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An Empirically-Validated Framework
for Industrial
Pricing
Peter M.
Noble
Humbolt State University
Thomas
S.
Gruca
University
of
Iowa
ISBM
Report
9-1998
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U.Ed.
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98-070
An
Empirically-Validated
Framework
for
Industrial
Pricing
Peter
M.
Noble
Humbolt State
University
1
Harpst
St.
Arcata, CA
95521
(707)
826-3224
Thomas
S.
Gruca
College
of
Business
University
of
Iowa
Iowa
City,
IA
52242-1000
319-335-0946
(phone)
319-335-1956
(fax)
thomas-gruca~uiowa.
edu
A
previous
version
of
this
paper was
presented
at the
1995
INFORMS International
Conference
in
Singapore.
The authors
would
like
to
thank
Gerry
Tellis
and
Kent
Monroe
for
their
review
of
the survey
used
in
this
research.
An
Empirically-Validated
Framework
for
Industrial
Pricing
Abstract
We
propose
and
test
a parsimonious
and
comprehensive two-level
framework
for
industrial
goods
pricing
which allows
for
multiple
pricingstrategies
for
a
single
product. We
identify
a
reduced
set
of
cost,
product
and
information conditions determining which
strategy
type
(new
product,
competitive,
product
line,
cost-based)
is
optimal.
We frirther
identify
a set
of
unique determinants under
which
a
given
principal
strategy
within
each type
is
optimal.
For
example,
the competitive pricing
strategy
type
(leader,
parity
or
low
cost supplier)
should
be
used
in
the later stages
of
the
product
life cycle.
Leader pricing
should
be
used
by
firms
with high
market share whereas parity pricing
should
be
used
by
firms
with
high
costs.
A
firm
should
consider
a
low
priced supplier
strategy
if it
has
relatively
low
costs.
Similar
relationships
between
pricing strategies and
determinants
are developed
for
a comprehensive set
of
10
industrial
pricing
strategies.
We validated the framework
through
a
national
survey
of
pricing
managers
in
capital
goods
industries.
Using
censored
regression
models,
we
tested
(and
confirmed)
the
relationships
between
the determinants, pricing
strategy
types
and
individual
pricing strategies.
This
framework
provides
an
important
tool
to
help
managers
make better pricing
decisions.
It
is
grounded
in
sound economic
and
marketing
analyses
and consistent
with
actual
managerial
practice.
Furthermore,..this
study
answers the
call
of
many
authors to bridge the gap
between
the normative
research
on pricing
and
actual
managerial behavior.
1
Introduction
Pricing
is
one
of
the most important
and
complex
of
all
marketing
decisions.
There
is
a
wide range
of
product,
company
and
competitive conditions determining
which
pricing
strategy
or
strategies
should
be
used
in
a
given
situation
(Diamantopoulos
1991,
1994).
For
example,
in
the
classic
FIBR case,
“Deere
&
Company:
Industrial
EquipmentOperations,”
the price
for
a
new
model
of
bulldozer has to be determined
(Shapiro,
1977).
This
new
model
has
an
innovative
transmission that may increase productivity
significantly.
Therefore, a
skimming
strategy
should
be more profitable
than
penetration
pricing.
However,
since market leader
Caterpillar
offers
comparable
models, the pricing
strategy
hasto reflect
competitive
prices as
well.
In
addition,
Deere
will sell
spare
parts
that
represent
a
significant
income stream over the
life
of
the
product.
Maximizing
the
revenuestream
from the
entire
product
line
(accessories,
spare parts,
etc.)
is
another
important consideration
in
the pricing strategy.
Finally,
a
high
mark-up
over
unit
manufacturing costs would be desired to
quickly
recover
the
high
development
and
tooling costs
for
this
model.
Therefore,
in
this
typical
case
study,
there
can
be
one,
two
or
more types
of
pricing strategies (i.e.,
new
product,
competitive,
product
line
and
cost-based)
involved
in
a
single
pricing
decision.
How
does
the marketing literature
help
a manager facing such a
complex
pricing situation?
Unfortunately,
most normative research on
pricing
concentrates
on
only
one
or
two
narrow
aspects
of
the
situation.
For
example,
Schoell and
Guiltinan
(1995)
outline the conditions that
favor choosing
skimming
over
penetration
pricing
for
a
new
product. The notable exception
is
the
comprehensive literature review
by
Tellis
(1986).
In
his
review,
Tellis
develops a
unif~jing
framework
that
highlights
the
similarities
and
differences
among
a wide range
of
pricing
strategies.
Two
dimensions
of
shared economies
2
available
to a
firm
and
the consumer
conditions
necessary to
exploit
these
economies determine
which
of
nine pricing strategies
(or
their related
counterparts)
should
be
adopted
by
the
firm.
The
Tellis
framework
represents a major contribution to the literature since it
is
the
first
comprehensive
comparison
and
integration
of
pricing strategies
which
had,
heretofore, been
discussed
in
relative
isolation.
The
focus
of
the
Tellis
paper
on
providing a
classification system
for
as wide a range
of
pricing strategies as
possible
presents some
challenges
when trying to
apply
its
results to
practical
pricing
situations.
For
example,
the two conditions
identified
by
Tellis
define the best
single
choice
of
pricing strategies
for
a
firm.
However,
there
are
additional
requirements
associated with
relative
quality
or
costs that are necessary
forthe
choice
of
strategy
to be optimal
(Tellis,
1986:
Table
2). Unfortunately, the
Tellis
framework
does
not
address
the options
for
a
firm
not
in
an
advantaged
position
in
terms
of
costs
or
quality.
By
construction
and
in
the interest
of
clarity
of
presentation, the
Tellis
framework
assumes
that
only
one
strategy
should
be
used
in
a
given
situation.
However,
empirical
research
on
pricing
objectives
shows
that
multiple objectives
are often
used
simultaneously
(Shipley
1981,
Jobber
and
Hooley
1987,
Samiee
1987,
Coe
1983; 1988; 1990;
Diamantopoulos and Mathews;
1994).
We
expect (and
find)
that the same
is
true
in
pricing
strategy
decisions.
Managers often
use
more than
one pricing
strategy
in
setting the price
for
a
single
product
.
Finally,
the
Tellis
framework has not been
empirically
validated
(Lilien,
Kotler
and
Moorthy,
1992).
This
is
a
critical
step
in
the
development
of
managerial
prescriptions
for
pricing.
Since
all
models are
necessarily
simplifications
of
reality,
it
is
important to
compare
the normative
results with actual
practice
in
order to validate the assumptions
underlying
the
normative
models.
In this paper, we have more modest goals
in
terms
of
integrating the
existing
pricing
3
literature.
However,
by
focusing
on
a
smaller
set
of
industrial
pricing problems (capital
goods),
we are able to
achieve
closure
through
empirical
validation
of
our
proposed
framework.
Specifically,
we
propose
and
test
a
parsimonious
and
complete
two-level
(strategy
type-principal
strategy)
framework
for
industrial
goods
pricing
which
allows
for
multiple
pricing strategies
for
a
single
product.
We
identify
a
reduced
set
of
cost,
product
and information
conditions
under which
a
given
strategy
type
(new
product,
competitive,
product
line,
cost-based)
should
be
used. We
then
identify
a set
of
unique
conditions
under
which
a
principal
strategy
within
each type
should
be used.
For
example,
one type
of
pricing
strategy
encompasses the competitive pricing
strategies.
The
principal
strategies within
this
type are Leader
pricing,
Parity
pricing
and
Low-Price
supplier.
A competitive pricing
strategy
should
be
employed
in
the
latter
stages
of
the
product
life cycle.
With
this
type,
Leader
pricing
should
be
used
by
firms
with
high
market share whereas
Parity
pricing
should
be
used
by
firms
with
high
costs.
A
firm
should
use
a
Low-price
Supplier
strategy
if
it has
relatively
low
costs.
Similar
relationships
between
pricing
strategy
types,
principal
strategies and determinants are developed
for
a
comprehensive set
of
four
strategy
types and
10
principal
pricing strategies..
We validated
our
framework
through
a
national
survey
of
pricing managers
in
capital
goods
industries.
We asked
them
about
characteristics
of
the
product,
their
company
and
the
product-market
at the time
of
their
last
pricing
decision.
Using
limited
dependent
variable
regression
models,
we
confirmed
most
of
the expected relationships
between
the
proposed
determinants, pricing
strategy
types
and
principal
pricing strategies.
This
framework
provides an important tool to help
managers
make
better
pricing
decisions.
It
is
grounded
in
sound economic
and
marketing analyses
and
consistent with actual
managerial
practice.
Furthermore,
this
study
answers the
call
of
many
authors (Bonoma,
4
Crittenden and
Dolan,
1988;
Lilien,
Kotler,
and
Moorthy
1992;
Diamantopoulos,
1994)
to bridge
the gap
between
the normative research on pricingand actual
managerial
behavior.
Related
Research
Most
of
the
empirical
research
investigating
how
managers
set prices has focused on
identifying
the
objectives
used
by
managers
in
pricing decisions (Diamantopoulos,
1991).
The
major studies
(Kaplan,
Dirlam,
and
Lanzillotti,
1958;
Shipley,
1981;
Jobber
and
Hooley,
1987;
Samiee,
1987;
Coe,
1983, 1988,
and
1990;
and
Diamantopoulos
and Mathews,
1994)
have shown
that profit
maximization
is
used
by
many
firms,
but it
is
clearly
not
dominant
across
all
firms
(Diamantopoulos,
1994).
These
studies
also
show that most
firms
use
multiple
pricing
objectives,
the objectives
change
over
time
(Coe,
1983, 1988,
1990)
and
the
choice
of
objective
is
related
to
the
pricingenvironment
of
the
firm
(Diamantopoulos and
Mathews,
1994).
The study
of
pricing
objectives
can provide information
on
what the
firm
is
trying to
accomplish,
but objectives
do
not
tell
us much about
how
the
firm
will
accomplish those
objectives.
These
studies
do
not address the
issue
of
what pricing strategies
will
be
used
to
accomplish
the goals
of
the
firm.
For the
purpose
of
this
study,
objectives are defined as the
results a decision
maker
seeks to
achieve
(e.g., profit
maximization).
A pricing
strategy
is
the
means
by
which
a pricing objective
is
to be
achieved.
A pricing
strategy
implies
a
specific
price
level
or
schedule
related
to costs,
competition,
or
customers. Determinants are
the
internal
and
external
conditions that determine
managers’
choices
of
pricing strategies.
A
brief
example may
help
distinguish
these
constructs.
Consider a firm with a pricing
objective
of
maximizing
profitability
for
a new
product.
In one scenario,
customers
might
be
insensitive
to
price
and the
products
in
this market are
highly
differentiated.
The
firm
can
use
a
price
skimming
strategy
to
achieve
their
profit
maximization
objective (Nagle and Holden,
1995:
5
154-158).
In a second scenario, the same company
is
faced with
highly
price
sensitive
customers.
If
the
firm
can
reduce
its
unit costs
by
spreading
its
fixed
costs over a
high
volume
of
output, the
firm
can
use
a
penetration
pricing
strategy
to
achieve
the profit
maximization
objective (Nagle and
Holden,
1995:
159-160).
