《企业数量分析 教程与案例 英文版》求取 ⇩

Chapter 1 Proactive Decision Making1

Routine Decisions2

The Challenges of Proactive Decision Making3

Alternatives3

Assumptions—Structure4

Assumptions—Assessments5

Performance6

Summary7

Chapter 2 Alternatives9

Small Number of Alternatives9

Sequential Decisions11

A Single Decision Quantity12

Two or More Decision Quantities17

Decision Rules17

Summary18

Chapter 3 Structuring Assumptions in Decision Making19

Structuring Relationships Using an Influence Diagram20

Structuring a Sequence of Decisions and Uncertainties Using a Decision Tree26

Influence Diagrams with Uncertain Quantities31

Final Examples of How to Develop an Influence Diagram34

The Use of Influence Diagrams and Decision Trees37

Case：Destiny Consulting Group39

Chapter 4 Assessment42

Sensitivity Analysis43

The Language of Probability48

Uncertainties with a Few Potential Outcomes48

Uncertainties with Many Potential Outcomes51

Summary Measures of Probability Distributions52

Deriving the Probability Distribution for Performance55

Summary56

Relevant Monetary Flows59

Chapter 5 Performance59

Evaluating Alternatives under Uncertainty62

Few Potential Outcomes62

Many Potential Outcomes67

Summary74

Chapter 6 Risk Management76

Value of Information76

Perfect Information77

Imperfect Information79

Value of Control81

Perfect Control82

Control of Continuously Ranging Quantities82

Adding Value and Reducing Risk83

Summary86

Chapter 7 Evaluating Multiperiod Performance87

Cash Flow88

An Example89

Time Value of Money91

Accumulated Value92

Present Value and Net Present Value94

Formulas for Accumulated and Present Value Calculations97

Streams in Perpetuity97

Pretax versus Aftertax Analyses98

The Reinvestment Rate98

Hurdle Rate99

Internal Rate of Return99

Nominal versus Effective Rates of Return101

Chapter 8 Multiobjective and Multistakeholder Choice103

The Generic Choice Problem103

Example104

First-Round Eliminations105

Dominance105

Decision Rules without Tradeoff Judgments107

Satisficing108

The Lexicographic Rule108

Rate and Weight：Linear Additive Scoring Rules109

Rating Alternatives109

Weighting Attributes110

Assumptions of Rate and Weight115

Multiple Stakeholder Problems116

Appendix 1 Comments on the Dependence of Weights on the Scaling of Attributes116

Exercises119

Chapter 9 Risk Preference and Utility120

The Utility of Monetary Consequences120

Risk Aversion123

Constant Risk Aversion：Negative Exponential Utility124

Decreasing Risk Aversion：Logarithmic Utility126

Using a Utility Curve for Risk Analysis129

Separation of Risk-Return and Mean-Variance Analysis131

Corporate Risk Policy132

Exercises133

Chapter 10 Competitor Analysis134

Characterizing Competitive Situations135

Matrix Format137

Classical Structures141

No(or Little) Conflict141

Prisoner s Dilemma142

Preemption144

Summary145

Chapter 11 Probability Distributions147

The Language of Probability Distributions147

The Probability Mass Function148

The Cumulative Distribution Function149

Continuous and Many-Valued Uncertain Quantities152

Assessment：Capturing Personal Judgment156

An Example of Assessing a Probability Distribution159

Assessment：Using Historical Data as a Guide160

Identifying Suitable Data161

Using the Suitable Data as a Guide162

Adjusting Data for One Distinguishing Factor167

Assessment：Appealing to Underlying Structure168

The Binomial Distribution169

The Normal Distribution172

The Poisson Distribution177

The Exponential Distribution178

Subjective Biases and Assessment180

Summary182

Chapter 12 Sampling183

Forecasting Sample Results184

Forecasting a Sample Average186

Forecasting a Sample Proportion188

Using Sample Results to Draw Inferences about the Underlying Probability Distribution191

