Author: Dominique M. Hanssens
Publisher: Springer Science & Business Media
ISBN: 9781402073687
Category : Business & Economics
Languages : en
Pages : 524
Book Description
This second edition of Market Response Models: -places much more emphasis on the basic building blocks of market response modeling: markets, data, and sales drivers, through a separate chapter. -splits the design of response models into separate chapters on static and dynamic models. -discusses techniques and findings spawned by the marketing information revolution, e.g., scanner data. -emphasizes new insights available on marketing sales drivers, especially improved understanding of sales promotion. -demonstrates methodological developments to assess long-term impacts, where present, of current marketing efforts. -includes a new chapter on sales forecasting. -adds mini-case histories in the form of boxed inserts entitled Industry Perspectives, which are primarily written by business executives. This book is truly the foundation of market response modeling.
Market Response Models
Author: Dominique M. Hanssens
Publisher: Springer Science & Business Media
ISBN: 9781402073687
Category : Business & Economics
Languages : en
Pages : 524
Book Description
This second edition of Market Response Models: -places much more emphasis on the basic building blocks of market response modeling: markets, data, and sales drivers, through a separate chapter. -splits the design of response models into separate chapters on static and dynamic models. -discusses techniques and findings spawned by the marketing information revolution, e.g., scanner data. -emphasizes new insights available on marketing sales drivers, especially improved understanding of sales promotion. -demonstrates methodological developments to assess long-term impacts, where present, of current marketing efforts. -includes a new chapter on sales forecasting. -adds mini-case histories in the form of boxed inserts entitled Industry Perspectives, which are primarily written by business executives. This book is truly the foundation of market response modeling.
Publisher: Springer Science & Business Media
ISBN: 9781402073687
Category : Business & Economics
Languages : en
Pages : 524
Book Description
This second edition of Market Response Models: -places much more emphasis on the basic building blocks of market response modeling: markets, data, and sales drivers, through a separate chapter. -splits the design of response models into separate chapters on static and dynamic models. -discusses techniques and findings spawned by the marketing information revolution, e.g., scanner data. -emphasizes new insights available on marketing sales drivers, especially improved understanding of sales promotion. -demonstrates methodological developments to assess long-term impacts, where present, of current marketing efforts. -includes a new chapter on sales forecasting. -adds mini-case histories in the form of boxed inserts entitled Industry Perspectives, which are primarily written by business executives. This book is truly the foundation of market response modeling.
Market Response Models
Author: Dominique M. Hanssens
Publisher: Springer Science & Business Media
ISBN: 0306475944
Category : Business & Economics
Languages : en
Pages : 507
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 0306475944
Category : Business & Economics
Languages : en
Pages : 507
Book Description
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.
Market Response Models: Econometric and Time Series Analysis
Author: Dominique M. Hanssens
Publisher: Springer Science & Business Media
ISBN: 9400910738
Category : Business & Economics
Languages : en
Pages : 389
Book Description
This book reports over a decade's worth of research on the development of empirical response models that have important uses for generating marketing knowledge and improving marketing decisions. Some of its contributions to marketing are the following: 1. It integrates state-of-the art technical material with discussions of its relevance to management. 2. It provides continuity to a research stream over 20 years old. 3. It illustrates how marketing generalizations are the basis of marketing theory and marketing knowledge. 4. It shows how the research can be applied to marketing planning and forecasting. 5. It presents original research in marketing. The book addresses both marketing researchers and marketing managers. This can be done because empirical decision models are helpful in practice and are also based on theories of response. Econometric and time series analysis (ETS) is one of the few areas in marketing where there is little, if any, conflict between the academic sphere and the world of professional practice. Market Response Models is a sequel to Marketing Models and Econometric Research, published in 1976. It is rare for a research-oriented book in market ing to be updated or to have a sequel. Unlike many other methodologies, ETS research in marketing has stood the test of time. It remains the main method for discovering relations among marketing variables.
Publisher: Springer Science & Business Media
ISBN: 9400910738
Category : Business & Economics
Languages : en
Pages : 389
Book Description
This book reports over a decade's worth of research on the development of empirical response models that have important uses for generating marketing knowledge and improving marketing decisions. Some of its contributions to marketing are the following: 1. It integrates state-of-the art technical material with discussions of its relevance to management. 2. It provides continuity to a research stream over 20 years old. 3. It illustrates how marketing generalizations are the basis of marketing theory and marketing knowledge. 4. It shows how the research can be applied to marketing planning and forecasting. 5. It presents original research in marketing. The book addresses both marketing researchers and marketing managers. This can be done because empirical decision models are helpful in practice and are also based on theories of response. Econometric and time series analysis (ETS) is one of the few areas in marketing where there is little, if any, conflict between the academic sphere and the world of professional practice. Market Response Models is a sequel to Marketing Models and Econometric Research, published in 1976. It is rare for a research-oriented book in market ing to be updated or to have a sequel. Unlike many other methodologies, ETS research in marketing has stood the test of time. It remains the main method for discovering relations among marketing variables.
Building Models for Marketing Decisions
Author: Peter S.H. Leeflang
Publisher: Springer Science & Business Media
ISBN: 146154050X
Category : Business & Economics
Languages : en
Pages : 642
Book Description
This book is about marketing models and the process of model building. Our primary focus is on models that can be used by managers to support marketing decisions. It has long been known that simple models usually outperform judgments in predicting outcomes in a wide variety of contexts. For example, models of judgments tend to provide better forecasts of the outcomes than the judgments themselves (because the model eliminates the noise in judgments). And since judgments never fully reflect the complexities of the many forces that influence outcomes, it is easy to see why models of actual outcomes should be very attractive to (marketing) decision makers. Thus, appropriately constructed models can provide insights about structural relations between marketing variables. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions. Managers often use rules of thumb for decisions. For example, a brand manager will have defined a specific set of alternative brands as the competitive set within a product category. Usually this set is based on perceived similarities in brand characteristics, advertising messages, etc. If a new marketing initiative occurs for one of the other brands, the brand manager will have a strong inclination to react. The reaction is partly based on the manager's desire to maintain some competitive parity in the mar keting variables.
