An Empirically-Validated Framework
for Industrial Pricing
Peter M. Noble
Humbolt State University
Thomas S. Gruca
University of Iowa
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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 pricing strategies 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 Equipment Operations,” 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 has to 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 revenue stream 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 for the 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 pricing and 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 pricing environment 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 pricing strategies have
generally been limited in scope to researching small numbers of firms or to identifying strategies
without regard 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.
A Framework 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. Several related 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 includes major elements of Tellis’ (1986)
framework including product differentiation, economies of scale, capacity utilization, and
switching costs. Other determinants are based on additional sources including pricing articles
(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
ofrelated 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 determinants are
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 ofProduct 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 as a 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 profitmaximizing 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 lowprice new product pricing strategies (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 pricing has 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 pricing involves imitating the prevailing prices in the market, maintaining a constant
relative price between competitors. In some 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), inelastic total 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-cutting behavior 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-price Supplier 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 than their 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 fullservice 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 framework contains 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, we tested 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 ofPricing Strategies
Previous research on pricing objectives shows that many managers use more than one
objective in their pricing decisions (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 pretest 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 pricing decisions of differentiated, durable capital goods in
business-to-business markets. We restricted our sample to these industries since industrial
components, supplies or raw materials are less likely to be highly differentiated which would
restrict the pricing strategy options ofthe 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 for the 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 oftoo 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 cover letter
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. Ofthese, 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 pricing decision 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 for the 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 pricing and 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 for the 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 ofthe 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 pricing was 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 if the 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 pricing strategy.
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 Costplus 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 ofthese 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 when they 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 ifthe 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 pricing was 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 for the selection of
pricing strategies for differentiated industrial products. By focusing on the unique determinants,
we can streamline the decision process without 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 pricing framework, 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 ofthe 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% ofthe 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 Janusfaced 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 ofthe
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 indicate the 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 ifLeader pricing was given a weight greater than
zero (3 1 observations), 0 ifthe 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 LowPrice 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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34
Table 1
Pricing Strategy Definitions
Principal
Strategy
Description
Related Strategies
New Product Pricing Strategies
Price Skimming We set the initial price high and then
systematically reduce it over time. Customers
expect prices to eventually fall.
Premium Pricing, Value-in-Use
Pricing
Penetration
Pricing
We initially set the price low to accelerate
product adoption.
Experience
Curve Pricing
We set the price low to build volume and reduce Learning Curve Pricing
costs through accumulated experience.
Competitive Pricing Strategies
Leader Pricing We initiate a price change and expect the other
firms to follow.
Umbrella Pricing, Cooperative
Pricing, Signaling
Parity Pricing
We match the price set by the overall market or
the price leader.
Neutral Pricing, Follower
Pricing
Low-Price
Supplier
We always strive to have the low price in the
market.
Parallel Pricing, Adaptive
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
several products, usually at a total price that
System Pricing
gives our customers an attractive savings over
the sum ofindividual prices.
Customer Value We price one version ofour product at very
Pricing
competitive levels, offering fewer features than
are available on other versions.
Cost-Based Pricing Strategies
Cost-Plus
We establish the price ofthe product at a point
Pricing
that gives us a specified percentage profit
margin over our costs.
