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copyCustomer segments as moving targets: Integrating customervalue dynamism into segment instability logic

Christopher P. Blockera,, Daniel J. Flintb,1

a Baylor University, Department of Marketing, One Bear Place #98007, Waco, TX 76798, USAb 304 Stokely Management Center, Department of Marketing and Logistics, College of Business Administration,

The University of Tennessee, Knoxville, TN 37996, USA

Received 13 May 2005; received in revised form 5 April 2006; accepted 1 May 2006

Available online 4 August 2006

Abstract

Segmentation is a mature concept in marketing strategy that continues to receive significant attention from managers and scholars alike. The

key goal in segmentation is identifying and reaching profitable segments with products and services that meet the common needs of these

customers. However, a fundamental issue needing rigorous attention is that customers' needs are dynamic and can induce segment instability. The

purpose of this paper is to draw focus to segment instability in business-to-business markets by conceptually exploring its theoretical

underpinnings and integrating related theory on customer value change to propose an agenda for future research.

2006 Elsevier Inc. All rights reserved.

Keywords: Customer value change; Segment instability; Industrial segmentation; Changing needs

1. Introduction

Segmentation has been called one of the most important

concepts in marketing (Dickson, 1982), based largely on its

capacity to serve as both a strategic lens for managers and a

tool to break down markets into customers grouped by

common needs (Freytag & Clarke, 2001). Skillful segmenta-

tion equips firms to target profitable customers, understand

customers' desires, allocate resources, and position against

competitors (Beane & Ennis, 1987; Berrigan & Finkbeiner,

1992; Tapp & Clowes, 2002). Yet, despite decades of research,scholars suggest that the discipline of segmentation has a long

way to go theoretically and methodologically (Bolton & Myers,

2003; Steenkamp & Hofstede, 2002; Wedel & Kamakura,

2002a). This is especially the case in business-to-business

markets and global contexts (Steenkamp, 2005; Sudharshan &

Winter, 1998).

The key challenges facing segmentation solutions are sum-

med up by established criteria, which require segments to be:

(1) measurable, (2) substantial, (3) accessible, (4) actionable, (5)

responsive, and (6) stable (Kotler, 1994; Wedel & Kamakura,

2002b). Researchers have also discussed barriers to implemen-

tation (Bottomley & Nairn, 2004; Dibb & Simkin, 2001), but

problems in segmentation frequently correspond to one or more

of these six requirements.

Dealing with the sixth requirement is a difficult challenge

that scholars refer to as segment instability (Farley, Winer, &

Lehmann, 1987; Hoek, Gendall, & Esslemont, 1993; Hu & Rau,

1995; Steenkamp & Hofstede, 2002; Wedel & Kamakura,

2002b). Specifically, researchers indicate that markets are be-coming increasingly dynamic (Barnett & McKendrick, 2004;

Douglas, 2001; Eisenhardt & Martin, 2000; Voelpel, Leibold,

Tekie, & Von Krogh, 2005) and customers' changing needs

and rapidly evolving preferences represent key drivers of this

market turbulence (Achrol & Etzel, 2003; Achrol & Kotler,

1999; D'Aveni, 1995; Joshi & Campbell, 2003). One important

consequence of rapid changes in customers' needs is that they

can render a firm's target segments unstable. Although both

consumers and business customers' needs are dynamic, scholars

suggest that segment instability is more pronounced in business

markets, which can be more sensitive to ongoing changes in

macro-economic conditions (Dickson, 1994; Mitchell &

Wilson, 1998).

Industrial Marketing Management 36 (2007) 810 822

Corresponding author. Tel.: +1 865 748 0791; fax: +1 865 974 1932.

E-mail addresses: [email protected] (C.P. Blocker), [email protected]

(D.J. Flint).1 Tel.: +1 865 974 8314.

0019-8501/$ - see front matter 2006 Elsevier Inc. All rights reserved.

doi:10.1016/j.indmarman.2006.05.016


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As business markets evolve, customers' changing needs can

induce segment instability in two important ways. First, what is

valued by individual business customers in a segment (i.e., de-

sired value) may change, reflecting what has been termed custo-

mer desired value change (CDVC) (Flint, Woodruff, & Gardial,1997, 2002). For example, a business customer that decides to

expand its operations internationally may begin valuing new

types of supplier benefits, such as having a global account team,

and no longer be adequately served by a supplier's offers targeted

for a domestic segment. When CDVC is widespread, the needs of

a segment's customers (over time) can diverge from the segment's

originally defined properties and weaken customers' responsive-

ness to offers (Wedel & Kamakura, 2002b). Second, when cus-

tomers undergo changes in what they value from suppliers, they

may move into or fall out of a firm's target segment, resulting in

size dynamics, i.e., the quantity of customers and revenue in a

segment increasing or decreasing.The intensity of CDVC can be low for some customers that

experience relatively few changes in what they value from

suppliers and, thus, remain in a segment for a long time.

Industrial customers purchasing commodity products for use in

mature manufacturing processes (e.g., chemicals company

purchasing raw materials) might reflect fewer changes in their

needs and desired value. CDVC can be high, for example, in

situations where customers are outsourcing business functions

(e.g., IT infrastructure) and customers' understanding of their

needs and the available solutions are continually changing. The

software sector is one illustration of a product-market where

business customer needs are changing rapidly, given that a

number of firms are closely considering how developments in

open-source code (e.g., Linux) and software-as-a-service (e.g.,

salesforce.com business model) might fit their evolving

business needs (Hamm, 2006).

The more extensive segment instability (SI) is, the more costly

it is for suppliers (Mitchell & Wilson, 1998; Plank, 1985). One

significant cost can be lost customers. Simply retaining an addi-

tional 5% of customers can translate into millions of dollars for

many firms (Reichheld, 1996). Yet, sometimes customers leave

because their needs have changed and they no longer derive

sufficient value from existing offers (Beverland, Farrelly, &

Woodhatch, 2004). Thus, it is critical that marketing managers

understand more about segment instability. In order to assistmanagers in this regard, theoretical exploration of SI must also

move forward quickly (Mitchell & Wilson, 1998; Steenkamp,

2005; Wedel & Kamakura, 2002a). Yet, recent reviews suggest it

is not moving quickly enough (Steenkamp & Hofstede, 2002).

Some advocate that more theory development exploring the

dynamic nature of customer value perceptions is an important

next step (Brangule-Vlagsma, Pieters, & Wedel, 2002; Flint et al.,

2002).

Thus, the purpose of this paper is to explore the theoretical

roots of SI and integrate related concepts addressing changes in

customers' desired value and needs to propose an agenda for

future research. Our initial question is what are the likely charac-

teristics of segment instability, including the way it occurs, as well

as its drivers and outcomes? Several steps are taken to address this

question. First, we examine relevant segmentation research and

offer a conceptual definition of SI. Second, we present a review of

previous studies dealing with SI and integrate key perspectives on

customer change. Last, we put forth a theoretical framework of SI

and an agenda for research.