The
determinants
in
these
examples
were price
sensitivity,
product
differentiation,
and
potential
for
economies
of
scale.
Diamantopoulos
(1991,
1994)
refers to these
determinants
collectively
as the
“pricing
environment,”
describing
them
as the elements that
constitute
the
setting
within
which
price
decision-making takes
place.
It
is
the goal
of
this
study
to develop a
framework
for
industrial
pricing decisions
which
simplifies
the
pricing
environment
for
the manager
by
identifying
those
conditions which separate
strategy
types and
principal
strategies
within
type.
Previous
empirical
studies
that have investigated the
use
of
pricingstrategies have
generally been
limited
in
scope to researching
small
numbers
of
firms
or
to
identifying
strategies
withoutregard
to determinants
(Abratt
and Pitt,
1985;
Morris
and Pitt,
1993;
Udell,
1972).
Studies that have looked at both strategies and determinants
across
a
large
number
of
firms
have
generally
not
been
statistically
rigorous
(see Diamantopoulos
1991
for
review
of
these
studies).
The
validation
study presented
in
this
paper
remedies
these short-comings. Our
framework
is
discussed
next.
AFramework for Industrial Pricing Strategy
After
an
extensive
review
of
the
literature, we
identified
a
set
of
industrial
pricing
strategies and determinants
following
the example set
by
Tellis
(1986).
However,
our
study
focuses
on
the under-researched
area
of
industrial
(capital
goods)
pricing
while
the
Tellis
framework
is
more oriented
towards
consumer
products. To
accommodate
these
differences,
we
6
have made some
modifications
to
his
original
framework.
First,
we
did
not consider strategies
predominantly
used with consumer products
(i.e.,
defensive
pricing,
random discounts), strategies
for
export markets
(i.e.,
second market
discounting)
or
pricing tactics (e.g.,
basing
point
pricing).
Second, Cost-Plus pricing
and
Customer
Value pricing were added due to
their
prominence
in
previous
studies
of
industrial
pricing
(Morris
and Calantone,
1990).
The ten
principal
pricing strategies are
described
in
Table
1.
Table
1
about here
Note that a
related strategy
is
either part
of
the
principal
strategy
(e.g.,
Markup
Pricing
is
a form
of
Cost-Plus
Pricing)
or
is
similar
to the
principal
strategy.
That
is,
the related
strategy
is
one
which
can be
expected
to
occur
under
similar
conditions and result
in
a
similar
price
level
(e.g.,
Opportunistic Pricing
and
Low-Price
Supplier).
Strategy
Types
and
Principal
Strategies
We have
divided
these ten strategies into
four
strategy
types based on the
similarity
of
the
situations
for
which
they are appropriate. The
four
strategy
types are:
1)
new
product
strategies,
2)
product
line
strategies, 3) competitive strategies,
and
4)
cost-based
strategies.
New
product
strategies share the common
attribute
of
being strategies
which
are
applied
early
in
the
life
of
the
model
in
question.
Included
in
the
category
of
entry strategies are:
1)
Skim
Pricing,
2)
Penetration
Pricing,
and
3)
Experience
Curve
Pricing.
Competitive strategies have as
their
main
focus the price
of
the
product
relative to
the
price
of
one
or
more
competitors.. Competitive pricing strategies
include:
1)
Leader
Pricing,
2)
Parity
Pricing,
and 3)
Low-price
Supplier.
Product
line
strategies are strategies
in
which the price
of
one
product
is
influenced
by
7
other
related
products
or
services
from the same
company.
These related
products
may
be
complements, substitutes,
or
ancillary
items
such as spare parts; they
may
be
products
sold
simultaneously
or
in
another
time
period. These
strategies
include:
1)
Complementary
Product
Pricing,
2) Price
Bundling,
and
3)
Customer
Value
Pricing.
Cost-based
strategies
consider
the internal costs
of
the
firm
including
fixed
and
variable
costs,
contribution
margins,
and
so
on.
The
principal
strategy
included
in
this
category
is
Cost-Plus
Pricing.
Severalrelated strategies, such as
Target-Return
Pricing,
are
included
as
part
of
Cost-based
pricing
strategies.
Strategy
Determinants
In every normative
discussion
of
pricing strategy, a set
of
market, company
and
competitive conditions
is
specified
under which a given
strategy
is
optimal
(profit-maximizing).
Since
these
conditions determine when a given
strategy
should
be used,
we
refer to them as
determinants.
The set
of
determinants we
include
in
our
study
includesmajor elements
of
Tellis’
(1986)
framework
including
product
differentiation,
economies
of
scale,
capacity
utilization,
and
switching costs. Other determinants are based on
additional
sources
including
pricingarticles
(Dean
1950),
specialized
pricing
monographs
(Oxenfeldt
1975,
Nagle
and
Holden
1995)
and
general
marketing
management
texts (Kotler,
1988;
Guiltinan,
Paul
and Madden
1997).
During
our
literature
review,
we
found that some determinants are common to more than
one strategy.
For
example,
if
brand demand
is
elastic,
then
Penetration
pricing,
Experience
Curve
pricing,
Parity
pricing,
Low-Price Supplier
pricing,
Complementary
product
pricing
and
Bundling
are
all
profit-maximizing
options depending on the
other
market,
company and
competitor
conditions.
Therefore,
high
levels
of
brand
elasticity
does
not separate
these
principal
strategies
8
from
each other.
On the
other
hand,
we
also
discovered
that
some
determinants
are unique to a
given
strategy
type.
For
example,
the presence
of
other
products
from the same
firm
(either substitutes
or
complements)
is
common to
Bundling,
Customer
Value
pricing
and
Complementary
Product
pricing.
Yet
this determinant
is
unique to the
Product
Line
strategy
type.
Therefore, the
presence
of
related
products
from the same
firm
separates
out
this
strategy
type from the
others.
The set
of
unique determinants
for
each
strategy
type forms the
first
level
of
industrial
pricing
framework.
Similarly,
within the
strategy
types,
there
are
determinants
which
separate one
principal
strategy
from
the
others.
In the Competitive Pricing strategies,
high
market share separates
Leader pricing from
the
Parity
and
Low-Price
Supplier
strategies.
Since
these
determinantsare
unique to a given
principal
strategy
within a
strategy
type, they are
also
referred
to as unique
determinants.
The unique
determinants
for each
principal
strategy
allow us to
identify
a
parsimonious set
of
conditions under
which
a
given
principal
strategy
is
optimal.
This
organization
of
the
strategy
types,
particular
strategies and
their
determinants are
presented
in
Table
2.
Table
2
about here
The unique
determinants
are indicated
by
underlined
type.
This
table
is
an
important
contribution
of
our
study
since it
simultaneously
summarizes
the
previous normative
research
and
identifies
a
testable
framework
for
managerial
pricing
strategy.
The determinants
for
strategy
types are discussed
in
detail next.
Determinants for Strategy Types
The determinant
for
choosing
a
New
Product
pricing
strategy
is
the age
of
the
model
being
priced.
Skim
pricing,
Penetration
pricing
and
Experience
curve pricing are
all
appropriate
for
new products.
9
One
might
expect that Competitive pricing strategies
would
be
appropriate
for
the
opposite
condition,
i.e.
the
pricing
of
older
products.
However, the common determinants
for
these strategies (Price
Leader,
Parity pricing and
Low-price
Supplier)
are a
late
stage
of
the
product
life
cycle
and the ease
of
determining demand. Note that these two conditions refer to a
mature market and not
necessarily
to the
age
of
the
model
being
priced.
Returning to
the
Deere
example
above,
the
model
being
priced was
new
to the market yet
it
was entering the mature bulldozer marketplace. Therefore, both New
Product
strategies
and
Competitive pricing strategies
should
be
incorporated
into the
final
decision
for
this new
model
of
bulldozer.
Inherent
in
the
definition
of
Product
Line pricing
strategies
is
the existence
of
other
products,
accessories
or
supplementary
goods
(e.g., spare parts) to guide the pricing
of
the
product
in
question
(Guiltinan,
Paul
and Madden,
1997).
Diamantopoulos
(1991)
claims
that
Cost-Plus
pricing
is
by far
and
away the most
widely
used
pricing strategy. The
Hall
and
Hitch
(1939)
survey
of
39
business
managers
found the
general
pattern
of
price
setting
to be
cost-based.
The Brookings Institution Studies
(Kaplan,
Dirlam,
and
Lanzillotti,
1958)
corroborated
this
finding.
Thirty
years later,
Bonoma,
Crittenden
and Dolan
(1988)
found
that
managers
continue
to
use
cost asa
primary
pricing concern.
Most
authors
caution managers against relying
on
cost-based
methods
for
establishing
prices
(e.g.
Nagle and
Holden,
1995).
The only situation
in
which
Cost-Plus
pricing
is
profit
-
maximizing
is
one
in
which
average
unit
costs
are
likely
to be
constant
over
time
and at
any
point
on
the demand
curve
(Lilien
and
Kotler
1983:
405-407). However, due to economies
of
scale
and/or experience
curve
effects,
neither
of
these
conditions are
likely
to hold
in
a manufacturing
industry (Lilien
and
Kotler,
1983:
407).
10
The
weakness
of
Cost-Plus
Pricing
is
that
it
ignores
consumer
and competitive
information.
However,
if
the
firm
has
little
or
no
information
about
demand, then Cost-Plus
pricing
is
the default
strategy
(Harrison
and
Wilkes,
1975).
Determinants
of
Principal Strategies
Three
of
the
strategy
types, New Product, Competitive
and
Product
Line,
contain
more
than one strategy.
For
each
of
these strategies,
we
have
identified
the
determinants
which
are
unique to that
strategy
and
those
which
are
common
to
other
strategies
within
that
strategy
type.
The unique and common determinants
for
these
principal
strategies are
discussed
next.
New
Product
Pricing
There are
three
options for pricing
new
products:
Skimming,
Penetration
and
Experience
Curve
pricing.
Skimming
is
the
practice
of
setting
a
high
initial
price which
is
often
systematically
discounted
over
time.
The
purpose
of
Skim
pricing
is
to
discriminate
between
those
buyers who
are
insensitive
to the
initial
high
price
because
of
special needs.
As
this
segment becomes
saturated, the price
is
lowered to
broaden
the appeal
of
the
product
(Dean,
1950).
Skim
pricing
is
recommended
over
Penetration
or
Experience
curve
pricing when
there
is
a
high
degree
of
product
differentiation
in
the market
(Jam,
1993).
Without
this
condition,
there
cannot
be
a “better”
product
which would
command
a
higher
price.
In addition,
there
must
be
some
buyers who are
price
insensitive,
i.e.
willing
to pay more
for
a
product
which
meets their
special
needs
(Guiltinan,
Paul and Madden,
1997;
Schoell and
Guiltinan,
1995).
The new
product
usually
represents a
major
improvement over previous versions
in
order
to
command
a
premium
price (Mercer,
1992).
Finally,
firms
with high
factory
utilization
(Schoell and
Guiltinan, 1995)
or
those who
lack
cost advantages due to scale
or
learning should
consider
skimming
over the
low
-
price new
product
pricingstrategies (Schoell
and
Guiltinan,
1995).
