Journal of Strategic Marketing

ISSN: 0965-254X (Print) 1466-4488 (Online) Journal homepage: https://www.tandfonline.com/loi/rjsm20

A taxonomy of mobile phone consumers: insights

for marketing managers

Lukman Aroean & Nina Michaelidou

To cite this article: Lukman Aroean & Nina Michaelidou (2014) A taxonomy of mobile phone
consumers: insights for marketing managers, Journal of Strategic Marketing, 22:1, 73-89, DOI:
10.1080/0965254X.2013.876063

To link to this article: https://doi.org/10.1080/0965254X.2013.876063

Published online: 23 Jan 2014.

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Journal of Strategic Marketing, 2014
Vol. 22, No. 1, 73–89, http://dx.doi.org/10.1080/0965254X.2013.876063

A taxonomy of mobile phone consumers: insights for marketing

managers
Lukman Aroeana* and Nina Michaelidoub
a
Business School, Bournemouth University, Bournemouth, UK; bSchool of Business and Economics,
Loughborough University, Leicestershire, UK
(Received 29 October 2012; accepted 18 November 2013)

Amid less attention to the market segmentation of innovations through positioning

innovations in the minds of consumers, the paper explores consumer innovativeness,
need for emotion, and prestige price sensitivity to develop a taxonomy of mobile phone
consumers. The study analyses survey data of 416 consumers using factor analysis and
cluster analyses indicating interesting findings. Four distinct clusters emerge, namely
cognitive adopters, prestige-seeking emotional innovators, emotional adopters, and
prestige-seeking cognitive innovators. Findings reveal that prestige-seeking emotional
innovators and prestige-seeking cognitive innovators have relatively higher level of
innovativeness and prestige price sensitivity, but at the same time differ between them
in terms of their level of need for emotion. The paper contributes to knowledge by
suggesting that marketing constructs such as consumers’ sensitivity to the prestige cue
of prices as well as consumers’ need for emotion are used to cluster mobile phone
consumers. The taxonomy is highly relevant to marketing managers as it gives insights
into potential additional bases for segmentation, positioning, and marketing
communication strategy targeting innovative consumers through cognitive and/or
emotional cues.
Keywords: consumer innovativeness; prestige price sensitivity; emotion; taxonomy;
cluster; mobile phones

Introduction
Consumer innovativeness accounts for much of the success or failure of new products. The
concept is important and relevant in management and marketing practices since
organizations rely on new products for their profitability and future growth (Steenkamp,
Hofstede, & Wedel, 1999), while innovative consumers are an important segment for
organizations (Park, Yu, & Zhou, 2010). Consumer innovators have a key impact on
consumer society as trendsetters since the rate by which they adopt new products
encourages other customers to follow (López-Nicolás, Molina-Castillo, & Bouwman,
2008; Shoham & Ruvio, 2008).
Previous research examines different conceptualizations of consumer innovativeness
(e.g., domain specific, cognitive, and sensory innovativeness) and links the concept with
the purchase of new products (Goldsmith, Freiden, & Eastman, 1995; Roehrich, 2004)
through psychological and other factors (e.g., personality). Academics and practitioners
focus on the personality of consumer innovators, which explains purchase behavior and
which is important for new products (Clark & Goldsmith, 2006). However, significant
gaps remain with regard to the profile and specific characteristics of the innovative

*Corresponding author. Email: laroean@bournemouth.ac.uk

q 2014 Taylor & Francis

74 L. Aroean and N. Michaelidou

consumer (Klink & Athaide, 2010; Okazaki, 2006). Specifically, gaps remain with respect
to consumer innovativeness and other factors such as emotions and prestige price
sensitivity, which although important in purchases of innovations, researchers investigate
mostly in isolation to consumer innovativeness. Previous research argues that emotions
guide and persuade individual behaviors (e.g., Duhachek, 2004) and even generate
‘an energy’ to pursue desires (e.g., Belk, Ger, & Askegaard, 2003); therefore, the purchase
of new products might serve to gratify emotion-related needs (e.g., need for emotion).
Similarly, consumer innovators are price sensitive (Goldsmith & Newell, 1997) and
purchases of new products can be expensive but at the same time ‘prestigious’. Companies
position innovations as high quality and/or exclusive products through ‘prestigious’
pricing that suggests high quality and status (Vigneron & Johnson, 1999). Vigneron and
Johnson (1999) link prestige with motives of sociability and self-expression, which show
that consumers who seek prestige in products or brands do so because of their values and
traits which include conspicuousness, need for uniqueness, sociability, and possibly need
for emotion. On this basis, emotions as trait and prestige price sensitivity are key
constructs to understand consumers’ adoption of innovations. These constructs are
relevant to marketers of varied innovations (e.g., mobile phones, electronics) to develop
successful segmentation and positioning strategies, as marketers can use them alongside
consumer innovativeness and other relevant psychological characteristics such as
mavenism (Goldsmith, Clark, & Goldsmith, 2006), need for variety and novelty, and need
for uniqueness (Goldsmith et al., 2006; Michaelidou, 2011; Rohm & Swaminathan, 2004)
to classify consumer innovators.
In line with the above discussion to embrace broader perspectives of key marketing
concepts such as emotions (Richins, 1997) and price sensitivity (Lichtenstein, Ridgway,
& Netemeyer, 1993), this study explores consumer innovativeness, need for emotion, and
prestige price sensitivity as segmentation bases used to cluster consumers. The study
focuses on domain-specific innovativeness, since importantly an individual’s innovative-
ness is a function of the product category of interest (Gatignon & Robertson, 1985;
Hirschman, 1980; Klink & Athaide, 2010). Research shows that domain-specific
innovativeness relates to the acceptance of new products (Goldsmith & Hofacker, 1991;
Goldsmith et al., 1995; Klink & Athaide, 2010) and suggests that consumers’
innovativeness manifests within specific product categories and leads to purchase of new
products within that particular domain.