2. Segmentation theory

Theory development in industrial segmentation has received

far less attention thanconsumersegmentation and,in recent years,

has proceeded slowly (Goller, Hogg, & Kalafatis, 2002). One

explanation for this slow growth might relate to questions about

the relevance of business segmentation (e.g., Dibb, 2001) in light

of increasing interest in marketing to individual customers, using

customer lifetime value models (CLV) and database marketing

strategies (Kumar & Petersen, 2005). However, recent empirical

research shows that these strategies lead potentially, but not

necessarily, to greater profitability. Furthermore, the difficulties in predicting CLV can weaken results (Malthouse & Blattberg,

2005). Other scholars suggest that the use of database marketing

does not preclude the significant scale advantages that can be

obtained through segmentation, but rather that the two strategies

should be used in tandem (Steenkamp & Hofstede, 2002). Thus,

calls for more theory development in segmentation seem justified

(Wedel & Kamakura, 2002a).

Recent reviews focus on organizational barriers to segmenta-

tion, methodological approaches, and poor results in segmenta-

tion practice as weak areas within industrial segmentation (Dibb

& Simkin, 2001; Goller et al., 2002; Wedel & Kamakura, 2002b).

What research shows is that many firms are more concerned with

identifying customergroups that coincide with existing marketing

programs than employing systematic processes to uncover seg-

ments that draw meaningful distinctions between customers (Dibb

& Simkin, 2001). Methodologically, two weak spots include the

need for empirical testing of the predictive validity of segment

solutions and more frequent model comparisons to identify con-

ditions where certain models provide the best representation of

business markets (Wedel & Kamakura, 2002b).

Conceptual discussion is particularly lacking in regard to

segment instability, where comments are often limited to noting

the inconsistency of segment solutions over time. Thus, the

following section highlights relevant foundations to ground SI

in existing segmentation theory.

2.1. Heterogeneity of needs in the market

Segmentation theory stipulates that customers' needs, prefer-

ences, or desired value dimensions are heterogeneous, (i.e., they

vary greatly) and this diversity can be captured using variables

that discriminate among these different needs (Beik & Buzby,

1973; Day, Shocker, & Srivastava, 1979; Freytag& Clarke, 2001;

Green & Krieger, 1991; Smith, 1956). Firms capitalize on need

heterogeneity by identifying meaningful clusters of customers

that have relatively homogeneous sets of needs. Despite con-

siderable extensions, exploration of variables, and an abundance

of research on the topic, the essence of segmentation theory for

nearly 50 years has been this notion of customer need hetero-

geneity (Smith, 1956; Wedel & Kamakura, 2002a).

811C.P. Blocker, D.J. Flint / Industrial Marketing Management 36 (2007) 810822


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It is well known that different business customers have

different needs and the same customer will need different things

from different suppliers. Where one customer might emphasize

low price and quick delivery, others might stress quality, reli-

ability, or service support. We can categorize what customersvalue from suppliers along at least eight dimensions, i.e., pro-

duct quality, service support, personal interaction, time-to-

market, delivery, direct costs, acquisition costs, and operating

costs (Ulaga & Eggert, 2006). These differences are driven not

only by the fact that products and services are used in numerous

ways across customer industries, but also application can vary

considerably across customers within a single industry (Powers,

1991).

2.2. Philosophical perspectives

Segmentation is often differentiated between scholars whodiscuss it as a strategic activity, related to the pursuit of compe-

titive advantage (Bonoma & Shapiro, 1983; Freytag & Clarke,

2001, Kotler, 1994; Smith, 1956) and scholars who focus more on

developing it as a technique that employs sophisticated mathe-

matical modeling (Brusco, Cradit, & Tashchian, 2003). A strong

focus on the latter perspective and model refinement in industrial

segmentation seems to convey a certain atheoretical perspective

for the field (Goller et al., 2002). A frequent debate in segmen-

tation is whether segments really exist. For example, segmenta-

tion can use almost any variable (e.g., NAICS codes) to divide

customers into groups without addressing whether groups are

distinguished by truly different needs. As such, scholars indicate

that (at best) segments represent managers' estimation of markets

and not the full reality of customer heterogeneity, as it exists

naturally in the marketplace (Wedel & Kamakura, 2002a).

Overall, at least two themes emerge from segmentation theory.

First, segmentation theory seeks to identify, explain, and capi-

talize on customer needheterogeneity in the marketplace. Second,

although there have been significant advances in mathematical

modeling and data analysis techniques, there seems to be a

shortage of theory development in industrial segmentation in

general (Dibb & Wensley, 2002; Dowling, Lilien, & Soni, 1993;

Goller et al., 2002) and conceptual understanding of segment

instability, in particular (Wedel & Kamakura, 2002a). Yet, before

exploring ideas that might begin to address this gap, we must firstdefine segment instability.

3. Conceptual definition of segment instability

In its current form, segmentation logic offers static snapshots

of a moving marketplace. Whereas, segmentation research has

explored the types of need heterogeneity from multiple angles

(e.g., variables to serve as a basis for segmenting customer

needs), there has been a dearth of work attempting to understand

the dynamics of need heterogeneity, that is, the nature and

manner in which a segments' needs change over time. This is

particularly the case in industrial segmentation where there are

few known studies that conceptually or empirically address SI,

despite stability being a core requirement for business segments

(Mitchell & Wilson, 1998; Dickson, 1994).

Given that a conceptual definition of SI has yet to be offered,

the following serves as an initial effort to define SI: Segment

Instability refers to a state of change in customers' needs and

what they value within identified market segments, as well as

changes in segment membership, as triggered by internal to thecustomer and external to the customer change drivers, and

reflected by changes in segment contents and segment structure.

One challenge for defining SI this way is that researchers

continue to search for the best variables to measure what

customers currently need and value from suppliers. Still, recent

research outlines both the importance and the process for

conducting need-based industrial segmentation (Albert, 2003).

Also, advances such as measuring multiple need-related

concepts (e.g., attributes, benefits, and values) make progress

toward capturing a holistic view (Hofstede et al., 1999).

Additionally, it is important to note that SI might also be

construed as being caused by shifts in managers' strategies toapproach business markets in new ways and introduce innova-

tions to influence changes in what customers value. Scholars have

discussed the factors that influence dynamic market behavior and

contend that both sellers' strategies/innovations and customers'

changing needs have reciprocal effects on each other (Boulding,

Staelin, Ehret, & Johnston, 2005; Dickson, 1992; Ratneshwar,

Shocker, Cotte, & Srivastava, 1999). We concur with this logic

and recognize the influence of suppliers in examples throughout

this discussion. Yet, we focus on the latter perspective of dynamic

customer value and needs given their association with customer

need heterogeneity and segmentation theory.

To advance conceptual understanding, several representa-

tions of SI are presented in Fig. 1.

3.1. Segment content change

Fig. 1 proposes two classes of segment change, i.e., content

changes and structural changes. Segment content change offers

an explanation for how customers' changing needs can induce

SI. Content changes can be construed in two ways. Latent

content change suggests that, within a market, segment types

and their properties, e.g., low-cost segment, premium segment,

etc., remain relatively stable while customers move in and out of

those segments in a varied manner. When an electronic com-

ponents manufacturer changes its down-stream strategy fromtargeting automotive manufacturers to targeting aerospace man-

ufacturers, they may change processes, people, and locations

that result in major shifts in what they value from an up-stream

supplier. Depending on how this supplier segments their mar-

kets, the electronics component customer might drop out of a

current segment (e.g., segment A) and enter another existing

segment (e.g., segment B). Although customers similar to this

one might leave segment A, latent content change suggests that

this segment will be viable over time, if its customer inflow is

equal or greater to the outflow.