11
Both
Penetration
and Experience curve pricing
involve setting
a
low
initial
price
for
a new
product.
Penetration
pricing
is
used
to
speed
adoption
of
a new
product
or
establish
it
as a
de
facto
standard.
It
is
suggested
that
firms
with
cost
advantages due to scale
use
Penetration
pricing
(e.g.,
Tellis
1986).
Experience
curve
pricinghas a
different
focus
and
source
of
advantage
than
penetration
pricing.
The
experience
(or
learning)
curve effect
shows
that unit costs
fall
with
cumulative
volume
due to
increased familiarity
with
the
assembly
process
and
other
factors (Boston
Consulting
Group
1972).
However,
there
is
a
great
deal
of
controversy
about
the extent
of
these
effects (e.g., Amit
1986).
Experience
curve
pricing seeks to exploit the
experience/learning
curve
by
setting
prices
low to
build
cumulative
volume
quickly
and,
thereby, drive down unit
costs.
The presence
of
these experience/learning curve effects are necessary
for
this pricing
strategy
to be a success
(Tellis
1986;
Jam
1993;
Nagle
and
Holden, 1995).
Whether
this
is
a sound long-term
strategy
has
been
questioned
on
many
fronts
(e.g.,
Abernathy
and
Wayne
1974;
Alberts,
1989;
Ghemawat
1985;
Kiechel
1981).
The common conditions
which
favor these
low-price
new
product
strategies
contrast
to
those
for
Skim
pricing:
low
product
differentiation
(Schoell
and
Guiltinan,
1995),
used
for
minor
product
revisions
(Mercer,
1992), elastic
demand
(Guiltinan,
Paul
and Madden,
1997),
and
low
capacity utilization (Schoell and
Guiltinan,
1995).
Competitive
Pricing
Price leaders initiate price changes and expect that others
in
the industry
will
follow
suit.
Price leaders
tend
to have higher prices than
their
competitors
who
use
the leader’s price to set
their
own price levels (Greer,
1984;
Jam,
1993).
Hence,
this
strategy
is
also
known
as
Umbrella
12
pricing.
Price Leaders such as
Caterpillar
in
heavy
equipment tend to have the
highest market
share as
well
(Kotler,
1997).
Parity pricinginvolves
imitating
the
prevailing
prices
in
the market,
maintaining
a constant
relative price
betweencompetitors.
Insome respects,
this
strategy
is
born
of
weakness.
If
a
firm
had
superior products, it
should
be
able
to
command
a
premium
price
(Guiltinan,
Paul
and
Madden,
1997). Or,
if
the
firm
had cost advantages, it could become a
low-price
supplier
(Jam,
1993).
If
a
firm
has
high
costs,
its
only
option
in
a mature market
is
to
employ
parity
pricing
(Jam,
1993,
Guiltinan,
Paul
and Madden,
1997).
Three
conditions
are
common
to both Leader pricing
and
Parity
pricing:
markets
in
which
price
changes are easy to
detect
(Nagle and Holden,
1995),
inelastictotal
demand
(Guiltinan,
Paul
and
Madden,
1997),
and
high
factory
utilization (Schoell and
Guiltinan,
1995).
Low-price
Suppliers
could be
exploiting
a cost
advantage
(Nagle and Holden,
1995)
or
reflecting a
weakness
(i.e., low factory
utilization:
Kotler,
1997).
In
addition,
a
Low-price
Supplier
might
be exploiting a lack
of
pricing
knowledge
in
the market
by
under-cutting
its
rivals
(Greer,
1984).
If
this
under-cuttingbehavior
were known,
it
might
ignite a damaging price
war.
Finally,
the
Low-price
Supplier strategy
should
be
more
successful
in
markets
with
high
levels
of
overall
elasticity
(Guiltinan,
Paul
and
Madden,
1997).
Common
to
both the
Low-price
Supplier
strategy
and
Price Leadership
is
low
costs
(Greer,
1984;
Nagle
and
Holden,
1995)
due to scale
or
experience curve effects
(Jam,
1993).
Low
market
share
is
a
common
determinant
for
Parity pricing
and
Low-priceSupplier
pricing
(Nagle
and
Holden,
1995;
Kotler,
1997).
Product
Line
Pricing
The economic and
psychological
aspects
of
price
bundling
have been
explored
in
depth
13
elsewhere
(Guiltinan,
1987).
Most
of
the
suggested
determinants
for
Bundling
pricing are
common
to
other
pricing
strategies. Therefore,
such determinants
cannot
be used to
identify
the
situation(s)
where Bundling
is
optimal.
The
sole
exception
is
the type
of
price-setting
process.
When
each sale
or
contract
is
priced
separately,
as
in
the
case
of
system
selling
of
mainframe
computers,
then
Bundling
is
a
preferred
option
(Jam,
1993).
For
example,
a major avionics
firm
uses
bundling
in
most
of
its
pricing.
Its
customers
need
systems
for
control,
communications
and
navigation.
To avoid a
competitive pricing
battle
for
each
system, this
firm
quotes
a
bundled
price
for
the
entire
package.
Since
this
firm
is
one
of
the
few
which
make
all
of
these
products, it
usually
wins the contract. In
addition,
this
approach
reduces
the
number
of
suppliers
(and
potential
incompatibility
problems)
for
the
airframe
manufacturer.
Complementary
Product
pricing
began with
King
Camp
Gillette’s
strategy
of
selling
razors
cheaply
and
blades
dearly.
For
many industrial
products,
there
are a wide range
of
supplies,
spare
parts
and
accessories
which make
up
a large
portion
of
the profit stream
from
the
customer. In the
Deere case above, it was suggested that a bulldozer consumes
90%
of
its
initial
purchase price
in
spare parts over
its
lifetime.
Under
this
strategy,
the
main
product
or
platform
is
sold
for
a
relatively
low
price
while
the
ancillary
or
supplementary products carry a
high
margin
(Guiltinan,
Paul
and
Madden,
1997).
For
bulldozers,
for
example,
the markup
on
spare
parts
can be
as
high
as
200%,
much
higher than
the
margin
on
the
main
product
(Kotler,
1997:
515).
In
addition,
Tellis
(1986)
suggests
that
high
customer
switching
costs may keep customers
buying
the captive,
high-margin additional
products.
Customer
Value pricing
is
becoming increasingly common
in
industrial
markets.
This
14
strategy
involves pricing one
version
of
the
product
at very competitive
levels,
offering
fewer
features
than are
available
for
other
versions.
The most
visible
applications
of
this
strategy
recently have been
in
consumer
markets.
For
example,
when
McDonald’s
lowered
the price
of
its
basic
hamburger
to
59
cents
in
1990,
its
was
employing
Customer
Value
pricing to spur
sales
in
a
low
growth
market (Gibson,
1990;
Rigdon, 1990).
Manufacturers
of
consumer
durables
such as Pella
Windows
have
introduced
new
lines
of
products
with fewer
features
and
lower pricing points
thantheir
traditional
customized
lines
(Nagle and
Holden,
1995:
165).
Usually,
these
products
are intended
for
a
specific
market
segment. In the case
of
Hon furniture,
it
produced
a
new
line
of
less
expensive
office furniture
for
home
offices
to be distributed through category
killers
such
as Staples
rather
than
their
full-
service dealer network.
In
contrast
to the case with consumer markets,
Customer
Value
pricing
in
industrial
markets
is
more
likely
to be
successful
if price changes
are
difficult
to detect.
Since
the
firm
is
providing most
of
the
functionality
of
its
main
product
for
a lower
price,
it
runs a
large
risk
of
cannibalizing
its
main,
higher priced
product
(Dolan and
Simon,
1995:
212-214).
A Parsimonious Pricing
Framework
We used the information
in
Tables
1
and
2
to
develop
a parsimonious
framework
for
industrial
pricing.
We
summarize
the
relationships
between
strategy
types,
principal
strategies
and
determinants
in
Figure
1.
Figure
1
about
here
This
frameworkcontains
three
separate
elements
which must be
tested.
The
first
is
the
relationship
between
the pricing
strategies
and
the
relative
price
of
the product.
This
serves
as a
cross-validation
of
our
self-reported measures
of
pricing strategies.
Second,
wetested
the
15
relationships
between
each
strategy
type
and
its unique determinants.
Third,
we
tested
the
relationship between
each
principal
strategy
and
its
unique
determinants.
In
addition,
we
tested
the
relationships
between
the
common
determinants and each
principal
strategy
within
strategy
type.
At
the
end
of
this
process,
we have a
reduced
set
of
conditions for managers to consider
when choosing pricing
strategies
for
an
industrial
product.
Validation Study Design
To validate
our
framework, we conducted a national survey
of
marketing managers
in
capital
goods
industries
in
the late
spring/early
summer
of
1994.
Survey
The survey
document
was a
four
page
questionnaire
mailed
to practicing managers
in
May
and
June
of
1994
(Figure 2). The survey
underwent
extensive pre-testing to
assure
readability
and
accurate
understanding
of
the
questions.
This
included
pilot testing with
written
and
verbal
feedback
from
a convenience sample
of
executive MBA students as
well
as a review
of
the survey
by
two noted
academic
pricing scholars
from
other
institutions.
Figure
2
about
here
To
avoid
the
criticisms
leveled
at
many
studies
of
pricing
objectives
by
Diamantopoulos
(1991:
136),
we asked the managers to provide information on
their
most recent pricing decision
of
a
single
industrial
capital good
rather
than
indicating
an
overall
pricing
strategy
for
all
products
or
circumstances.
Measures
of
Pricing
Strategies
Previous
research
on pricing
objectives
shows that
many
managers
use
more than one
objective
in
their
pricingdecisions (e.g., Diamantopoulos,
1991).
To reflect the
similar
complexity
of
the pricing
strategy
decision,
we
allowed
respondents
to
indicate
their
usage
of
up to
three
16
pricing
strategies.
The
response
to
this
question
was
ratio-scaled
(importance weights
summing
to
100%)
in
order
to assess the magnitude
of
the
importance
of
a
given
strategy
in
the
decIsIon.
In
the
pre-testing
for
this
study,
we found that none
of
the managers used
more
than
three
alternatives.
In
our
final
results,
we
found that
48.5%
used
one strategy, 28.5% two and
22.5%
used
three
strategies. We
note
that the average
importance
of
the third strategy was
15%
(versus
28%
for
the second strategy).
Therefore,
if
there
is
any
bias
in
not
allowing
for
more
than
three
strategies, it
is
not expected to
be
very
large.
In addition,
we
allowed
the
manager to
specify
a pricing
strategy
which
was
not
part
of
the list
often
strategies
provided.
Of
the
21
who
did,
a total
of
17,
upon
review
by
two
independent
judges
and
the authors, were found to be
special
cases
or
related
strategies
of
the
original
ten
strategies.
The
remaining
observations were
dropped
from the
analysis
Measures
of
Determinants
We modeled the scales to measure the
determinants
after
the
questions
used
in
the
PIMS
database (Buzzell and
Gale,
1986).
We
pre-tested
the
wording
and
meaning
of
the scales
in
a
pre
-
test
with
experienced
managers. The determinants and
their
measurement
scales
are
presented
in
Table
3.
