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Quantitative Methods for Business

ISBN: 9780324184136 | 0324184131
Edition: 9th
Format: Hardcover
Publisher: Cengage Learning
Pub. Date: 4/4/2003

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SummaryTable of Contents
This revision of QUANTITATIVE METHODS FOR BUSINESS provides students with a conceptual understanding of the role that quantitative methods play in the decision-making process. This text describes the many quantitative methods that have been developed over the years, explains how they work, and shows how the decision-maker can apply and interpret data. Written with the non-mathematician in mind, this text is applications-oriented. Its "Problem-Scenario Approach" motivates and helps students understand and apply mathematical concepts and techniqu... MORE
Prefacexiii
About the Authorsxviii
Introduction
1(29)
Problem Solving and Decision Making
... MORE(1)
Quantitative Analysis and Decision Making
4(2)
Quantitative Analysis
6(8)
Model Development
7(3)
Data Preparation
10(1)
Model Solution
11(1)
Report Generation
12(1)
A Note Regarding Implementation
12(2)
Models of Cost, Revenue, and Profit
14(3)
Cost and Volume Models
14(1)
Revenue and Volume Models
15(1)
Profit and Volume Models
15(1)
Breakeven Analysis
16(1)
Quantitative Methods in Practice
17(13)
Methods Used Most Frequently
17(2)
Summary
19(1)
Glossary
19(1)
Problems
20(3)
Appendix 1.1 The Management Scientist Software
23(3)
Appendix 1.2 Using Excel for Breakeven Analysis
26(4)
Introduction to Probability
30(30)
Experiments and the Sample Space
32(1)
Assigning Probabilities to Experimental Outcomes
33(2)
Classical Method
33(1)
Relative Frequency Method
34(1)
Subjective Method
34(1)
Events and Their Probabilities
35(1)
Some Basic Relationships of Probability
36(8)
Complement of an Event
36(1)
Addition Law
37(2)
Conditional Probability
39(4)
Multiplication Law
43(1)
Bayes' Theorem
44(16)
The Tabular Approach
48(2)
Summary
50(1)
Glossary
50(1)
Problems
50(8)
Case Problem Hamilton County Judges
58(2)
Probability Distributions
60(38)
Random Variables
61(1)
Discrete Random Variables
62(5)
Probability Distribution of a Discrete Random Variable
63(1)
Expected Value
64(1)
Variance
65(2)
Binomial Probability Distribution
67(4)
Nastke Clothing Store Problem
67(2)
Expected Value and Variance for the Binomial Distribution
69(2)
Poisson Probability Distribution
71(2)
An Example Involving Time Intervals
72(1)
An Example Involving Length or Distance Intervals
72(1)
Continuous Random Variables
73(3)
Applying the Uniform Distribution
74(1)
Area as a Measure of Probability
75(1)
Normal Probability Distribution
76(8)
Standard Normal Distribution
78(3)
Computing Probabilities for Any Normal Distribution
81(1)
Grear Tire Company Problem
82(2)
Exponential Probability Distribution
84(14)
Computing Probabilities for the Exponential Distribution
85(1)
Relationship Between the Poisson and Exponential Distributions
86(1)
Summary
87(1)
Glossary
87(1)
Problems
88(6)
Case Problem Specialty Toys
94(2)
Appendix 3.1 Computing Discrete Probabilities with Excel
96(1)
Appendix 3.2 Computing Probabilities for Continuous Distributions with Excel
97(1)
Decision Analysis
98(57)
Problem Formulation
100(3)
Influence Diagrams
101(1)
Payoff Tables
101(1)
Decision Trees
102(1)
Decision Making without Probabilities
103(3)
Optimistic Approach
103(1)
Conservative Approach
103(1)
Minimax Regret Approach
104(2)
Decision Making with Probabilities
106(4)
Expected Value to Perfect Information
108(2)
Risk Analysis and Sensitivity Analysis
110(6)
Risk Analysis
111(1)
Sensitivity Analysis
111(5)
Decision Analysis with Sample Information
116(10)
Influence Diagram
116(1)
Decision Tree
117(2)
Decision Strategy
119(4)
Risk Profile
123(2)
Expected Value of Sample Information
125(1)
Efficiency of Sample Information
126(1)
Computing Branch Probabilities
126(29)
Summary
130(2)
Glossary
132(1)
Problems
133(13)
Case Problem 1 Property Purchase Strategy
146(1)
Case Problem 2 Lawsuit Defense Strategy
147(1)
Appendix 4.1 Decision Analysis with TreePlan
