Emperically Vaildated Framework for Industrial Pricing

8/3/2019 Emperically Vaildated Framework for Industrial Pricing

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An Empirically-Validated Framework

for Industrial Pricing

Peter M. NobleHumbolt State University

Thomas S. GrucaUniversity ofIowa

ISBM Report 9-1998

Institute for the Study ofBusiness MarketsThe Pennsylvania State University

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University Park, PA 16802-3004(814) 863-2782 or (814) 863-0413 Fax


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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 ofBusiness

University ofIowaIowa City, IA 52242-1000

319-335-0946 (phone)

319-335-1956 (fax)

thomas-gruca~uiowa.edu

A previous version ofthis paper was presented at the 1995 INFORMS International Conference

in Singapore. The authors would like to thankGerry Tellis and Kent Monroe for their review ofthe survey used in this research.


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An Empirically-Validated Frameworkfor Industrial Pricing

Abstract

We propose and test a parsimonious and comprehensive two-level frameworkfor

industrial goods pricing which allows for multiple pricing strategies for a single product. We

identify a reduced set ofcost, 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 ofthe 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 of10 industrial pricing

strategies.

We validated the frameworkthrough a national survey ofpricing 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 ofmany authors to bridge the gap between the normative

research on pricing and actual managerial behavior.

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Introduction

Pricing is one ofthe most important and complex ofall marketing decisions. There is a

wide range ofproduct, 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 ofbulldozer 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 ofthe 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 recoverthe 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 ofthe 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 frameworkthat highlights the similarities and

differences among a wide range ofpricing strategies. Two dimensions ofshared economies

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available to a firm and the consumer conditions necessary to exploit these economies determine

which ofnine 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 ofpricing strategies which had, heretofore, been

discussed in relative isolation.

The focus ofthe 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 ofpricing strategies for a firm. However, there are additional requirements associated with

relative quality or costs that are necessary for the choice ofstrategy 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 ofcosts or quality.

By construction and in the interest ofclarity ofpresentation, the Tellis frameworkassumes

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 ofmanagerial prescriptions for pricing.

Since all models are necessarily simplifications ofreality, 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 ofintegrating the existing pricing

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literature. However, by focusing on a smaller set ofindustrial pricing problems (capital goods),

we are able to achieve closure through empirical validation ofour 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 ofcost, 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 ofunique conditions under which a principal strategy within each type should

be used. For example, one type ofpricing 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 ofthe 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

ifit has relatively low costs. Similar relationships between pricing strategy types, principal

strategies and determinants are developed for a comprehensive set offour strategy types and 10

principal pricing strategies..

We validated our framework through a national survey ofpricing managers in capital

goods industries. We asked them about characteristics ofthe product, their company and the

product-market at the time oftheir last pricing decision. Using limited dependent variable

regression models, we confirmed most ofthe expected relationships between the proposed

determinants, pricing strategy types and principal pricing strategies.

This frameworkprovides 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 ofmany authors (Bonoma,

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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 ofthe 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 ofobjective is related to

the pricing environment ofthe firm (Diamantopoulos and Mathews, 1994).

The study ofpricing 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 ofwhat pricing strategies will be used to

accomplish the goals ofthe firm. For the purpose ofthis 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 ofpricing strategies.

A briefexample may help distinguish these constructs. Consider a firm with a pricing

objective ofmaximizing 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:

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154-158). In a second scenario, the same company is faced with highly price sensitive customers.

Ifthe firm can reduce its unit costs by spreading its fixed costs over a high volume ofoutput, 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 ofscale.

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 ofthis study to develop a frameworkfor 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 ofpricing strategies have

generally been limited in scope to researching small numbers offirms 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 offirms have

generally not been statistically rigorous (see Diamantopoulos 1991 for review ofthese 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 ofthe literature, we identified a set ofindustrial pricing

strategies and determinants following the example set by Tellis (1986). However, our study

focuses on the under-researched area ofindustrial (capital goods) pricing while the Tellis

framework is more oriented towards consumer products. To accommodate these differences, we

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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 ofindustrial

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 ofthe principal strategy (e.g., Markup Pricing is a form

ofCost-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 ofthe

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 ofbeing strategies which are applied

early in the life ofthe model in question. Included in the category ofentry strategies are: 1) Skim

Pricing, 2) Penetration Pricing, and 3) Experience Curve Pricing.

Competitive strategies have as their main focus the price ofthe product relative to the

price ofone 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 ofone product is influenced by

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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 ofthe 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

ofCost-based pricing strategies.

Strategy Determinants

In every normative discussion ofpricing strategy, a set ofmarket, 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 ofdeterminants we include in our study includes major elements ofTellis (1986)

frameworkincluding product differentiation, economies ofscale, 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, ifbrand 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 ofbrand elasticity does not separate these principal strategies

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from each other.