Table
3
about
here
Sample
We focused
our
survey
on
the pricingdecisions
of
differentiated,
durable capital
goods
in
business-to-business markets. We restricted
our
sampleto
these
industries
since
industrial
components,
supplies
or
raw
materials are
less
likely
to be
highly
differentiated
which
would
restrict the pricing
strategy
options
of
the
firms.
Furthermore,
since
channels
of
distribution
in
industrial
markets
tend to
be
shorter
than those
in
consumer
markets, the
manufacturer
exerts
17
more
control
over
pricing
to end-users.
Fifteen such
industries
were
identified
using
4-digit
SIC
codes.
The target industries
and
distribution
of
firm
sizes
are
presented
in
Table
4.
Table
4
about here
Contact
names
and
addresses
forthe
1534
firms
were purchased from Dun and Bradstreet.
Initially,
surveys
were to be addressed
only
to
job
titles
including
Director
of
Marketing,
Sales
Manager, Pricing
Manager,
and
variations
of
these
title.
However,
this
targeting
approach
resulted
in
the
exclusion
of
too
many
smaller
companies.
Therefore, the
category
of
President,
CEO,
and
variations
of
these
titles
was included as
well
since
this
was the
only
title
available
for
the majority
of
the
smaller
companies.
A
total
of
1021
firms
was
selected
from
this
list
(after
deleting replicated records from the
total
of
1034).
In a
pre-test
using
a
similar
survey1, a
sample
of
200
mailings
was sent out. The
sample was stratified based
on
firm size. This
pre-test
showed
that
response
rate
increased
monotonically
with firm size.
In
order
to best represent the pricing behavior
in
these
industries,
we
drew
a
disproportionate
stratified
sample
for
the
final
study.
There were
five
size
categories
of
firms.
The
number
of
firms remaining
after
the
pre-test
in
the
largest
four
categories
were
relatively
small
(342,
130,
65
and
70
from
the
smallest
to
largest
size
group).
The
remaining
427 names were
randomly selected
from
the
727
available
in
the
smallest
category.
This
approach
is
consistent
with syndicated
surveys
such
as the
Neilsen
Retail
Index.
Our
intent
is
to
understand
marketing
behavior
in
as large a
proportion
of
the
market
as
possible.
Therefore, this
sampling
approach
should
capture
the widest variation
in
pricing
behavior
in
these
industries since
there
are more
strategic
options
for
larger
firms
than
smaller
ones.
18
Each
firm
was sent a survey package
including
a personalized,
hand-signed
coverletter
with
a pledge
of
confidentiality
of
individual
responses, a
four-page
survey
and
a
$1
incentive.
The
pretest
also
showed that the
response
rate
for
a
$2
incentive (32%) was
identical
to that
for
a
$1
incentive
(31%).
A
total
of
347
surveys
were
returned
to the authors.
Of
these,
77
were
returned
blank
(62), incomplete
or
were otherwise2 unusable (15).
This
yielded
a gross
response
rate
of
34%
(347/1007
delivered).
The total usable sample was
270
for
a usable response
rate
of
27%
which
is
a
similar
sample
size3
and
usable
response
rate4
to recent surveys
of
marketing managers.
Respondent Profile
The responding managers are
highly
experienced with pricing as the
majority
are
involved
in
such decisions
for
more than
20
products. The majority
of
respondents
also
report
10+
years
of
experience
in
the industry
and
with
their
current
company. In
addition,
these managers
were
highly
involved
in
the pricingdecision they
describe.
On a
seven-point
scale (7
=
high,
1
=
low),
the average
self-reported
involvement
was
5.98.
Median firm
size
was
between
$15 and $50
million
in
annual
sales.
These
firms
compete
in
highly
concentrated
markets
with
an average
3-firm
concentration
ratio about 70%.
Validation Study Results
There
are
three
aspects
of
our
pricing
framework
which
require
validation.
The first
is
the
relative price levels
forthe
various
principal
pricing strategies.
Second,
we test the relationships
between
strategy
types
and
their
unique determinants.
Finally,
we
examine
the relationships
between principal strategies and
their
unique (within-type)
and
common determinants.
Relative Price Validation
One
of
the
limitations
of
previous
studies
of
pricing objectives
is
the lack
of
an objective
19
measure to
cross-validate
the pricing
objective
indicated
by
the
respondent.
For
example,
a
firm
whose
objective
is
to
maximize
profits may have a
relatively
low
price
or
a
relatively
high
price
depending on
its
strategy
(Penetration
v.
Skim
pricing).
Therefore, the
price
charged
by
the firm
cannot
be
used
to cross-validate the
self-reported
measure
of
pricing
objective.
For most pricing strategies, however,
there
is
a
one-to-one
correspondence
between
the
level
of
pricing
in
the
marketplace and the pricing
strategy.
Strategies
leading
to
relatively
high
prices
include
Leader pricingand
Skim
pricing.
Relatively
low
prices
should
be expected from
those
firms
employing
the
Penetration
pricing, Experience Curve
pricing,
Complementary
Product
pricing,
Customer
Value
pricing
or
Low-Price
Supplier strategies.
Market-equivalent
prices
should
result from Parity
pricing.
For
Bundling
pricing,
we
do
not
have a prior expectation
since
the
product
is
priced
as
part
of
a
bundle.
Similarly,
the relationship
between
relative price
level
and Cost-plus pricing
will
be based
on
relative costs
which
are
known
and
profitability
levels
which
are not.
We asked the respondents to indicate
the
relative price
of
their
product
in
addition to
their
pricing strategies. The scale ranged from
1
=
5%
or
less
than
the
market
to
5
=
5%
or
more than
the
market.
We
compared
the average
response
from managers
indicating
that they
used
a given
strategy
with the average
response
forthe
entire
sample.
We
used
a
1-tail
t-test
with
the
overall
average
as
the
population mean
for
all
but
the comparison
for
Parity
pricing.
Since
the
null
hypothesis
is
that
there
is
no
difference
between
the price
level
for
firms using
this
strategy
and
the
overall
relative price
for
all
firms,
we
used
a
2-tailed
t-test. The results are
in
Table
5.
Table
5
about here
The two
groups
with
an
expected
high relative price are indeed higher
than
the average
for
20
all
respondents
(Skim pricing,
Leader
pricing).
Parity pricing
had
an average price
level
no
different
from
the
overall
mean,
as
we
expected (2-tailed test).
Finally,
three
of
the
five
pricing
strategies with
expected
relatively
low
prices
had
average price levels that were
significantly
lower
than the overall
average.
Based
on
these
results,
we conclude that the self-reported measures
of
pricing
strategies
are quite
robust.
Determinants
of
Strategy Types
From the
importance
weights
for
the
principal
strategies,
we
determined
if
a
respondent
chose a
strategy
within
each
of
the
four
strategy
types.
A value
of
one was
assigned
to a
strategy
type
if
a
respondent
assigned
a
positive
weight to a
principal
strategy
within
that type
(chosen).
The value was zero otherwise (not chosen).
The independent
variable
for
New
Product
pricingwas the time
of
introduction
of
the
current
model
of
the
product
being
priced (Question
1.3.i
on
page
3
of
the
survey).
The possible
answers range from
0
(not yet
available)
to
5
(10
years
or
more).
We expect this
variable
to be
negatively associated with the probability
of
choosing
this
strategy
type.
For
Competitive
pricing,
the
first
independent
variable
is
the
stage
of
the
product
life
cycle
(Question
1
.3.a
on
page 3).
This
variable ranged from
1
for
products
in
their
introductory
stage to
4
for
products
in
decline.
We expect the
product
life
cycle
to be
positively
related to the
probability
of
choosing
of
a Competitive pricing strategy. In
addition,
we
expect that Competitive
Pricing
strategies
will
be
used
when demand
is
easy
to determine
(lain,
1993).
To
determine
ifthe
firm sells
other
supplementary
or
complementary
products
to the
model
being priced,
we
used
Question
7
on page
1
of
the
survey.
In
our
analysis,
we
constructed
a
dummy variable which
had
the value
of
1
of
the
firm
produced
either substitute
or
complementary
products
and
zero
otherwise. We expect that
this
variable
will
be
positively
21
related to
the
probability
of
choosing
a
Product
Line
pricingstrategy.
The
sole
determinant for
Cost-based
pricing
is
the ease
of
determining demand
in
the
market.
We
expect
that
this
variable
will
be
positively
related to probability
of
choosing
the Cost-
plus
strategy
since it
is
the
only
principal
strategy
in
this
type.
Since
we
defined
our
dependent variable as a
binary choice,
we
used
a
logit
model
to
test
the relationship
between
the
choice
of
strategy
type
and
their
determinants5. The results are
given
in
Table
6.
Table
6
about here
New
Product
strategies were chosen
by
32%
(87)
of
the
respondents. The choice
of
this
strategy
type was
negatively
and
significantly
(p
<0.00)
related to
the
age
of
the
product
being
priced. Therefore, as
expected,
these
strategies
are
being
used with
new
models.
A total
of
127
(47%)
respondents
chose a Competitive pricing
strategy.
This
choice was
positively
and
significantly
(p
<0.01)
related
to the stage
of
product
life cycle.
The
relationship
between
this
strategy
type
and
ease
of
estimating
demand was not different from zero.
This
strategy
type was
used
when pricing
products
in
mature markets.
Product
line
strategies were used
least
often (76
or
28%
of
the respondents).
As
expected,
these
strategies
were used when the
firm also
offered
other
substitutable
products
or
complementary
products
(p
<0.06).
Consistent
with previous research, Cost-based pricing was the
most
often chosen
type.
A
majority
of
respondents
(152/270
=
56%)
reported
using
this
type
of
strategy
in
their
decision.
The choice
of
this
strategy
types
was
positively
and
significantly
related to
the
difficulty
in
estimating
demand
(p
<0.10).
Based on these
overall results,
we
find
support
for
our
first
level
of
organization
in
our
22
framework.
Determinants
of
Principal Strategies
In
order
to
test
the determinants
for
principal
pricing strategies,
we
used
a tobit
model
for
censored
dependent
variables
(Tobin, 1958).
Our measure
of
pricing
strategies
included
information on the magnitude
of
the
importance
of
the
given
principal
strategy. The tobit
model
will
take
advantage
of
the magnitude information
for
testing
the relationships
between
principal
strategies and
their
determinants.
We
tested
the
restricted
set
of
unique determinants as
well
as
the
full
set
of
unique
and
common
determinants.
All
of
these results are
presented
in
Table
7.
Table
7
about
here.
The results
for
each
principal
strategy
are
presented
next.
Skim
Pricing
There
are seven determinants
which
separate
Skim
pricing from the low priced new
product
strategies. They are
high
levels
of
product
differentiation,
a major
product
change,
high
costs,
cost
disadvantage
due to
scale,
cost disadvantages due to
learning,
low market
elasticity,
low brand
elasticity
and
high
capacity
utilization.
About
14%
of
respondents (37/27)
incorporated
skim
pricing into
their
overall
strategy.
The
overall
tobit
model
was
significant
at the
p
<0.04
level.
The condition number for
this
set
of
independent
variables
was
18.89
50
there
should
be
few
problems with
multicollinearity
among the
independent
variables (Kennedy,
1985:
153).