148(7)
Utility and Decision Making
155(17)
The Meaning of Utility
156(1)
Developing Utilities for Monetary Payoffs
157(4)
The Expected Utility Approach
160(1)
Summary of Steps for Determining the Utility of Money
161(1)
Risk Avoiders versus Risk Takers
162(3)
Expected Monetary Value versus Expected Utility as an Approach to Decision Making
165(7)
Summary
166(1)
Glossary
167(1)
Problems
167(5)
Forecasting
172(51)
The Components of a Times Series
175(2)
Trend Component
175(1)
Cyclical Component
176(1)
Seasonal Component
177(1)
Irregular Component
177(1)
Smoothing Methods
177(9)
Moving Averages
177(3)
Weighted Moving Averages
180(1)
Exponential Smoothing
181(5)
Trend Projection
186(3)
Trend and Seasonal Components
189(9)
The Multiplicative Model
190(1)
Calculating the Seasonal Indexes
190(4)
Deseasonalizing the Time Series
194(1)
Using the Deseasonalized Time Series to Identify Trend
195(2)
Seasonal Adjustments
197(1)
Models Based on Monthly Data
197(1)
Cyclical Component
198(1)
Regression Analysis
198(8)
Using Regression Analysis as a Causal Forecasting Method
198(6)
Using Regression Analysis with Times Series Data
204(2)
Qualitative Approaches
206(17)
Delphi Method
206(1)
Expert Judgment
206(1)
Scenario Writing
206(1)
Intuitive Approaches
206(1)
Summary
207(1)
Glossary
207(1)
Problems
208(10)
Case Problem 1 Forecasting Sales
218(1)
Case Problem 2 Forecasting Lost Sales
219(1)
Appendix 6.1 Using Excel for Forecasting
220(3)
Introduction to Linear Programming
223(60)
A Simple Maximization Problem
225(5)
Problem Formulation
226(3)
Mathematical Model for the RMC Problem
229(1)
Graphical Solution Procedure
230(13)
A Note on Graphing Lines
238(2)
Summary of the Graphical Solution Procedure for Maximization Problems
240(1)
Slack Variables
240(3)
Extreme Points and the Optimal Solution
243(1)
Computer Solution of the RMC Problem
244(3)
Interpretation of Computer Output
245(2)
A Simple Minimization Problem
247(5)
Summary of the Graphical Solution Procedure for Minimization Problems
249(1)
Surplus Variables
250(1)
Computer Solution of the M&D Chemicals Problem
251(1)
Special Cases
252(4)
Alternative Optimal Solutions
252(1)
Infeasibility
253(2)
Unbounded
255(1)
General Linear Programming Notation
256(27)
Summary
258(1)
Glossary
259(1)
Problems
260(13)
Case Problem 1 Advertising Strategy
273(1)
Case Problem 2 Production Strategy
274(1)
Case Problem 3 Hart Venture Capital
275(1)
Appendix 7.1 Solving Linear Programs with The Management Scientist
276(1)
Appendix 7.2 Solving Linear Programs with LINDO®
277(1)
Appendix 7.3 Solving Linear Programs with Excel
278(5)
Linear Programming: Sensitivity Analysis and Interpretation of Solution
283(55)
Introduction to Sensitivity Analysis
285(1)
Objective Function Coefficients
286(5)
Simultaneous Changes
290(1)
Right-Hand Sides
291(8)
Simultaneous Changes
294(2)
A Second Example
296(2)
Cautionary Note on the Interpretation of Dual Prices
298(1)
More Than Two Decisions Variables
299(9)
Modified RMC Problem
299(4)
Bluegrass Farms Problem
303(5)
Electronic Communications Problem
308(30)
Problem Formulation
309(1)
Computer Solution and Interpretation
310(3)
Summary
313(1)
Glossary
314(1)
Problems
315(17)
Case Problem 1 Product Mix
332(1)
Case Problem 2 Investment Strategy
333(1)
Case Problem 3 Truck Leasing Strategy
334(1)
Appendix 8.1 Sensitivity Analysis with Excel
335(3)
Linear Programming Applications
338(79)
Marketing Applications
339(7)
Media Selection
340(3)
Marketing Research
343(3)
Financial Applications
346(8)
Portfolio Selection
346(4)
Financial Planning
350(4)
Production Management Applications
354(16)
A Make-or-Buy Decision
354(4)
Production Scheduling
358(8)
Workforce Assignment
366(4)
Blending Problems
370(4)
Data Envelopment Analysis
374(8)
Evaluating the Performance of Hospitals
375(1)
Overview of the DEA Approach
376(1)
DEA Linear Programming Model
377(5)
Summary of the DEA Approach
382(1)
Revenue Management
382(35)
Summary
388(1)
Glossary
388(1)
Problems
389(15)
Case Problem 1 Environmental Protection
404(2)
Case Problem 2 Phoenix Computer
406(1)