Context of study
Previous research in the domain of innovation management highlights the novelty and
importance of the mobile communication technology, which involves high rates of growth,
and rapid rate of diffusion and adoption of mobile communication technology in both
developed and developing countries (Chircu & Mahajan, 2009). Currently, there are four
billion mobile phones in use globally of which more than one billion (27%) are smartphones
and three billion have SMS capability (Digitalbuzz, 2012). Figure 1 shows that currently
82.3% of the global population have a mobile phone (Google statistics, 2012).
According to Kalba (2008), mobile phones are a ‘manifestation of globalization’ and
have out-diffused all prior technologies within a relatively short period of time. Mobile
and smartphones are versatile in terms of usage and allow their users to access information
(e.g., weather, maps, news), listen to music, play games, and watch videos as well as
socialize via Facebook and Twitter. Similarly, mobile and smartphones represent a
contemporary marketing communication tool that companies utilize to target their
 Journal of Strategic Marketing 75

Figure 1. Percentage of world population with mobile phones.

customers with SMS messages and promotions. Simply, consumers’ rate of adoption of
mobile and smartphones encourages advertisers to invest in mobile space. Statistics show
that mobile advertising in the UK has grown 116% to £83 million ($130 million) in 2010
(Internet Advertising Bureau UK, 2012). In 2011, mobile phones outperforms PCs in
terms of Internet searches, whereas analysts predict that in 2014 mobile Internet will
takeover desktop Internet usage (Digitalbuzz, 2012). In 2010, the market volume of
mobile phones in the UK was 27.2 million units, and analysts forecast that it will reach
36.6 million units in 2015, an increase of 34.5% (Datamonitor, 2011). Statistics from
Ofcom show that 91% of adults in the UK own or use a mobile phone, while 27% of adults
and 47% of teenagers own a smartphone (Ofcom, 2011).
Another important aspect is that mobile and smartphones have a short life cycle, are
more risky and complex than other innovative products, and they require consumers to
learn about them (Saaksjarvi, 2003). Hence, the identification of innovators within this
specific domain is highly useful and relevant for practitioners to develop their marketing
and communication strategies. Previous research examines mobile phones on the basis of
switching costs and satisfaction (e.g., Lee, Lee, & Feick, 2001), customer confusion
(Turnbull, Leek, & Ying, 2000), and buyer behavior (Kimiloglu, Nasir, & Nasir, 2010).
Other research examines mobile technology (e.g., mobile phones) in four fast-growing
developing countries (Chircu & Mahajan, 2009). Recently, research investigates a mobile
phone-based money transfer service in Kenya (Wooder & Baker, 2012). However,
research devotes less attention to the market segmentation of mobile phones (e.g.,
Kimiloglu et al., 2010; O’Regan, Kalidas, Maksimova, & Reshetin, 2011), despite some
studies focus on the categorization of buyers of mobile phones on the basis of the
importance they attached to various attributes of mobile phones, such as physical features
and functionality (e.g., Kimiloglu et al., 2010).
To the authors’ best knowledge, a taxonomy of consumers in the domain of the mobile
phone market on the basis of consumer innovativeness, need for emotion, and prestige
price sensitivity does not exist. This study therefore offers original insights that advance
management practice in the mobile phone market, since understanding how innovative,
emotional, and prestigiously price-sensitive consumers are will give practitioners insights
into how to better plan their marketing campaigns, position their innovations, and target
their customers with emotion- and prestige-customized promotional messages. The study
begins with a review of the extant literature on consumer innovativeness, need for
emotion, and prestige price sensitivity. It proceeds with a description of the methodology,
76 L. Aroean and N. Michaelidou

data analysis, and results. The discussion of the results and the implications for marketing
practitioners then follow. The paper concludes with limitations and future research.

Conceptual background
Market segmentation is a vital notion in marketing practice with important benefits
(Dickson & Ginter, 1987; O’Connor & Sullivan, 1995; Wedel & Kamakura, 1999) for
business and organizations. Academics and practitioners use market segmentation as a
method to identify consumer and business segments in varied sectors, for example banking
and financial services (e.g., Athanassopoulos, 2000; Machauer & Morgner, 2001),
hospitality and tourism industry (e.g., Bojanic, 2007; Shani, Wang, Hutchinson, & Lai,
2010), and high-tech industry (e.g., Sharma & Lambert, 1994). In the domain of
innovation, early research (Rogers, 1962) used personal characteristics and innovativeness
to classify consumers according to their adoption of new products as innovators, early
adopters, early majority, late majority, and laggards. Other early research identified
characteristics of adopters of innovations on the basis of demographic and psychographic
characteristics such as experience with the product and creativity (Dickerson & Gentry,
1983). Dickerson and Gentry (1983) investigate adopters of home computers and identify
that these consumers had more experience with the product and that their profile was
similar with that of creative consumers (also Hirschman, 1980). Later, research links
consumer innovation with product involvement and shows that innovators have a high
degree of involvement with the product category of interest (Foxall, 1994, 1995; Foxall &
Bhate, 1993). The authors examine innovators for food items and suggest that this type of
consumers are willing to try new products, accept the risk of unsatisfactory purchases, use
more environmental stimuli (e.g., information), and are more active in their search for
information (Foxall, 1994, 1995; Foxall & Bhate, 1993). Furthermore, other research
classifies innovators of technological products according to knowledge and compatibility
into technovators, supplemental experts, novices, and core experts, and suggests that
technovators have a high level of involvement and are willing to test new products
(Saaksjarvi, 2003). Moreover, commercial research (e.g., Sri consulting) has also used
innovativeness to classify segments of US consumers (VALS) into eight categories (http://
strategicbusinessinsights.com/).

Consumer innovativeness
Consumer innovativeness is a personality trait that concerns individual differences in
response to new products (Goldsmith & Hofacker, 1991; Midgley & Dowling, 1978;
Mudd, 1990). Early literature defines consumer innovativeness as a tendency or
disposition to buy new products faster than other consumers (Midgley & Dowling, 1978).
Although there is no consensus as to what constitutes ‘innovativeness’ (Roehrich, 2004),
earlier research distinguishes innovativeness as ‘innate’ and ‘actualized’ (Midgley, 1977;
Midgley & Dowling, 1978). Steenkamp et al. (1999) define innate innovativeness as a
‘predisposition to buy new and different products and brands rather than remain with
previous choices and consumer patterns’ (p. 56), while ‘actualized’ innovativeness
denotes an overt response toward new products (Gatignon & Robertson, 1991). Previous
research uses ‘actualized’ innovativeness to exemplify the diffusion of innovations and
hence to categorize consumers into innovators, early adopters, early majority, late
majority, or laggards (e.g., Rogers, 1962). In contrast, researchers treat ‘innate’
innovativeness as a personality trait which refers to the propensities or latent preferences
 Journal of Strategic Marketing 77

of consumers to adopt novel experiences and products (e.g., Hirschman, 1980;