The results
in
Table
7
show that
Skim
pricing
is
used
by
firms
in
markets
with
high
levels
of
product
differentiation (p
<
0.01)
and
when
firms
have cost disadvantages due to scale (p
<
0.08).
23
Penetration
Pricing
Nine
percent
of
respondents (25/270) indicated that they used this strategy.
The
sole
unique
determinant
for
this
strategy
is
a cost
advantage
due to
scale.
This
determinant
is
significantly
related to Penetration pricing
for
the
restricted
model
(p
<0.02).
The
full
model
fit the
data
well
(p
<0.00).
The condition number was
19.02.
The
common
determinants
which
are
significant
are a
high
level
of
market
elasticity
(p
<
0.01)
and
a
low
level
of
brand
elasticity
(p
<0.01).
This
may indicate that
penetration
pricing
is
being used
in
the early
stages
in
the product.life
cycle
when
there
are few direct
competitors
and competition comes
primarily
from
substitutes.
Experience Curve Pricing
Eleven
percent
of
respondents (31/270)
used
Experience
Curve
pricing.
The unique determinant
for
this
strategy
is
a cost advantage due to
learning
curve
effects.
Neither
the
restricted
nor
the
full
model
fit
the
data
well. Since
the
coefficient
for
overall
cost was
not
different
from zero
(p
<0.99),
we
dropped
this
variable
from the
full
model which
is
presented
in
Table
7
and discussed
next.
For the
full
set
of
conditions
(less
overall
cost),
the
tobit
model
was
significant
(p
<0.08).
The
condition
number
for
this formulation was
19.0.
Firms
in
this
sample use
Experience
Curve
pricing
in
markets
with
high
levels
of
product
differentiation
(p
<0.07),
for
products
which
are
not major
revisions
(p
<
0.06)
and
whenthey have
low
capacity utilization (p
<
0.05).
While
the
latter
two results are consistent with previous research,
the
use
of
this
strategy
in
markets with
high
levels
of
product
differentiation
is
not.
One possible
explanation
is
that
firms
using
this
strategy
are market
followers
who are cutting prices now
in
order
to build
volume
and
drive down costs
in
anticipation
of
the future commoditization
of
the
market.
This
is
one mode
of
24
competition
in
the
computer
chip
industry when clone
chip
producers
introduce
their
products at
much lower prices to
shift
the focus
of
competition
from performance
only
to a price-performance
condition.
At
that point, the clone manufacturers try to
build
an
advantage over the
innovating
firm
by
lowering
their
costs via large
volumes.
Unfortunately,
firms
using
this
approach
might
also
be
“leaving
money
on
the
table”
by
cutting prices to
build
volume
if
the
expected
price-dominant
phase
of
competition
does
not
materialize.
Leader Pricing
Eleven percent
of
respondents (31/270)
used
Leader
pricing.
High
market
share
is
the
sole
unique determinant
of
Leader
pricing.
The
overall
model
is
significant
(p
<0.10).
While
the
coefficient
is
positive as expected,
it
is
not
different
from zero (p
.6
<0.
.12)
based
on
the
chi-square statistic
In the
full
model
(condition number
=
16.86),
we
see that
firms
choose Leader pricing
when price changes are easy to
detect
(p
<0.10).
This
is
an
important
informational
condition
for
the success
of
Leader
pricing.
Parity Pricing
Parity pricing was used
by
30%
(82/270)
of
respondents.
This
strategy
is
used
by firms
with high
costs
as
expected (p
<
0.00). The
sources
of
these
high
costs are not
necessarily
a lack
of
scale
or
learning
curve
effects.
In the
full
model
(condition
number
=
15.71),
we
see that
firms
employing
Parity pricing
also
have low market
shares
(p
K
0.00)
and
high
levels
of
capacity utilization (p
<0.07).
Contrary
to
expectations,
parity pricing
is
used
in
markets
with
high
levels
of
overall
elasticity
(p
<0.01).
This
is
an
interesting result
since
it
suggests
that some determinants
might
be
binding
while
others are not. The characteristics
of
the
firm
(high
cost, low market share and
high
25
utilization)
do
not allow it to
exploit
an
otherwise
favorable
external
condition
(high
market
elasticity).
An interesting direction
for
future
pricing
research
would
be to
identify
those
conditions
which
constrain
the choices faced
by
the
firm
and those which are
merely
favorable
to
a given strategy.
Low-Price
Supplier
About 9%
(24/270)
of
respondents followed the Low-Price Supplier strategy.
Of
the
three
conditions
which
favor this
strategy
(difficulty
in
detecting
price
changes,
high
market
elasticity
and low
capacity
utilization),
only
low factory
capacity
utilization
is
related
to the
use
of
this
strategy
(p
<0.04).
In the
full
model,
we
also
see
that
firms
following
this
strategy
have low costs
overall
(p
<
0.00)
and
this
advantage
is
due to scale (p
<0.07).
A
firm with
low
overall
costs has the
ability
to
price low
and
low
factory
capacity utilization provides the
incentive.
Price Bundling
Thirteen
percent
of
respondents
(35/270)
chose
Bundling.
The results show that
this
strategy
is
used
by
firms
when they are pricing each
sale
or
contract
individually
(p
<0.01).
As
in
the earlier avionics
example,
the
product
composition
of
many
industrial
purchases
is
unique
from
one
order
to
the
next.
Bundling
allows
the
supplier
to
address
the unique needs
of
the
customer
and remain
highly
competitive.
Complementary
Product
Pricing
About
9%
(24/270)
of
respondents
incorporated
Complementary
Product
pricing
into
their
overall
strategy.
Of
the
three
unique
determinants,
it
is
the
high
profitability
of
accompanying
sales
which
influences
the
use
of
this
strategy
(p
<0.02).
Note
also that the relative
price
is
low. This
is
very
26
consistent
with what we predict
with
razor-and-blade
type
products
and
durables
which
require
the
eventual
purchase
of
captive spare parts
in
large quantities.
Customer
Value
Pricing
Customer Value pricingwas used
by
11%
(29/270)
of
respondents.
The
Tobit
results
for
this
strategy
suggest that
firms
choose this
strategy
for
products
which would appeal
to a
narrow
segment (p
<0.10).
It
is
also
used
in
markets
where price
changes are
difficult
to
detect
(p
<0.02).
The results
imply
that these
firms
may
be
using
the
Customer
Value
strategy
to secretly cut prices
for
a
specific
segment
without
taking
the risks
associated
with
straight
price
reductions
which
might
spark
a costly price war.
Summary
of
Results
We
summarize
the results
from
our
validation
study
in
Table
8.
Table
8
about
here
The results
of
our
validation study
are
an
important
step
in
the evolution
of
research
in
pricing strategy. We have
identified statistically significant relationships
between
strategy
types
and
their
unique determinants. We have
identified significant relationships
between
principal
strategies
and
their
unique
determinants.
In every case,
these
relationships
were
in
the expected
direction.
The
combination
of
these results provides
important
guidelines
forthe
selection
of
pricing strategies
for
differentiated
industrial
products.
By
focusing
on
the unique
determinants,
we
can
streamline
the
decision
processwithout
sacrificing
the
appropriateness
of
the
outcome.
Therefore,
this
validated
framework
unites
the normative
and
managerial
streams
of
pricing
research
for
the
first
time.
In
addition to
these
results,
we
also
have identified
favorable
conditions under
which
given
principal
strategies
should
be and are
used
in
pricing
industrial
products.
Since
these
conditions
27
are
not
unique to a
given
principal
strategy, they
should
be viewed
with
some
caution.
The
same
conditions
might
be
appropriate
for
another
principal
strategy
but
this
relationship was not
confirmed
by
our
data.
Limitations
and Directions for Future
Research
While
the results
reported
above are
very
exciting,
they are not
complete
due to the
sample
in
our
verification
study.
We are
limited
in
the types
of
products
(industrial
capital goods),
customers
(domestic U.S.) and companies (domestic U.S.)
studied.
For
example,
there
is
little
variation
in
the sample
in
concentration
and
height
of
entry
barriers.
In
addition,
there
was very
little
variation
in
self-evaluated
product
quality.
The average
rating was
5.79
out
of
7
(std.
dev.
=
1.08).
This
is
not
surprising
given
a manager’s
bias
towards
his/her own
firm’s
products.
However,
keep
in
mind
that
these
are
very
highly
concentrated
markets
from
which
firms
with
marginal
quality
may have already been
eliminated.
In addition to providing
validation
of
our
pricingframework, the
empirical study
of
pricing
managers
provides some
important
insights
into
current
pricing
practices.
One
of
the more
interesting results
is
the varied
importance
of
different
pricing
strategies.
The
distributions
of
the
importance
weights and
median
importance
weight
for
each
strategy
is
presented
in
Table
9.
Table
9
about here
Consider
the
distributions
of
the
importance
weights
for
two strategies,
Price
Skimming
and Complementary
Product
Pricing.
Note
that the
distribution
for
Price
Skimming
has a
strong
skew
to
the
left
while
the
distribution
for
Complementary
Product
Pricing
is
skewed to the
right.
Several
of
the
other
strategies follow
similar
patterns.
We interpret
this
as an
indication
that some
of
the pricing
strategies
are primary strategies
while others are
secondary,
or
supporting,
strategies.
The
distributions
in
Table
9
indicate that
28
Cost-Plus
Pricing,
Low-price
Supplier
Pricing,
and
Price
Skimming
strategies
appear
to
be
primary strategies.
Complementary
Product
Pricing,
Bundle
Pricing,
and
Customer
Value
Pricing
appear
to
be
secondary strategies. (The
median
importance
weights
for
each
strategy
are indicated
in
Table 9).
Note that
all
three
of
the strategies
classified
as secondary are from the
product
line
group
of
strategies (Complementary
Product
Pricing,
Price
Bundling,
and
Customer
Value
Pricing).
This
suggests
that
product
line
pricing strategies, when
chosen,
will
rarely
be
paramount
in
importance.
The pricing
framework
developed
in
this
paper
can
be
used
to determine
which
pricing
strategies
should
be
considered
when pricing a
complex,
high-value industrial
product.
However,
it
does
not suggest how
these
strategies
should
be
combined
to determine the ultimate pricing
schedule.
At
this
stage it
is
only
possible
to comment
on
the relative
importance
of
the strategies.
For
example,
it
is
not known
if
the strategies are
usually
chosen
simultaneously
or
sequentially.
An interesting path
for
future
research
would
be to explore
how
these
strategies are
integrated
by
managers into a
final
decision
Another
interesting result was the prevalence
of
Cost-Plus
Pricing.
A
full
56%
of
the 270
managers mentioned
Cost-Plus
Pricing.
When it was used, it was the
dominant
strategy
(with an
importance
weight larger than
any
of
the others mentioned)
71%
of
the
time.
This
confirms
the
observations
of
Simon
(1989) and others
that,
even
after
all
of
the research
on
market- and
competitive-oriented
pricing,
cost-based
methods
remain
prevalent.
Cost-Plus
Pricing
is
an inward oriented strategy,
involving
company
and
product
considerations,
while
the
other
nine
pricing
strategies generally have
an
outward
orientation,
focusing on the
customer
and competition
(Day
and
Nedungadi
1994).
