An Introduction to Management Science: Quantitative Approaches to Decision Making 14th Edition by David R. Anderson/Dennis J. Sweeney/Thomas A. Williams/Jeffrey D. Camm/James J. Cochran/Michael J. Fry/Jeffrey W. Ohlmann

Overview

Integrating the latest developments in Microsoft® Office Excel® 2013, Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, 14E equips students with a sound conceptual understanding of the role that management science plays in the decision-making process. The trusted market leader for more than two decades, the text defines today's management science course. The authors continue to provide unwavering accuracy with the book's emphasis on applications and timely, powerful examples. The book's hallmark problem-scenario approach introduces each quantitative technique within an applications setting. Students must apply the management science model to generate solutions and recommendations for management. For the 14th Edition, all data sets, applications, and screen visuals reflect the details of Excel 2013 to accurately prepare your students to work with the latest spreadsheet tools. In addition, a comprehensive support package offers all the written and online timesaving support you need with trusted solutions written by the text authors. Online content includes online chapters, LINGO software and Excel add-ins.

David R. Anderson

David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati. Dr. Anderson has served as head of the Department of Quantitative Analysis and Operations Management and as associate dean of the College of Business Administration. He was also coordinator of the college’s first executive program. In addition to introductory statistics for business students, Dr. Anderson taught graduate-level courses in regression analysis, multivariate analysis and management science. He also taught statistical courses at the Department of Labor in Washington, D.C. Dr. Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the co-author of ten well-respected textbooks related to decision sciences and he actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, Dr. Anderson earned his B.S., M.S. and Ph.D. degrees from Purdue University.

Dennis J. Sweeney

Dennis J. Sweeney is professor emeritus of quantitative analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a B.S.B.A. degree from Drake University and his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA fellow. Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. He also served as head of the Department of Quantitative Analysis and served four years as associate dean of the College of Business Administration at the University of Cincinnati. Dr. Sweeney has published more than 30 articles and monographs in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger and Cincinnati Gas & Electric have funded his research, which has been published in journals such as Management Science, Operations Research, Mathematical Programming and Decision Sciences. Dr. Sweeney has co-authored 10 textbooks in the areas of statistics, management science, linear programming and production and operations management.

Thomas A. Williams

N/A

Jeffrey D. Camm

Jeffrey D. Camm is the Inmar Presidential Chair of Analytics and Senior Associate Dean for Faculty in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, Dr. Camm served on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 45 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, The INFORMS Journal on Applied Analytics and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the recipient of the 2006 INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as a consultant to numerous companies and government agencies. Dr. Camm served as editor-in-chief of INFORMS Journal on Applied Analytics and is an INFORMS fellow.

James J. Cochran

James J. Cochran is Professor of Applied Statistics, the Mike and Cathy Mouron Research Chair and Associate Dean for Faculty and Research at the University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S. and M.B.A. degrees from Wright State University and his Ph.D. from the University of Cincinnati. Dr. Cochran has served at The University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 50 papers in the development and application of operations research and statistical methods. He has published his research in Management Science, The American Statistician, Communications in Statistics-Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, INFORMS Journal on Applied Analytics, BMJ Global Health and Statistics and Probability Letters. He was the 2008 recipient of the INFORMS Prize for the Teaching of Operations Research Practice and the 2010 recipient of the Mu Sigma Rho Statistical Education Award. He received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In 2017 he received the American Statistical Association’s Waller Distinguished Teaching Career Award and in 2018 he received the INFORMS President’s Award. Dr. Cochran is an elected member of the International Statistics Institute, a fellow of the American Statistical Association and a fellow of INFORMS. A strong advocate for effective statistics and operations research education as a means of improving the quality of applications to real problems, Dr. Cochran has organized and chaired teaching workshops throughout the world.

Michael J. Fry

Michael J. Fry is Professor of Operations, Business Analytics and Information Systems, Lindner Research Fellow and Managing Director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a B.S. from Texas A&M University and his M.S.E. and Ph.D. from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department head. He has also been a visiting professor at Cornell University and the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IISE Transactions, Critical Care Medicine and INFORMS Journal on Applied Analytics. His research interests are in applying quantitative management methods to the areas of supply chain analytics, sports analytics and public-policy operations. He has worked with many organizations for his research, including Dell, Inc., Starbucks Coffee Company, Great American Insurance Group, the Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals and the Cincinnati Zoo and Botanical Garden. Dr. Fry was named a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, and he has been recognized for both his research and teaching excellence at the University of Cincinnati.

