An Economic Approach to a Marketing Decision Model

Overview

This book describes the creation of a simulation model that is designed to serve as an artificial test market. The market is sufficiently realistic to permit it to be used for experimenting with a wide range of alternative marketing programs for a manufacturer of a branded,frequently purchased food product.The simulator includes characterizations by brand and size of: (1)the rates of retailer promotions (such as retail price discounts, newspaper advertising, displays,signs and banners, special offers, and ...

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Overview

This book describes the creation of a simulation model that is designed to serve as an artificial test market. The market is sufficiently realistic to permit it to be used for experimenting with a wide range of alternative marketing programs for a manufacturer of a branded,frequently purchased food product.The simulator includes characterizations by brand and size of: (1)the rates of retailer promotions (such as retail price discounts, newspaper advertising, displays,signs and banners, special offers, and premiums) as a function of the promotional allowances offered by competing manufacturers; (2) the response of costumers in terms of sales volume to the aforementioned retailer's promotional activities; and (3) the transformation of these volume movement figures into estimates of manufacturer profitability. The simulation model is designed to take advantage of modern time-sharing computation facilities and permit virtually instantaneous assessment of alternatives, and to encourage the combining of executive judgments on current market conditions and probable retailer responses with historical data.In order to develop the component of the stimulator which relates retailer promotional activities to consumer volume movement,econometric methods are used to analyze a remarkably complete set of data in such a way that the reader may follow the author's thought processes as they work through complex quantitative techniques. The econometric model that they develop is a multiple-equation model. The use of this type of model is relatively new in marketing, although econometricians have been familiar with these techniques for a number of years. The present study develops and discusses the special statistical methods required to estimate the parameters of such a model and postulates a specific model linking the demand for a given brand and size to the promotional activities of all the brand-size combinations present in the marketplace for the product in question.

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Product Details

  • ISBN-13: 9780262561891
  • Publisher: MIT Press
  • Publication date: 4/15/1971
  • Pages: 236
  • Product dimensions: 5.90 (w) x 9.00 (h) x 0.70 (d)

Table of Contents

1 Objectives and Strategy 1

1.1 Our Objective and Its Context 1

1.2 The Product's Marketing System 1

1.3 Our Model-Building Strategy 3

1.4 The Need for Coding 5

1.5 Organization of the Study 5

2 The Data 8

2.1 Introduction 8

2.2 The Audit 8

2.3 Coding Procedures and Initial Variable Definitions 11

2.4 Summary 17

3 Single-Equation Analysis 18

3.1 Introduction 18

3.2 Logical Flow of the Analysis 19

3.3 A Methodological Comment on the Single-Equation Variable Specifications 19

3.4 Initial Formulation of the Model 22

3.5 Store Differences in Response 30

3.6 Reformulating the Model 39

3.7 Concluding Comment 42

4 Theory of the Multiple-Equation Model 44

4.1 Introduction 44

4.2 Promotional Interaction 45

4.3 Definition of the Multiple-Equation System 50

4.4 Estimation Methods for the Multiple-Equation Model 62

Appendix 4A Matrix Representation of the Multiple-Equation Model 65

Appendix 4B The Instrumental Variables Estimating Procedure 66

5 Experiments with the Multiple-Equation Model 69

5.1 Introduction 69

5.2 Empirical Comparison of Least Squares and Instrumental Variables Estimation 69

5.3 An Alternative Set of Y-Summary Variable Definitions 73

5.4 Time Trend and AD-NPL Interaction Experiments 75

5.5 Absolute AD-Price Definitions 80

5.6 The Final Multiple-Equation Model 84

6 Results of the Multiple-Equation Analysis 87

6.1 Introduction 87

6.2 Predictive Efficacy 87

6.3 Structure: Main Effects 91

6.4 Reduced Form Analysis 109

6.5 Concluding Statement 116

7 Results of the Residuals Analysis 117

7.1 Introduction 117

7.2 Needed: A "Cleaner" Measure of Sales 118

7.3 Method of Analysis 120

7.4 Results 122

7.5 Concluding Statement 130

8 Simulation of Promotional Effects 132

8.1 Overview of the Model 132

8.2 Detailed Description of the Simulation 138

8.3 Technical Considerations 162

8.4 Conclusions 171

Appendix 8A Sample Output from the Simulation 173

Appendix A Coding Conventions 186

Appendix B Tables 188

Bibliography 220

Index 221

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