Over
35%
of
the
managers responding
used
a
combination
of
Cost-Plus
Pricing
and one
of
29
the
other
nine
market based strategies,
implying
that a
significant
number
of
managers are
looking
inward and looking
outward
to set
their
prices.
This
suggests that
many
managers have a Janus-
faced
approach
to choosing a pricing strategy. Their
gaze
is
fixed both
inside
and
outside
their
companies at the same
time
(Monroe
1990).
Whether
this
approach
leads to better market
(sales,
share,
customer
retention)
or
financial
results
would
be
another
fruitful
avenue
of
research.
Conclusion
In
their
1988
article,
Bonoma,
Crittenden
and
Dolan
stated
that
managers
find little
of
the
pricing
research
in
marketing to
be
of
any
practical
help.
The
industrial
pricing framework
presented
here can
help
mangers
cut
through
some
of
the
“fog”
of
the pricing literature without
resorting
to
simplistic
or
misleading
rules
of
thumb.
30
End
Notes:
1.
The Noble
(1997)
study
of
pricing
objectives
is
identical
except
for
the measures
of
pricing
strategies.
2.
For
example,
the
respondent
indicated
multiple
price levels
which
may
indicatethe
response
was
for
a
product
line
rather
than a
single
product.
3.
During the
five
years
preceding
this
study
(1989-1994), twenty-two
surveys
of
managers were
published
in
the Journal
of
Marketing
Research
(JMR).
The average sample
for
all
of
the surveys
was
284.
During
the
same period, the Journal
of
Marketing
(JM)
published
41
articles
involving
surveys
of
managers. The average sample
for
all
of
the surveys was
270..
4.
In the period 1989-1994,
response
rates were often
unreported
for
studies
in
IMIR
and JM.
Managerial survey studies
in
the JM
articles
had
average gross
response
rates
of
about
32%
and
usable
response
rates
of
29%. In the JMR
articles,
the
response
rates were
higher,
with
the gross
response
rate
about
40%
and the usable
response
rate
of
37%.
5.
If
we
restricted
our
respondents to a
single
choice
of
principal
strategy, we could have
used
a
multinomial
choice
model.
Managers could choose
strategies
from
up
to
three
different
strategy
types.
We decided to
model
this
process
as a
set
of
binary
choices since the determinants
we
identified
are related to the choice
of
individual
strategy
types and not to the choice
of
combinations
of
strategy
types.
6.
We
also
tested
the
relationship
between
the choice
of
Leader
pricing
and
market share
using
a
logit
model.
The independent
variable
was
1
if
Leader pricing was given a weight
greater
than
zero
(3
1
observations),
0
if
the
firm
gave a
positive
weight to either Parity
or
Low
Price Supplier
(96
=
127
-
31
observations),
or
missing
if
no
Competitive pricing
strategy
was
given
a
positive
weight (143
=
270
-
127
cases).
Thus,
we
tested the relationship
between
the
choice
of
Leader
pricing and market share
given
that a
Competitive
pricing
strategy
was
chosen.
This
“conditiohal”
logit
model
was
significant
at the
0.01.
The
coefficient
for
market share was
positive
and
significant
at the
0.01
level.
In
general,
the results from
the
logit
models were
identical
to those
from
the tobit
models.
For
Skim,
Experience
Curve and
Customer
Value
Pricing,
the
full
logit
models were not
significant
at the
0.
10
level.
The results
for
Penetration pricing
were
identical
for
the
restricted
and full
logit
models.
For
the
full
Leader pricing
model,
the
coefficient
for
Cost advantage due
to
learning
was
significant
at
the
0.10
level.
For
Parity
pricing,
the
restricted
model
results were
identical
but market share and utilization were not
significant
in
the
full
logit
model.
For
Low
-
Price
supplier,
the
restricted
model
was
identical
but the
coefficient
for
Cost advantage due to
learning
was negative (p
<0.06)
in
the
full
logit
model,
contrary
to expectations.
For
Bundle
and
Complementary
Product
pricing,
the
results are the same
using
the
logit
model.
Given
the
similarity
of
the results
for
these two different
estimation methods,
we
conclude
that the results
reported
in
Table
7
are
robust.
These results are
available
from
the authors.
31
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Table
1
Pricing
Strategy
Definitions
Principal
Strategy
Description
Related
Strategies
New Product Pricing Strategies
Price
Skimming
We
set
the
initial
price
high
and
then
Premium
Pricing, Value-in-Use
systematically reduce
it
over
time.
Customers
Pricing
expect
prices
to
eventually
fall.
Penetration
We
initially
set
the
price
low to
accelerate
Pricing
product
adoption.
Experience
We
set
the
price
low to
build
volume
and
reduce
Learning
Curve
Pricing
Curve
Pricing
costs
through
accumulated
experience.
Competitive
Pricing Strategies
Leader
Pricing
We
initiate
a
price
change and
expect
the
other
Umbrella
Pricing,
Cooperative
firms
to
follow.
Pricing,
Signaling
Parity
Pricing
We
match the
price
set
by
the
overall market
or
Neutral Pricing, Follower
the
price
leader.
Pricing
Low-Price
We
always
strive
to
have
the
low
price
in
the Parallel Pricing, Adaptive
Supplier
market.
Pricing, Opportunistic
Pricing
Product Line Pricing Strategies
Complementaxy
We
price
the
core
product
low
when
Razor-and-Blade
Pricing
Product
Pricing
complementary items
such
as
accessories,
supplies,
spare
pans,
services,
etc.
can
be
priced
with
a
higher
premium.
Price
Bundling
We
offer
this
product
as part
ofa
bundle
of
System
Pricing
several
products,
usually
at
a
total
price
that
gives
ourcustomers
an
attractive
savings
over
the
sum
of
individual
prices.
Customer
Value
We
price
one
version
of
our
product
at
very
Economy
Pricing
Pricing
competitive
levels,
offering
fewer
features
than
are
available
on
other versions.
Cost-Based
Pricing Strategies
Cost-Plus
We
establish
the
price
of
the product
at
a
point
Contribution
Pricing,
Rate-of
Pricing
that
gives
us a
specified
percentage
profit
Return
Pricing,
Target
Return
margin
over
our
costs.
Pricing,
Contingency
Pricing,
Markup
Pricing
35
Table
2:
Determinants
of
Pricing Strategies
New Product Pricing Strategies Skim
Pricing
Penetration
Pricing Experience Curve
Pricing
Unique
to
Strategy
Product
age
Type:
New
(1.10)
New
(1.10)
New
(10.11)
Within-type
Product
Determinants: differentiation
High
(4.8.10)
Low
(4,8,10)
Low
(4.8.10)
Significance
of
product change
Maior
(6.10)
Minor
(6,10)
Minor
(6.8.10)
Costs
Hi2h (4.10)
Low
(4)
Low
(4)
Scale
or
experience
curve
effects
Demand
Disadvanta2e
(10)
Inelastic
(4.8.10)
Advantaae:
scale
(3.4.8.10.11)
Elastic (1.3,4.6.8)
Advanta~ie:
experience
(4.8.10.11
Elastic (1.3.4,6.8.9)
Factorvcapacity
utilization
Hi~h(3.l0)
Low(l0.1l)
Low(10.l1)
Price Low-Price
Competitive
Pricing Strategies Leadership Parity Pricing
Supplier
Unique
to
Strategy
Product
Life
Cycle
Type:
Mature
(5)
Mature
(3.5)
Mature (5)
Ease
of
determining
demand
Easy
(4)
Ea~
(4)
Easy
(4)
Within-type
Market
share
Determinants:
High
(4.5)
Low
(8)
Low
(2,5)
Costs
Low
(4)
Hi2h
(2.3.4)
Low
(8)
Scale
or
experience
curve
effects
Advantage
(2,4)
Disadvantaae
(3)
Advantage
(4)
Ease
of
detecting
price
changes
Easy
(2)
Easy (3,8)
Difficult
(2)
Total
demand
Inelastic
(2,3)
Inelastic (3)
Elastic
(3)
Factory
capacity
utilization
High
(10)
High
(10)
Low
(5)
Other
Determinants:
Product
differentiation
Low
(8)
Low
(8)
Brand
Demand
Elastic
(3)
Elastic
(3)
36
Product Line Pricing Strategies
Complementary
Product
Pricing
Customer
Value
Bundling Pricing
Pricing
Unique
to
Strategy
Type:
Common
(within
-
type)
Determinants:
Firm
sells
entire
product
line
(other
models,
ancillary
products.
supplemen
-
tan
products)
Profitability
of
accompanying
or
supplementary
sales
Switching
costs
Per
sale/contract
pricing
Market
appeal
Market
growth
rate
Ease
of
detecting
price
changes
Hi!h
(3.5
)
Hii~h
(11
)
Yes
(4
)
Narrow
Low
Difficult
Other
Detenninants:
Brand demand
Elastic
(3)
Elastic
(3.7.8.
10)
Cost-Based
Pricing Strategies
Unique
to
Strategy
Ease
of
determining
Diflicult
(3)
Type:
demand
Common
(within-
none
type)
Determinants:
Other
Determinants:
none
References:
I.
Dean (1950)
2.
Greer(1984)
3.
Guiltinan,
Paul
and
Madden
(1997)
4.
Jam
(1993)
6.
Mercer
(1992)
7.
Monroe
(1990)
8.
Nagle
and
Holden
(1995)
9.
Oxenfeldt
(1975)
10.
Schoell
and
Guiltinan
(1995)
11,
Tellis
(1986)
Yes
(3
)
Yes
(3
)
Yes
(3
)
Cost-
Plus
Pricing
37
Table
3
Determinants
of
Pricing Strategies
Definition
of
Determinant
Market Conditions
Sensitivity
of
customers
to
price
differences
between
brands
Sensitivity
of
total
demand
to changes in
average
price
Ease
of
determining
market
demand
Market
growth
Switching
costs
Competitive
Conditions
Ease
of
detecting
competitive price
changes
Concentration:
Three firm concentration ratio
Product differentiation
Product/Company
Conditions
Age
of
product
in
years
Cost (dis)advantage
due
to
experience
curve
Cost (dis)advantage
due
to
economies
of
scale
Capacity
utilization
(relative)
Costs (relative to
competitors)
Major
Product
Change:
Significance
of
most current
design
change
Market
Coverage
Market
Share
Per
Sale/Contract
Pricing
Profitability
of
accompanying
sales (e.g.,
other
products)
Profitability
of
supplementary
sales (e.g..
spare parts. service)
Scale
in
Survey
=
insensitive,
7
=
sensitive
I
=
insensitive,
7
=
sensitive
=
easy,
7
=
difficult
I
=
low,
7
=
high
=
low,
7
high
=
difficult,
7
=
easy
I
=K5%,
7=>
80%
I
=
low.