35
Economy Pricing
Contribution Pricing, Rate-of
Return Pricing, Target Return
Pricing, Contingency Pricing,
Markup Pricing
Table 2:
Determinants of Pricing Strategies
New Product Pricing Strategies
Skim Pricing
Penetration
Pricing
Unique to Strategy
Type:
Product age
New (1.10)
New (1.10)
New (10.11)
Within-type
Determinants:
Product
differentiation
Significance of
product change
Costs
Scale or experience
curve effects
Demand
Factorvcapacity
utilization
High (4.8.10)
Low (4,8,10)
Low (4.8.10)
Maior (6.10)
Minor (6,10)
Minor (6.8.10)
Hi2h (4.10)
Low (4)
Advantaae: scale
(3.4.8.10.11)
Elastic (1.3,4.6.8)
Low(l0.1l)
Low (4)
Disadvanta2e (10)
Inelastic (4.8.10)
Hi~h(3.l0)
Within-type
Determinants:
Other Determinants:
Advanta~ie:
experience (4.8.10.11
Elastic (1.3.4,6.8.9)
Low(10.l1)
Price
Leadership
Parity Pricing
Low-Price
Supplier
Product Life Cycle
Mature (5)
Mature (3.5)
Mature (5)
Ease of determining
demand
Easy (4)
Ea~ (4)
Easy (4)
Market share
High (4.5)
Low (8)
Low (2,5)
Costs
Scale or experience
curve effects
Low (4)
Advantage (2,4)
Hi2h (2.3.4)
Low (8)
Disadvantaae (3)
Advantage (4)
Ease of detecting
price changes
Total demand
Factory capacity
utilization
Easy (2)
Easy (3,8)
Difficult (2)
Inelastic (2,3)
High (10)
Inelastic (3)
High (10)
Elastic (3)
Low (5)
Low (8)
Low (8)
Elastic (3)
Elastic (3)
Competitive Pricing Strategies
Unique to Strategy
Type:
Experience Curve
Pricing
Product
differentiation
Brand Demand
36
)
Complementary
Product Pricing
Product Line Pricing Strategies
Unique to Strategy
Type:
Common (withintype) Determinants:
Other Detenninants:
Firm sells entire
Yes (3
product line (other
models, ancillary
products. supplementan products)
Profitability of
Hi!h
accompanying or
supplementary sales
Switching costs
Per sale/contract
pricing
Market appeal
Market growth rate
Ease of detecting
price changes
Bundling Pricing
Customer Value
Pricing
Yes (3
Yes (3
(3.5
Hii~h (11
Yes (4
Narrow
Low
Difficult
Brand demand
Elastic (3)
Cost-Based Pricing Strategies
Cost-Plus
Pricing
Unique to Strategy
Ease ofdetermining
Diflicult (3)
Type:
demand
Common (within-
none
type) Determinants:
Other Determinants:
none
References:
I. Dean (1950)
2.
7. Monroe (1990)
Greer(1984)
3. Guiltinan, Paul and Madden
4. Jam (1993)
8. Nagle and Holden (1995)
(1997)
Oxenfeldt (1975)
10. Schoell and Guiltinan (1995)
9.
11, Tellis (1986)
6. Mercer (1992)
37
Elastic (3.7.8. 10)
Table 3
Determinants of Pricing Strategies
Definition of Determinant
Scale in Survey
Market Conditions
Sensitivity of customers to price differences between brands
I
Sensitivity oftotal demand to changes in average price
Ease ofdetermining market demand
I
Market growth
Switching costs
=
insensitive, 7
=
insensitive, 7 = sensitive
=
easy, 7 = difficult
=
low, 7
=
low, 7
=
difficult, 7 = easy
=
=
sensitive
high
high
Competitive Conditions
Ease of detecting competitive price changes
Concentration: Three firm concentration ratio
I =K5%, 7=> 80%
Product differentiation
I = low. 7
high
Product/Company Conditions
Age ofproduct in years
1
Cost (dis)advantage due to experience curve
I = (dis)advantage, 0 = otherwise
Cost (dis)advantage due to economies ofscale
not yet available, 2
6= lO+years
=
<
1 year,
=
(dis)advantage, 0 = otherwise
Capacity utilization (relative)
I
=
low, 7
Costs (relative to competitors)
1
=
advantage, 7
Major Product Change: Significance of most current design
change
1
=
high
=
disadvantage
totally new product,
= otherwise
o
Market Coverage