Venkataraman, 1991; Venkataraman & Price, 1990), and it is distinct from that of
innovation adoption categorization (Rogers, 1962). Researchers have also studied
innovativeness in relation to cognition and sensation (Venkataraman & Price, 1990) and
suggest that cognitive innovators prefer a greater amount of information and tend to be
price sensitive, while sensory innovators are more interested in pleasure and novelty
(Aroean, 2012; Park et al., 2010).
Furthermore, Roehrich (2004) provides a discussion of the ‘forces,’ or ‘inherent needs,’
which relate to and explain innate innovativeness. The author suggests that a number of
underlying needs explain innate innovativeness such as the need for stimulation, variety-
seeking tendency (Joachimstaler & Lastovicka, 1984; Raju, 1980; Venkatesan, 1973;
Wahlers, Dunn, & Etzel, 1986), novelty-seeking and creativity (Hirschman, 1980; Mudd,
1990), and need for uniqueness (Burns & Krampf, 1991; Gatignon & Robertson, 1985).
Innovativeness thus closely relates to a creative and variety-seeking mentality that includes
the thinking of new ideas, the desire for new experiences, and the exploration of unique
solutions to problems (Ridgway & Price, 1994, p. 69). Innate innovativeness also relates to
willingness to change (Aroean, 2012; Im, Bayus, & Mason, 2003), risk taking (Rogers,
1962) as well as novelty-seeking, which is an internal force that drives the individual to seek
out novel information (Aroean, 2012; Hirschman, 1980; Manning, Bearden, & Madden,
1995). As such, innovative consumers are keen to update their knowledge with the newest
information on innovation independently of the influence of others (Manning et al., 1995).
Theorists describe innovativeness as a normally distributed characteristic in the consumer
population (Gatignon & Robertson, 1991; Goldsmith, d’Hauteville, & Flynn, 1998;
Midgley & Dowling, 1978).

Need for emotion

Extant literature extensively examines emotions and shows that emotions motivate
consumers and guide their attitudes and behavior (Allen, Machleit, Kleine, & Notani, 2005;
Bagozzi, Gopinath, & Nyer, 1999; Duhachek, 2004). In addition, emotions affect customer
satisfaction, retention, and mistrust of firms (Vanhamme & Lindgreen, 2001; Westbrook &
Oliver 1991) as well as customers’ approach and avoidance behaviors (Penz & Hogg, 2011).
Researchers view emotions as an enduring trait, namely ‘need for emotion’ (Lee, Amir,
& Ariely, 2009; Roehm & Roehm, 2005), which refers to the tendency to see affective
stimuli and enjoy emotionally laden situations (Raman, Chattopadhyay, & Hoyer, 1995),
irrespective of the strength of the experiential emotion per se; thus, need for emotion differs
from the notion of ‘affect intensity’ (Larsen, Diener, & Emmons, 1986). Need for emotion is
relevant to the ‘sensory’ property of consumer innovativeness (Park et al., 2010;
Venkataraman & Price, 1990) given that the construct indicates that individuals prefer to use
emotions in their interactions with marketing stimuli (Raman et al., 1995). Arguably, need
for emotion relates to consumer innovativeness through stimulation, impulsivity, and
creative capability (e.g., Sethi, Smith, & Park, 2001; Steenkamp et al., 1999). First, research
emphasizes that need for emotion relates to an individual’s personal value of stimulation,
and hence as a stimulation-laden trait, it indicates sensitivity and receptiveness to emotional
stimulation (Schwartz & Sagiv, 1995). On this basis, need for emotion therefore leads to
consumer innovativeness and subsequently to the adoption of innovations (Raju, 1980).
In addition, Roehrich’s (2004) suggestion that innovative individuals seek stimulation in
their consumption (e.g., emotional or sensory stimulation) supports the idea that stimulation
predicts adoption of innovations. Second, need for emotion relates to consumer
78 L. Aroean and N. Michaelidou

innovativeness through impulsivity. Impulsivity refers to ‘a sudden inclination to act

without deliberation’ (Goldenson, 1984, p. 37). The author suggests that impulsivity is a
manifestation of consumer innovativeness whereby consumer innovativeness exerts an
impulsive enactment, which leads to adoption of product innovations. In other words,
innovative consumers adopt an innovation on impulse as a consequence of new stimuli (e.g.,
information) about the innovation. This indicates that innovative consumers are sensitive
and receptive to stimuli that lead to an immediate reaction (i.e., purchasing on impulse),
and suggests that need for emotion provides space for such impulsive reaction. On this
basis, need for emotion interacts with consumer innovativeness because it can trigger
an impulsive response, such as the purchase of an innovation, as a consequence of
consumers’ receptiveness to the stimuli. Third, in line with previous research (e.g.,
Dickerson & Gentry, 1983; Ridgway & Price, 1994), need for emotion relates to consumer
innovativeness via creativity. Consumer innovators have an ‘emergent nature,’ which
reflects a ‘unique capability to imagine or envision how concepts might be further
developed so that they will be successful in the mainstream marketplace’ (Hoffman,
Kopalle, & Novak, 2009, p. 4). Environmental psychology and specifically optimal
stimulation level theory explain the link between need for emotion and innovativeness via
creativity whereby creative individuals engage in creative activities to maintain their
optimal stimulation level which includes emotional or sensory stimulation (Mehrabian &
Russell, 1974; Raju, 1980).