7
high
1
=
not yet
available,
2
=
<
1
year,
6=
lO+years
I
=
(dis)advantage,
0
=
otherwise
=
(dis)advantage,
0
=
otherwise
I
=
low,
7
high
1
=
advantage,
7
=
disadvantage
1
=
totally new product,
o
=
otherwise
=
all
segments,
7
=
one
segment
1
=
low,
7
=
leader
1
=
yes,
0
=
no
1
=
low,
7
high
I
=
low,
7
high
38
Table
4
Mailing List by
SIC
Code
and
Revenue
4-digit
SIC
Code
Industry
Number
of
Firms
3523
Farm
138
353
1
Construction
142
3532
Mining
63
3537
Industrial
Trucks
and
Tractors
93
3541
Machine Tools,
Cutting
57
3542
Machine Tools, Forming
77
3549
Metal Working
Machines
32
3554
Paper
Industry
Machines
83
3571
Electronic
Computers
269
3663
Radio
and
TV
Communication
Equipment
188
3711
Tractor
and
Tractor
Trucks
18
3721
Aircraft
41
3743
Railroad
Equipment
64
3812
Search
and
Navigation
Equipment
118
3823
Process Control Instruments
151
Total
1534
Company Size
Number
of
Firms
in
Number
of
Firms
(Annual
Revenue
in
millions) Mailing
List
/
Sample
Responding
$5-$14
836/427
93
$15-$49
393/342
77
$50-$149
149/130
36
$150-$499
75/65
24
$500+
81/70
39
unknown
Total
1534/1034
270
39
Table
5
Cross-Validation
of
Pricing Strategy Using
Relative
Price
Strategy
Skim
Pricing
Leader Pricing
Parity Pricing
Customer
Value
Pricing
Experience
Curve
Pricing
Complementary
Product
Pricing
Penetration Pricing
Low Priced
Supplier
Entire
Sample
Number
of
Respondents
37
31
82
29
32
24
25
24
Expected
Relative
Price
High
High
Same
Low
Low
Low
Low
Low
270
Mean of
Relative
Price
4.11
3.97
3.35
3.37
3.68
3.21
2.68
2.00
Std.
Dev.
Of
Relative
Price
1.51
1.40
1.20
1.42
1.49
1.25
1.77
1.25
t-statistic
(p-value)
*
2.22
(0.02)
1.63
(0.06)
1.59
(0.12)**
-0.72 (0.24)
-0.46
(0.33)
-1.37 (0.09)
-2.49 (0.01)
-6.46
(0.00)
3.56
*
p-value
calculated
for
1-tail
t-test
except
for
**
which
is
the p-value
for
the 2-tailed t-test.
40
Table
6
Test
of
Uniaue
Determinants
of
Strategy
Types
New
Product
Strategies
Estimate
Std.
Error
Chi-square
Prob>Chi2
ProductAge(-)
Intercept
Model
Chi-square
Model
Fit
Positive
Responses
Competitive
Strategies
-0.31
0.32
12.24
p
<0.00
87
0.09
0.33
11.56
0.95 0.00
0.33
0.51
-0.03
-1.21
11.39
p
<0.00
127
0.16
0.08
0.50
10.22
0.21
5.77
0.00
0.65
0.02
ProductLifeCycle(+)
Ease
of
Estimating Demand
(-)
Intercept
Model
Chi-square
Model
Fit
Positive Responses
Product Line
Strategies
0.81
-1.64
3.90
p
K
0.05
76
0.43
0.41
3.42
15.72
0.06
0.00
Sell
substitute and/or
Complementary Products
(+)
Intercept
Model
Chi-square
Model
Fit
Positive
Responses
Cost-Based
Strategies
Ease
of
Estimating
Demand
(+)
Intercept
Model
Chi-square
Model
Fit
Positive
Responses
0.13
-0.20
2.89
p
<0.09
152
0.07
0.29
2.85
0.45 0.09
0.50
41
Table
7:
Test
of
Determinants
of
Individual
Pricing Strategies
Estimate
(Prob
>
Chi2)
Restricted
Full
Tobit
Tobit
Skim
Pricing
Unique
Determinants1
Product
Differentiation
(+)
Major
Product Change
(+)
Cost
(+)
Cost disadvantage: scale
(+)
Cost disadvantage:
learning
(+)
Market
Elasticity
(-)
Brand Elasticity
(-)
Capacity
Utilization
(+)
19.22
(0.01)
1.07
(0.96)
2.07
(0.82)
40.65
(0.08)
-65.46 (0.14)
0.85
(0.90)
-10.16
(0.15)
2.35
(0.70)
-185.61
(0.00)
Intercept
Model
Fit
pK
0.04
37
Sample
Penetration Pricing
Unique Determinants’
Cost
advantage:
scale
(+)
Common Determinants’
Product
Differentiation
(-)
Major
Product Change
(-)
Cost
(-)
Market
Elasticity
(+)
Brand
Elasticity
(+)
Capacity
Utilization
(-)
Intercept
55.88
(0.02)
-156.98
(0.00)
43.49
(0.05)
8.65
(0.24)
12.76
(0.56)
-14.61
(0.11)
19.23
(0.01)
-17.69
(0.01)
-0.82
(0.89)
141.17
(0.03)
Model
Fit
Sample
Experience Curve Pricing
Unique Determinants’
Cost
advantage:
learning
(+)
Common
Determinants
Product
Differentiation
(-)
Major
Product
Change
(-)
Market
Elasticity
(+)
Brand
Elasticity
(+)
Capacity
Utilization
(-)
Intercept
Model
Fit
Sample
4.09
(0.84)
-125.91
(0.00)
p
<0.84
31
2.99
(0.87)
13.18
(0.07)
-45.15
(0.06)
6.45
(0.33)
5.56
(0.35)
-11.80
(0.05)
-176.69
(0.00)
p<0.08
31
p
<0.01
25
p
<0.00
25
42
Price Leadership
Unique Determinants’
Market
Share
(+)
Common Determinants’
Cost
(-)
Cost
advantage:
scale
(+)
Cost
advantage: learning
(+)
Ease:
detecting
price
changes
(+)
Market
Elasticity
(-)
Capacity
Utilization
(+)
Intercept
-148.29(0.00)
12.12
(0.20)
31.05
(0.13)
33.03
(0.11)
9.52
(0.10)
-3.86
(0.50)
-0.11
(0.98)
-321.63
(0.00)
Model
Fit
Sample
Parity Pricing
Unique Determinants’
Cost
(+)
Cost disadvantage: scale
(+)
Cost disadvantage:
learning
(+)
Common Determinants’
Market
Share
(-)
Ease:
detecting
price
changes
(+)
Market
Elasticity
(-)
Capacity
Utilization
(+)
Intercept
15.55
(0.00)
20.55
(0.13)
16.39 (0.38)
-94.23
(0.00)
16.57
(0.00)
10.24
(0.44)
5.60
(0.76)
-9.15
(0.00)
-0.18
(0.96)
9.12
(0.01)
6.07
(0.07)
-113.06
(0.00)
Model
Fit
Sample
Low-Price
Supplier
Unique Determinants’
Ease:
detecting
price
changes
(-)
Market Elasticity (+)
Capacity
Utilization
(-)
Common
Determinants’
Market
Share
(-)
Cost
(-)
Cost advantages
due
to
scale
(+)
Cost
advantage: learning
(+)
Intercept
Model
Fit
Sample
1.54
(0.82)
-5.93
(0.42)
-15.52
(0.04)
-82.93 (0.11)
p
<0.01
24
-0.87
(0.89)
-7.61
(0.31)
-12.63
(0.08)
-5.98
(0.32)
-42.57 (0.00)
51.26
(0.07)
-38.25 (0.15)
81.44 (0.18)
p
<0.00
24
Restricted
Tobit
7.93
(0.12)
Full
Tobit
6.33
(0.20)
p
<0.10
31
p
<0.04
31
pK
0.00
82
pK
0.00
82
43
Bundling
Pricing
Full
Tobit
Unique Determinants’
Per
Sale/Contract
Pricing
(+)
Intercept
38.32
(0.02)
-99.25
(0.00)
Model
Fit
Sample
p <
0.01
35
Complementary Product
Pricing
Unique
Determinants’
Profitability
of
accompanying
sales
(+)
Profitability
of
supplementary
sales
(+)
Switching
Costs
(+)
Intercept
-0.23 (0.96)
15.17
(0.01)
2.01
(0.56)
-160.09
(0.00)
ModelFit
Sample
p<O.Ol
24
Customer
Value
Pricing
Unique
Determinants
Ease:
detecting
price
changes
(-)
Market
Coverage
(+)
Market
Growth
(-)
Intercept
-12.72 (0.02)
8.53
(0.10)
7.13
(0.20)
-112.42
(0.00)
Model
Fit
Sample
p
<0.02
29
44
Table
8:
Validated Pricing
Strategy
Framework
Strategy
Type
New
Product
Pricing
Determinants
.
New
model
Principal
Strategies
related
strategies
Skimming
Premium
Pricing
Value-in-Use
Pricing
Penetration
Pricing
Unique
Determinants
High product
differentiation
in
the
market
Cost
disadvantage
due
to
scale
Cost
advantage due
to
scale
Experience/Learning
Curve
Pricing
Competitive
Mature market
Pricing
Product
Line
Pricing
Firm
sells
substitute
or
complement
ary
products
Cost-Based
Difficult
to
Pricing
determine
demand
*
based
ont-tests
in
Table
5
Leader
Pricing
Umbrella
Pricing
Cooperative
Pricing
Sianaling
Parity
Pricing
Neutral
pricing
Follower
pricing
High costs
Additional
Favorable
Conditions
Elastic market
demand
Inelastic brand
demand
Not
a
major
product
change
High product
differentiation
in
the
market
Low
capacity
utilization
Cost
advantages
due
to
learning
Easy
to
detect
price
changes
Low
market
share
Elastic market
demand
High
capacity
utilization
Low
costs
Cost
advantages
due
to
scale
No
cost
advantage
due
to
learning
Low
-price
Supplier
Low
factory
Parallel
pricing
utilization
Adaptive
pricing
Opportunistic
pricing
Bundling
Per
sale
I
contract
System
Pricing
pricing
Complementary
Product
High
profit
on
Pricing
supplementa~
sales
Razor-and-blade
pricing
Customer
Value
Pricing
Hard
to
detect
price
Economy
pricing
changes
Narrow market
appeal
Cost-plus
pricing
Contribution
Pricing
Target
return
pricing
Markup
pricing
Relative
Price
High
Low
el-liali
Equal
Low
Low
45
Table
9
Importance
Weight Distribution by
Pricing
Strategy
Strategy 10%
20% 30%
400/0
50% 60%
70%
800/o
90%
100%
Total
New
Product
Pricing
Strate
ies
SkimPricing
Penetration
Pricing
ExperienceCurvePricing
2 6
2 5
4 5
5
5
5
0
0
0
3
3
3
1
2
0
3
1
3
1
1
1
0
0
0
16
5
9
36
25
31
ies
[1
3
6
210
4
[31
12
5 3
6f1
22
81
112
0
3
3 j 0 7
f
24
Strategies
——
—.
—.—.