=
all segments, 7 = one segment
Market Share
1
=
low, 7
Per Sale/Contract Pricing
1
=
yes, 0
Profitability of accompanying sales (e.g., other products)
1
=
low, 7
high
Profitability of supplementary sales (e.g.. spare parts. service)
I
=
low, 7
high
38
=
=
=
leader
no
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
3537
3541
3542
3549
3554
3571
3663
Industrial Trucks and Tractors
Machine Tools, Cutting
Machine Tools, Forming
Metal Working Machines
Paper Industry Machines
Electronic Computers
Radio and TV Communication Equipment
3711
Tractor and Tractor Trucks
3721
Aircraft
3743
Railroad Equipment
3812
Search and Navigation Equipment
3823
Process Control Instruments
63
188
18
41
64
Total
Company Size
(Annual Revenue in millions)
93
57
77
32
83
269
Number of Firms in
Mailing List / Sample
118
151
1534
Number of Firms
Responding
$5-$14
$15-$49
836/427
393/342
93
77
$50-$149
$150-$499
149/130
75/65
36
24
81/70
39
$500+
unknown
Total
1534/1034
39
270
Table 5
Cross-Validation of Pricing Strategy Using Relative Price
Expected
Price
Std. Dev. Of
Relative
Price
t-statistic
(p-value) *
High
4.11
1.51
2.22 (0.02)
31
High
3.97
1.40
1.63 (0.06)
Parity Pricing
82
Same
3.35
1.20
1.59 (0.12)**
Customer Value
29
Low
3.37
1.42
-0.72 (0.24)
32
Low
3.68
1.49
-0.46 (0.33)
24
Low
3.21
1.25
-1.37 (0.09)
Penetration Pricing
25
Low
2.68
1.77
-2.49 (0.01)
Low Priced
24
Low
2.00
1.25
-6.46 (0.00)
Number of
Respondents
Relative
Price
Skim Pricing
37
Leader Pricing
Strategy
Mean of
Relative
Pricing
Experience Curve
Pricing
Complementary
Product Pricing
Supplier
Entire Sample
*
270
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
ProductAge(-)
Intercept
Model Chi-square
Model Fit
Positive Responses
Competitive Strategies
ProductLifeCycle(+)
Ease ofEstimating Demand (-)
Intercept
Model Chi-square
Model Fit
Positive Responses
Estimate
-0.31
0.32
12.24
p <0.00
87
0.51
-0.03
-1.21
Std. Error
0.09
0.33
Chi-square
11.56
0.95
Prob>Chi2
0.00
0.33
0.16
0.08
0.50
10.22
0.21
5.77
0.00
0.65
0.02
0.43
0.41
3.42
15.72
0.06
0.00
0.07
0.29
2.85
0.45
0.09
0.50
11.39
p <0.00
127
Product Line Strategies
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
0.81
-1.64
3.90
p K 0.05
76
0.13
-0.20
2.89
p <0.09
152
41
Table 7: Test of Determinants of Individual Pricing Strategies
Skim Pricing
Estimate (Prob > Chi2)
Restricted
Full Tobit
Tobit
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)
Intercept
-185.61 (0.00)
Model Fit
p K 0.04
37
Sample
Penetration Pricing
Unique Determinants’
Cost advantage: scale (+)
55.88 (0.02)
Common Determinants’
Product Differentiation (-)
Major Product Change (-)
Cost (-)
8.65 (0.24)
12.76 (0.56)
-14.61 (0.11)
19.23 (0.01)
Market Elasticity (+)
Brand Elasticity (+)
Capacity Utilization (-)
Intercept
Model Fit
Sample
Experience Curve Pricing
43.49 (0.05)
-17.69 (0.01)
-156.98 (0.00)
p <0.01
-0.82 (0.89)
141.17 (0.03)
p <0.00
25
25
Unique Determinants’
Cost advantage: learning (+)
4.09 (0.84)
2.99 (0.87)
Common Determinants
13.18
-45.15
6.45
5.56
Product Differentiation (-)
Major Product Change (-)
Market Elasticity (+)
Brand Elasticity (+)
Capacity Utilization (-)
Intercept
Model Fit
Sample
(0.07)
(0.06)
(0.33)
(0.35)
-11.80 (0.05)
-125.91 (0.00)
-176.69 (0.00)
p <0.84
p<0.08
31
31
42
Price Leadership
Restricted
Tobit
Full Tobit
Unique Determinants’
Market Share (+)
7.93 (0.12)
Common Determinants’
Cost (-)
6.33 (0.20)
12.12 (0.20)
31.05 (0.13)
33.03 (0.11)
9.52 (0.10)
Cost advantage: scale (+)
Cost advantage: learning (+)