Prestige price sensitivity

Previous research links consumer innovativeness with price sensitivity, for example
Goldsmith and Newell (1997) suggest that innovative consumers are price insensitive, while
Park et al. (2010) show that cognitive innovative consumers are price conscious as opposed
to sensory innovative consumers. According to Lichtenstein et al. (1993), price as a cue
construes of positive perceptions about what price ‘signals to other people about the
purchaser’ (p. 236), including status and prestige. Prestige price sensitivity refers to a belief
by consumers that the purchase of the most expensive brand is a positive experience, which
impresses others (Lichtenstein et al., 1993; Netemeyer, Burton, & Lichtenstein, 1995). The
authors define prestige sensitivity as ‘a favorable perception of the price cue based on
feelings of prominence and status that higher prices signal to other people about the
purchaser’ (Lichtenstein et al., 1993, p. 236). Consumers purchase expensive products
because of what others will think about them. Hence, prestige is valuable for consumers who
like to express their social status, or persona to others (Lichtenstein et al., 1993; Zeithaml,
1988). In addition, the purchase of new products or innovations may express high status and
prestige, and price can be a cue that demonstrates the prestige of those products (O’Neill &
Lambert, 2001). Previous research highlights the role of power, self-enhancement, and
expression in consumer innovativeness (e.g., Roehrich, 2004; Rogers, 1962; Steenkamp
et al., 1999; Vandecasteele & Geuens, 2010; Vigneron & Johnson, 1999). Such values drive
consumers to achieve high social status and prestige (see Schwartz, 1992) through
purchases of new products (Simonson & Nowlis, 2000; Steenkamp et al., 1999).

Methodology
Method and sample
The present study employs Hirschman’s (1980) and Goldsmith and Hofacker’s (1991)
attitudinal perspective of innovativeness and uses an exploratory research design (without
 Journal of Strategic Marketing 79

a priori assumptions) to develop a taxonomy of mobile phone consumers based on these

constructs. A questionnaire was used to collect data from a sample of respondents in two
metropolitan cities in the UK. A drop-off-and-collect survey technique was utilized
whereby questionnaires were distributed and collected from places such as offices,
residential areas, shopping centers, sport centers, and other public premises. A total of 416
completed questionnaires were collected out of 800 dropped-off, representing a response
rate of more than 50%.

Measurements
The scale used to capture consumer innovativeness derives from Goldsmith and Hofacker
(1991) and was preferred over other scales due of its originality in capturing domain-specific
innovativeness (Roehrich, 2004) and which is linked to the purchase of new products
(Goldsmith et al., 1995). The scale consists of six items measured on a range of 1– 7.
To measure prestige price sensitivity, a scale of nine items originating from Lichtenstein
et al. (1993) was used. Finally, a set of 12 items originating from Raman et al. (1995) was
used to measure need for emotion on a scale of 1– 7. Items capturing consumer
innovativeness and prestige price sensitivity (i.e., Goldsmith & Hofacker, 1991;
Lichtenstein et al., 1993) were gauged for mobile phones. To capture need for emotion,
respondents were asked to consider mobile phones when indicating their answers. The
reason for doing this is that although need for emotion is viewed as a personality trait, which
maybe beyond product domain specificity, literature suggests that emotions differ
according to consumption situations (Richins, 1997). Previous research measuring similar
personality traits (e.g., optimal stimulation level, variety-seeking) did not gauge the items
according to the product domain (e.g., Michaelidou 2011; Rohm & Swaminathan, 2004).
Therefore, for the purchase of different products, consumers may be confronted with
different emotions. In addition, literature suggests that emotions refer to specific objects or
stimulus events (Scherer, 2005), thus they are likely to vary across consumption contexts.
Hence, consumers’ need for emotion is likely to be manifested differently across purchase
and consumption contexts.

Analysis and results

The sample consists of 48% males and 52% females. Table 1 indicates the sample’s age
and gender.

Exploratory factor analysis

In line with previous research (Michaelidou, 2011; Rohm & Swaminathan, 2004), prior
to cluster analysis, we run exploratory factor analysis (EFA) via Principal Component

Table 1. Sample by age and gender.

Male Female Total
Age 17 – 29 64 98 162
30 – 39 74 60 134
40 – 49 51 33 84
50 – 59 10 21 31
60 þ 1 4 5
Total 200 216 416
80 L. Aroean and N. Michaelidou

Analysis with oblique rotation, in view of the theoretical linkage among the factors,
to reduce the data and be able to yield clean and interpretable clusters. As expected, the
solution from EFA indicates three distinct and interpretable factors explaining 68.9% of
the variance (Table 2). We do not include items with loadings below 0.40 in the analysis
in order to allow a clearer interpretation. Reliability analysis indicates that coefficient a

Table 2. Component matrix.

Component
Items 1 2 3
Compared to my friends, I do little purchasing for mobile phones 0.781
In general, I am the last in my circle of friends to know the latest 0.851
trends for mobile phones
I know more about new versions of mobile phones than other 0.897
people
If I heard that a new version of this product was available, I would 0.803
be interested enough to buy it
In general, I am among the last in my circle of friends to purchase 0.881
new products like this
I will consider buying a new version of a mobile phone, even if 0.712
I have just heard about it
People notice when I buy the most expensive mobile phone 0.604
Buying a high-priced mobile phone makes me feel good about 0.897
myself
Buying the most expensive mobile phone makes me feel classy 0.924
I enjoy the prestige of buying a high-priced mobile phone 0.880
It says something to people when I buy the high-priced 0.862
version of a mobile phone
My friends will think I am cheap if I consistently buy the 0.881
lowest-priced version of a mobile phone
I have purchased the most expensive mobile phone just because 0.863
I knew other people would notice
I think others make judgments about me by the mobile phone I buy 0.838
Even for a relatively inexpensive product, I think that buying 0.867
a costly brand is impressive
I try to anticipate and avoid situations where there is a likely chance 0.799
of my getting emotionally involved
Experiencing strong emotions is not something I enjoy very much 0.852
I would rather be in a situation where I experience little emotion than 0.861
one which is sure to get me emotionally involved
I don’t look forward to being in situations that others have found 0.813
emotional
I look forward to situations that I know are less emotionally 0.821
involving
I like to be unemotional in emotional situations 0.789
I find little satisfaction in experiencing strong emotions 0.827
I prefer to keep my feelings under check 0.744
I feel relieved rather than fulfilled after experiencing a situation 0.801
that was very emotional
I prefer to ignore the emotional aspects of situations rather 0.834
than getting involved in them
More often than not, making decisions based on emotions just 0.647
leads to more errors
I don’t like to have the responsibility of handling a situation 0.813
that is emotional in nature.
 Journal of Strategic Marketing 81

values are above 0.91 for the three factors. This solution is rationalized as scales have
been used to measure consumer innovativeness, need for emotion, and perceived price
sensitivity. An alternative method of data reduction would have been to take overall
scores of the scales for cluster analysis, although this approach would have yielded the
same results. The factors represent the three different constructs, consumer
innovativeness (c 3), need for emotion (c 2), and prestige price sensitivity (c 1), thus
these names were retained.