Complementary
Product 7
9
3
1
2 0
1
0 0
1
24
Pricing
BundlePricing
8 9
3
2
1
.2
4 2 0 4
24
Customer
Value
Pricing
2 9 8 0
1
2
1 1
0 6
30
Competitive
Pricing Strate
f
5
Ill
3
LeaderPricing
ParityPricing
Low-PriceSupplier
4
4
4
1
1
1
7
7
Product Line Pricing
Cost-based
Pricing Strategies
Cost-Plus
Pricing
10 8 10 9 14
13
12 14
3
57
150
Importance
Weight
Note:
Median
is
indicated
by
underlined
type.
46
Figure
1:
Overview
of
Industrial
Pricing
Framework
New
model
of
product
Company
sells
complementary
or
substitute
products
Per
sale./contract
pricing
Narrow
market
appeal
Low
market growth
Difficultto detect
price
changes
Complementary
Product
Pricing
(low)
Bundling
Pricing
Customer
Value
Pricing
(low)
Difficult
to
estimate
demand
Cost-based
Pricing
Strategies
Strategy
Type
Determinants
Strategy Types
Unique
Principal
Strategy
Determinants
Principal
Pricing
Strategies
(relative
price)
High
product
differentiation
Significant
design
change
High
relative
costs
Cost disadvantage due
to
scale
or
experience
Inelastic
demand
Low factory
utilization
Skim
Pricing
(high)
High
relative
costs
Cost
disadvantage
due
to
scale
or
experience
S
0
Difficultto detect
price
changes
Elastic
total
demand
Low
capacity
utilization
High
profitability
of
accompanying
or
supplementary
sales
High
switching
costs
Cost-Plus
Pricing
47
Figure
2:
Managerial Pricing Strategy Survey
GENERAL PRODUCF
ENFORMATION
pale
lam
interested
in
the
most
recent
pricing
decision
you
were
involved
with
in
the
last
12
months
for the
U.S.
market. The
decision
you
describe
should
be
for
a
single
durable
good9
sold
in business-to-business
markets. Please
provide
some
general
back~ound
information
for
your
product.
Answer
for one oroduct only
.
1.
This
specific
product
is
best described
as:
_____________________________________________________
2.
The
principal
industry
you
consider
the
product to
he
part
of
(e.g.,
heavy
truck,
machine
tool,
etc.):
3.
Your
approximate
~wi~
selling
price
is:
under
from
$1,000
from $3,000
from
SIO.000
from
S30.000
from
$100,000 $300,000
$
1.000
to
$2,999
to
S9.999
to
$29,999
to
$99,999
to
S299,999
or
over
00
0 0 0 0 0
4. How
often
do
you
(or
your
company)
set
the
pricing
for
this product?
weekly
monthly
quarterly
semi-annually
annually
each
saledcontmct
Otlw
____________
o
0 0 0 0 0 0
5.
What
percent
of
the
annual
dollar
sales
of
your
division
(or
company,
as appropriate)
does
this
product
represent?
~
lessthan
atleas:
1%
atleastS%
atleast2.5%
50%
I
Division
I
1%
but
under
5%
but
under
25%
but
under
30%
or
over
0 0 0 0
0
6. When
the
current
model
was
znti~oduced,
how
significant
was
the
design
change?
totally
new
product
major
revision
minor
revision
no
change
0 0 0 0
7.
We
offer
other products
to
this market
which,
relative
to
this
product.
are
(check
all
that
apply):
substitutes
complements have no relationship
to
this
product
no
other
products
are
available
o o
0 0
8.
How
would
you
charecterize
~
in
relation
toy~
THREE
largest
competitors?
morethan5%
2%to5%
about
2%to5%
mored~an5%
Suchacompauisonis
below below
equal
above
above
meaningless
in
my
situation
o
0 0 0 0 0
9.
Approximately
what
percentage
of
the
dollar
sales
for
this
product
categoiy
in
the
U.S.
market
is
made
by
the
THREE
largest
manufactiws?
If
there
are
fewer
than
three
manufacturers
in
total,
mark
“80%
or
more.”
-lessihan
atleast20%but
atleast3S%hut
a:leaszS0%but
arie,ast65%bsn
80%or
20%
under35% under50% under65%
wider80%
mom
0
Ii 000
0
10.
How
extensive
is
your
coverege
of
the
various
market
segments
for
this
product?
Mark
an
X”
at
the
point
on
the
scale
that
best
describes
the
number
of
market
segments
in
which you
are
active:
all
segments
i————!————l————~————i————~————~————I
only
one
segment
I
I.
How
easy
is
it
to
determine
the
market
demand
for
thr~
single
product?
Mark
an
“X” at
the appropriate
point.
very
difWuli
STRATEGY
USED
IN
YOUR
PRICING
DECISION
page
2
Consider
which
of
the
following
best
describes
the
pricing
strategy
that you
used
for
the product
you
just
described
on
the
previous
page.
Remember
that
this
is
for
the
decision
made
in
the
past
12
months
for
a
single
product.
£IEAIE~X
A.
Price
Skimming
B. Penetration
Pricing
C.
Experience Curve
Pricing
D.
Complementary
Product
Pricing
E.
Price
Bundling
F.
Customer
Value
Pricing
G.
Price
Leader
H.
Parity
Pricing
I.
Low
Price
Supplier
J.
Cost-plus
pricing
DESCRIPTION
We
set
the
initial
price
high
and
then
systematically
reduce
it
over
time.
Customers
expect
prices to
eventually
fall.
Related
Strategies:
Premium Pricing,
Value-in-Use
Pricing
We
initially
set
the
price
low to accelerate
product
adoption.
We
set
the
price
low
to
build
volume
and
reduce
costs
through
accumulated
experience.
Related Strategies:
Learning
Curve
Pricing
We
price
the
core
product
low
when
complementary
items
such
as
accessories,
supplies,
spare
parts,
services,
etc. can
be
priced
with a higher
margin.
Related
Strategies:
Razor-and-Blade
Pricing
We
offer
this
product
as
part
of
a
bundle
of
several
products,
usually
at
a
total
price
that
gives
our
customers
an
attractive
savings
over
the
stun
of
the
individual
prices.
Related
Strategies:
System
Pricing
We
price
one version
of
our
product
at
very
competitive
levels,
offering
fewer
features
than
are
available
on
other
versions.
Related
Strategies:
Economy
Pricing
We
initiate
a
price
change
and
expect
the
other
firms
to
follow.
Related
Strategies:
Umbrella
Pricing, Cooperative Pricing,
Signaling
We
match
the
price
set
by
the
overall
market
or
by
the
price
leader.
Related Strategies:
Neutral
Pricing,
Price
Follower
Pricing.
We always
strive
to
have
the
low
price
in
the market.
Related Strategies:
Parallel Pricing, Adaptive Pricing,
Opportunistic Pricing
We
establish
the
price
of
the
product at
a
point
that
gives
us
a
specified
percentage
profit
margin
over
our
costs.
Related Strategies:
Contribution Pricing, Rate-of-Return
Pricing,
Target-Return
Pricing,
Contingency Pricing,
Markup
Pricing
Questions:
I.
If
you
used
a
pricing
strategy
not
listed
above please
‘~
~
2.
Which
pricing
strategy
~
describes
what
you
used
for
pricing
this
product?
Enter
the
appropriate
letter
from
above:
strategy:
3.
If
you
used
more
than
one
strategy in
your
decision,
enter
the letter
of
each
strategy
and
its
relative
importance
in
your
decision
b
dividing
l00~
among
the various
strategies
used:
strategy:
[J
:
_________
strategy:
III:
..........................%;
strategy:
~IJ
:
_________
SITUATION
WHEN
YOU
MADE
THE
PRICING DECISION
page
3
I.
Circle
the
number
on
the
scale
which
best
describes
the
situation
at
the
tune
the
pricing
decision
~
made.
1.1
YOUR
MARKET
a.
Market
growth
rate:
b.
Sensitivity
of
market
demand
to
changes
in
the
average
market
price:
c.
Sensitivity
of
customers
to
price differences
between
brands:
d. Customer
switching
costs (difficulty
of
changing
brands):
I
.2 YOUR
COMPETITION
a.
Product
differentiation
among
competitors:
b.
Technical
support
differentiation
among
competitors
(design
capability,
service
and
parts support.
etc.i
c.
Ease
for
new
conipetitors to
enter
the
market:
d.
Ease
of
detecting competitive
price changes:
I.s
YOUR
PRODUCT
a.
Product
life
cycle
stage
(circle
one):
b.
Share
of
market:
c.
Profitability
of
i~~lm~Ia~
sales (e.g.,
spare
parts,
services:
d.
Profitability
of
goc
~~ny.ujg
sales
(e.g.,
other
products):
e.
Factory
capacity
utilization:
highgrowth
7 6
5 4 3
2
1
vetysensitive
7
65 432
verysenhitive
7
6 5 4 3 2
veryhigh
7
6
5
4 3 2
very
high
very
high
verycasy
7
6
5
4
3
2
I
verycasy
7 6
5
4
3
2
I
introduction
ma*et
linda’
viny high
very high
operating
at
capsety
Growth
765
765
765
765
Matiaw
4321
4321
4321
4321
low
or
negative
growth
I
veiy
insensitive
I
very
insensitive
I
very
low
veryhigh
7
6
5
432
1
verylow
f.
Perceived
quality
(relative
to
the
average
of
your
three
largest
competitors)
g.
How
would
you describe your
cost
nosition
relative
to
your
competitors?
strong cost
moderate
cost
nobody
has
a
cost
moderate
cost
strong cost
advantage
advantage
advantage
disadvantage
disadvantage
0 0 0 0 0
h.
What
are
the
sources
of
this
cost
difference
in
item
“g’?
Enter
a
(plus
for
your
advantage) or
(minus
for
your
disadvantage) in
all
boxes
that
apply
to
describe
y~
positron
relative
to
your
competitors.
economies
of
experience or
labor
nurerial
OIhu
_________________________
scale:
learning
cw’ve:
costs:
costs:
D
D
DD
D
i.
How many
years
ago
was
the
current
model
of
this
product
introduced
(i.e.,
available
for
shipment)?
notyet
lessthan
I
atleast
I
but
atleast2but
atleast5but
l0yearsor
available
year
under
2 years
under
5
years
under
10
years
more
0 0
0
0 0 0
2.
Are
there
any
important
factors
missing
from
the
above
list
which
influence
your
choice
of
pricing
suategy?
If
so,
describe
them
and
indicate
their
levels
at that
time:
____________________________
veryhigh765J32
Iverylow
__________________________________________
vgrv
hugh
7
6
5
.1
3 2
I
~
7
6 5 4 3 2
I
verylow
7
6
5 4 3 2
I
verylow
very
difficult
very
difficult
Decline
very
low
very
low
very
low
could
easily
increase
production
YOUR
BACKGROUND
page
4
To
understand
more
about
the
managers
involved
with
this
survey,
please
tell
me
something
about
yourself.
1.
How
many years
have
you
spent
in
this
industry
?
lessthan
I
atleast
I
but
atleast2
but
atleast5but atleast
lObut
at
least
20
year
under
2
years
under
S
years
under
10
years
under
20
years
years
00000
0
2.
How
many years
have
you
spent
with
this
~~gny?
lessthan
I
atleast
I
but
atleast2but
atleast5but atleast
lObur
atleast
20
year
under2years
underSyears
underl0years
under20years
years
0 0 0
0 0 0
3.
What
is
your
current