Ease: detecting price changes (+)
Market Elasticity (-)
Capacity Utilization (+)
-3.86 (0.50)
-0.11 (0.98)
Intercept
-148.29(0.00)
-321.63 (0.00)
Model Fit
p <0.10
p <0.04
31
Sample
31
Parity Pricing
Unique Determinants’
Cost (+)
Cost disadvantage: scale (+)
Cost disadvantage: learning (+)
Common Determinants’
Market Share (-)
Ease: detecting price changes (+)
Market Elasticity (-)
Capacity Utilization (+)
Intercept
Model Fit
Sample
15.55 (0.00)
20.55 (0.13)
16.39 (0.38)
-94.23 (0.00)
p
K
0.00
82
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)
p K 0.00
82
Low-Price Supplier
Unique Determinants’
Ease: detecting price changes (-)
Market Elasticity (+)
Capacity Utilization (-)
1.54 (0.82)
-5.93 (0.42)
-15.52 (0.04)
Common Determinants’
Market Share (-)
-0.87 (0.89)
-7.61 (0.31)
-12.63 (0.08)
-5.98 (0.32)
Cost (-)
-42.57 (0.00)
Cost advantages due to scale (+)
Cost advantage: learning (+)
Intercept
51.26 (0.07)
-38.25 (0.15)
Model Fit
Sample
-82.93 (0.11)
p <0.01
81.44 (0.18)
p <0.00
24
24
43
Bundling Pricing
Unique Determinants’
Per Sale/Contract Pricing (+)
Intercept
Model Fit
Sample
Complementary Product Pricing
Unique Determinants’
Profitability of accompanying
sales (+)
Profitability ofsupplementary
sales (+)
Switching Costs (+)
Intercept
ModelFit
Sample
Customer Value Pricing
Unique Determinants
Ease: detecting price changes (-)
Market Coverage (+)
Market Growth (-)
Intercept
Model Fit
Sample
Full Tobit
38.32 (0.02)
-99.25 (0.00)
p < 0.01
35
-0.23 (0.96)
15.17 (0.01)
2.01 (0.56)
-160.09 (0.00)
p<O.Ol
24
-12.72
8.53
7.13
-112.42
(0.02)
(0.10)
(0.20)
(0.00)
p <0.02
29
44
Table 8:
Strategy
Type
• New Product
Pricing
Validated Pricing Strategy Framework
Principal Strategies
• related strategies
Determinants
.
New model
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
Pricing
• Product Line
Pricing
• Cost-Based
Pricing
•
Mature market
• Firm sells
substitute or
complement
ary products
determine
demand
High costs
Low -price Supplier
• Parallel pricing
• Adaptive pricing
• Opportunistic pricing
• Low factory
Bundling
• System Pricing
• Per sale I contract
Complementary Product
Pricing
• Razor-and-blade
pricing
Customer Value Pricing
• Economy pricing
• High profit on
utilization
Relative
Price
• High
• 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
el-liali
• Equal
• Low
pricing
Cost-plus pricing
• Contribution Pricing
• Target return pricing
• Markup pricing
• Difficult to
* based on t-tests in Table
Leader Pricing
• Umbrella Pricing
• Cooperative Pricing
• Sianaling
Parity Pricing
• Neutral pricing
• Follower pricing
Additional
Favorable
Conditions
5
45
supplementa~ sales
• Hard to detect price
changes
• Narrow market
appeal
• Low
Table 9
Importance Weight Distribution by Pricing Strategy
Importance Weight
Strategy
10%
20%
30%
400/0
50%
60%
70%
800/o
90%
100%
Total
New Product Pricing Strate ies
SkimPricing
2
6
5
0
3
1
2
1
0
16
36
Penetration Pricing
ExperienceCurvePricing
2
4
5
5
5
5
0
0
3
3
0
1
3
3
1
0
5
25
1
0
9
31
4
1
7
4
1
7
12
4
1
112
3
5
0
6
3
3
210
6f1
3 j 0
Competitive Pricing Strate ies
LeaderPricing
f 5
ParityPricing
Ill
Low-PriceSupplier
3
Product Line Pricing Strategies — — —.
Complementary Product
7
9
3
1
Pricing
BundlePricing
8
9
3
2
Customer Value Pricing
[1
4 [31
22
81
7 f 24
2
— —. —. —
0
1
0
0
1
24
1
.2
4
2
0
4
24
2
9
8
0
1
2
1
1
0
6
30
Cost-based Pricing Strategies
Cost-Plus Pricing
10
8
10
9
14
13
12
14
3
57
150
Note: Median is indicated by underlined type.
