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2015 | Buch

Modeling Markets

Analyzing Marketing Phenomena and Improving Marketing Decision Making

verfasst von: Peter S.H. Leeflang, Jaap E. Wieringa, Tammo H.A. Bijmolt, Koen H. Pauwels

Verlag: Springer New York

Buchreihe : International Series in Quantitative Marketing

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Über dieses Buch

This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions. The market environment is changing rapidly and constantly. Prior to the introduction of scanner equipment in retail outlets, ACNielsen, the major supplier of information on brand performance, claimed that its business was to provide the score but not to explain or predict it. With technological advances and the introduction of the Internet, the opportunity to obtain meaningful estimates of demand functions has vastly improved; models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today’s environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Building Models for Markets
Abstract
Managers often use rules of thumb for decisions. For example, a brand manager may have defined a specific set of 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 marketing variables. An economic perspective, however, would suggest that the need for a reaction depends on the impact of the marketing activity for the other brand on the demand for the manager’s brand. The models we present and discuss in this book are designed to provide managers with such information.
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 2. Model Specification
Abstract
Specification is an important step in the model building process. As discussed in Chap. 1, the goal of this step is to express the most important elements of a real-world system in one or more mathematical equations. In other words: the outcome of this step is a formula that summarizes the most important relationships of the phenomenon that we are studying.
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 3. Data
Abstract
Decision making in marketing must be based on appropriate, high quality data. Revolutionary developments in data collection during the last few decades offer many opportunities for advanced model building and the application of advanced research methods. For example, with the scanning revolution, the Internet invasion (Little 2004) and the “Big Data” era (see Pauwels 2014) , we observed exponential increases in the availability of data.
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 4. Estimation and Testing
Abstract
In this chapter we turn to estimation, the step in the marketing model building process that follows model specification, where we consider methods and procedures for obtaining numerical values for the model parameters in the model. Throughout this chapter we will mainly consider the case where the independent variables are linearly related to the dependent variable or where one or more variables can be transformed in such a way that the relation between the variables becomes linear. In such cases, it is appropriate to estimate a linear model. Linear models do not only provide reasonable specifications for many practical applications, they are also attractive for a careful treatment of model assumptions, and for a conceptual explanation of the basis for the assumptions. Most of the principles that apply to the linear model remain relevant as long as nonlinear effects for the original variables can be accommodated by transforming variables (so that the transformed variables are linearly related).
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 5. Validation and Testing
Abstract
Two critical steps in the model building process are model specification and model estimation. In this chapter we turn to the next stage in model building: validation (also verification or evaluation).
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 6. Re-estimation: Introduction to More Advanced Estimation Methods
Abstract
In this chapter we consider methods and procedures for the estimation of model parameters in cases where the basic assumptions of the general linear model are violated. When this is the case we need either other specifications and/or other estimation methods: “re-estimation”. In Sect. 6.2 we introduce Generalized Least Squares (GLS) estimation methods.
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 7. Examples of Models for Aggregate Demand
Abstract
In this chapter we give some examples of marketing models which have been estimated using the general linear model. Most of these models have been estimated using aggregate demand data. Aggregate demand refers to the demand across a sample of customers or households and can be measured at levels such as store, chain and market demand.
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 8. Individual Demand Models
Abstract
Big Data obtained through web search, digital media, e-commerce, mobile and social media have become important for understanding consumers’ behavior. Studying and modeling individual behavior has become more and more the focus in marketing research. Individual demand constitutes an important part of individual behavior, but we are now also able to study word-of-mouth (WOM-behavior), online-browsing
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 9. Examples of Database Marketing Models
Abstract
Database marketing and list management are more vital than ever, as marketers have troves of consumer information at their fingertips (Marketing News, October 2013, p. 54).
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Chapter 10. Use: Implementation Issues
Abstract
In this chapter we discuss several issues that are related to the actual use of a model. We first examine the determinants of model implementation. We categorize the dimensions that contribute to the likelihood of implementation as follows:
  • model-related dimensions;
  • organization-related dimensions;
  • implementation-strategy dimensions.
Peter S. H. Leeflang, Jaap E. Wieringa, Tammo H. A. Bijmolt, Koen H. Pauwels
Backmatter
Metadaten
Titel
Modeling Markets
verfasst von
Peter S.H. Leeflang
Jaap E. Wieringa
Tammo H.A. Bijmolt
Koen H. Pauwels
Copyright-Jahr
2015
Verlag
Springer New York
Electronic ISBN
978-1-4939-2086-0
Print ISBN
978-1-4939-2085-3
DOI
https://doi.org/10.1007/978-1-4939-2086-0