Conversely, manifest content change proposes that groups of

customers can move together through similar shifts in their

desired value and needs to arrive at sets of needs that compose

new segments. Manifest content change might be best reflected

by segment changes that occur during the initial phases of new

812 C.P. Blocker, D.J. Flint / Industrial Marketing Management 36 (2007) 810822


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product cycles, where the market as a whole and segments

within it are making sense out of new products, their features,

their uses, and formulating preferences. For example, during

initial years of the product's existence, laptop computers were

categorized and targeted to business markets (among other

criteria) by their size and weight. Over time, as customers

became more sophisticated and laptop design matured, the

importance of size/weight to customers diminished and gave

way to other features (Ulrich & Ellison, 1999). Thus, segments

whose properties included needs for specific size/weight ranges

likely experienced broad shifts. A more recent example is seen

in high-end server markets, where the needs of some customers preferring proprietary-server architectures have begun shifting

toward open-standard server architectures that require more

training, but offer more flexibility and scalability (Corcoran,

2003).

An extreme illustration of manifest content change would be

the dramatic shift that occurred in the commercial catering

industry's airline segment in the wake of 9/11 terrorist attacks in

the U.S. Due to fluctuations in the demand for air travel and the

pressure of offering low fares while simultaneously upgrading

security, a majority of airline firms demoted in-flight meals to a

lower priority and reduced spending with catering suppliers by

eliminating 90% of in-flight meals in favor of buy-on-board

programs (Deutsche Lufthansa AG, 2005). Whereas rapid

changes like this occur less frequently, corporate history is replete

with examples of firms that were impacted by shifts in market

segments triggered by environmental changes (e.g., see Day &

Schoemaker, 2004).

Together, the notions of latent and manifest change, as de-

lineated here, represent the most in-depth theoretical articulation

of SI thus far and have served as key assumptions in modeling

techniques (Wedel & Kamakura, 2002b). Despite being described

separately, latent and manifest change are not mutually exclusive.

Some customers in a given market might undergo similar shifts in

needs (manifest content change) such as in growth segments,

while other customers remain within or shift between relatively

stable segments (latent content change) over time.

3.2. Segment structural change

Segment structural changes represent the spatial outcomes of

segment content changes and provide an analytical assessment

of the change that has occurred from a firm's perspective.

Changes in segment size, dispersion of customers' needs within

a segment, and boundary clarity are suggested as key descrip-

tors of structural change. Segments grow (shrink) when the

needs of customers shift toward (away from) the defined pro-

perties of a segment and, thus, its target offers. One illustration

of an industry sector likely experiencing significant structural

changes is business telecommunications. Although a majority

of business customers reside within segments whose needs are

met with traditional digital phone lines to office desks, a large

number of customers' needs are shifting toward emerging

Fig. 1. Representations of segment instability.



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segments that target business offices with voice-over-the-

Internet (VoIP) phone lines to each desk (e.g., 11.5 million

new VoIP lines delivered in 2005, representing a 46% increase

over 2004, see Crockett, 2006). These growth segments cater to

business firms that desire to leverage their investments incomputing infrastructure and integrate employees' phones and

personal computers, even if the start-up costs are much higher.

Segment dispersion refers to how tightly or loosely that

customers within a segment share a set of core needs. Boundary

clarity describes the degree to which customers' needs overlap

more than one segment. In both cases, these structural charac-

teristics are originally determined by how tightly (dispersion) and

distinctly (boundary clarity) a firm's defined segmentsinclud-

ing mean scores for variablescorrespond to the market's needs.

The point is that changes in segment dispersion and boundary

clarity can occur when customers are changing what they value

from suppliers. For example, mature industries, e.g., steel, petro-leum, commercial construction, etc., might contain segments

where customers' needs havebeencontinually converging around

a few core requirements (less dispersion, higher clarity in segment

boundaries). Conversely, segment dispersion might be increasing

and boundaryclarity more ambiguous in sectors likemanagement

consulting.Over time, the fragmentation of customerneeds, growth

of outsourcing, and evolution of consulting has spawned dozens of

sub-markets and segments, such that customers can now obtain

expertise from firms who specialize in strategic planning, change

management, information technology, forecasting, supply-chain

integration, accounting, satisfaction measurement, etc.

4. SI in segmentation literature

Despite no known studies that empirically test SI in business-

to-business segmentation either through longitudinal or cross-

sectional methods, there has been some development on the

topic in consumer segmentation literature. This research in-

cludes (1) model extensions, (2) selecting stable, undynamic

variables, (3) longitudinal studies (see Table 1), and (4) sug-

gestions for continuous segmentation to mitigate the impact of

SI.

4.1. Model extensions in segmentation literature

First, several have attempted to integrate dynamic components

of segments into mathematical models. Kamakura, Kim, and Lee

(1996) extended a brand choice mixture model to accommodate

changes in segment sizes and structural composition over time.

Within the context of new product introductions, Ramaswamy

(1997) developed a latent Markov model to examine the temporal

shifts of preference segments. This model, based on synthetic

data, allows for the creation of new segments during a new

product introduction phase, similar to what might be classified as

manifest segment change. Wedel and Kamakura (2002b) dedicate

a chapter in their book on segmentation to discussing latent and

manifest models that account for changes in segment sizes. Gen-

erally, these solutions relax assumptions from previous models

and extend them to include dynamic elements (Bockenholt &

Dillon,1997, 2000). Forexample,Bernoulli processes andMarkov

models use brand switching matrices and assume transition pro-

babilities exist between segments, i.e., probability that a customer

will switchfrom onesegment to another. A keydistinctionbetween

this research andrecent calls forSI theorydevelopment seems to be

that these models allow for changes in segment solutions, but havenot sought to explain or predict them.

4.2. Selecting undynamic variables

Second, some studies attempt to mitigate SI by selecting less

dynamic variables like geography, demographics, or personal

values (Brangule-Vlagsma et al., 2002). Unfortunately, studies

show that these general variables perform poorly when it comes to

linking them with actual customer needs and responses

(Steenkamp & Hofstede, 2002). For example, even though a

customer's geographic location is less dynamic, this does not

diminish the reality that customers within those geographies haveneeds that frequently change. If sets of homogeneous needs lie at

the core of segmentsand these needs are dynamic in nature

attempts to suppress this reality by choosing change-resistant

variables would seem to give a false impression of success.

4.3. Longitudinal studies

Third, some consumer segmentation studies have measured

segment membership longitudinally as a way to explore the

instability. These studiesalthough limited in explaining the

antecedents, complexities, and outcomes of SIare arguably

where the most insight of the phenomenon has been generated.

Calantone and Sawyer (1978) were the first to examine

instability of the benefits customers seek for banking services.

This study found that over a 2-year period, although the overall

classes of benefits (e.g., one-stop bankers wanting convenient

hours) and segment sizes were relatively consistent, segment

membership at a consumer level changed substantially. In one

segment, only 28% of the members were the same between

periods. Yuspeh and Fein (1982) found similar results in a 12-

month study of an undisclosed consumer product, except that

the level of instability was even greater. Less than half the

sample (40%) remained within the same segments, and some

key segments experienced even greater turnover.