46
Figure 1: Overview of Industrial
Pricing Framework
•
•
•
•
•
•
High product
differentiation
Significant design
change
High relative costs
Cost disadvantage due
to scale or experience
Inelastic demand
Low factory
utilization
Skim Pricing
(high)
New model of
product
•
High relative costs
•
Cost disadvantage due
to scale or experience
•
Difficult to detect
S
price changes
Elastic total demand
Low capacity
0
utilization
•
High profitability of
accompanying or
supplementary sales
High switching costs
Complementary
Product Pricing
(low)
•
Per sale./contract
pricing
Bundling
Pricing
•
Narrow market appeal
•
Low market growth
•
Difficult to detect
•
•
Company sells
complementary or
substitute products
price changes
Difficult to
estimate demand
Strategy Type
Determinants
Cost-based Pricing
Strategies
Strategy Types
Customer
Value Pricing
(low)
Cost-Plus
Pricing
Unique Principal
Strategy Determinants
47
Principal Pricing
Strategies
(relative price)
.
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
9 sold in business-to-business markets. Please provide some
decision you describe should be for a single durable good
general back~ound information for your product. Answer for one oroduct only
1.
This specific product
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:
4.
from $3,000
to S9.999
from SIO.000
from S30.000
to $29,999
to $99,999
from $100,000
to S299,999
$300,000
or over
00
0
0
0
0
0
How often do you (or your company) set the pricing for this product?
weekly
5.
monthly
quarterly
semi-annually
annually
each saledcontmct
Otlw
0
0
0
0
0
0
I
atleas: 1%
but under 5%
0
0
atleastS%
but under 25%
0
atleast2.5%
50%
but under 30% or over
0
0
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
We offer other products to this market which, relative to this product. are (check all that apply):
substitutes
complements
o
have no relationship tothis product
0
How would you charecterize ~
morethan5%
below
o
9.
lessthan
I 1%
Division
o
8.
____________
What percent ofthe annual dollar sales of your division (or company, as appropriate) does this product represent?
~
7.
_____________________________________________________
under from $1,000
$ 1.000 to $2,999
o
6.
is best described as:
no other products are available
0
in relation toy~ THREE largest competitors?
2%to5%
below
about
equal
2%to5%
above
mored~an5%
above
Suchacompauisonis
meaningless in my situation
0
0
0
0
0
Approximately what percentage of the dollar sales for this product categoiy in the U.S. market is made by the
THREE largest manufactiws? Ifthere 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
0
0
0
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 ofmarket 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.
A.
£IEAIE~X
DESCRIPTION
Price Skimming
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
B.
Penetration
Pricing
We initially set the price low to accelerate product adoption.
C.
Experience Curve We set the price low to build volume and reduce costs through accumulated experience.
Pricing
Related Strategies: Learning Curve Pricing
D.
Complementary
We price the core product low when complementary items such as accessories, supplies,
Product Pricing
spare parts, services, etc. can be priced with a higher margin.
E.
Price Bundling
We offer this product as part ofa bundle of several products, usually at a total price that
gives our customers an attractive savings over the stun of the individual prices.
F.
Customer Value
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
G.
Price Leader
We initiate a price change and expect the other firms to follow.
H.
Parity Pricing
We match the price set by the overall market or by the price leader.
Related Strategies: Neutral Pricing, Price Follower Pricing.
I.
Low Price
Supplier
We always strive to have the low price in the market.
Related Strategies: Parallel Pricing, Adaptive Pricing,Opportunistic Pricing
J.
Cost-plus
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
Related Strategies: Razor-and-Blade Pricing
Related Strategies: System Pricing
Related Strategies: Umbrella Pricing, Cooperative Pricing, Signaling
Questions:
I. Ifyou used a pricing strategy not listed above please
2. Which pricing strategy ~
‘~
~
describes what you used for pricing this
strategy:
product? Enter the appropriate letter from above:
3. Ifyou used more than one strategy in your decision, enter the letter ofeach strategy and its relative importance in
yourdecision 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 atthe tune the pricing decision ~
1.1
YOUR MARKET
a. Market growth rate:
made.