Inferences about the Mean of the Underlying Probability Distribution192

Inferences about the Underlying Probability194

Using Sample Results to Forecast Future Sample Results195

Using Sample Results to Forecast a Future Sample Average196

Using Sample Results to Forecast a Future Sample Proportion197

Summary198

Chapter 13 Time-Series Forecasting199

Basic Approaches for One-Period Forecasts200

Simple Approaches200

Moving Average201

Smoothed Average202

Comparison of Forecasts203

Precision204

Bias205

Exploiting Multiperiod Patterns207

Treating Seasonality208

Deseasonalizing a Time Series208

Forecasting the Deseasonalized Series211

Decomposition of Time Series into Seasonality and Trend Components213

Reseasonalizing the Forecast213

Generating the Probability Distribution Forecast213

Separating out Seasonality214

Extrapolating Trend and Cycle Components215

Holt s Model：Exponential Smoothing with Trend217

Winter s Model：Exponential Smoothing with Trend and Seasonality220

Other Advanced Techniques221

Considerations in Preparing and Using a Forecast222

Chapter 14 Regression：Forecasting Using Explanatory Factors224

The Simple Linear Model224

Fitting the Model Using “Least Squares”227

Important Properties of the Least-Squares Regression Line229

Summary Regression Statistics230

Standard Error of Estimate232

Adjusted R Square233

Standard Error of the Coefficients235

Assumptions behind the Linear Regression Model236

Linearity237

Independence239

Homoscedasticity241

Normality242

Summary of Regression Assumptions243

Model-Building Philosophy244

Uses of the Linear Model245

Nature of the Relationship among Variables246

The Importance of the Underlying Relationship to the Use of the Model247

Model-Building Procedure249

Common Mistakes253

Summary254

Forecasting Using the Linear Regression Model255

Point Forecast255

Interval Forecast255

Analogy to Simple Random Sampling257

Using Dummy Variables to Represent Categorical Variables259

Example259

Dummy Variables for More than Two Groups261

Useful Data Transformations262

Example263

Choosing a Transformation267

Transforming the Y-Variable270

Chapter 15 Discrete-Event Simulation273

An Example Application of Discrete-Event Simulation274

The Model275

Important Issues in Discrete-Event Simulation283

Calibrating the Uncertainties283

Validating the Model284

Avoiding Peculiarities Associated with Start-up285

Terminating the Model Run285

Summary286

Chapter 16 Introduction to Optimization Models287

Transforming an Evaluation Model into an Optimization Model288

Example 1：Optimal Order Quantity288

Example 2：Product Mix Planning299

Example 3：Facility Location301

Summary of Examples307

Categorizing and Solving Optimization Models308

Example 1：Nonlinear Programming308

Example 2：Linear Programming312

Example 3：Integer Programming314

Uncertainty in Optimization Models：Sensitivity Analysis319

Lagrange Multipliers319

Linear Programming Models322

Building an Optimization Model from Scratch326

Chapter 17 The Mathematics of Optimization332

Functions333

Algebraic Framework for Optimization Models333

General Structure of an Optimization Model335

Integer Programming337

Linear Programming (LP)337

Graphical Representation of Example 2338

The Simplex Algorithm341

Some Final Comments on the Simplex Algorithm and LP344

Karmarkar s Algorithm：An Alternative Approach to Solving LP Models345

Nonlinear Programming (NLP)346

Levers to Control the GS Solution Approach349

Integer Programming (IP)352

Final Observations：LP，NLP，and IP358

Summary360

Cases361

Case 1：American Lawbook Corporation（A）361

Case 2：American Lawbook Corporation（B）372

Case 3：Amore Frozen Foods375

Case 4：Athens Glass Works381

Case 5：Buckeye Power Light Company384

Case 6：Buckeye Power Light Company Supplement389

Case 7：California Oil Company397

Case 8：C．K．Coolidge，Inc．（A）401

Case 9：The Commerce Tavern413

Case 10：CyberLab：A New Business Opportunity for PRICO（A）420

Case 11：CyberLab：Supplement428

Case 12：CyberLab：A New Business Opportunity for PRICO（B）430

Case 13：Dhahran Roads（A）432

Case 14：Dhahran Roads（B）434

Case 15：Discounted Cash Flow Exercises436

Case 16：Edgcomb Metals（A）438

Case 17：Florida Glass Company（A）447

Case 18：Florida Glass Company（A）Supplement454

Case 19：Foulke Consumer Products，Inc．457

Case 20：Foulke Consumer Products，Inc．，Supplement463

Case 21：Freemark Abbey Winery475

Case 22：Galaxy Micro Systems478

Case 23：Galaxy Micro Systems Supplement480

Case 24：George s T-Shirts481

Case 25：Harimann International483

Case 26：Hightower Department Stores：Imported Stuffed Animals490

Case 27：International Guidance and Controls499

Case 28：Jade Shampoo（A）501

Case 29：Jade Shampoo（B）506

Case 30：Jaikumar Textiles，Ltd．;The Nylon Division（A）509

Case 31：Jaikumar Textiles，Ltd．;The Nylon Division（B）513

Case 32：Lesser Antilles Lines：The Island of San Huberto515

Case 33：Lightweight Aluminum Company：The Lebanon Plant524

Case 34：Lorex Pharmaceuticals536

Case 35：Maxco，Inc．，and the Gambit Company539

Case 36：The Oakland A s（A）546

Case 37：The Oakland A s（A）Supplement555

Case 38：The Oakland A s（B）563

Case 39：Piedmont Airlines：Discount Seat Allocation（A）566

Case 40：Piedmont Airlines：Discount Seat Allocation（B）574

Case 41：Probability Assessment Exercise579

Case 42：Problems in Regression581

Case 43：Roadway Construction Company585

Case 44：Shumway，Horch，and Sager（A）588

Case 45：Shumway，Horch，and Sager（B）591

Case 46：Sleepmore Mattress Manufacturing：Plant Consolidation595

Case 47：Sprigg Lane（A）600

Case 48：T．Rowe Price Associates611

Case 49：Wachovia Bank and Trust Company，N．A．（B）619

Case 50：Wachovia Bank and Trust Company，N．A．（B）：Supplement622

Case 51：Waite First Securities625

Case 52：The Waldorf Property632