Farley et al. (1987) found significant SI and reported evidenceof change patterns between shifting consumers and non-shifting

consumers. They speculated that changing use situations, va-

riety-seeking, promotional activity, and household lifecycle

changes were potential causes of observed change patterns.

Change patterns were also reported by Hu and Rau (1995).

Finally, Brangule-Vlagsma et al. (2002) recently showed

evidence of consumers shifting between segments defined by

personal values (Rokeach Value Survey). An interesting finding

here is that segments did not change in the same ways over time,

in terms of rate or composition of change. Yet, uncovering the

underlying mechanisms and reasons for change patterns was a

limitation of the study (Brangule-Vlagsma et al., 2002, p. 282).

Beyond comparing consumers to business buyers, one

challenge for extrapolating these findings to theory develop-

ment for industrial SI is thatwith the exception of Calantone



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and Sawyer (1978) and Yuspeh and Fein (1982) who measured

desired attributes and benefitssome variables in these studies

do not correspond closely to needs. For example, personal

values measured by Brangule-Vlagsma et al. (2002) are linked

to buying needs through a means-end hierarchy (Gutman,

1982), but research shows them to be distal indicators, i.e.,

change in an individual's personal values (e.g., friendship)

would not necessarily equate to change in actual buying needs.

Furthermore, the needs of business customers such as reliable

delivery or having a good supplier working relationship might

show different sensitivities to segment instability.

That said, these five studies helps us begin to understand

industrial SI in at least three ways. Specifically, they (1) validate

the existence of the SI phenomenon in downstream consumer

markets, (2) suggest that, in some cases, classes of needs arerelatively stable while segment membership changes significantly

(e.g., latent content change) and (3) suggest that need change

patterns can exist, such that segment members go through need

changes and contribute to SI in different ways. These points can

serve as a springboard for understanding SI in an industrial

context. However, as is common with most research, more

questions arise and some existing questions remained unan-

swered. For instance, Calantone and Sawyer's concluding ques-

tion of why or how customers' attribute and benefit importances

change over time has yet to be tested or explored further (1978,

p. 403). Additionally, whereas all of these studies support the

notion of latent content change, none involved contexts such as

new product introductions or products fading from the com-

mercial landscape, which might lean toward a manifest content

change model.

4.4. Continuous segmentation

Finally, several authors suggest, in light of the dilemmas

posed by SI, managers should simply commit to constantly re-

analyzing segment solutions (Freytag & Clarke, 2001; Goller

et al., 2002; Hlavacek & Reddy, 1986). While this approach

seems inevitable to a degree, it is inherently reactive, in that no

attempt is made to predict shifts in needs, segment sizes, or

segment membership. This practice falls short of current

strategic thinking urging firms to practice foresight about

changing market needs (Prahalad & Ramaswamy, 2004).

Additionally, the hefty costs of segmentation research might

challenge the practicality of this approach (Dibb & Wensley,

2002).

5. Perspectives on customers' changing needs

Several streams of literature in marketing discuss change in

customer markets and may offer insights for further under-

standing segment instability. While SI is concerned with change

at a segment unit of analysis, it originates with the changing

desired value and needs of individual customers. Therefore,

conceptual understanding can incorporate insights ranging from

an individual customer level to a market level. Also, where

knowledge concerning the changing needs of industrial custo-

mers is lacking, consumer-based perspectives should be given

consideration.

With this in mind, several perspectives on need change are

briefly summarized in Table 2: (1) market-level perspectives,

including environmental turbulence and market definition; (2)

Table 1

Studies addressing segment instability

Study Context Approach Segment base Key findings on SI Reasons

given for

change(SI)?

Brangule-

Vlagsma et al.

(2002)

Netherlands Consumer

Survey, (no product)

Modeling and longitudinal

survey instrument

administered in three waves

over 36 months

Personal values

(Rokeach Value

Survey)

Found segment types stable, but substantial size

changes and systematic membership switching over a

36-month period. Certain segments showed high

proneness for switching. Rate and composition of

change varied across segments.

No

Ramaswamy

(1997)

Synthetic data set

studying new product

introduction

Modeled brand preference

segments before and after new

product introductions

Brand preference Illustrate a modeling approach that could

accommodate and detect segment evolution in a new

product scenario (manifest change)

N/A

Hu and Rau

(1995)

U.S. households,

consumer long-

distance service

Analyzed segment

membership changes within

a single brand over 12 months

Product usage-

volume

Found segment types and sizes relatively stable over

12 months but membership changed significantly;

evidence of shifting patterns.

No

Farley et al.

(1987)

U.S. households, low-

cost grocery items

Use of survey and a split-cable

TV panel, whereby study could

incorporate increasedadvertising to experimental

group over 24 months

Response to

marketing media

Four household segments revealed high degree of

instability with over 50% of households changing in a

2-year period; Follow-up study suggests that heavyadvertising can curb some segment switching

No

Yuspeh and Fein

(1982)

U.S. households

(undisclosed product)

Longitudinal survey

administered to 1200

households over a 12-month

period

Product benefits Despite a stable product market environment only 30

40% of original segment members were re-classified in

the same segment over a 12-month period

No

Calantone and

Sawyer

(1978)

U.S. households, retail

banking market

Longitudinal survey

administered at two time

periods, 2 years apart

Desired attributes

and benefits

Found segment types and sizes relatively stable over

24-month period, but membership changed

significantly

No



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customer-level perspectives, including brand switching, loyalty,

and organizational learning; and (3) individual decision-maker

perspectives, including changes in attitudes and satisfaction.

Concepts like environmental turbulence, organizational learn-

ing, and customer satisfaction point to drivers of change, whileothers such as customer loyalty identify potential moderators.

Market definition and the role of persuasive communication in

attitude changes suggest that need changes extend beyond

customer borders to include suppliers' actions and other mar-

ket actors such as the media. Together, these perspectives

stimulate some interesting questions about segment instability

(Table 2).

Yet, we do not believe any of these perspectives addresses the

notion of business customers' changing needs in a comprehensive

manner. While they highlight the importance of understanding

change in markets and point to its drivers and outcomes, they do

not directly explore the complexity of the change phenomenon

itself, which is a critical step in the conceptual development of SI.

Hence, the next section turns to customervalue change theory as a

promising area to build upon.

6. Customer value change and segment instability

Whereas insights from the literature areas mentioned above

provide some knowledge about changing needs and change-

related behavior, recent advances in customer value and valuechange theory appear to capture the role of customers' changing

needs in a holistic way. Customer value change theory explores

the way change occurs for customers, ranging from its drivers, to

the complex nature of the change phenomenon, and its potential

outcomes. It also has a research agenda that lies close to the pulse

of the phenomenon. Specifically, it starts with an assumption that,

before being able to predict or respond to change, we must

understand the change process itself (Flint et al., 1997). This paper

proposes that a similar theoretical agenda is needed to make

progress in understanding segment instability.