On the other hand, we also discovered that some determinants are unique to a given

strategy type. For example, the presence ofother 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 ofindustrial 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 ofconditions under which a given principal strategy is optimal. This organization

ofthe 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 ofour 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 ofthe model

being priced. Skim pricing, Penetration pricing and Experience curve pricing are al l appropriate

for new products.

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One might expect that Competitive pricing strategies would be appropriate for the

opposite condition, i.e. the pricing ofolder products. However, the common determinants for

these strategies (Price Leader, Parity pricing and Low-price Supplier) are a late stage ofthe

product life cycle and the ease ofdetermining demand. Note that these two conditions refer to a

mature market and not necessarily to the age ofthe 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 ofother

products, accessories or supplementary goods (e.g., spare parts) to guide the pricing ofthe

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 of39 business managers found the

general pattern ofprice 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 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 ofscale

and/or experience curve effects, neither ofthese conditions are likely to hold in a manufacturing

industry (Lilien and Kotler, 1983: 407).

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The weakness ofCost-Plus Pricing is that it ignores consumer and competitive

information. However, ifthe firm has little or no information about demand, then Cost-Plus

pricing is the default strategy (Harrison and Wilkes, 1975).

Determinants ofPrincipal Strategies

Three ofthe strategy types, New Product, Competitive and Product Line, contain more

than one strategy. For each ofthese 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 ofsetting a high initial price which is often systematically

discounted over time. The purpose ofSkim pricing is to discriminate between those buyers who

are insensitive to the initial high price because ofspecial needs. As this segment becomes

saturated, the price is lowered to broaden the appeal ofthe product (Dean, 1950).

Skim pricing is recommended over Penetration or Experience curve pricing when there is

a high degree ofproduct 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 lackcost advantages due to scale or learning should consider skimming over the low-

price new product pricing strategies (Schoell and Guiltinan, 1995).

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Both Penetration and Experience curve pricing involve setting a low initial price for a new

product. Penetration pricing is used to speed adoption ofa 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 ofadvantage 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 ofcontroversy about the extent ofthese

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; J a m 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 leaders price to set

their own price levels (Greer, 1984; Jam, 1993). Hence, this strategy is also known as Umbrella

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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 ofweakness. Ifa firm

had superior products, it should be able to command a premium price (Guiltinan, Paul and

Madden, 1997). Or, ifthe firm had cost advantages, it could become a low-price supplier (Jam,

1993). Ifa 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 lackofpricing knowledge in the market by under-cutting its rivals

(Greer, 1984). Ifthis 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 ofprice bundling have been explored in depth

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elsewhere (Guiltinan, 1987). Most ofthe 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 ofprice-setting process. When each sale or contract is

priced separately, as in the case ofsystem selling ofmainframe computers, then Bundling is a

preferred option (Jam, 1993). For example, a major avionics firm uses bundling in most ofits

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 ofthe few which make al l ofthese products, it usually wins the contract. In

addition, this approach reduces the number ofsuppliers (and potential incompatibility problems)

for the airframe manufacturer.

Complementary Product pricing began with King Camp Gillettes strategy ofselling razors

cheaply and blades dearly. For many industrial products, there are a wide range ofsupplies, spare

parts and accessories which make up a large portion ofthe profit stream from the customer. In the

Deere case above, it was suggested that a bulldozer consumes 90% ofits 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

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strategy involves pricing one version ofthe product at very competitive levels, offering fewer

features than are available for other versions. The most visible applications ofthis strategy

recently have been in consumer markets. For example, when McDonalds lowered the price ofits

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 ofconsumer 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 ofHon furniture, it produced a new line ofless 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 ofthe functionality ofits 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 frameworkfor

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 ofthe product. This serves as a

cross-validation ofour self-reported measures ofpricing strategies. Second, we tested the

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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 ofthis process, we have a reduced set ofconditions for managers to consider

when choosing pricing strategies for an industrial product.

Validation Study Design

To validate our framework, we conducted a national survey ofmarketing managers in

capital goods industries in the late spring/early summer of1994.

Survey

The survey document was a four page questionnaire mailed to practicing managers in May

and June of1994 (Figure 2). The survey underwent extensive pre-testing to assure readability and

accurate understanding ofthe questions. This included pilot testing with written and verbal

feedback from a convenience sample ofexecutive MBA students as well as a review ofthe survey

by two noted academic pricing scholars from other institutions.