Case Problem 3 Textile Mill Scheduling
407(1)
Case Problem 4 Workforce Scheduling
408(2)
Case Problem 5 Cinergy Coal Allocation
410(3)
Appendix 9.1 Excel Solution of Hewlitt Corporation Financial Planning Problem
413(4)
Transportation, Assignment, and Transshipment Problems
417(49)
The Transportation Problem: The Network Model and a Linear Programming Formulation
418(7)
Problem Variations
421(3)
A General Linear Programming Model of the Transportation Problem
424(1)
The Assignment Problem: The Network Model and a Linear Programming Formulation
425(6)
Problem Variations
428(1)
A General Linear Programming Model of the Assignment Problem
429(1)
Multiple Assignments
429(2)
The Transshipment Problem: The Network Model and a Linear Programming Formulation
431(7)
Problem Variations
436(1)
A General Linear Programming Model of the Transshipment Problem
437(1)
A Production and Inventory Application
438(28)
Summary
441(1)
Glossary
442(1)
Problems
442(15)
Case Problem Distribution System Design
457(2)
Appendix 10.1 Excel Solution of Transportation, Assignment, and Transshipment Problems
459(7)
Integer Linear Programming
466(47)
Types of Integer Linear Programming Models
468(2)
Graphical and Computer Solutions for an All-Integer Program
470(4)
Graphical Solution of the LP Relaxation
471(1)
Rounding to Obtain an Integer Solution
471(1)
Graphical Solution to the All-Integer Problem
472(1)
Using the LP Relaxation to Establish Bounds
472(2)
Computer Solution
474(1)
Application Involving 0--1 Variables
474(17)
Capital Budgeting
475(1)
Fixed Cost
476(3)
Distribution System Design
479(3)
Bank Location
482(4)
Product Design and Market Share Optimization
486(5)
Modeling Flexibility Provided by 0--1 Integer Variables
491(22)
Multiple-Choice and Mutually Exclusive Constraints
491(1)
k Out of n Alternatives Constraint
492(1)
Conditional and Corequisite Constraints
492(2)
A Cautionary Note About Sensitivity Analysis
494(1)
Summary
494(1)
Glossary
495(1)
Problems
496(10)
Case Problem 1 Textbook Publishing
506(1)
Case Problem 2 Yeager National Bank
507(1)
Case Problem 3 Production Scheduling with Changeover Costs
508(1)
Appendix 11.1 Excel Solution of Integer Linear Programs
509(4)
Project Scheduling: PERT/CPM
513(37)
Project Scheduling with Known Activity Times
514(10)
The Concept of a Critical Path
515(2)
Determining the Critical Path
517(5)
Contributions of PERT/CPM
522(1)
Summary of the PERT/CPM Critical Path Procedure
522(2)
Project Scheduling with Uncertain Activity Times
524(8)
The Daugherty Porta-Vac Project
524(1)
Uncertain Activity Times
524(3)
The Critical Path
527(1)
Variability in Project Completion Time
528(4)
Considering Time-Cost Trade-Offs
532(18)
Crashing Activity Times
532(2)
Linear Programming Model for Crashing
534(3)
Summary
537(1)
Glossary
538(1)
Problems
538(10)
Case Problem R. C. Coleman
548(2)
Inventory Models
550(49)
Economic Order Quantity (EOQ) Model
552(9)
The How-Much-to-Order Decision
556(1)
The When-to-Order Decision
557(1)
Sensitivity Analysis for the EOQ Model
558(1)
Excel Solution of the EOQ Model
559(1)
Summary of the EOQ Model Assumptions
560(1)
Economic Production Lot-Size Model
561(3)
Total Cost Model
562(2)
Economic Production Lot Size
564(1)
Inventory Model with Planned Shortages
564(5)
Quantity Discounts for the EOQ Model
569(3)
Single-Period Inventory Model with Probabilistic Demand
572(5)
Johnson Shoe Company
572(3)
Nationwide Car Rental
575(2)
Order-Quantity, Reorder Point Model with Probabilistic Demand
577(4)
The How-Much-to-Order Decision
579(1)
The When-to-Order Decision
579(2)
Periodic Review Model with Probabilistic Demand
581(18)
More Complex Periodic Review Models
584(2)
Summary
586(1)
Glossary
586(1)
Problems
587(8)
Case Problem 1 Wagner Fabricating Company
595(1)
Case Problem 2 River City Fire Department
596(1)
Appendix 13.1 Development of the Optimal Order Quantity (Q) Formula for the EOQ Model
597(1)
Appendix 13.2 Development of the Optimal Lot-Size (Q*) Formula for the Production Lot-Size Model
598(1)
Waiting Line Models
599(41)
Structure of a Waiting Line System
