Advances in Business and Management Forecasting, Volume 4 (Advances in Business and Management Forecasting) (Advances in Business and Management Forecasting)

copyright......Page 5
Contents......Page 6
List of Contributors......Page 10
Statement of Purpose......Page 12
An Introduction to Supply Chain Management......Page 16
Demand Chains......Page 18
Forecasting in Supply Chain......Page 19
Forecasting at the SKU Level......Page 20
Inventory Drivers......Page 22
The Bullwhip Effect......Page 23
References......Page 24
One View of the Future......Page 26
A Second and Alternative View of the Future......Page 28
More Precise Prior Posterior Notation......Page 30
Guiding the Sales Trajectory Y(t|t) with the Signals P¯¹ (t)*Z(t) from the Advance Orders......Page 31
An Application......Page 33
Guided Forecasts Converge on the True Sales Trajectory......Page 36
Early Warnings of Future Changes......Page 37
References......Page 38
Introduction......Page 40
Literature Review......Page 41
Motivation and Background......Page 44
Descriptive Statistics......Page 46
Durable Products......Page 51
Non-Durable Products......Page 53
Total Products......Page 56
Forecast Comparisons......Page 59
Discussion......Page 61
Acknowledgment......Page 62
References......Page 63
Appendix......Page 64
An Application of Confirmatory Factor Analysis to the A Priori Classification of Financial Ratios......Page 70
Introduction......Page 71
Literature Review......Page 72
Data and Modeling Considerations......Page 76
Results......Page 80
Concluding Remarks......Page 86
References......Page 88
Introduction......Page 90
Background......Page 91
Literature Review......Page 92
Data, Research Design, and Results......Page 95
Future Research......Page 100
References......Page 101
Forecasting Security Returns: The use of Heterogeneous Expectations......Page 106
Introduction......Page 107
Review of the literature......Page 108
Data and Sample Characteristics......Page 114
Results......Page 116
Conclusions, Recommendations and Directions for Future Research......Page 122
References......Page 126
Combining Moving Averages with Exponential Smoothing to Produce More Stable Sales Forecasts......Page 132
Introduction......Page 133
Notation......Page 134
Proposed Forecasting Model......Page 135
Computation of Seasonal Factors......Page 136
Computation of Projected Base Levels......Page 137
Model Fitting and Application......Page 138
Conclusion......Page 139
Reference......Page 140
Introduction......Page 146
Proposed Smoothing Equation......Page 147
Applications to Sales Forecasting......Page 149
References......Page 151
Flow-Through Models......Page 152
Diffusion Models......Page 153
The Oral/Nasal Insulin Example......Page 155
References......Page 156
An Application of a Repeat Purchase Diffusion Model to the Pharmaceutical Industry......Page 158
Introduction......Page 159
Diffusion and Repeat Purchase......Page 160
Marketing/Sales Organization/Customer Relationship in a Detail-Intensive Industry......Page 163
Allocation Percentages and the Effects of the Marketing Mix......Page 169
The Full Allocation Model......Page 172
The Data......Page 174
Fit Statistics (H4)......Page 175
Parameter Estimates and Standard Errors (H1)......Page 178
λ1, λ2, and r(t) values (H2 and H3)......Page 179
Forecasting......Page 181
Conclusion......Page 183
References......Page 185
Conjoint Analysis......Page 188
Competitive Reaction......Page 190
Funnel Analysis......Page 193
Choice Probabilities: Necessary but Insufficient......Page 194
References......Page 195
Improving Sales Forecastsby Testing Underlying Hypotheses about Consumer Behavior: A Proposed Qualitative Method......Page 196
Introduction......Page 197
Quantitative Survey Methods......Page 198
The Biasing Influence of a Priori Hypotheses......Page 200
Outline of Proposed Method......Page 201
Qualitative Researcher......Page 202
ZMET Data Collection......Page 203
ZMET Analysis......Page 205
The Hypothesis Test......Page 206
Limitations of the Proposed Method......Page 207
Applicability of the Proposed Method......Page 208
References......Page 209
Forecasting Sales of Comparable Units with Data Envelopment Analysis (DEA)......Page 214
Introduction......Page 215
Data Envelopment Analysis (DEA)......Page 216
New Regression Forecasting Methodology......Page 218
Example of Regression Analysis of Comparable Units......Page 219
References......Page 221
Appendix......Page 223
Data Mining Reliability: Model-Building with MARS and Neural Networks......Page 228
Data Mining, Reliability, and Model-Building......Page 229
Forward Stepwise Regression......Page 231
Network Architecture......Page 232
Solving the Network: ‘‘Training’’ Multi-Layer Perceptrons......Page 233
Multivariate Adaptive Regression Splines......Page 234
Previous Studies......Page 235
Study Protocol......Page 237
Data Development......Page 239
Accuracy......Page 240
Overall......Page 242
Underfit......Page 244
Overfit......Page 245
Underfit......Page 246
Conclusions......Page 250
References......Page 252
Appendix: Data Description......Page 253
Introduction......Page 256
Variance and Forecasting Accuracy......Page 257
Accuracy Determined by Selected Interval......Page 258
Conclusion......Page 259
Forecasting Simultaneous Brand Life Cycle Trajectories......Page 260
Real Markets and an Equivalent URN Model......Page 261
The Probability Density Governing Simultaneous Market Shares......Page 262
Using Current Market Output Signals to Update the Prior Share Estimates......Page 263
Increasing the Relative Weight of New Information......Page 264
An Efficient Algorithm for Revising Conditional Probabilities Sequentially......Page 265
An Application: Measuring the Market Shares of Five Competing Brands......Page 266
Consistent, Simultaneous Share and Life Cycle Forecasts......Page 268
Forecast the Shares of the Brands in Category 1 for Declining Brands......Page 269
Identify the Dominant Growth Brand in Category 2......Page 270
Forecast the Market Share of the Dominant Growth Brand......Page 271
Forecast the Shares of the Remaining Brands in Category 2......Page 272
Forecast Compared with Actual......Page 273
Summary and Conclusions......Page 275
References......Page 276
Introduction......Page 278
Types of Psychological Biases......Page 279
Cognitive......Page 280
Philosophical Orientation......Page 282
Organizational......Page 283
Categories of Biases......Page 285
Summary......Page 286
References......Page 287
Introduction......Page 290
Forecast Combination......Page 291
Case Study......Page 294
Stage 3: Generation of Alternative Combined Forecasts......Page 295
Discussion......Page 297
References......Page 299