Figure 2 about here

To avoid the criticisms leveled at many studies ofpricing objectives by Diamantopoulos

(1991: 136), we asked the managers to provide information on their most recent pricing decision

ofa 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

ofthe pricing strategy decision, we allowed respondents to indicate their usage ofup to three

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pricing strategies. The response to this question was ratio-scaled (importance weights summing to

100%) in order to assess the magnitude ofthe importance ofa given strategy in the decIsIon.

In the pre-testing for this study, we found that none ofthe 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 ofthe third strategy was 15% (versus

28% for the second strategy). Therefore, ifthere 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. Ofthe 21 who did, a total of17 , upon review by two

independentjudges and the authors, were found to be special cases or related strategies ofthe

original ten strategies. The remaining observations were dropped from the analysis

Measures ofDeterminants

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 ofthe 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 pricing decisions ofdifferentiated, 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 ofdistribution in

industrial markets tend to be shorter than those in consumer markets, the manufacturer exerts

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more control over pricing to end-users.

Fifteen such industries were identified using 4-digit SIC codes. The target industries and

distribution offirm 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 ofMarketing, Sales

Manager, Pricing Manager, and variations ofthese title. However, this targeting approach

resulted in the exclusion oftoo many smaller companies. Therefore, the category ofPresident,

CEO, and variations ofthese titles was included as well since this was the only title available for

the majority ofthe smaller companies.

A total of1021 firms was selected from this list (after deleting replicated records from the

total of1034). In a pre-test using a similar survey1, a sample of200 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 offirms. The

number offirms 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 ofthe 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


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Each firm was sent a survey package including a personalized, hand-signed cover letter

with a pledge ofconfidentiality ofindividual 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 of347 surveys were returned to the authors. Ofthese, 77 were returned blank

(62), incomplete or were otherwise2 unusable (15). This yielded a gross response rate of34%

(347/1007 delivered). The total usable sample was 270 for a usable response rate of27% which is

a similar sample size3 and usable response rate4 to recent surveys ofmarketing 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 ofrespondents 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 ofour pricing frameworkwhich 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 ofthe limitations ofprevious studies ofpricing objectives is the lackofan objective

19


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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 ofpricing objective.

For most pricing strategies, however, there is a one-to-one correspondence between the

level ofpricing 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 ofa 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 oftheir 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 al l 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


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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 ofthe 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 ofStrategy Types

From the importance weights for the principal strategies, we determined ifa respondent

chose a strategy within each ofthe four strategy types. A value ofone was assigned to a strategy

type ifa 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 ofintroduction ofthe

current model ofthe product being priced (Question 1.3.i on page 3 ofthe 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 ofchoosing this strategy type.

For Competitive pricing, the first independent variable is the stage ofthe 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 ofchoosing ofa 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 ofthe survey. In our analysis, we constructed

a dummy variable which had the value of1 ofthe firm produced either substitute or

complementary products and zero otherwise. We expect that this variable will be positively

21


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related to the probability ofchoosing a Product Line pricing strategy.

The sole determinant for Cost-based pricing is the ease ofdetermining demand in the

market. We expect that this variable will be positively related to probability ofchoosing 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 ofstrategy type and their determinants5. The results are given

in Table 6.

Table 6 about here

New Product strategies were chosen by 32% (87) ofthe respondents. The choice ofthis

strategy type was negatively and significantly (p


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framework.

Determinants ofPrincipal Strategies

In order to test the determinants for principal pricing strategies, we used a tobit model for

censored dependent variables (Tobin, 1958). Our measure ofpricing strategies included

information on the magnitude ofthe importance ofthe given principal strategy. The tobit model

will take advantage ofthe magnitude information for testing the relationships between principal

strategies and their determinants. We tested the restricted set ofunique determinants as well as

the full set ofunique 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 ofproduct 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% ofrespondents (37/27) incorporated skim pricing into their overall strategy.

The overall tobit model was significant at the p


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Penetration Pricing

Nine percent ofrespondents (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


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competition in the computer chip industry when clone chip producers introduce their products at

much lower prices to shift the focus ofcompetition 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 ofcompetition does not materialize.

Leader Pricing

Eleven percent ofrespondents (31/270) used Leader pricing.

High market share is the sole unique determinant ofLeader pricing. The overall model is

significant (p


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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) ofrespondents followed the Low-Price Supplier strategy.

Ofthe 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 ofthis strategy (p


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consistent with what we predict with razor-and-blade type products and durables which require

the eventual purchase ofcaptive spare parts in large quantities.

Customer Value Pricing

Customer Value pricing was used by 11% (29/270) ofrespondents.

The Tobit results for this strategy suggest that firms choose this strategy for products

which would appeal to a narrow segment (p


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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 ofproducts (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 ofentry barriers.

