Market Response Models: Econometric and Time Series Analysis, Том 2Springer Science & Business Media, 31 янв. 2003 г. - Всего страниц: 502 From 1976 to the beginning of the millennium—covering the quarter-century life span of this book and its predecessor—something remarkable has happened to market response research: it has become practice. Academics who teach in professional fields, like we do, dream of such things. Imagine the satisfaction of knowing that your work has been incorporated into the decision-making routine of brand managers, that category management relies on techniques you developed, that marketing management believes in something you struggled to establish in their minds. It’s not just us that we are talking about. This pride must be shared by all of the researchers who pioneered the simple concept that the determinants of sales could be found if someone just looked for them. Of course, economists had always studied demand. But the project of extending demand analysis would fall to marketing researchers, now called marketing scientists for good reason, who saw that in reality the marketing mix was more than price; it was advertising, sales force effort, distribution, promotion, and every other decision variable that potentially affected sales. The bibliography of this book supports the notion that the academic research in marketing led the way. The journey was difficult, sometimes halting, but ultimately market response research advanced and then insinuated itself into the fabric of modern management. |
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Содержание
RESPONSE MODELS FOR MARKETING MANAGEMENT | 3 |
Modeling Marketing Systems | 4 |
Empirical Response Models | 8 |
Marketing Management Tasks | 10 |
Marketing Information | 13 |
ModelBased Planning and Forecasting | 16 |
Plan of the Book | 19 |
MARKETS DATA AND SALES DRIVERS | 23 |
Univariate Time Series Models | 262 |
Model Identification and Estimation | 269 |
Evolution vs Stationarity | 279 |
MULTIPLE MARKETING TIME SERIES | 285 |
The Transfer Function Model | 286 |
Multivariate Persistence | 298 |
Incorporating Longterm Equilibrium Conditions | 303 |
Diagnosing LongTerm Marketing Strategic Scenarios | 305 |
Markets | 24 |
Data | 25 |
Response Measures and Drivers | 48 |
Aggregation | 70 |
Road Map of Market Response Modeling Techniques | 75 |
MARKET RESPONSE IN STATIONARY MARKETS | 87 |
DESIGN OF STATIC RESPONSE MODELS | 89 |
Relations Among Variables | 90 |
Functional Forms | 94 |
Aggregation of Relations | 129 |
DESIGN OF DYNAMIC RESPONSE MODELS | 139 |
Specification Issues in Dynamic Models | 140 |
DiscreteTime Models of Carryover | 142 |
Shape of the Response Function Revisited | 156 |
Reaction Functions | 166 |
Temporal Aggregation Revisited | 173 |
Marketing Models and Prior Knowledge | 178 |
PARAMETER ESTIMATION AND MODEL TESTING | 183 |
Classification of Variables | 184 |
Estimation | 185 |
Testing | 201 |
Flexible Functional Forms | 225 |
Model Selection | 229 |
Confirmatory vs Exploratory Data Analysis | 240 |
MARKET RESPONSE IN EVOLVING MARKETS | 249 |
SINGLE MARKETING TIME SERIES | 251 |
Why Analyze Single Marketing Time Series? | 252 |
The Components of a Time Series | 253 |
Empirical Causal Ordering | 309 |
On Using Time Series Analysis | 315 |
MARKETING PROBLEMS WITH ETS | 317 |
EMPIRICAL FINDINGS AND MANAGERIAL INSIGHTS | 319 |
Measuring Marketing Effects | 320 |
Empirical Marketing Generalizations | 324 |
BrandLevel Findings and Generalizations | 328 |
IndustryLevel Findings and Generalizations | 350 |
MAKING MARKETING PLANS AND SALES FORECASTS | 357 |
Optimal Marketing Decisions | 358 |
Embedded Competition | 367 |
Forecasting | 374 |
Automatic Forecasting Systems | 386 |
Forecasting with Market Response Models | 390 |
Simulation with Market Response Models | 398 |
Combining Forecasting Methods and Models | 399 |
CONCLUSION | 405 |
IMPLEMENTATION | 407 |
Nature of Implementation | 408 |
Factors Affecting Implementation | 412 |
The Demand for Market Response Models | 420 |
BIBLIOGRAPHY | 427 |
481 | |
489 | |
491 | |
493 | |
Другие издания - Просмотреть все
Market Response Models: Econometric and Time Series Analysis Dominique M. Hanssens,Leonard J. Parsons,Randall L. Schultz Ограниченный просмотр - 2006 |
Market Response Models: Econometric and Time Series Analysis Dominique M. Hanssens,Leonard J. Parsons,Randall L. Schultz Недоступно для просмотра - 2001 |
Market Response Models: Econometric and Time Series Analysis Dominique M. Hanssens,Leonard J. Parsons,Randall L. Schultz Недоступно для просмотра - 2003 |
Часто встречающиеся слова и выражения
actions advertising aggregation alternative analysis applications approach assumed assumption average behavior better brand budget called Chapter coefficients combined competitive competitors constant consumer customers decision demand dependent determined developed discussed distribution dynamic econometric effects effort elasticity empirical equal equation error estimated example expenditures factors Figure findings firm forecasting functional form given impact implementation important increase individual industry involves Journal known lead least linear managers market response models market share marketing mix mean measure method multiplicative observations obtained occur optimal parameters pattern performance period planning positive predicted problem promotion purchase reaction regression relation relative represent requires retail rule sales response function sample scanner seasonal shown shows Source specification squares statistical structure Table techniques unit usually variables volume zero
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