Additionally, customer value and value change theory can be

seen as a nexus for the convergence of several core need-related

concepts, such as customers' desired: attributes, benefits/conse-

quences, preferences, goals in use-situations, and overall needs

sought from sellers. This is due, in large part, to its ties with

Table 2

Review of literature related to customer need change and segment instability

Level of analysis Potential linkage to need change Key question(s) to ask Illustrative authors

Market level

Environmentalturbulence

Characterizes external drivers of need change and purportedly measures the overall rate of industry

change

What is the relative influence of environmentalturbulence on customer need change and overall SI?

(Bourgeois and Eisenhardt, 1988;Dess and Beard, 1984; Glazer and

Weiss, 1993) How do specific drivers impact SI (i.e., regulatory

vs. industry events)?

Market

definition

References the dynamic nature of customer needs as

a key aspect and proposes that the dynamic process

of market definition is built upon an ongoing

dialogue between customers and suppliers. Also

suggests the degree of r igidity within the

sociocognitive framework of the market might

impact patterns of need change.

At a market level, in what ways do the ongoing

dialogue between customers and suppliers as

reflected by shared knowledge (e.g., market

stories, media) influence need change and overall

SI?

(Anderson, Salisbury, Mick, &

Lehmann, 2003; Ratneshwar et al.,

1999; Rosa, Porac, Runser-Spanjol,

& Saxon, 1999)

How might levels of market maturity, norms, and

overall degree of rigidity impact patterns of need

change and overall SI?

Customer firm level

Brand

switching

Represents a key platform for and potential outcome

of customer need change.

What is the relationship between need change and

brand switching in various contexts? For example,do high levels of brand switching reflect high

degrees of SI and under what conditions?

(Brusco et al., 2003; Kamakura and

Russell, 1989; Sun, Neslin, &Srinivasan, 2003)

Loyalty In certain cases, might serve as an inhibitor for need

change or explain specific change patterns

What is the role of customer loyalty to need

change and overall SI?

(Chaudhuri and Holbrook, 2001;

Sirdeshmukh, Singh, & Sabol,

2002; Too, Souchon, & Thirkell,

2001)

Might certain contexts or product markets

conducive to higher levels of loyalty inhibit SI?

Organizational

Learning

Characterizes internal drivers of need change and a

process by which it can occur in customer

organizations.

How might aspects of organizational learning

reflect the internal drivers or process of need

change?

(Bell, Whitwell, & Lukas, 2002;

Hurley and Hult, 1998; Sinkula &

Baker, 1997; Slater and Narver,

1995) How can suppliers capitalize on various learning

techniques to identify and predict need changes in

customers and segments overall?

Decision maker level

Attitude Suggests suppliers can play a role in need changes

through use of persuasive communication

What is the role that various tools of persuasive

communication (e.g., advertising, sales, etc.) can

play in actively shaping need change and SI in

critical segments?

(Farley et al., 1987; Lutz, 1991;

Meyers-Levy and Malaviya, 1999)

Satisfaction Serves an internal driver of need change through

feedback loops into customer expectations and new

desires from suppliers

How might aggregate measures of satisfaction

serve as clues to SI in various contexts?

(Anderson et al., 2003; Oliver, 1997;

Woodruff, Cadotte, & Jenkins, 1983;

Woodruff and Gardial, 1996)



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means-end chain (MEC) theory, which links customer needs at

several levels (Gutman, 1982; Holbrook, 1994; Woodruff, 1997;

Zeithaml, 1988). A recent review defines customer value as a

customer's perceived preference for and evaluation of those pro-

duct attributes, attribute performances, and consequences arisingfrom use that facilitate (block) achieving the customer's goals and

purposes in use situations (Woodruff, 1997, p. 142). One draw-

back, however, is that customer value change research is in its

infancy and, despite rigorous work, has been explored in limited

contexts (Beverland et al., 2004; Beverland & Lockshin, 2003;

Blocker & Flint, in press; Flint et al., 2002).

As a way of integrating customer value change theory into an

aggregate level theory of SI, a brief review of customer value and

customer value change theory is outlined. Then, a discussion of

SI, which builds on customer value change theory, is presented

along with a conceptual framework.

6.1. Customer value theory

The study of customer value has grown in importance. For

example, the American Marketing Association recently revised

its definition of marketing around the notion of value for

customers and important debates about dominant logic in the field

suggest that customer value plays a central role (American

Marketing Association, 2006; Vargo & Lusch, 2004). Despite

being discussed in various ways, a consensus seems to be

emerging in key areas of customer value (Flintet al., 2002; Peteraf

& Bergen,2003; Prahalad & Ramaswamy, 2004; Slater & Narver,

2000). For one, customer value is seen as the customer's

perceived trade-off between benefits (what you get) versus

sacrifices (what you give) within use situations (Lapierre, 2000;

Slater & Narver, 2000;Ulaga & Eggert, 2006). These tradeoffs are

subjective and relative to competitive offers (Gale, 1994).

Researchers also agree that customers' value perceptions are

dynamic (Woodruff, 1997). Attention to this reality has led to

initial work exploring customer desired value change.

6.2. Customer-desired value change theory

Customer-desired value change in a business context is

generally defined as any alteration in what a customer desires

from a supplier. Based on a grounded theory study, Flint et al.

(2002) proposed an initial model of customer desired value

change (CDVC) that arose out of business customers' perceptions

of their changing needs and desires from suppliers. The CDVC

model posits that changes in desired value can take numerous

forms, such as (1) changes in the desired attributes, consequences,

and/or end goals in a customer's value hierarchy; (2) the emer-

gence of completely new desires; (3) a rise in the standard ofexisting desires; and (4) changes in relative priorities for existing

desires. Desired value changes can also vary in intensity. Spe-

cifically, the rate, magnitude and number of changes taking place

within customer organizations will vary from customer to custo-

mer and one time to the next.

In addition to the change itself, CDVC can be driven by

external to the customer organization (e.g., economic events or

shifts) and internal to the customer organization (e.g., strategic

changes) environmental turbulence. It also can result in actions

customers taketo alter their relationships with suppliers. Finally, it

has been suggested that firms could use customer desired value

change as a factor in segmenting customers (Flint et al., 2002). In

this way, types and/or degree of change might be factored into the

way customers are grouped. Certain groups might exhibit intense

change, while others go through change more slowly. Along with

Fig. 2. Conceptual framework of B2B Segment Instability (SI).



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longitudinal research, this might be one wayto capture levels of SI

in a single study.

7. B2B segment instability framework

In light of this discussion, we present a theoretical framework

for SI in business-to-business markets (Fig. 2). The framework

incorporates several levels of change for segments ranging from

the individual business customer, to the segment, and overall

market. This is the first known attempt to pull together theoretical

concepts involved with SI and is purposefully broad in scope.

7.1. Nature of SI

7.1.1. Segment member change

At the core of the model is a progression of change beginning

with individual customer's need change within a segment.Changeshere are proposed to follow a process like the one outlined in

customer desired value change theory. The basic extension is that,

as customers change what they value, so does their degree of

belongingness to the segment. Degree of belongingness is mea-

sured by comparing a customer's set of needs to the segment's

average scores across its core properties or variables. Individual

customer change feed into aggregate changes across customers in

the segment.