In addition, there was very little variation in self-evaluated product quality. The average

rating was 5.79 out of7 (std. dev. = 1.08). This is not surprising given a managers bias towards

his/her own firms 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 ofour pricing framework, the empirical study ofpricing

managers provides some important insights into current pricing practices. One ofthe more

interesting results is the varied importance ofdifferent pricing strategies. The distributions ofthe

importance weights and median importance weight for each strategy is presented in Table 9.

Table 9 about here

Consider the distributions ofthe 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 ofthe 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

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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 al l three ofthe strategies classified as secondary are from the product line group

ofstrategies (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 frameworkdeveloped 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 ofthe strategies.

For example, it is not known ifthe 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 ofCost-Plus Pricing. A full 56% ofthe 270

managers mentioned Cost-Plus Pricing. When it was used, it was the dominant strategy (with an

importance weight larger than any ofthe others mentioned) 71% ofthe time. This confirms the

observations ofSimon (1989) and others that, even after all ofthe 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 ofCost-Plus Pricing and one of

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the other nine market based strategies, implying that a significant number ofmanagers 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 ofresearch.

Conclusion

In their 1988 article, Bonoma, Crittenden and Dolan stated that managers find little ofthe

pricing research in marketing to be ofany practical help. The industrial pricing framework

presented here can help mangers cut through some ofthe fog ofthe pricing literature without

resorting to simplistic or misleading rules ofthumb.

30


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End Notes:

1 . The Noble (1997) study ofpricing objectives is identical except for the measures ofpricing

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 ofmanagers were

published in the Journal ofMarketing Research (JMR). The average sample for al l ofthe surveyswas 284. During the same period, the Journal ofMarketing (JM) published 41 articles involving

surveys ofmanagers. The average sample for al l ofthe 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 ofabout 32% andusable response rates of29%. In the JMR articles, the response rates were higher, with the gross

response rate about 40% and the usable response rate of37%.

5. Ifwe restricted our respondents to a single choice ofprincipal strategy, we could have used a

multinomial choice model. Managers could choose strategies from up to three different strategytypes. We decided to model this process as a set ofbinary choices since the determinants we

identified are related to the choice ofindividual strategy types and not to the choice of

combinations ofstrategy types.

6. We also tested the relationship between the choice ofLeader pricing and market share using a

logit model. The independent variable was 1 ifLeader pricing was given a weight greater thanzero (3 1 observations), 0 ifthe firm gave a positive weight to either Parity or Low Price Supplier

(96 = 127 - 31 observations), or missing ifno Competitive pricing strategy was given a positiveweight (143 = 270 - 127 cases). Thus, we tested the relationship between the choice ofLeader

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 andsignificant 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. Forthe full Leader pricing model, the coefficient for Cost advantage due tolearning 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 tolearning was negative (p


36/55

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_____________ (1990), Strategy in Retreat: Pricing Drops Out, The Journal ofBusiness andIndustrial Marketing, Vol. 5 No. 1 (Winter/Spring), pp. 5-25.

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Guiltinan, Joseph P. (1976), The Price Bundling ofServices: A Normative Framework, JournalofMarketing, 51(2), 74-85.

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Table 1 Pricing Strategy Definitions

PrincipalStrategy Description Related Strategies

New Product Pricing StrategiesPrice Skimming W e se t the initial price high and then Premium Pricing, Value-in-Usesystematically reduce it over t ime. Customers Pricingexpect prices to eventually fall.

Penetration W e initially se t th e price low to acceleratePricing product adoption.

Experience W e se t the price low to build volume an d reduce Learning Curve PricingCurve Pricing costs through accumulated experience.

Competitive Pricing StrategiesLeader Pricing We initiate a price change and expect th e other Umbrella Pricing, Cooperativefirms to follow. Pricing, Signaling

Parity Pricing We match the price s e t b y the overall market or Neutral Pricing, Follow erth e price leader. Pricing

Low-Price We always strive to have th e low price in t he Pa ra ll el P ri cing , Adap ti veSupplier market. Pricing, Opportunistic Pricing

Product Line Pricing StrategiesComplementaxy W e price the core product low w hen Razor-and-Blade PricingProduct Pricing complementary items such as accessories,

supplies, spare pans, services, etc. can be pricedw ith a higher premium.

Price Bundling W e offer this product as part ofa bundle of System Pricingseveral products, usually at a total price thatgivesour customers an attractive savings over

th e sum ofindividual prices.

Customer Value W e price on e version ofour product a t very Economy PricingPricing competitive levels, offering fewer features than

are available on other versio ns.