601(3)
Single-Channel Waiting Line
601(1)
Distribution of Arrivals
601(2)
Distribution of Service Times
603(1)
Queue Discipline
604(1)
Steady-State Operations
604(1)
Single-Channel Waiting Line Model with Poisson Arrivals and Exponential Service Times
604(5)
Operating Characteristics
604(2)
Operating Characteristics for the Burger Dome Problem
606(1)
Managers' Use of Waiting Line Models
606(1)
Improving the Waiting Line Operation
607(1)
Excel Solution of Waiting Line Model
608(1)
Multiple-Channel Waiting Line Model with Poisson Arrivals and Exponential Service Times
609(5)
Operating Characteristics
610(1)
Operating Characteristics for the Burger Dome Problem
611(3)
Some General Relationships for Waiting Line Models
614(2)
Economic Analysis of Waiting Lines
616(2)
Other Waiting Line Models
618(1)
Single-Channel Waiting Line Model with Poisson Arrivals and Arbitrary Service Times
619(2)
Operating Characteristics for the M/G/1 Model
619(1)
Constant Service Times
620(1)
Multiple-Channel Model with Poisson Arrivals, Arbitrary Service Times, and No Waiting Line
621(3)
Operating Characteristics for the M/G/k Model with Blocked Customers Cleared
622(2)
Waiting Line Models with Finite Calling Populations
624(16)
Operating Characteristics for the M/M/1 Model with a Finite Calling Population
624(3)
Summary
627(1)
Glossary
628(1)
Problems
629(7)
Case Problem 1 Regional Airlines
636(2)
Case Problem 2 Office Equipment, Inc.
638(2)
Simulation
640(60)
Risk Analysis
643(13)
PortaCom Project
643(1)
What-If Analysis
643(2)
Simulation
645(8)
Simulation of the PortaCom Problem
653(3)
Inventory Simulation
656(6)
Simulation of the Butler Inventory Problem
659(3)
Waiting Line Simulation
662(11)
Hammondsport Savings Bank ATM Waiting Line
662(1)
Customer Arrival Times
662(1)
Customer Service Times
663(1)
Simulation Model
664(3)
Simulation of the Hammondsport Savings Bank ATM Problem
667(2)
Simulation with Two ATMs
669(2)
Simulation Results with Two ATMs
671(2)
Other Simulation Issues
673(27)
Computer Implementation
673(1)
Verification and Validation
674(1)
Advantages and Disadvantages of Using Simulation
674(1)
Summary
675(1)
Glossary
676(1)
Problems
677(7)
Case Problem 1 Tri-State Corporation
684(2)
Case Problem 2 Harbor Dunes Golf Course
686(2)
Case Problem 3 County Beverage Drive-Thru
688(1)
Appendix 15.1 Simulation with Excel
689(6)
Appendix 15.2 Simulation of the PortaCom Problem Using Crystal Ball
695(5)
Markov Processes
700(24)
Market Share Analysis
702(7)
Accounts Receivable Analysis
709(15)
Fundamental Matrix and Associated Calculations
711(1)
Establishing the Allowance for Doubtful Accounts
712(2)
Summary
714(1)
Glossary
715(1)
Problems
716(4)
Appendix 16.1 Matrix Notation and Operations
720(4)
Multicriteria Decisions
724(45)
Goal Programming: Formulation and Graphical Solution
725(8)
Developing the Constraints and the Goal Equations
726(2)
Developing an Objective Function with Preemptive Priorities
728(1)
Graphical Solution Procedure
729(3)
Goal Programming Model
732(1)
Goal Programming: Solving More Complex Problems
733(6)
Suncoast Office Supplies Problem
733(1)
Formulating the Goal Equations
734(1)
Formulating the Objective Function
735(1)
Computer Solution
736(3)
Scoring Models
739(5)
Analytic Hierarchy Process
744(2)
Developing the Hierarchy
745(1)
Establishing Priorities Using AHP
746(8)
Pairwise Comparisons
746(2)
Pairwise Comparison Matrix
748(1)
Synthesization
749(1)
Consistency
750(2)
Other Pairwise Comparisons for the Car Selection Problem
752(2)
Using AHP to Develop an Overall Priority Ranking
754(15)
Summary
755(1)
Glossary
756(1)
Problems
757(9)
Case Problem EZ Trailers, Inc.
766(1)
Appendix 17.1 Scoring Models with Excel
767(2)
Appendixes
769(47)
Appendix A Binomial Probabilities
770(7)
Appendix B Poisson Probabilities
777(6)
Appendix C Areas for the Standard Normal Distribution
783(1)
Appendix D Values of e-λ
784(1)
Appendix E References and Bibliography
785(2)
Appendix F Self-Test Solutions and Answers to Even-Numbered Problems
787(29)
Index816

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