Table Of ContentOPTIMAL ADVERTISING SCHEDULING STRATEGIES IN THE PRESENCE OF
ADVERTISING WEAROUT
By
PRASAD ANAND NAIK
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1996
Copyright 1996
by
Prasad Naik
To my parents, Anand and Ratan,
who made sacrifices so that I may benefit.
.
ACKNOWLEDGMENTS
I deeply appreciate the collective and cumulative
efforts of the marketing faculty and graduate students in
building a remarkable doctoral program conducive for
intellectual growth. I am indeed fortunate to have been in
this wonderful setting, thanks to John Lynch. Here, I had
the freedom to pursue my academic interests: for this, I am
indebted to all my committee members. In particular, my
special thanks go to Prof. Alan Sawyer for his leadership on
my dissertation project, and to Prof. Murali Mantrala for
his encouragement and guidance at every step of the process.
I am obliged to several individuals who contributed to
this dissertation. Specifically, the concept of overlearning
is due to Alan Sawyer; repetition wearout is due to Joel
Cohen; the idea that ads may rejuvenate during media hiatus
is due to Joffre Swait and John Lynch; a two-state variable
control-theoretic formulation is due to Jonathan Hamilton;
the leads to advertising industry experts are due to Prof.
Kent Lancaster (Dept, of Advertising), Prof. Paul Farris
(University of Virginia) and John Lynch; the empirical data
,
sets were referred to me by Prof. Jeff Harrison (Chair,
Department of Statistics, University of Warwick, U.K) But,
IV
above all, the nurturing of all of these ideas is due to
Murali and Alan.
My sincere gratitude goes to several others who were
instrumental in my professional development, notably, Alan
Agresti, Ronald Ward, and Henri Theil, whose teachings
helped me appreciate the principles of statistics and
econometrics, Ira Horowitz and Kalyan Raman (University of
Michigan) for building my interests in stochastic process.
My special thanks go to Prof. Charles Moss (Dept, of Food
and Resource Economics) who taught me the concepts of Kalman
filtering, and to Prof. Murali Rao (Dept, of Mathematics)
for clarifying subtle issues that led to its deeper
understanding. I am really indebted to all of them.
Finally, I thank my family for instilling in me the
value of education, my friends for their emotional support,
and my wife, Chetana, for her love and understanding which
has made this endeavor worthwhile.
v
TABLE OF CONTENTS
ACKNOWLEDGMENTS iv
LIST OF TABLES X
LIST OF FIGURES xi
ABSTRACT xiv
ADVERTISING WEAROUT AND PULSING MEDIA SCHEDULES 1
Introduction 1
The Organization Of Dissertation 5
LITERATURE REVIEW 7
Overview 7
Definition of Media Schedules 11
Media Scheduling Strategies 12
Optimal Advertising Policies 12
Chattering schedule 15
An even schedule 16
Empirical Pulsing Policies 18
Field Experiments 18
Zielske and Henry (1980): An econometric study.... 20
Theoretical Pulsing Literature 24
Naslund (1979) 24
ADPULS (H. Simon 1982) 27
Luhmer, Stendl, Feichtinger, Hartl, Sorger
(1988) 28
Mesak (1985), (1992), Mesak and Darrat (1992) 31
Hahn and Hyun 1991 32
Feinberg (1992) 35
Competitive Models 36
A Summary of Pulsing Literature 37
Advertising Wearout, Ad Quality, and Overlearning 39
Advertising Wearout 39
What is ad wearout? 39
What causes wearout? 42
What are its consequences? 44
How to forestall wearout? 45
Quality of Advertisements 47
What is it? A definition 47
Why is ad quality important 49
Overlearning 50
vi
A MODEL OF ADVERTISING WEAROUT AND EMPIRICAL SUPPORT 51
Model Development 51
Awareness Formation 51
Advertising Wearout 52
Ad Quality Evolution During Media Hiatus 54
Overlearning 56
Model Summary 57
Empirical Analysis 58
Field Experimental Data 58
Description of wearout experiments 58
Estimation approach 60
Estimation results 61
Bootstrapping for small sample inference 63
Empirical Support and Models Comparison 65
Awareness Tracking Data 66
Alternative Awareness Formation Models 68
1. Vidale and Wolfe (1957) 68
2. Nerlove and Arrow (1962) 69
3. Brandaid (Little 1975) 69
4. Tracker (Blattberg and Golanty 1978) 70
5. Litmus (Blackburn and Clancy 1982) 70
6. News (Pringle, Wilson and Brody 1982) 70
7. Dodson and Muller (1978) 71
An Unified Estimation Framework for Dynamic Models .. 72
Estimation Results 73
Summary 85
THEORETICAL RESULTS FOR BLITZ AND TWO-PULSE SCHEDULES 86
Overview 86
Theoretical Blitz Schedule 87
Dynamics of Awareness in the Presence of Ad
Wearout 87
Result 1: Inverted-U awareness evolution 88
Result 2: Onset of wearout 90
Should Resources Be Concentrated or Spread Evenly? .. 91
Result 3: Revenues for any blitz schedule 92
Result 4: When is even schedule superior? 93
Result 5: Blitz is superior when ads wearout 93
A numerical example 94
A distinction between copy and repetition
wearout matters 96
Theoretical Two-pulse Schedules 98
Result 6: Ad quality dynamics 100
Result 7: Awareness dynamics 101
Result 8: Revenues generated by two-pulse
schedule 103
A Numerical Example 104
Revenue as a function of the duration of bursts.. 104
Result 9: Optimal two-pulse media schedule 105
Result 10: Effects of copy wearout 107
Result 11: Effects of repetition wearout 109
vii
Result 12: Effects of forgetting rate Ill
Summary 112
OPTIMAL MULTI-PULSE SCHEDULE 115
Introduction 115
Problem Statement 115
Solution Procedure 118
General 119
Optimal multi-pulse schedule: An application 121
Summary 129
CONCLUSIONS 131
Summary 131
Future Research 133
GLOSSARY 135
APPENDIX A IMPRESSIONS BASED ON AN INFORMAL SURVEY 138
APPENDIX B NOTATIONS 140
APPENDIX C BOOTSTRAPPING INFERENCE IN SMALL SAMPLE 142
APPENDIX D OPTIMAL STATE ESTIMATION 144
APPENDIX E AWARENESS EVOLUTION IN THE PRESENCE OF
WEAROUT 147
APPENDIX F AWARENESS PEAKS AT t* 150
APPENDIX G MONOTONICITY OF AWARENESS EVOLUTION IN THE
ABSENCE OF WEAROUT 152
APPENDIX H ON THE ONSET OF WEAROUT 153
APPENDIX I REVENUES FOR A BLITZ SCHEDULE 155
APPENDIX J SUPERIORITY OF AN EVEN SCHEDULE WHEN NO AD
WEAROUT 156
APPENDIX K SUPERIORITY OF BLITZ 159
APPENDIX L DERIVATION OF AD QUALITY DYNAMICS 162
APPENDIX M DERIVATION OF AWARENESS DYNAMICS 164
APPENDIX N DERIVATION OF REVENUES UNDER TWO PULSE
SCHEDULES 167
LIST OF REFERENCES 170
viii
iix
LIST OF TABLES
2-
Tab3l-e page
2-1. Empirical performance of media schedules 19
2-2. Performance of various media plans 22
3. Summary of the pulsing literature 40
1. Parameter estimates for experimental data 61
3-2. System matrices for awareness formation
models 76
3-3. Results for mature product models 78
3-4. Results for new product models 80
3-5. Estimates of ad wearout models 82
5-1. Pulsing schedules and the expected payoffs 107
x