Cost-Based Pricing Strategies

Cost-Plus W e establish th e price ofthe product a t a point Contribution Pricing, Rate-ofPricing that gives us a specified percentage profit Return Pricing, Target Return

margin over our costs. Pricing, Contingency Pricing,Markup Pricing

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Table 2: Determinants ofPricing Strategies

New Product Pricing Strategies Skim Pricing

Penetration

Pricing

Experience Cur

Pricing

Unique to Strategy Product ag eType:

New (1.10) New (1.10) New (10.11)

Within-type ProductDeterminants: differentiation

High (4.8.10) Low (4,8,10) L ow (4.8.10)

Significance of

product change

Maior (6.10) Minor (6,10) Minor (6.8.10)

Costs Hi2h (4.10) Low (4) L ow (4)

Scale or experience

curve effectsDemand

Disadvanta2e (10)

Inelastic (4.8.10)

Advantaae: scale

(3.4.8.10.11)Elastic (1.3,4.6.8)

A dvant a~ i e :

experience (4.8.10.1Elastic (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 CycleType:

Mature (5) Mature (3.5) Mature (5)

Ease ofdeterminingdemand

Easy (4) Ea~ (4) Easy (4)

Within-type Market shareDeterminants:

High (4.5) Low (8) Low (2,5)

C osts L ow (4) Hi2h (2.3.4) L ow (8)

Scale or experiencecurve effects

Advantage (2,4) Disadvantaae (3 ) Advantage (4 )

Ease ofdetectingprice 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

L ow (8) L ow (8)

Brand Demand Elastic (3) Elastic (3)

3 6


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Product Line Pricing StrategiesComplementaryProduct Pricing

Customer Va

Bundling Pricing Pricing

Unique to StrategyType:

Common (within-type) Determinants:

Firm sells entireproduct line (othermodels, ancillaryproducts. supplemen-tan products)

Profitability ofaccompanying orsupplementary sales

Switching costs

Per sale/contractpricing

Market appealMarket growth rate

Ease ofdetecting

price changes

Hi!h (3.5

H ii~h (1 1

Y es (4

Narrow

Low

Difficult

Other Detenninants: Brand demand Elastic (3 ) Elastic (3.7.8. 10)

Cost-Based Pricing Strategies

Unique to Strategy Ease ofdetermining Diflicult (3 )Type: demand

Common (within- nonetype) Determinants:

Other Determinants: none

References:I. Dean (1950)2. Greer(1984)3 . Guiltinan, Paul and Madden (1997)

4. J a m (1993)

6. Mercer (1992)

7. Monroe (1990)8 . Nagle andHolden (1995)9. Oxenfeldt (1975)

1 0 . Schoell and Guiltinan (1995)1 1 , Tellis (1986)

Y es (3 Yes (3 Y es (3

Cost-Plus

Pricing

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Table 3 Determinants ofPricing Strategies

Definition of Determinant

Market Conditions

Sensitivity ofcustomers to price differences between brands

Sensitivity oftotal demand to changes in average price

Ease ofdetermining market demand

Market growth

Switching costs

Competitive Conditions

Ease ofdetecting competitive price changes

Concentration: Three firm concentration ratio

Product differentiation

Product/Company Conditions

Age ofproduct in years

Cost (dis)advantage due to experience curve

Cost (dis)advantage due to economies ofscale

Capacity utilization (relative)

Costs (relative to competitors)

Major Product Change: Significance ofmost current design

change

Market Coverage

Market Share

Per Sale/Contract Pricing

Profitability ofaccompanying sales ( e.g., other products)

Profitability ofsupplementary sales (e.g.. spare parts. service)

Scale in Survey

= insensitive, 7 = sensit ive

I = insensitive, 7 = sensit ive

=easy, 7 = difficult

I = low , 7 =high

= low, 7 high

=difficult, 7 = easy

I =K5%, 7=> 80%

I = low . 7 high

1 =notyet 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

3 8


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Table 4 Mailing List by SIC Code and Revenue

4-digit SIC Code Industry Number ofFirms

3523 Farm 1 3 8353 1 Construction 1423532 Mining 6 3

3 5 3 7 I n d u s t r i a l T r u c k s a n d T r a c t o r s 933541 Machine Tools, Cutting 573542 Machine Tools, Forming 773549 Metal Working Machines 323554 Paper Industry Machines 8 33571 Electronic Computers 2693663 Radio and TV Communication Equipment 1883711 Tractor and Tractor Trucks 18

3721 Aircraft 413743 Railroad Equipment 643812 Search and Navigation Equipment 1183823 Process Control Instruments 151

Total 1534

Company Size Number ofFirms in Number ofFirms

(Annual Revenue in millions) Mailing List / Sample Responding

$5-$14 836/427 9 3$15-$49 393/342 77

$50-$149 149/130 3 6$150-$499 75/65 2 4

$500+ 81/70 3 9

unknownTotal 1534/1034 270

39


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Table 5 Cross-Validation ofPricing Strategy Using Relative Price

