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. |
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
ACNielsen adstock Advertising Effects advertising expenditures aggregation approach ARMA autocorrelation autoregressive behavior Blattberg Box-Jenkins brand budget carryover causal Chapter coefficients collinearity competitive reaction competitors consumer correlated coupon cross-elasticities customers decision rule dependent variable discussed distributed lag dummy variables dynamic Economics empirical equation error example explanatory variables firm functional form Hanssens heteroscedasticity impact implementation increase industry Journal of Marketing lag operator least squares Leeflang linear model long-run market response models market share models marketing decision marketing effort marketing instruments marketing managers marketing mix Marketing Models Marketing Research Marketing Science matrix measure method multiplicative nonlinear null hypothesis observations optimal Partial Autocorrelation performance period planning and forecasting predicted price elasticity problem product category promotion purchase Q₁ reaction functions relation residuals retail sales response function sample scanner data Schultz specification stationary statistical structure transfer function vector w₁ Wittink zero
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