Publisher: Springer Science & Business Media
ISBN: 146154050X
Category : Business & Economics
Languages : en
Pages : 642
Book Description
This book is about marketing models and the process of model building. Our primary focus is on models that can be used by managers to support marketing decisions. It has long been known that simple models usually outperform judgments in predicting outcomes in a wide variety of contexts. For example, models of judgments tend to provide better forecasts of the outcomes than the judgments themselves (because the model eliminates the noise in judgments). And since judgments never fully reflect the complexities of the many forces that influence outcomes, it is easy to see why models of actual outcomes should be very attractive to (marketing) decision makers. Thus, appropriately constructed models can provide insights about structural relations between marketing variables. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions. Managers often use rules of thumb for decisions. For example, a brand manager will have defined a specific set of alternative brands as the competitive set within a product category. Usually this set is based on perceived similarities in brand characteristics, advertising messages, etc. If a new marketing initiative occurs for one of the other brands, the brand manager will have a strong inclination to react. The reaction is partly based on the manager's desire to maintain some competitive parity in the mar keting variables.
Evaluation of Econometric Models
Author: Jan Kmenta
Publisher: Academic Press
ISBN: 1483267342
Category : Business & Economics
Languages : en
Pages : 425
Book Description
Evaluation of Econometric Models presents approaches to assessing and enhancing the progress of applied economic research. This book discusses the problems and issues in evaluating econometric models, use of exploratory methods in economic analysis, and model construction and evaluation when theoretical knowledge is scarce. The data analysis by partial least squares, prediction analysis of economic models, and aggregation and disaggregation of nonlinear equations are also elaborated. This text likewise covers the comparison of econometric models by optimal control techniques, role of time series analysis in econometric model evaluation, and hypothesis testing in spectral regression. Other topics include the relevance of laboratory experiments to testing resource allocation theory and token economy and animal models for the experimental analysis of economic behavior. This publication is intended for students and researchers interested in evaluating econometric models.
Publisher: Academic Press
ISBN: 1483267342
Category : Business & Economics
Languages : en
Pages : 425
Book Description
Evaluation of Econometric Models presents approaches to assessing and enhancing the progress of applied economic research. This book discusses the problems and issues in evaluating econometric models, use of exploratory methods in economic analysis, and model construction and evaluation when theoretical knowledge is scarce. The data analysis by partial least squares, prediction analysis of economic models, and aggregation and disaggregation of nonlinear equations are also elaborated. This text likewise covers the comparison of econometric models by optimal control techniques, role of time series analysis in econometric model evaluation, and hypothesis testing in spectral regression. Other topics include the relevance of laboratory experiments to testing resource allocation theory and token economy and animal models for the experimental analysis of economic behavior. This publication is intended for students and researchers interested in evaluating econometric models.
Introduction to Estimating Economic Models
Author: Atsushi Maki
Publisher: Taylor & Francis US
ISBN: 9780415589871
Category : Economics
Languages : en
Pages : 0
Book Description
For beginning econometrics students or practitioners, the book illustrates the application of econometric methods to empirical analysis of economic issues perfectly. Its comprehensive treatment uncovers the missing link between economic theory and econometrics.
Publisher: Taylor & Francis US
ISBN: 9780415589871
Category : Economics
Languages : en
Pages : 0
Book Description
For beginning econometrics students or practitioners, the book illustrates the application of econometric methods to empirical analysis of economic issues perfectly. Its comprehensive treatment uncovers the missing link between economic theory and econometrics.
Applied Regression Analysis in Econometrics
Author: Howard E. Doran
Publisher: CRC Press
ISBN: 9780824780494
Category : Technology & Engineering
Languages : en
Pages : 400
Book Description
A textbook for a one-semester course for advanced undergraduate and graduate students in economics. Covers regression techniques in the context of single equation econometric models, featuring MINITAB and SHAZAM software examples for attacking real-world problems. Annotation copyright Book News, Inc
Publisher: CRC Press
ISBN: 9780824780494
Category : Technology & Engineering
Languages : en
Pages : 400
Book Description
A textbook for a one-semester course for advanced undergraduate and graduate students in economics. Covers regression techniques in the context of single equation econometric models, featuring MINITAB and SHAZAM software examples for attacking real-world problems. Annotation copyright Book News, Inc
Time Series and Panel Data Econometrics
Author: M. Hashem Pesaran
Publisher: Oxford University Press, USA
ISBN: 0198759983
Category : Business & Economics
Languages : en
Pages : 1095
Book Description
The book describes and illustrates many advances that have taken place in a number of areas in theoretical and applied econometrics over the past four decades.
Publisher: Oxford University Press, USA
ISBN: 0198759983
Category : Business & Economics
Languages : en
Pages : 1095
Book Description
The book describes and illustrates many advances that have taken place in a number of areas in theoretical and applied econometrics over the past four decades.
Multiple Time Series Models
Author: Patrick T. Brandt
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121
Book Description
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121
Book Description
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
Introduction to Modern Time Series Analysis
Author: Gebhard Kirchgässner
Publisher: Springer Science & Business Media
ISBN: 9783540687351
Category : Business & Economics
Languages : en
Pages : 288
Book Description
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.
Publisher: Springer Science & Business Media
ISBN: 9783540687351
Category : Business & Economics
Languages : en
Pages : 288
Book Description
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.