Strategy

Skim Pricing

Leader Pricing

Parity Pricing

Customer Value

Pricing

Experience CurvePricing

Complementary

Product Pricing

Penetration Pricing

Low Priced

Supplier

Entire Sample

Number of

Respondents

3 7

3 1

82

2 9

3 2

24

2 5

2 4

Expected

Relative

Price

High

High

Same

Low

Low

Low

Low

Low

270

Mean of

Relative

Price

4.11

3 . 9 7

3.35

3 . 3 7

3. 6 8

3 . 2 1

2.68

2 . 0 0

Std. Dev. Of

Relative

Price

1 . 5 1

1 . 4 0

1 . 2 0

1.42

1 . 4 9

1.25

1 . 7 7

1 . 2 5

t-statistic

(p-value)*

2 . 2 2 ( 0 . 0 2 )

1 . 6 3 ( 0 . 0 6 )

1 . 5 9 ( 0 . 1 2 ) * *

- 0 . 7 2 ( 0 . 2 4 )

-0.46 (0.33)

- 1 . 3 7 ( 0 . 0 9 )

- 2 . 4 9 ( 0 . 0 1 )

-6.46 (0.00)

3 . 5 6

* p-value calculated for 1-tail t-test except for ** which is the p-value forthe 2-tailed t-test.

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Table 6 Test ofUniaue Determinants ofStrategy Types

New Product Strategies Estimate Std. Error Chi-square Prob>Chi2

ProductAge(-)

InterceptModel Chi-squareModel FitPositive Responses

Competitive Strategies

-0.31

0.3212.24

p


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Table 7 : Test ofDeterminants ofIndividual Pricing Strategies

Estimate (Prob > Chi2)

Restricted Full Tobit

TobitSkim Pricing

Unique Determinants1Product Differentiation (+)Major Product Change (+ )Cost (+)

Cost disadvantage: scale (+ )Cost disadvantage: learning (+ )Market Elasticity (-)Brand Elasticity (-)

Capacity Utilization (+ )

1 9 . 2 2 ( 0 . 0 1 )

1 . 0 7 ( 0 . 9 6 )

2 . 0 7 ( 0 . 8 2 )

4 0 . 6 5 ( 0 . 0 8 )

-65.46 (0.14)

0.85 (0.90)

-10.16 (0.15)

2 . 3 5 ( 0 . 7 0 )

-185.61 (0.00)Intercept

Model Fit p K 0.043 7Sample

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)

- 1 5 6 . 9 8 ( 0 . 0 0 )

43.49 (0.05)

8.65 (0.24)

1 2 . 7 6 ( 0 . 5 6 )

-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 FitSample

4.09 (0.84)

-125.91 (0.00)

p


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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)

1 2 . 1 2 ( 0 . 2 0 )

3 1 . 0 5 (0.13)

3 3 . 0 3 ( 0 . 1 1 )

9.52 (0.10)

-3.86 (0.50)-0.11 (0.98)

- 3 2 1 . 6 3 ( 0 . 0 0 )

Model FitSample

Parity Pricing

Unique Determinants

Cost (+)

Cost disadvantage: scale (+ )Cost disadvantage: learning (+ )

Common DeterminantsMarket Share (-)Ease: detecting price changes (+ )Market Elasticity (-)Capacity Utilization (+)

Intercept

15.55 ( 0 . 0 0 )

20.55 (0.13)16.39 (0.38)

-94.23 (0.00)

16.57 (0.00)1 0 . 2 4 ( 0 . 4 4 )

5.60 (0.76)

-9.15 ( 0 . 0 0 )

-0.18 (0.96)9.12 (0.01)6.07 (0.07)

-113.06 (0.00)

Model FitSample

Low-Price Supplier

Unique DeterminantsEase : detecting price changes (-)Market Elasticity (+)

Capacity Utilization (-)

C o m m o n DeterminantsMarket Share (-)Cost (-)

Cost advantages due to scale (+ )Cost advantage: learning (+ )Intercept

Model FitSample

1.54 (0.82)-5.93 (0.42)

-15.52 (0.04)

-82.93 (0.11)

p


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Bundling Pricing Full Tobit

Unique DeterminantsPer Sale/Contract Pricing (+ )Intercept

38.32 (0.02)

-99.25 (0.00)

Model FitSample

p < 0.0135

Complementary Product Pricing

Unique DeterminantsProfitability ofaccompanying

sales (+)Profitability ofsupplementary

sales (+)Switching Costs (+ )Intercept

- 0 . 2 3 ( 0 . 9 6 )

1 5 . 1 7 ( 0 . 0 1 )

2 . 0 1 ( 0 . 5 6 )

- 1 6 0 . 0 9 ( 0 . 0 0 )

