Hawkins et al-Marketing Productivity
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Transcript Hawkins et al-Marketing Productivity
The Nature and Measurement of
Marketing Productivity in Consumer
Durables Industries: A Firm Level
Analysis
HAWKINS, DELL I, ROGER J. BEST AND
CHARLES M. LILLIS (1987), “THE NATURE
AND MEASUREMENT OF MARKETING
PRODUCTIVITY IN CONSUMER DURABLES
INDUSTRIES: A FIRM LEVEL ANALYSIS,”
JOURNAL OF THE ACADEMY OF MARKETING
SCIENCE, 15 (4), 1-8.
Authors
Del I. Hawkins
Professor of Marketing
Various marketing Journals and Textbooks
Roger J. Best
Associate Professor of Marketing
Journals and Textbooks
Charles M. Lillis
Vice President of Strategic Marketing for US WEST
Inc.
Various Journals
Marketing executive
Purpose of the Article
Develop a managerially relevant concept of
marketing productivity
Construct an operational measurement of
marketing productivity-a validity issue
Establish environment specific benchmarks
with which to compare the marketing
productivity of various businesses
Model Development
How the authors develop the model step by step is
a good learning exercise (this is one of the reason I
have included this article in the reading list)
Define the variables first
Explain conceptualization and limitation of variables
Identify their relevance in the area
Operationalize the variables-validity
Testing the model with credible data
Explain limitations
Model has no meaning in isolation, relative to
what is the question
The Nature of Marketing Productivity
Concept of Productivity: Output/Input
Marketing productivity = marketing output
divided by marketing input
Marketing Output = (Relative market share) x
(Relative Price)
Marketing input= (Marketing Expenditures)
/(Sales)
Percentage or ratio measures, not in absolute
dollars
Marketing Productivity
Marketing Productivity Formula:
Relative Market Share x Relative Price
Marketing Expenditures/Sales
» Marketing Productivity Score (MPS) – In
isolation it has no meaning !
» Marketing Productivity Index (MPI)
PIMS Database
(now Marketing Science Institute)
Sources of data: firms pay a fee to join
PIMS
Self reported data, multiplied by an
unknown constant when supplied to PIMS
Questionnaire is provided by PIMS
Operational Definitions of Variables (ses
Table 1)
Variables Influencing Marketing Productivity
Variables
Influence
Relative Product Breadth (RPB)
+
Number of Competitors (NC)
-
Relative Product Quality (RPQ)
+
Relative Customer Size Range (RCSR)
+
Served Market Growth (SMG)
+
Number of Immediate Customer (NIC)
-
Importance of Auxiliary Services to End User
(IASE)
-
Frequency of Product Changes (FPC)
-
Purchase Amount Immediate Customers (PAIC)
+
Customization (C)
+
Construction of the Model
Firms
Correlation
Model
• Durables and Nondurables
• 135 Firms
• Correlation between Y and X1,….,X10
• Correlation between X1,….,X10
• Regression Equation Y= X1+………+X10
Correlation Analysis
Model Evaluation
R² is significant
Model is reasonably stable
Durables, nondurables, split-half…..all
supports the model
Supports the overall structure of the model
developed for the durables industries
Variables that were collinear were removed
before implementing the model
Critique of the Article
Positive Contribution:
First of its kind
Reasonable model
Credible database
Coming from industry
Questionable Issues
Limitation in variable definition
Variability in the dataset
Collinearity
Future direction
Discussion Questions
What is marketing productivity? What problems
do we face in measuring productivity? How can
we overcome them?
What are the drawbacks/limitations of the
Hawkins et al.’s (1987) marketing productivity
score/index? Can we apply the index to measure
productivity in other industries? How?
Write a critique of the article.