Cluster analysis
We subsequently run cluster analysis to partition the sample of mobile phone consumers
into segments using the factor scores derived from EFA, following widely accepted
cluster procedures (Everitt, Sabene, & Leese, 2001; Punj & Stewart, 1983; Rohm &
Swaminathan, 2004). Cluster analysis is an exploratory procedure, which aims to discover
groups of observations that are homogenous and separated from others (Everitt et al.,
2001) and is widely used in diverse disciplines for classifying samples. Compared to other
classification techniques, cluster analysis makes no a priori assumptions with regard to
differences within populations (Punj & Stewart, 1983), therefore as a method it is
considered free of management’ bias in that it allows consumer-revealed segments to
emerge from the data (Allred, Smith, & Swinyard, 2006; Kimiloglu et al., 2010).
The clustering procedure involves two stages, with stage 1 as the internal validation
where the data were randomly divided into two subsets. Using hierarchical cluster analysis
with Ward’s method, the analysis on the first subset generates the possible alternative
cluster solutions (Punj & Stewart, 1983). Stage 2 involves the use of the second data subset
to conduct K-means cluster analysis using the cluster solutions (3, 4, and 5) indicated by
the hierarchical cluster analysis. We then compare the cluster memberships from the
K-means analysis on the second data subset with those produced by the hierarchical cluster
analysis in order to choose the most appropriate solution (Punj & Stewart, 1983). We
consider the four-cluster solution as the most meaningful and interpretable. We then run a
final K-means cluster analysis with four-cluster solution (Everitt et al., 2001). Table 3
shows the final cluster solution.

Cluster descriptors
The section below describes the clusters. The analysis shows that clusters discriminate in
terms of the level of consumer innovativeness: clusters 2 and 4 with higher level of
innovativeness (e.g., positive score) as opposed to clusters 1 and 3 that score negatively.
On this basis, we use the terms innovators versus adopters to name the clusters.

Table 3. Final cluster solution.

Clusters
1 2 3 4 ANOVA (F) P
Prestige price sensitivity 2 0.503 0.972 2 0.806 1.27 223.454 0.000
Need for emotion 2 0.426 0.500 1.39 21.14 173.775 0.000
Consumer innovativeness 2 0.565 0.894 2 0.251 0.927 115.772 0.000
N 207 110 62 37
Note: Cluster descriptors are based on factor scores. Scores range from 3 to 23 (high to low).
82 L. Aroean and N. Michaelidou

Cluster 1: cognitive adopters

This is the largest of the four clusters and includes 50% of sample. In comparison to the
other clusters, consumers in this cluster score below average in all three variables. These
mobile phone consumers are less innovative and have a lower need for emotion as opposed
to clusters 2 and 3. Given their score, these consumers are not very familiar with the latest
innovations in mobile and smartphones and they do not keep up with the new technologies.
Consumers in this cluster are not prestigiously price sensitive, thus they do not seek luxury
and prestige in their purchases of mobile phones, although they are likely to be value
conscious. It is argued that such consumers maybe more interested in cognitive and
tangible attributes of mobile phones such as the functionality, cost efficiency, and practical
design, and are less interested in the intangible attributes such as image and prestige (e.g.,
what the mobile phone says about the user). Consumers in this cluster somewhat resemble
the profile of cognitive innovators (Venkataraman & Price, 1990), therefore are likely to
be more susceptible to cognitive types of communication strategies such as strategies
based on unique functional selling points and generic or comparative advertising (e.g.,
Laskey, Day, & Crask, 1989).

Cluster 2: prestige-seeking emotional innovators

This cluster includes 26% of sample and score above average on all three descriptors. They
have the second highest score for consumer innovativeness following cluster 4. This
cluster also has the relative highest prestige price sensitivity indicating that these
individuals enjoy the prestige of buying a pricey mobile phone and they are concerned
with what others think about their mobile phone. These consumers feel that their mobile
phones indicate status and are a reflection of themselves, and therefore they consider
expensive mobile phones to buy. At the same time, they are innovative, which indicates
that they keep up with the latest developments and innovations in order to make sure that
they buy the most expensive mobile phone. Finally, these individuals score above average
on need for emotion, which indicates their preference for emotional stimuli, as opposed to
cognitive stimuli, and therefore are likely to be more susceptive to affective or
transformational advertising, including emotional, resonance, and brand image (Laskey
et al., 1989).

Cluster 3: emotional adopters

Consumers in this cluster comprise 15% of the sample of mobile phone consumers that
have the highest need for emotion and lowest level of prestige price sensitivity compared
to the other clusters. They also have a below-average level of consumer innovativeness.
On the basis of their scores, mobile phone consumers in this cluster like to experience
emotions but are less innovative compared to clusters 2 and 4. As such, they are less
concerned about luxury and prestige when it comes to purchasing mobile phones although
they are concerned with the emotional experience and emotional aspects of buying a
mobile phone. This indicates that consumers in this group rely on their emotion (or is
emotionally impulsive) in purchasing mobile phones, possibly utilizing affective or
emotional cues to make decisions on mobile phones. These consumers are therefore more
susceptive to affective or transformational message strategies, albeit those not focusing on
prestige, such as for example ‘use occasion’ (Laskey et al., 1989) where the emphasis
would be to establish a link between the product and a highly emotional situation.
 Journal of Strategic Marketing 83

Figure 2. Final cluster solution map.

Cluster 4: prestige-seeking cognitive innovators

Cluster 4 is the smallest cluster with only 9% of consumers. This cluster comprises of
mobile phone consumers with the highest level of consumer innovativeness, the lowest
need for emotion, and the highest prestige price sensitivity, relative to the other clusters.
Individuals in this cluster are innovative, and compared to consumers in the other clusters
are the most knowledgeable about mobile phone innovations and are concerned about the
luxury and prestige of their mobile phones. They are likely to own and buy expensive
brands/versions of mobile phones because they make them feel classy. On the other hand,
these consumers have a low need for emotion in their consumption experiences, which
indicates that they are likely to seek prestige based on functional attributes of innovations,
such as the latest technology and functional capabilities of the mobile phones or
smartphones as opposed to intangible attributes such as brand image. These individuals are
therefore likely to be cognitive innovators (Venkataraman & Price, 1990), and are likely to
respond more favorably to cognitive communication strategies that focus on technological
aspects and features of mobile phones. Marketers that wish to target such individuals may
also integrate transformational elements in communication strategies such as user images
(Laskey et al., 1989) as these consumers are concerned with what their mobile phones
reflect about them.

