企业数量分析 教程与案例 英文版PDF电子书下载

Chapter 1 Proactive Decision Making 1

Routine Decisions 2

The Challenges of Proactive Decision Making 3

Alternatives 3

Assumptions—Structure 4

Assumptions—Assessments 5

Performance 6

Summary 7

Chapter 2 Alternatives 9

Small Number of Alternatives 9

Sequential Decisions 11

A Single Decision Quantity 12

Two or More Decision Quantities 17

Decision Rules 17

Summary 18

Chapter 3 Structuring Assumptions in Decision Making 19

Structuring Relationships Using an Influence Diagram 20

Structuring a Sequence of Decisions and Uncertainties Using a Decision Tree 26

Influence Diagrams with Uncertain Quantities 31

Final Examples of How to Develop an Influence Diagram 34

The Use of Influence Diagrams and Decision Trees 37

Case：Destiny Consulting Group 39

Chapter 4 Assessment 42

Sensitivity Analysis 43

The Language of Probability 48

Uncertainties with a Few Potential Outcomes 48

Uncertainties with Many Potential Outcomes 51

Summary Measures of Probability Distributions 52

Deriving the Probability Distribution for Performance 55

Summary 56

Relevant Monetary Flows 59

Chapter 5 Performance 59

Evaluating Alternatives under Uncertainty 62

Few Potential Outcomes 62

Many Potential Outcomes 67

Summary 74

Chapter 6 Risk Management 76

Value of Information 76

Perfect Information 77

Imperfect Information 79

Value of Control 81

Perfect Control 82

Control of Continuously Ranging Quantities 82

Adding Value and Reducing Risk 83

Summary 86

Chapter 7 Evaluating Multiperiod Performance 87

Cash Flow 88

An Example 89

Time Value of Money 91

Accumulated Value 92

Present Value and Net Present Value 94

Formulas for Accumulated and Present Value Calculations 97

Streams in Perpetuity 97

Pretax versus Aftertax Analyses 98

The Reinvestment Rate 98

Hurdle Rate 99

Internal Rate of Return 99

Nominal versus Effective Rates of Return 101

Chapter 8 Multiobjective and Multistakeholder Choice 103

The Generic Choice Problem 103

Example 104

First-Round Eliminations 105

Dominance 105

Decision Rules without Tradeoff Judgments 107

Satisficing 108

The Lexicographic Rule 108

Rate and Weight：Linear Additive Scoring Rules 109

Rating Alternatives 109

Weighting Attributes 110

Assumptions of Rate and Weight 115

Multiple Stakeholder Problems 116

Appendix 1 Comments on the Dependence of Weights on the Scaling of Attributes 116

Exercises 119

Chapter 9 Risk Preference and Utility 120

The Utility of Monetary Consequences 120

Risk Aversion 123

Constant Risk Aversion：Negative Exponential Utility 124

Decreasing Risk Aversion：Logarithmic Utility 126

Using a Utility Curve for Risk Analysis 129

Separation of Risk-Return and Mean-Variance Analysis 131

Corporate Risk Policy 132

Exercises 133

Chapter 10 Competitor Analysis 134

Characterizing Competitive Situations 135

Matrix Format 137

Classical Structures 141

No(or Little) Conflict 141

Prisoner s Dilemma 142

Preemption 144

Summary 145

Chapter 11 Probability Distributions 147

The Language of Probability Distributions 147

The Probability Mass Function 148

The Cumulative Distribution Function 149

Continuous and Many-Valued Uncertain Quantities 152

Assessment：Capturing Personal Judgment 156

An Example of Assessing a Probability Distribution 159

Assessment：Using Historical Data as a Guide 160

Identifying Suitable Data 161

Using the Suitable Data as a Guide 162

Adjusting Data for One Distinguishing Factor 167

Assessment：Appealing to Underlying Structure 168

The Binomial Distribution 169

The Normal Distribution 172

The Poisson Distribution 177

The Exponential Distribution 178

Subjective Biases and Assessment 180

Summary 182

Chapter 12 Sampling 183

Forecasting Sample Results 184

Forecasting a Sample Average 186

Forecasting a Sample Proportion 188

Using Sample Results to Draw Inferences about the Underlying Probability Distribution 191