Jeffrey W. Ohlmann

Jeffrey W. Ohlmann is Associate Professor of Business Analytics and Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a B.S. from the University of Nebraska and his M.S. and Ph.D. from the University of Michigan. He has been at the University of Iowa since 2003. Dr. Ohlmann’s research on the modeling and solution of decision-making problems has produced more than two dozen research papers in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science, the European Journal of Operational Research and INFORMS Journal on Applied Analytics (formerly Interfaces). He has collaborated with companies such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections as well as three National Football League franchises. Because of the relevance of his work to industry, he was bestowed the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.
  • ADDITIONAL AUTHORS. For the new 14th Edition, the text's renowned author team is joined by three new, outstanding authors--James J. Cochran of the University of Alabama, Michael J. Fry of the University of Cincinnati, and Jeffrey W. Ohlmann of the University of Iowa. All three are strong contributors who bring a thoughtful and fresh view to the subject matter.
  • NEW UTILITY THEORY COVERAGE. Chapter 13 "Decision Analysis" includes an all-new section on Utility Theory to complement the comprehensive material on decision analysis.
  • MICROSOFT® OFFICE EXCEL® 2013 INTEGRATION. Detailing the latest information from Excel 2013, chapter appendices offer step-by-step instructions on how to use Excel Solver and LINGO. Both Excel and LINGO files are available on the text's companion Website for every model illustrated in the text.
  • UPDATED APPENDIX A: BUILDING SPREADSHEET MODELS. This helpful, optional appendix provides useful insights for solving optimization models with Excel Solver. It also discusses the principles of good spreadsheet modeling and offers helping auditing tips as well as practical exercises.
  • UPDATED TRENDS AND SEASONALITY COVERAGE. A fully revised Chapter 15 "Time Series Analysis and Forecasting" includes an updated discussion of trends and seasonality that focuses on the use of regression to estimate linear trends and seasonal effects. In addition, a discussion on using the Excel INEST function to estimate linear trends and seasonal effect has been added to an appendix at the end of this chapter. The revisions represent industry approaches to these important topics.
  • PROVEN AUTHORS. Respected leaders and active consultants in the fields of business and statistics, the Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann team of authors personally write and confirm all text presentation examples, problems, and Test Bank content to ensure unwavering accuracy and dependability.
  • PROBLEM-SCENARIO APPROACH. A hallmark strength of this text, the authors' proven problem-scenario approach introduces problems using the management science model and introduces each quantitative technique within an application setting. Students must apply the management science technique to each problem to generate a business solution or recommendation.
  • REAL-DATA EXAMPLES. Known for its practical, real-world emphasis, the text provides actual data drawn from real business that emphasizes applications as well as solid management science and quantitative methodology.
  • INTEGRATED SOFTWARE APPLICATIONS. The text integrates coverage of the software applications most commonly used today, helping you equip students with critical skills in LINGO as well as Excel with quantitative add-ins. For your convenience, coverage of LINGO and Excel with add-ins such as TreePlan and Analytic Solver Platform appear in appendixes--enabling you to introduce them when it best fits with your course.
  • ROBUST ONLINE CONTENT. The text's wealth of digital content provides five online chapters, excel templates and add-ins that correspond with text examples and models, and software. Students can also access LINGO trial edition software and Analytic Solver Platform.
  • SELF-TEST EXERCISES. Helpful Self-Test Exercises throughout each chapter with complete solutions allow students to check their understanding of concepts as they progress through the text. The exercises also serve as excellent exam-prep tools. A complete, step-by-step solution to each Self-Test exercise is included in Appendix E.
1. Introduction.
2. An Introduction to Linear Programming.
3. Linear Programming: Sensitivity Analysis and Interpretation of Solution.
4. Linear Programming Applications in Marketing, Finance, and Operations Management.
5. Advanced Linear Programming Applications.
6. Distribution and Network Models.
7. Integer Linear Programming.
8. Nonlinear Optimization Models.
9. Project Scheduling: PERT/CPM.
10. Inventory Models.
11. Waiting Line Models.
12. Simulation.
13. Decision Analysis.
14. Multicriteria Decisions.
15. Time Series Analysis and Forecasting.
16. Markov Processes.
17. Linear Programming: Simplex Method (on Website).
18. Simplex-Based Sensitivity Analysis and Duality (on Website).
19. Solutions Procedures for Transportation and Assignment Problems (on Website).
20. Minimal Spanning Tree (on Website).
21. Dynamic Programming (on Website).
Appendix A: Building Spreadsheet Models.
Appendix B: Areas for the Standard Normal Distribution.
Appendix C: Values of e–λ.
Appendix D: References and Bibliography.
Appendix E: Self-Test Solutions and Answers to Even-Numbered Problems.

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  • ISBN-10: 0357686934
  • ISBN-13: 9780357686935
  • RETAIL $77.95

  • ISBN-10: 1111823618
  • ISBN-13: 9781111823610
  • RETAIL $216.95