Cluster validation
Previous research uses non-clustering demographic variables to perform external validity
checks, which validate their clustering solutions (Ketchen & Shook, 1996; Michaelidou,
2011; Rohm & Swaminathan, 2004). In this study, we examine external validity of the
clusters by assessing criterion-related validity using gender and age, via x 2 tests. Findings
report that age discriminates the clusters (x 2 ¼ 56.362, df ¼ 12, p , 0.000) but gender
does not (x 2 ¼ 3.911, df ¼ 3, p . 0.05). Therefore, in terms of gender, all clusters
roughly have equal ratio between genders. In terms of age, most of consumers in cluster 1
span from 17 to 49, while clusters 2 and 4 (with the relative highest level of innovativeness
and prestige price sensitivity) consist of mostly younger individuals aged 17 –29. Table 4
shows the clusters in terms of gender and age.
84 L. Aroean and N. Michaelidou

Table 4. Clusters by gender and age.

Sex Age
Cluster Male Female 17 – 29 30 – 39 40 – 49 50 –59 60 þ
1 99 108 55 70 56 22 4
2 52 58 63 34 12 1 0
3 26 36 20 24 9 8 1
4 23 14 24 6 7 0 0
Total 200 216 162 134 84 31 5

Discussion and implications

The study explores consumer innovativeness, prestige price sensitivity, and need for
emotion as clustering variables to develop a taxonomy of consumer in the domain of
mobile phones. While previous research categorizes mobile phone consumers (e.g.,
Kimiloglu et al., 2010) on the basis of overt behavioral variables, this study differentiates
from this research in that it explores consumer innovativeness, prestige price sensitivity,
and need for emotion as clustering variables to segment mobile phone consumers, and
hence highlights their relevance to market segmentation and development of marketing
communication campaigns.
Results indicate four interpretable clusters: cognitive adopters, prestige-seeking
emotional innovators, emotional adopters, and prestige-seeking cognitive innovators.
Cognitive adopters score below average on all three factors. These consumers are not very
interested in mobile phone innovations and the prestige involved in the purchase of a new
mobile phone. They are most likely to be concerned with the functional attributes of
mobile phones as opposed to emotional intangible attributes and are not likely to adopt a
mobile phone innovation earlier than others (e.g., Rogers, 1962), as they may not seem to
be open to changes and novelties. In contrast, cluster 3, the emotional adopters, are
consumers who are mostly interested in emotional experiences and emotional aspects of
buying a mobile phone as opposed to prestige and innovation. Managers should target this
group of consumers via the use of emotional cues in their communications campaigns to
signify the emotional connection between the mobile phone and the user.
Clusters 2 and 4, which comprise of consumers below 30 years of age, score
statistically higher on consumer innovativeness and they represent the prestige-seeking
emotional innovators and the prestige-seeking cognitive innovators. In line with previous
research (Hirschman, 1980; Midgley & Dowling, 1978; Rogers, 1962), these consumers
have a tendency to buy mobile phone innovations faster than others and they look for
novelty and prestige in their purchases of mobile phone innovations. They therefore
represent an important market segment for mobile phone managers who favor to promote
the prestige sense of new product. Between them, the two clusters differ in terms of their
need for emotion. The prestige-seeking emotional innovators in cluster 2 have a relatively
higher need for emotion in the domain of mobile phone purchases, whereas individuals in
cluster 4, the prestige seeking cognitive innovators, are more receptive to cognitive
information about mobile phones. A possible explanation might be that the cluster of
prestige-seeking cognitive innovators includes more men than women, although gender
does not statistically discriminate these clusters. Both clusters 2 and 4 have a relatively
higher level of prestige seeking in their purchases of mobile phones, compared to clusters
1 and 3. This prestige-seeking tendency that manifests in the domain of mobile phone
purchases is a result of goals of self-enhancement and social status (Steenkamp, et al.,
 Journal of Strategic Marketing 85

1999; Vigneron & Johnson, 1999) and indicates that mobile phone managers should target
such individuals with marketing communication campaigns that entail self-expression and
user image.

Conclusion and implications

The study explores consumer innovativeness, prestige price sensitivity, and need for
emotion as clustering variables to develop a taxonomy of mobile phone consumers and
provides exploratory insights into the usefulness of these constructs for market
segmentation, targeting, and promotion of innovations. Four distinct and interpretable
clusters emerge from the data analysis with statistically significant differences in terms of
consumer innovativeness, prestige price sensitivity, and need for emotion. Within the
constellation of mobile phone consumers in this study, interestingly, there are two clusters
(2 and 4), which have relatively higher level of innovativeness and prestige price
sensitivity, but at the same time differ between them in terms of their level of need for
emotion. These consumers in clusters 2 and 4, who comprise 35% of the sample, are
innovative consumers in the domain of mobile phone purchases and therefore are the most
desirable prospect customers for mobile phone companies. These consumers are interested
in the latest mobile phone innovations, they actively seek information (cognitive or
emotional) that pertains to mobile phones, and they are among the first to buy new
innovations of mobile phones in the market. However, they differ in terms of their need for
emotion which indicates that marketing managers should develop integrated
communication approaches to target these individuals, for example via a creative and
stimulating integration of both cognitive or rational and emotional appeals. Specifically,
apart from the factual, latest trends in the mobile phone market, marketing managers
should provide emotional cues such as celebrities, humor, and other emotional cues in
their marketing communication campaigns.

Limitations
This study is not free of limitations. First, as the cluster analysis emphasizes the within-
cluster homogeneity against between-cluster heterogeneity, and within the context of the
sample size of this paper, the findings represent an initial reference for further larger-scale
research that may produce larger groups/clusters. However, the findings somehow
demonstrate a common sense, where the majority of consumers are not likely to be highly
innovative and highly prestigious, but the minority are (clusters 2 and 4). Second, the
findings exist within the selected cluster variables of innovativeness, need for emotion,
and prestige price sensitivity. There are other emotion-related measures with different
context of research, therefore the findings should be treated and comprehended carefully
within their present context. Last, additional demographic variables could provide a more
complete profile of the consumer clusters.