Inferences about the Mean of the Underlying Probability Distribution 192

Inferences about the Underlying Probability 194

Using Sample Results to Forecast Future Sample Results 195

Using Sample Results to Forecast a Future Sample Average 196

Using Sample Results to Forecast a Future Sample Proportion 197

Summary 198

Chapter 13 Time-Series Forecasting 199

Basic Approaches for One-Period Forecasts 200

Simple Approaches 200

Moving Average 201

Smoothed Average 202

Comparison of Forecasts 203

Precision 204

Bias 205

Exploiting Multiperiod Patterns 207

Treating Seasonality 208

Deseasonalizing a Time Series 208

Forecasting the Deseasonalized Series 211

Decomposition of Time Series into Seasonality and Trend Components 213

Reseasonalizing the Forecast 213

Generating the Probability Distribution Forecast 213

Separating out Seasonality 214

Extrapolating Trend and Cycle Components 215

Holt s Model：Exponential Smoothing with Trend 217

Winter s Model：Exponential Smoothing with Trend and Seasonality 220

Other Advanced Techniques 221

Considerations in Preparing and Using a Forecast 222

Chapter 14 Regression：Forecasting Using Explanatory Factors 224

The Simple Linear Model 224

Fitting the Model Using “Least Squares” 227

Important Properties of the Least-Squares Regression Line 229

Summary Regression Statistics 230

Standard Error of Estimate 232

Adjusted R Square 233

Standard Error of the Coefficients 235

Assumptions behind the Linear Regression Model 236

Linearity 237

Independence 239

Homoscedasticity 241

Normality 242

Summary of Regression Assumptions 243

Model-Building Philosophy 244

Uses of the Linear Model 245

Nature of the Relationship among Variables 246

The Importance of the Underlying Relationship to the Use of the Model 247

Model-Building Procedure 249

Common Mistakes 253

Summary 254

Forecasting Using the Linear Regression Model 255

Point Forecast 255

Interval Forecast 255

Analogy to Simple Random Sampling 257

Using Dummy Variables to Represent Categorical Variables 259

Example 259

Dummy Variables for More than Two Groups 261

Useful Data Transformations 262

Example 263

Choosing a Transformation 267

Transforming the Y-Variable 270

Chapter 15 Discrete-Event Simulation 273

An Example Application of Discrete-Event Simulation 274

The Model 275

Important Issues in Discrete-Event Simulation 283

Calibrating the Uncertainties 283

Validating the Model 284

Avoiding Peculiarities Associated with Start-up 285

Terminating the Model Run 285

Summary 286

Chapter 16 Introduction to Optimization Models 287

Transforming an Evaluation Model into an Optimization Model 288

Example 1：Optimal Order Quantity 288

Example 2：Product Mix Planning 299

Example 3：Facility Location 301

Summary of Examples 307

Categorizing and Solving Optimization Models 308

Example 1：Nonlinear Programming 308

Example 2：Linear Programming 312

Example 3：Integer Programming 314

Uncertainty in Optimization Models：Sensitivity Analysis 319

Lagrange Multipliers 319

Linear Programming Models 322

Building an Optimization Model from Scratch 326

Chapter 17 The Mathematics of Optimization 332

Functions 333

Algebraic Framework for Optimization Models 333

General Structure of an Optimization Model 335

Integer Programming 337

Linear Programming (LP) 337

Graphical Representation of Example 2 338

The Simplex Algorithm 341

Some Final Comments on the Simplex Algorithm and LP 344

Karmarkar s Algorithm：An Alternative Approach to Solving LP Models 345

Nonlinear Programming (NLP) 346

Levers to Control the GS Solution Approach 349

Integer Programming (IP) 352

Final Observations：LP，NLP，and IP 358

Summary 360

Cases 361

Case 1：American Lawbook Corporation（A） 361

Case 2：American Lawbook Corporation（B） 372

Case 3：Amore Frozen Foods 375

Case 4：Athens Glass Works 381

Case 5：Buckeye Power Light Company 384

Case 6：Buckeye Power Light Company Supplement 389

Case 7：California Oil Company 397

Case 8：C．K．Coolidge，Inc．（A） 401

Case 9：The Commerce Tavern 413

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

Case 11：CyberLab：Supplement 428

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 Exercises 436

Case 16：Edgcomb Metals（A） 438

Case 17：Florida Glass Company（A） 447

Case 18：Florida Glass Company（A）Supplement 454

Case 19：Foulke Consumer Products，Inc． 457

Case 20：Foulke Consumer Products，Inc．，Supplement 463

Case 21：Freemark Abbey Winery 475

Case 22：Galaxy Micro Systems 478

Case 23：Galaxy Micro Systems Supplement 480

Case 24：George s T-Shirts 481

Case 25：Harimann International 483

Case 26：Hightower Department Stores：Imported Stuffed Animals 490

Case 27：International Guidance and Controls 499

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 Huberto 515

Case 33：Lightweight Aluminum Company：The Lebanon Plant 524

Case 34：Lorex Pharmaceuticals 536

Case 35：Maxco，Inc．，and the Gambit Company 539

Case 36：The Oakland A s（A） 546

Case 37：The Oakland A s（A）Supplement 555

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 Exercise 579

Case 42：Problems in Regression 581

Case 43：Roadway Construction Company 585

Case 44：Shumway，Horch，and Sager（A） 588

Case 45：Shumway，Horch，and Sager（B） 591

Case 46：Sleepmore Mattress Manufacturing：Plant Consolidation 595

Case 47：Sprigg Lane（A） 600

Case 48：T．Rowe Price Associates 611

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

Case 50：Wachovia Bank and Trust Company，N．A．（B）：Supplement 622

Case 51：Waite First Securities 625

Case 52：The Waldorf Property 632