Market Response Models

Market Response Models PDF

Author: Dominique M. Hanssens

Publisher: Springer Science & Business Media

Published: 2005-12-19

Total Pages: 507

ISBN-13: 0306475944

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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

Market Response Models PDF

Author: Dominique M. Hanssens

Publisher: Springer Science & Business Media

Published: 2003-01-31

Total Pages: 524

ISBN-13: 9781402073687

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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.

Modeling Dynamic Relations Among Marketing and Performance Metrics

Modeling Dynamic Relations Among Marketing and Performance Metrics PDF

Author: Koen H. Pauwels

Publisher: Foundations and Trends (R) in Marketing

Published: 2018-12-05

Total Pages: 90

ISBN-13: 9781680834901

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Details the analysis steps, interpretation and marketing insights from traditional time series models and econometric models. The objective of this monograph is to give you a foundation in these models and to enable you to apply them to your own research domain of interest.

Market Response Models: Econometric and Time Series Analysis

Market Response Models: Econometric and Time Series Analysis PDF

Author: Dominique M. Hanssens

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 389

ISBN-13: 9400910738

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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.

Handbook of Marketing Decision Models

Handbook of Marketing Decision Models PDF

Author: Berend Wierenga

Publisher: Springer Science & Business Media

Published: 2008-09-11

Total Pages: 621

ISBN-13: 0387782125

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Marketing models is a core component of the marketing discipline. The recent developments in marketing models have been incredibly fast with information technology (e.g., the Internet), online marketing (e-commerce) and customer relationship management (CRM) creating radical changes in the way companies interact with their customers. This has created completely new breeds of marketing models, but major progress has also taken place in existing types of marketing models. The HANDBOOK OF MARKETING DECISION MODELS presents the state of the art in marketing decision models, dealing with new modeling areas such as customer relationship management, customer value and online marketing, but also describes recent developments in other areas. In the category of marketing mix models, the latest models for advertising, sales promotions, sales management, and competition are dealt with. New developments are presented in consumer decision models, models for return on marketing, marketing management support systems, and in special techniques such as time series and neural nets. Not only are the most recent models discussed, but the book also pays attention to the implementation of marketing models in companies and to applications in specific industries.

Time Series and Panel Data Econometrics

Time Series and Panel Data Econometrics PDF

Author: M. Hashem Pesaran

Publisher: Oxford University Press, USA

Published: 2015

Total Pages: 1095

ISBN-13: 0198759983

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This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.

Time Series Models for Business and Economic Forecasting

Time Series Models for Business and Economic Forecasting PDF

Author: Philip Hans Franses

Publisher: Cambridge University Press

Published: 2014-04-24

Total Pages: 421

ISBN-13: 1139952129

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With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.

Applied Econometrics with R

Applied Econometrics with R PDF

Author: Christian Kleiber

Publisher: Springer Science & Business Media

Published: 2008-12-10

Total Pages: 229

ISBN-13: 0387773185

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R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

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