Future research
In terms of future research, additional systematic research should examine the role of
prestige and emotion in purchases of innovation products given the implications in
segmentation, targeting, and positioning strategy. A possible research route would be to
compare the findings (the clusters) from the UK market to other countries to explore
similarities and discrepancies that are important for mobile phone marketers that operate
86 L. Aroean and N. Michaelidou

internationally. To get a more comprehensive picture of the mobile phone consumers,

particularly with young, dynamic consumers, another possible research direction is to
expand the cluster variable set, for example to include other relevant constructs such as
need for cognition, need for uniqueness, mavenism, and attitude toward mobile phone
services. Last, it is hopeful that the findings of this study will serve as and encourage
further advancement in technology innovation development and marketing study.

References
Allen, C. T., Machleit, K. A., Kleine, S. S., & Notani, A. S. (2005). A place for emotion in attitude
models. Journal of Business Research, 58, 494–499.
Allred, C. R., Smith, S. M., & Swinyard, W. R. (2006). E-shopping lovers and fearful conservatives:
A market segmentation analysis. International Journal of Retail & Distribution Management,
34, 308– 333.
Aroean, L. (2012). Friend or foe: In enjoying playfulness, do innovative consumers tend to switch
brand? Journal of Consumer Behaviour, 11, 67 – 80.
Athanassopoulos, A. D. (2000). Customer satisfaction cues to support market segmentation and
explain switching behavior. Journal of Business Research, 47, 191– 207.
Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of
the Academy of Marketing Science, 27, 184– 206.
Belk, R. W., Ger, G., & Askegaard, S. (2003). The fire of desire: A multisited inquiry into consumer
passion. Journal of Consumer Research, 30, 326–351.
Bojanic, D. (2007). Customer profile of the carryout segment for restaurants. International Journal
of Contemporary Hospitality Management, 19, 21 – 31.
Burns, D. J., & Krampf, R. F. (1991). A semiotic perspective on innovative behavior: Developments
in marketing science. 15th Annual Conference, Academy of Marketing Science, 14, 32 – 35.
Chircu, A. C., & Mahajan, V. (2009). Perspective: Revisiting the digital divide: An analysis of
mobile technology depth and service breadth in the BRIC countries. Journal of Product
Innovation Management, 26, 455– 466.
Clark, R. A., & Goldsmith, R. E. (2006). Interpersonal influence and consumer innovativeness.
International Journal of Consumer Studies, 30, 34 –43.
Datamonitor. (2011). Mobile phones in the UK (industry profile). London: Datamonitor Group.
Dickerson, M. D., & Gentry, J. W. (1983). Characteristics of adopters and non-adopters of home
computers. Journal of Consumer Research, 10, 225– 235.
Dickson, P. R., & Ginter, J. L. (1987). Market segmentation, product differentiation, and marketing
strategy. Journal of Marketing, 51, 1 – 10.
Digitalbuzz. (2012). Infographic: Mobile statistics, stats and facts 2011. Retrieved from March 9,
2012, from http://www.digitalbuzzblog.com/2011-mobile-statistics-stats-facts-marketing-
infographic/
Duhachek, A. (2004). Investigating links between consumption emotions and behaviour. Advances
in Consumer Research, 31, 666.
Everitt, B., Sabene, L., & Leese, M. (2001). Cluster analysis (4th ed.). London: Arnold.
Foxall, G. R. (1994). Consumer initiators: Adaptors and innovators. British Journal of Management,
5(s1), 3– 12.
Foxall, G. R. (1995). Cognitive styles of consumer initiators. Technovation, 15, 269– 288.
Foxall, G. R., & Bhate, S. (1993). Cognitive style and use-innovativeness for applications software
in home computing: Implications for new product strategy. Technovation, 13, 311– 323.
Gatignon, H., & Robertson, T. S. (1985). A propositional inventory for new diffusion research.
Journal of Consumer Research, 11, 849– 867.
Gatignon, H., & Robertson, T. S. (1991). Innovative decision process. In T. S. Robertson &
H. H. Kassarjian (Eds.), Handbook of consumer behaviour (pp. 316– 346). Englewood Cliffs,
NJ: Prentice Hall.
Goldenson, R. M. (1984). Longman dictionary of psychology and psychiatry. New York, NY:
Longman.
Goldsmith, R. E., Clark, R. A., & Goldsmith, E. B. (2006). Extending the psychological profile of
market mavenism. Journal of Consumer Behaviour, 5, 411– 419.
 Journal of Strategic Marketing 87