4 3 2
1 low or negative
growth
highgrowth 7 6 5
b. Sensitivity of market demand to changes in the average
market price:
vetysensitive 7
6
5
4
3
2
I
c. Sensitivity of customers to price differences between brands:
verysenhitive 7
6
5
4
3
2
I very insensitive
veryhigh 7 6 5 4
d. Customer switching costs (difficulty ofchanging brands):
3 2
veiy insensitive
I very low
I .2 YOUR COMPETITION
7
6 5 4 3 2 I
7
6
5
4
3
2
I verylow
c. Ease for new conipetitors to enter the market:
verycasy 7 6
5
4
3
2
I
d. Ease ofdetecting competitive price changes:
verycasy
7 6 5 4 3 2
I
a. Product differentiation among competitors:
very high
b. Technical support differentiation among competitors
(design capability, service and parts support. etc.i
very high
verylow
very difficult
very difficult
I.s YOUR PRODUCT
introduction
a. Product life cycle stage (circle one):
b. Share ofmarket:
Growth
viny high
d. Profitability of goc ~~ny.ujgsales (e.g., other products):
very high 765
operating at
capsety
e. Factory capacity utilization:
f. Perceived quality (relative to the average of your three
very low
4321
ma*et linda’ 765
c. Profitability of i~~lm~Ia~ sales (e.g., spare parts, services:
Decline
Matiaw
very low
4321
765
very low
4321
765
could easily increase
4321
production
4 3 2
veryhigh 7 6 5
1
verylow
largest competitors)
g. How would you describe your cost nosition relative to your competitors?
strong cost
advantage
moderate cost
advantage
nobody has a cost
advantage
moderate cost
disadvantage
strong cost
disadvantage
0
0
0
0
0
h. What are the sources ofthis 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
scale:
experience or
learning cw’ve:
D
i.
2.
D
labor
costs:
nurerial
costs:
OIhu
DD
_________________________
D
How many years ago was the current model of this product introduced (i.e., available for shipment)?
notyet
lessthan I
atleast I but
available
year
under 2 years
atleast2but
under 5 years
atleast5but
under 10 years
l0yearsor
more
0
0
0
0
0
0
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:
32
____________________________
veryhigh765J
__________________________________________
vgrv hugh 7 6 5 .1 3
Iverylow
2
I
~
?
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
year
atleast I but
under 2 years
atleast2 but
under S years
atleast5but
under 10 years
atleast lObut
under 20 years
at least 20
years
0
0
0
0
0
0
2. How many years have you spent with this ~~gny?
year
lessthan I
under2years
atleast I but
atleast2but
atleast5but
atleast lObur
atleast 20
0
0
0
0
0
0
underSyears
underl0years
under20years
years
3. What is your current title in this company?
4. In which deparunent are you currently employed?
5. In what other areas do you have professional experience (e.g., accounting, production, marketing, engineering.
human resources, etc.)?
6. What is the approximate size of your division (or company, as appropriate) in terms ofannual sales (in millions of
dollars)?
~
Divisiofi
~~J0
Ieasthan
from SSto
from SISto
from SSOto
fuomSISO:o
55
514
S49
5149
3499
0
0
0
0
from S500to
51.499
SI.500
orover
0
0
7. ltyou responded for your division in question 6, please indicate the approximate size of your ~~tiy
annual sales (in ~jjjj~ of dollars).
leisthan
35
St4
fiunSlSto
$49
fwmSS0to
$149
fromSl5Oto
$499
0
0
0
0
0
fromiSto
fmmS500to
31.499
in terms of
31,500
orover
0
0
D
8. How many people were involved in this pricing decision?
Please indicate your level of involvement in the decision compared to the other people by placing an “X” at the
appropnaze point on the following scale:
major
I
I
1!
about equal
I
I
I
none
9. How many different products are you personally involvedwith for pricing decisions?
onlythisone
2toS
6tolO
lIto2O
morethan20
0
0
0
0
0
ThANK YOU again for your help in completing this survey. Please fold it in three and return it in the enclosed envelope
to:
Peter M. Noble
College of Business Administration
The University of Iowa
108 Pappajohn Bus. Adm. Bldg., Suite S-250
Iowa City, IA S2242-l000
Ifyou are interested inacopy ofthe results of the survey, available late summer. 1994, please enclose your business
card.