ModelFitSample

p


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Table 8: Validated Pricing Strategy Framework

Strategy

Type

New ProductPricing

Determinants

.New model

Principal Strategies

related strategies

Skimming

Premium Pricing Value-in-Use Pricing

Penetration Pricing

Unique Determinants

High productdifferentiation in the

market Cost disadvantage

due to scale

Cost advantage dueto scale

Experience/LearningCurve Pricing

Competitive Mature marketPricing

Product LinePricing

Firmsells

substitute or

complement

ary products

Cost-Based Difficult toPricing determine

demand

* based on t-tests in Table 5

Leader Pricing

UmbrellaPricing Cooperative Pricing

SianalingParityPricing

Neutral pricing

Follower pricing

High costs

Additional

Favorable

Conditions

Elastic marketdemand

Inelastic branddemand

N ot a majorproduct change

High productdifferentiation inthe market

Low capacity

utilization Cost advantages

due to learning Easy to detectprice

changes

Low market share

Elastic marketdemand

High capacityutilization

Low costs

Cost advantagesdue to scale

No cost advantagedue to learning

Low -price Supplier Lowfactory Parallel pricing utilization

Adaptive pricing

Opportunistic pricing

Bundling Per saleI contract

System Pricing pricing

Complementary Product High profit onPricing supplementa~ sales

Razor-and-bladepricing

Customer Value Pricing Hard to detect price

Economy pricing changes

Narrow marketappeal

Cost-plus pricing Contribution Pricing Target return pricing

Markup pricing

Relative

Price

High

Low

el-liali

Equal

Low

Low

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Table 9 ImportanceWeight 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

3 1

ies[1 3 6 210 4 [31

1 2 5 3 6f1 2 2 8 1

112 0 3 3 j 0 7 f 2 4

Strategies . . .

C om plem entary Product 7 9 3 1 2 0 1 0 0 1 2 4Pricing

BundlePricing 8 9 3 2 1 .2 4 2 0 4 2 4

Customer Value Pricing 2 9 8 0 1 2 1 1 0 6 3 0

Competitive Pricing Stratef 5

Ill

3

LeaderPricing

ParityPricing

Low-PriceSuppl ier

4

4

4

1

1

1

7

7

Product Line Pricing

Cost-based Pricing Strategies

Cost-Plus Pricing 1 0 8 1 0 9 1 4 1 3 1 2 1 4 3 5 7 1 50

Importance Weight

Note: Median is indicated by underlined type.

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Figure 1: Overview ofIndustrialPricing Framework

New model ofproduct

Company sellsc o m p l e m e n t a r y o r

substitute products

P e r s a l e . / c o n t r a c t

p r i c i n g

Narrow market appeal Low market growth

Difficultto detectp r i c e c h a n g e s

Complementary

Product Pricing( low)

BundlingPricing

CustomerValue Pricing( low)

D i f f i c u l t t o

e s t i m a t e demand

C o s t - b a s e d P r i c i n g

S t r a t e g i e s

S t r a t e g y T y p eD e t e r m i n a n t s

S t r a te g y T y p e s U n i q u e P r i n c ip a lS t r a t e g y D e t e r m i n a n t sPrincipal Pricing

Strategies(relative price)

H i g h p r o d u c t

d i f f e r e n t i a t i o n

S i g n i f i c a n t d e s i g nc h a n g e

H i g h r e l a t i v e c o s t s C o s t d i s a d v a n t a g e d u e

to scale or experience Inelastic demand Low factory

u t i l i z a t i o n

Skim Pricing(high)

High relative costs

Cost disadvantage dueto scale or experience

S

0

Difficultto detect

p r i c e c h a n g e s

E l a s t i c t o t a l demand

Low c a p a c i t yutilization

H i g h p r o f i t a b i l i t y o f

a c c o m p a n y i n g o rs u p p l e m e n t a r y s a l e s

H i g h s w i t c h i n g c o s t s

Cost-PlusPricing

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Figure 2: Managerial Pricing Strategy Survey

GENERAL PRODUCF E NFORM ATION pale

lam interested in th e most recent pricing decision you were involved with in th e last 1 2 months forthe U.S. market. The

decision you describe should b e fo r a s i n g l e d u r a b l e 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 p r i n c i p a l i n d u s t r y you consider th e product to he part of (e.g., heav y truck, machine tool, etc.):

3 . Your a p p r o x i m a t e ~wi~selling price i s :

u n d e r from $ 1 , 0 0 0 f r o m $ 3 , 0 0 0 from SIO .000 from S30.000 f r o m $ 10 0 , 0 0 0 $ 30 0 , 0 0 0$ 1.000 t o $2,999 to S9.999 t o $ 2 9 , 9 9 9 t o $ 9 9 , 9 9 9 t o S2 9 9 , 9 9 9 o r o v e r

00 0 0 0 0 0

4. How often do you (or your company) set th e pricing for this product?

weekly monthly quarterly semi-annually annually each saledcontmct Otlw ____________

o 0 0 0 0 0 05. Wha t percent ofth e annua l dollar sales of your division (or company, as appropriate) does this product represent?