7.1.2. Segment content change

The content of segment change can be construed to follow

some combination of latent change and manifest change depend-

ing on the context.The onlyknown empirical studies demonstrate

latent change, but none include contexts where an entire market's

needs might be shifting, e.g., new product introductions, which

might reveal manifest change. Based on customer value change, it

is proposed that the understanding of content change might be

enhanced by examining the variety of change types and intensity

of changes on a segment level.

These two constructs build off the customer value change

process and link changes at a customer level to the types and

intensity of need changes at a segment level. These concepts might

be used in segmentation studies to capture changeprobabilities or a

measure of SI for a segment. Observing need-change form variety

and need-change intensity for the segment might also provideclues about SI patterns.Segmentswhose need-change form variety

and need-change intensity have low means and variance are likely

stagnant, whereas high averages and variance might reveal chaotic

segments. Also, different types of variance found among members

might be one indicator of whether a latent (high variance) or

manifest model (low variance) of change is prevalent.

7.1.3. Segment structural change

Finally, SI can be analyzed through resulting structural

changes to the segment. Dispersion is a type of spatial shift that

occurs as customers' changing needs move them around within a

segment or potentially out of it. Segments are based on members'

similarity to a common set of needs. So, as needs change, one can

envision customers moving within or outside some acceptable

range or confidence interval of the segment. Segment size is a

result of members entering or exiting segments based on need

change. One could also argue that degree of growth/decline of

members themselves (e.g., financially, etc.) might represent ano-

ther measure of size changes. Boundary clarity, describes whether

the segment in question has a clear distinction or overlaps withother segments, such that some members belong to more than one

segment. Overall the framework seeks to capture the origins,

content, and structure of SI.

Looking beyond a single segment, market instability is an

aggregate concept that describes change across segments and is

made up of similar structural characteristics. At this level, one

could analyze relationships between segments, for example, by

looking at overlapping segments to assess whether SI in one

segment influences the size or changing characteristics of ano-

ther. Market instability is similar to but more explicit than the

notion of market turbulence.

7.2. Environmental drivers of SI

The framework proposes that changes are driven by external

conditions and organizational changes occurring inside the firm,

which are extensions made directly from customer value change

theory. Evidence from value change research shows that these

factors contribute individually to customer firm change(Flint et al.,

2002), but research has yet to explore how external drivers might

interact or impact value change across members of a market

segment(s). For example, one might expect that significant in-

creases in interest rates might trigger more noticeable changes in

the buying needs of firms with relatively high debt-to-equity ratios

but have less of an impact on customer firms with relatively low

ones. The point is that external drivers of change, e.g., from

changes in technology, customers' competitors' actions, and sup-

pliers, are likely to have a varying impact on customers' desired

value changes in a segment. Furthermore, it seems there has been

an extensive amount of work describing external change drivers,

but less so on internal change drivers (Flint & Mentzer, 2000). For

instance, there is little research explaining how managers and their

mental models of supply markets, impacts changes in segments. At

this point, it is recognized that internal organizational events can

play a significant role in change and likely operate through an

organizational learning process, as described by customer value

change theory.

7.3. Outcomes of SI

Several potential outcomes of SI are expected. The segmenta-

tion literature is limited to discussing a few negative SI outcomes,

such as wasted investment on segmentation when segments

change. However, the significant evidence for results of good,

stable segments can be examined for further clues. Segmentation

studies generally link well-defined segments to several potential

benefits, including closer matching of a firm's products and capa-

bilities with customer needs (Dibb & Simkin, 2001; Tapp &

Clowes, 2002), greater understanding of how to maximize com-

munication with customers (Van Raaij & Verhallen, 1994), better

strategic decision-making about new products or re-positioning of

old ones (Hoek et al., 1993; Van Raaij & Verhallen, 1994), and



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better resource allocation among served customers (Lindridge &

Dibb, 2003; Wind, 1978). Based on these premises, a logical

extension to segment instability is thatto the degree firms rely

upon segmentation to design offers, align strategy, and allocate

resources to fit their view of the marketSI weakens the effective-ness of these efforts and, thus, overall market performance.

Three potential mismatch outcomes for SI include customer

needs-offering mismatch, market strategy mismatch, and a re-

source allocation mismatch. The ability to match products and

services to fit the needs of the segment is a central benefit of

segmentation. As the content and structure of segments change,

however, the strength of the matchcould weaken. When needs are

changingrapidly, a needs-offering match could disappear entirely,

such that a supplier's offers are seen as out of touch. Firms also

depend on segmentation to aid in decision making about market

strategy, including positioning new and existing products. As

segments change, target marketing strategies designed to alignwith individual segments and the overall market can become less

relevant. Thus, SI may force firms to consistently reexamine

communication strategies, pricing schedules, and other key

variables. Today's firms are urged to realize that not all customers

are created equal (Selden & Colvin, 2003), and resources should

be allocated to serve profitable, growing customers first. SI can

blur the picture on which segmentsdeserve greater focus. This can

be the case as segments grow or shrink, potentially creating a

resource deficit or excess scenario. For example, segments might

take on new needs, which cannot be served as profitably.

Finally, potential mismatches are connected to market perfor-

mance. While this relationship is speculative, mismatches of

strategy and resources likely contribute to suboptimal cost struc-

tures and needs-offer mismatches can lead to unhappy, dissatis-

fied customers that are more susceptible to take their business to

competitors. This could occur as customers feel under-served or

confused by suppliers who communicate or approach them in

ways more suited for other segments.

8. Discussion

All things being equal, suppliers would prefer customers'

needs to stay relatively stable and predictable. Unfortunately,

few market segments can boast this trait. Rather, studies suggest

that customers are constantly undergoing changes in what theyvalue from suppliers. In his review of industrial segmentation

literature, Plank went so far as to say segment stability has

been ignored both conceptually and empirically, as there has

been no longitudinal work, nor suggestions for the same (1985,

p. 87). Unfortunately, almost 20 years later, it is fair to say the

only considerable difference is more concerns have been

expressed (Freytag & Clarke, 2001; Mitchell & Wilson, 1998;

Steenkamp & Hofstede, 2002). Likely reasons for this gap

include an overemphasis on quantitative modeling coupled by

an ongoing search for better variables and the difficulties of

longitudinal research. Furthermore, attempts to understand what

segments currently need has been a significant challenge, and

until recently, most marketing literature has not focused deeply

on understanding the complexity of customers' change process-

es (Flint et al., 2002).

We sought to take an initial step toward closing this gap by

offering several contributions to the exploration of SI. First, our

discussion represents an initial attempt to conceptually define the

SI phenomenon and highlight the issues it creates in industrial

contexts. Second, a review of literature directly addressing SI inconsumer settings and in other perspectives attempts to under-

stand the phenomenon from several levels of analysis. Third, we

proposed a theoretical framework of SI to guide further con-

ceptual development and empirical study. This framework at-

tempts to provide an initial response to the question posed earlier,

which calls for clarity around the characteristics of SI and the way

it occurs, including its drivers and outcomes. In this process, we

explored theoretical insights for understanding the dynamics of

customer need heterogeneity within segments (Wedel &

Kamakura, 2002a). Finally, the model extends current customer

value change theory by conceptualizing it at a broader level of

analysis and applying it in a strategic context.

8.1. Managerial relevance

Depending on a supplier's approach, segment instability and

its outcomes can represent both a dilemma and an opportunity.

