Building Models for Marketing Decisions
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 outcome
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BUILDING MODELS FOR MARKETING DECISIONS by
Peter S.H. Leeflang University ofGroningen, The Netherlands
Dick R. Wittink Yale School of Management, U.S.A. and University ofGroningen, The Netherlands
Michel Wedel University ofGroningen, The Netherlands and
Philippe A. Naert Tilburg University, The Netherlands
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
Library of Congress Cataloging-in-Publication Data
ISBN 978-0-7923-7813-6 DOI 10.1007/978-1-4615-4050-2
ISBN 978-1-4615-4050-2 (eBook)
Printed on acid-free paper
All Rights Reserved © 2000 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 2000 Softcover reprint of the hardcover I st edition 2000 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.
To our spouses: Hanneke Marian Rennie Magda
Contents
Preface . . . . . . . . . . . . . . .
Xlll
PART ONE: Introduction to marketing models
2
Introduction . 1.1 Purpose 1.2 Outline 1.3 The model concept
10
Classifying marketing models according to degree of explicitness 2.1 Implicit models 2.2 Verbal models . . . . . . 2.3 Formalized models . . . . 2.4 Numerically specified models
13 13 13 15 18
3 4 7
3 Benefits from using marketing models 3.1 Are marketing problems quantifiable? 3.2 Benefits from marketing decision models 3.3 Building models to advance our knowledge of marketing 3.4 On the use of a marketing model: a case study
21 24 28 32
4
A typology of marketing models
37
4.1 4.2
37
4.3 4.4 4.5
. . . . . . . Intended use: descriptive, predictive, normative models Demand models: product class sales, brand sales, and market share models . . . . . . . . Behavioral detail . . . . . . . . . . . Time series and causal models . . . . . . Models of"single" versus "multiple" products
21
40 41 44 45
PART TWO: Specification . .
47
5 Elements of model building 5.1 The model-building process 5.2 Some basic model-building terminology
49 49 55
CONTENTS
Vlll
5.3
6
85
Modeling lagged effects: one explanatory variable . . Modeling lagged effects: several explanatory variables Selection of(dynamic) models Lead effects . . . . . .
85 96 97 98
Implementation criteria with respect to model structure 7.1 7.2
7.3 7.4 7.5 8
Introduction Implementation criteria . . . . Models should be simple 7 .2.1 Models should be built in an evolutionary way 7.2.2 7.2.3 Models should be complete on important issues Models should be adaptive . . 7.2.4 Models should be robust . . . 7.2.5 Can non-robust models be good models? Robustness related to intended use Robustness related to the problem situation
Specifying models according to intended use . . . . . 8.1 Descriptive models 8.2 Predictive models 8.3 Normative models A profit maximization model 8.3.1 Allocation models . . . 8.3.2 Dorfman-Steiner theorem . The Appendix:
9
66 66 67 79
Marketing