~ lessthan atleas: 1% atleastS% atleast2.5% 50%I Division I 1 % bu t under 5% but under 25% but under 3 0 % or over0 0 0 0 0

6. W hen th e current model w as znti~oduced, how significant w as th e design change?

totally new p ro du ct m aj or revision m inor revision no change

0 0 0 0

7. We offer other products to th i s m arket which , relative to th i s product. ar e (check al l that apply):sub s t i tu t e s c om p l e m e n t s h a v e n o r e la t io n s h i p to this p r oduc t no o ther produc t s are ava i lab leo o 0 0

8. How would yo u charecterize ~ in relation toy~ THREE l a rges t competitors?

morethan5% 2%to5% about 2%to5% mored~an5% Suchacompauisonisbelow below equal above above meaningless in m y situation

o 0 0 0 0 09 . Approximately what percentage ofth e dollar sales fo r this product categoiy in the U.S. market is made by the

THREE largest manufactiws? Ifthere ar e fewer than three manufacturers in total, mark 8 0% or more.

-lessihan atleast20%but atleast3S%hut a:leaszS0%but arie ,as t65% bsn 80%or20 % under35% under50% under65% wider80% mom0 Ii 0 0 0 0

10. H ow extensive is y o u r coverege of th e various market segments for th i s product? Mark an X at the p o i n t on th e

scale that best describes th e number ofmarket segments in which you ar e active:

al l segments i!l~i~~I only one segment

I I. H ow easy is it to determine the m ark et demand for th r ~ single product? M ark an X at the appropriate po int .

very d i f W u l i


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STRATEGY USED IN YOUR PRICING DECISION page 2

Consider which ofthe follow ing best describes th e pricing strategy that you used fo r the product you just described on the

previous page. Remember that this is fo r th e decision made in th e past 12 months fo r a single product.

IEAIE~X

A. Price Skimming

B. PenetrationPricing

C. Experience CurvePricing

D. ComplementaryProduct Pricing

E . Price Bundling

F. Customer ValuePricing

G. Price Leader

H. Parity Pricing

I. Low PriceSupplier

J. Cost-pluspricing

DE S CRIPTION

We se t th e initial price high an d then systematically reduce it o v e r t i m e . C u s t o m e r s e x p e c tprices to eventually fall.Related Strategies: Premium Pricing, Value-in-Use Pr ic ing

W e initially se t the price low to accelerate product adoption.

W e se t the price low to build volume and reducecosts through accumulated experience.Related Strategies: Learning Curve Pricing

We price th e core product low when complementary i tems such as accessories, supplies,spare parts, services, etc. can be priced with a higher margin.Related Strategies: R azor -and-B lade Pricing

We offer this product as part ofa bundle ofseveral products , usually at a to ta l price th a tgives our customers an attractive savings over th e stun of th e individual prices.Related Strategies: System Pr ic ing

We price one version ofou r product at very competitive levels, offering fewer features thanare available on other versions.Related Strategies: Economy Pricing

We initiate a price change an d expect th e other f irms to follow.Related Strategies: Umbrella Pricing, Co operative Pricing, Signaling

We match th e price set by th e overall market or by th e 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 P ricing

We establish th e price ofthe produ ct at a point that gives us a specified percentage profitmargin over our costs.Related Strategies: Con tribution Pricing, Rate-of-Return Pricing, Target-ReturnPricing, Contingency Pricing, Markup Pricing

Questions:

I. Ifyo u used a pricing strategy not listed above p l ea s e ~ ~

2. Which pricing strategy ~ describes what yo u used for pricing this

product? Enter the appropriate letter from above: s t ra t egy :

3. Ifyou used more than one strategy in your decision, enter th e letter ofeach strategy an d its relative importance in

your decision b dividing l00~ among the various strategies used:

strategy: [J : _________ strategy: III: ..........................%; s t ra t egy :~IJ: _________


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SITUATION WHEN Y O U MADE THE PRICING DE CIS ION page 3

I. Circle th e number on th e scale w hich best describes th e situation atth e t u n e th e p r ic ingdecision ~ made.

1.1 YOUR MARKET

a. Market growth rate:

b. Sensitivity ofmarket demand to changes in th e average

m a r k e t p r i c e :

c. Sensitivity ofcusto

Emperically Vaildated Framework for Industrial Pricing

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