Firms taking a reactive approach to SI are relegated to two main

options. They can serve existing segments, hoping that classes

of segments are relatively stable and the inflow of customers

into those segments is greater than or equal to their outflow.

Alternatively, firms can wait until segment change is readily

apparent, in which case, they must play catch up with customers

and competitors who are tracking changes more closely.

Conversely, firms who can proactively measure and under-

stand SI, as it is occurring, position themselves to not only track

along with customers, but potentially give themselves the oppor-

tunity to shape the change as it occurs. Managers wanting to take

this approach might begin to explore implementing feedback

loops into current segmentation processes to understand SI.

Analyzing SI could be handled by a number of teams within the

firm, including strategists, forecasters, and front-line personnel

dealing with customers on a daily basis. However, at this point,

more research is needed to offer practical means of understanding

and predicting SI.

8.2. Future research agenda

This review has stimulated several questions about SI

needing further exploration.

Understanding models of segment content change in different

contexts. The limited evidence suggests that SI follows a

model of latent segment change, but exploring this assump-

tion in other contexts could reveal otherwise. Other than one

known study in a single western European country, SI has

not been explored in international contexts. A key question is

whether segment members change in generally the same

ways or in a divergent manner across global markets. Gene-

ralizing this principle through empirical research to under-

stand SI across contexts could be a fundamental step in

making progress towards understanding the phenomenon.



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Day, G. S., & Schoemaker, P. J. H. (2004, April). Driving through the fog:

Managing at the edge. Long Range Planning, 37(2), 127142.

Day, G. S., Shocker, A. D., & Srivastava, R. K. (1979, Fall). Customer-oriented

approaches to identifying product markets.Journal of Marketing, 43(4), 819.

Dess, G. G., & Beard, D. W. (1984). Dimensions of organizational task

environments. Administrative science quarterly, 29(1), 52

73.Deutsche Lufthansa AG. (2005). Annual report. Cologne: Von-Gablenz-Str.

2-6, 50679.

Dibb, S. (2001, September). New millennium, new segments: Moving towards

the segment of one? Journal of Strategic Marketing, 9(3), 193213.

Dibb, S., & Simkin, L. (2001, November). Market segmentation: Diagnosing

and treating the barriers. Industrial Marketing Management, 30(8),

609625.

Dibb, S., & Wensley, R. (2002). Segmentation analysis for industrial markets:

Problems of integrating customer requirements into operations strategy.

European Journal of Marketing, 36(1/2), 231251.

Dickson, P. R. (1982, Fall). Personsituation: Segmentation's missing link.

Journal of Marketing, 46(4), 5664.

Dickson, P. R. (1992). Toward a general theory of competitive rationality.


Dickson, P. R. (1994). Marketing management. Orlando, FL: Dryden Press.

Douglas, S. P. (2001, January). Exploring new worlds: The challenge of global

marketing. Journal of Marketing, 65(1), 103.

Dowling, G. R., Lilien, G. L., & Soni, P. K. (1993). A business market

segmentation procedure for product planning. Journal of Business-to-

Business Marketing, 1(4), 3162.

Eisenhardt, K. M., & Martin, J. A. (2000, October November). Dynamic

capabilities: What are they? Strategic Management Journal, 21(10/11),

11051121.

Farley, J. U., Winer, R. S., & Lehmann, D. R. (1987, August). Stability of

membership in market segments identified with a disaggregate consumption

model. Journal of Business Research, 15(4), 313328.

Flint, D. J., & Mentzer, J. T. (2000). Logitisticians as marketers: Their role when

customers' desired value changes. Journal of Business Logistics, 21(2),

1946.

Flint, D. J., Woodruff, R. B., & Gardial, S. F. (1997, March). Customer value

change in industrial marketing relationships: A call for new strategies and

research. Industrial Marketing Management, 26(2), 163176.

Flint, D. J., Woodruff, R. B., & Gardial, S. F. (2002, October). Exploring the

phenomenon of customers' desired value change in a business-to-business

context. Journal of Marketing, 66(4), 102117.

Freytag, P. V., & Clarke, A. H. (2001, August). Business to business market

segmentation. Industrial Marketing Management, 30(6), 473486.

Gale, B. T. (1994). Managing customer value. New York: Free Press.

Glazer, R., & Weiss, A. M. (1993, November). Marketing in turbulent

environments: Decision processes and the time-sensitivity of information.

Journal of Marketing Research, 30(4), 509521.

Goller, S., Hogg, A., & Kalafatis, S. P. (2002). A new research agenda for

business segmentation. European Journal of Marketing, 36(1/2),

252271.

Green, P. E., & Krieger, A. M. (1991, October). Segmenting markets with

conjoint analysis. Journal of Marketing, 55(4), 2031.

Gutman, J. (1982, Spring). A means-end chain model based on consumer

categorization processes. Journal of Marketing, 46(2).

Hamm, S. (2006, February 3rd). SAP gets on-demand religion. Business Week.

Hlavacek, J. D., & Reddy, N. M. (1986). Identifying and qualifying industrial

market segments. European Journal of Marketing, 20(2), 821.

Hoek, J., Gendall, P., & Esslemont, D. (1993). Market segmentation: A search

for the holy grail? Asia Australia Marketing Journal, 1(1), 4146.

Hofstede, F. T., Steenkamp, J. -B. E. M., & Wedel, M. (1999, February).

International market segmentation based on consumer product relations.


Holbrook, M. B. (1994). The nature of consumer value. In R. T. Rust, & R. L.

Oliver (Eds.), Service quality: New directions in theory and practice.

Newbury Park, CA: Sage Publications, Inc.Hu, M. Y., & Rau, P. A. (1995, June). Stability of usage segments, membership

shifts across segments and implications for marketing strategyan

empirical examination. Mid-Atlantic Journal of Business, 31(2), 161177.

Hurley, R. F., & Hult, G. T. M. (1998, July). Innovation, market orientation, and

organizational learning: An integration and empirical examination. Journal

of Marketing, 62(3), 4254.

Joshi, A. W., & Campbell, A. J. (2003, Spring). Effect of environmental

dynamism on relational governance in manufacturersupplier relationships:

A contingency framework and an empirical test. Journal of the Academy of

Marketing Science, 31(2), 176188.

Kamakura, W. A., Kim, B. -D., & Lee, J. (1996). Modeling preference and

structural heterogeneity in consumer choice. Marketing Science, 15(2),

152171.

Kamakura, W. A., & Russell, G. J. (1989, November). A probabilistic choice

model for market segmentation and elasticity structure. Journal of

Marketing Research, 26(4), 379390.

Kotler, P. (1994). Marketing management. Englewood Cliffs, NJ: Prentice-Hall.

Kumar, V., & Petersen, J. A. (2005, Fall). Using a customer-level marketing

strategy to enhance firm performance: A review of theoretical and empirical

evidence. Journal of the Academy of Marketing Science, 33(4), 504519.

Lapierre, J. (2000). Customer-perceived value in industrial contexts. Journal of

Business and Industrial Marketing, 15(2/3), 122143.

Lindridge, A., & Dibb, S. (2003, March). Is culture a justifiable variable for

market segmentation? A cross-cultural example. Journal of Consumer

Behaviour, 2(3), 269286.

Lutz, R. L. (1991). The role of attitude theory in marketing. In K. Robertson

(Ed.), Perspectives in consumer behavior. Foresman, Glenview, IL: Scott.

Malthouse, E. C., & Blattberg, R. C. (2005, Winter). Can we predict customer

lifetime value? Journal of Interactive Marketing, 19(1), 216.

Meyers-Levy, J., & Malaviya, P. (1999). Consumers' processing of persuasive

advertisements: An integrative framework of persuasion theories. Journal of

Marketing, 63(special issue), 4560.

Mitchell, V. W., & Wilson, D. F. (1998, September). Balancing theory and

practicea reappraisal of business-to-business segmentation. Industrial

Marketing Management, 27(5), 429445.

Oliver, R. L. (1997). Satisfaction: A behavioral perspective on the consumer.

New York: McGraw-Hill.

Peteraf, M. A., & Bergen, M. A. (2003, October). Scanning dynamic

competitive landscapes: A market-based and resource-based framework.

Strategic Management Journal, 24(10), 10271041.

Plank, R. E. (1985, May). A critical review of industrial market segmentation.

Industrial Marketing Management, 14(2), 7991.

Powers, T. L. (1991).Modern business marketinga strategic planning approach

to business and industrial markets. St. Paul, MN: West Publishing Co.

Prahalad, C. K., & Ramaswamy, V. (2004). Co-creating unique value with

customers. Strategy and Leadership, 32(3), 49.

Ramaswamy, V. (1997, February). Evolutionary preference segmentation with

panel survey data: An application to new products. International Journal of

Research in Marketing, 14(1), 5780.

Ratneshwar, S., Shocker, A. D., Cotte, J., & Srivastava, R. K. (1999, September).

Product, person, and purpose: Putting the consumer back into theories of

dynamic market behavior. Journal of Strategic Marketing, 7(3), 191208.

Reichheld, F. (1996). The loyalty effect. Cambridge, MA: Harvard Business

School Press.

Rosa, J. A., Porac, J. F., Runser-Spanjol, J., & Saxon, M. S. (1999, October).

Sociocognitive dynamics in a product market. Journal of Marketing, 63(4),

6477.

Selden, L., & Colvin, G. (2003).Angel customers and demon customers: Discover

which is which and turbo-charge your stock. New York: Penguin Group.

Sinkula, J. M., & Baker, W. E. (1997, Fall). A framework for market-based

organizational learning: Linking values, knowledge, and behavior. Journal

of the Academy of Marketing Science, 25(4), 305318.

Sirdeshmukh, D., Singh, J., & Sabol, B. (2002, January). Consumer trust, value,

and loyalty in relational exchanges. Journal of Marketing, 66(1), 1537.

Slater, S. F., & Narver, J. C. (1995, July). Market orientation and the learning

organization. Journal of Marketing, 59(3), 6374.

Slater, S. F., & Narver, J. C. (2000, Winter). Intelligence generation and superior

customer value. Journal of the Academy of Marketing Science, 28(1),120127.

Smith, W. R. (1956, July). Product differentiation and market segmentation as

alternative marketing strategies. Journal of Marketing, 21(1), 38.



14/14

Autho

r's

pe

rsonal

copy

Steenkamp, J. -B. E. M. (2005, October). Moving out of the U.S. Silo: A call to

arms for conducting international marketing research, an invited essay to

Marketing Renaissance: Opportunities and Imperatives for Improving

Marketing Thought, Practice, and Infrastructure. In Ruth Bolton (Ed.).


Steenkamp, J. -B. E. M., & Hofstede, F. (2002, September). International marketsegmentation: Issues and perspectives. International Journal of Research in

Marketing, 19(3), 185213.

Sudharshan, D., & Winter, F. (1998). Strategic segmentation of industrial

markets. Journal of Business and Industrial Marketing, 13(1), 821.

Sun, B., Neslin, S. A., & Srinivasan, K. (2003, November). Measuring the

impact of promotions on brand switching when consumers are forward

looking. Journal of Marketing Research, 40(4), 389405.

Tapp, A., & Clowes, J. (2002). From carefree casuals to professional

wanderers: Segmentation possibilities for football supporters. European

Journal of Marketing, 36(11/12), 12481269.

Too, L. H. Y., Souchon, A. L., & Thirkell, P. C. (2001, April). Relationship

marketing and customer loyalty in a retail setting: A dyadic exploration.

Journal of Marketing Management, 17(3/4), 287319.

Ulaga, W., & Eggert, A. (2006). Value-based differentiation in business relation-

ships: Gaining and sustaining key supplier status.Journal of Marketing, 70(1).

Ulrich, K. T., & Ellison, D. J. (1999). Holistic customer requirements and the

design-select decision. Management Science, 45(5), 641658.

Van Raaij, W. F., & Verhallen, T. M. M. (1994). Domain-specific market

segmentation. European Journal of Marketing, 28(10), 4966.

Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for

marketing. Journal of Marketing, 68(1), 117.

Voelpel, S., Leibold, M., Tekie, E., & Von Krogh, G. (2005, February). Escaping

the red queen effect in competitive strategy: Sense-testing business models.

European Management Journal, 23(1), 3749.

Wedel, M., & Kamakura, W. (2002, September). Introduction to the special issue

on market segmentation. International Journal of Research in Marketing,

19(3), 181183.

Wedel, M., & Kamakura, W. (2002). Market segmentation: Conceptual and

methodological foundations. Norwell, MA: Kluwer Academic Publishing.

Wind, Y. (1978, August). Issues and advances in segmentation research.


Woodruff, R. B. (1997, Spring). Customer value: The next source for competitive

advantage. Journal of the Academy of Marketing Science, 25(2), 139154.

Woodruff, R. B., Cadotte, E. R., & Jenkins, R. L. (1983, August). Modeling

consumer satisfaction processes using experience-based norms. Journal of

Marketing Research, 20(3), 296304.

Woodruff, R. B., & Gardial, S. F. (1996). Know your customer: New approaches

to understanding customer value and satisfaction. Cambridge, MA:

Blackwell Business.

Yuspeh, S., & Fein, G. (1982, JuneJuly). Can segments be born again? Journal

of Advertising Research, 22(3), 1322.

Zeithaml, V. A. (1988, July). Consumer perceptions of price, quality, and value: A

means-end model and synthesis of evidence. Journal of Marketing, 52(3),

221.

Christopher P. Blocker is an Assistant Professor in the Department of

Marketing at Baylor University and has past experience in business-to-business

marketing and global account management. His research interests include

customer value management, international buyer behavior, and global market-

ing strategy. He has published research in the Journal of Business and

Industrial Marketing and a number of conference proceedings of leading

marketing academic organizations.

Dr. Daniel J. Flint is the Proffitt's, Inc. Professor of Marketing and an

Associate Professor of Marketing in the Department of Marketing and Logistics

at the University of Tennessee. He received his Ph.D. in the areas of marketing

and logistics from the University of Tennessee and has published numerous

articles in the Journal of Marketing, Industrial Marketing Management,

Journal of Business Logistics, International Journal of Physical Distribution

and Logistics Management, and other journals.


blocker 2007 imm segment instability - customer value

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