Goldsmith, R. E., d’Hauteville, F., & Flynn, L. R. (1998). Theory and measurement of consumer
innovativeness. European Journal of Marketing, 32, 340– 353.
Goldsmith, R. E., Freiden, J. B., & Eastman, J. K. (1995). The generality/specificity issue in
consumer innovativeness research. Technovation, 15, 601– 612.
Goldsmith, R. E., & Hofacker, C. (1991). Measuring consumer innovativeness. Journal of the
Academy of Marketing Science, 19, 209– 221.
Goldsmith, R. E., & Newell, S. J. (1997). Innovativeness and price sensitivity: Managerial,
theoretical and methodological issues. Journal of Product & Brand Management, 6, 63 – 174.
Google statistics. (2012). Percentage of population with mobile phones, Retrieved March 2012, from
http://www.google.com/publicdata/explore?ds¼n4ff2muj8bh2a_&ctype ¼ l&met_y¼ICTMOBIL
Hirschman, E. C. (1980). Innovativeness, novelty seeking and consumer creativity. Journal of
Consumer Research, 7, 283– 295.
Hoffman, D. L., Kopalle, P. K., & Novak, T. P. (2009). The “right” consumers for better concepts:
Identifying and using consumers high in emergent nature to further develop new product
concepts. Retrieved February 25, 2012, from http://forum.johnson.cornell.edu/faculty/kadiyali/
JMR%20emergent%20consumers.pdf
Im, S., Bayus, B. L., & Mason, C. H. (2003). An empirical study of innate consumer innovativeness,
personal characteristics, and new-product adoption behavior. Journal of the Academy of
Marketing Science, 31, 61 – 73.
Internet Advertising Bureau UK. (2012). 2010 mobile adspend figures. Retrieved March 10, 2012,
from http://www.iabuk.net/news/2010-mobile-adspend-figures
Joachimsthaler, E. A., & Lastovicka, J. L. (1984). Optimal stimulation level-exploratory behavior
models. Journal of Consumer Research, 11, 830– 835.
Kalba, K. (2008). The global adoption and diffusion of mobile phones. (Program on Information
Resources Policy). Cambridge, MA: Center for Information Policy Research, Harvard
University.
Ketchen, D. J., & Shook, C. (1996). The application of cluster analysis in strategic management
research: An analysis and critique. Strategic Management Journal, 17, 441– 458.
Kimiloglu, H., Nasir, A. V., & Nasir, S. (2010). Discovering behavioral segments in the mobile
phone market. Journal of Consumer Marketing, 27, 401– 413.
Klink, R. R., & Athaide, G. A. (2010). Consumer innovativeness and the use of new versus extended
brand names for new products. Journal of Product Innovation Management, 27, 23 – 32.
Larsen, R. J., Diener, E., & Emmons, R. A. (1986). Affect intensity and reactions to daily life events.
Journal of Personality and Social Psychology, 51, 803– 814.
Laskey, H. A., Day, E., & Crask, M. R. (1989). Typology of main message strategies for television
commercials. Journal of Advertising, 18, 36 – 41.
Lee, L., Amir, O., & Ariely, D. (2009). In search of homo economicus: Cognitive noise and the role
of emotion in preference consistency. Journal of Consumer Research, 36, 173– 187.
Lee, J., Lee, J., & Feick, L. (2001). The impact of switching costs on the customer satisfaction-
loyalty link: Mobile phone service in France. Journal of Services Marketing, 15, 35 – 48.
Lichtenstein, D. R., Ridgway, N. M., & Netemeyer, R. G. (1993). Price perceptions and consumer
shopping behavior: A field study. Journal of Marketing Research, 30, 234– 245.
López-Nicolás, C., Molina-Castillo, F. J., & Bouwman, H. (2008). An assessment of advanced
mobile services acceptance: Contributions from TAM and diffusion theory models. Information
& Management, 45, 359– 364.
Machauer, A., & Morgner, S. (2001). Segmentation of bank customers by expected benefits and
attitudes. International Journal of Bank Marketing, 19, 6 – 18.
Manning, K. C., Bearden, W. O., & Madden, T. J. (1995). Consumer innovativeness and the adoption
process. Journal of Consumer Psychology, 4, 329– 345.
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA:
MIT Press.
Michaelidou, N. (2011). A typology of consumers’ disposition based on inherent needs. Journal of
Marketing Management, 28, 676– 694.
Midgley, D. F. (1977). Innovation and new product marketing. Londra: Croom Helm.
Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal
of Consumer Research, 4, 229– 242.
Mudd, S. (1990). The place of innovativeness in models of the adoption process: An integrative
review. Technovation, 10, 119– 136.
88 L. Aroean and N. Michaelidou

Netemeyer, R. G., Burton, S., & Lichtenstein, D. R. (1995). Trait aspects of vanity: Measurement
and relevance to consumer behavior. Journal of Consumer Research, 21, 612– 626.
O’Connor, P. J., & Sullivan, G. L. (1995). Market segmentation: A comparison of benefits/attributes
desired and brand preference. Psychology & Marketing, 12, 613– 636.
Ofcom. (2011). The communications market 2011. Retrieved February 15, 2012, from http://
stakeholders.ofcom.org.uk/binaries/research/cmr/cmr11/UK_CMR_2011_FINAL.pdf
Okazaki, S. (2006). What do we know about mobile internet adopters? A cluster analysis.
Information & Management, 43, 127– 141.
O’Neill, R. M., & Lambert, D. R. (2001). The emotional side of price. Psychology & Marketing, 18,
217– 237.
O’Regan, M., Kalidas, A., Maksimova, O., & Reshetin, O. (2011). Optimizing market segmentation
for a global mobile phone provider for both targeting and insight. Journal of Advertising
Research, 51, 571– 577.
Park, J. E., Yu, J., & Zhou, J. X. (2010). Consumer innovativeness and shopping styles. Journal of
Consumer Marketing, 27, 437– 446.
Penz, E., & Hogg, M. K. (2011). The role of mixed emotions in consumer behavior: Investigating
ambivalence in consumers’ experiences of approach-avoidance conflicts in online and offline
settings. European Journal of Marketing, 45, 104–132.
Punj, G., & Stewart, D. W. (1983). Cluster analysis in marketing research: Review and suggestions
for application. Journal of Marketing Research, 20(May), 134–148.
Raju, P. S. (1980). Optimum stimulation level: Its relationship to personality, demographics, and
exploratory behavior. Journal of Consumer Research, 7, 272– 282.
Raman, N. V., Chattopadhyay, P., & Hoyer, W. (1995). Do consumers seek emotional situations:
The need for emotion scale. Advances in Consumer Research, 22, 537– 542.
Richins, M. L. (1997). Measuring emotions in the consumption experience. Journal of Consumer
Research, 24, 127– 146.
Ridgway, N. M., & Price, L. L. (1994). Exploration in product usage: A model of use innovativeness.
Psychology & Marketing, 11, 69 – 84.
Roehm, H. A. Jr., & Roehm, M. L. (2005). Revisiting the effect of positive mood on variety seeking.
Journal of Consumer Research, 32, 330– 336.
Roehrich, G. (2004). Consumer innovativeness: Concepts and measurements. Journal of Business
Research, 57, 671– 677.
Rogers, E. M. (1962). Diffusion of innovations. New York, NY: The Free Press.
Rohm, A. J., & Swaminathan, V. (2004). A typology of online shoppers based on shopping
motivations. Journal of Business Research, 57, 748– 757.
Saaksjarvi, M. (2003). Consumer adoption of technological innovations. European Journal of
Innovation Management, 6, 90 – 100.
Scherer, K. R. (2005). What are emotions? And how can they be measured. Social Science
Information, 44, 695– 729.
Schwartz, S. H. (1992). Universals in the content and structure of values: Theoretical advances and
empirical tests in 20 countries. In M. P. Zanna (Ed.), Advances in experimental psychology (vol.
25, pp. 1 – 65). New York: Academic Press.
Schwartz, S. H., & Sagiv, L. (1995). Identifying culture-specifics in the content and structure of
values. Journal of Cross-Cultural Psychology, 26, 92 – 116.
Sethi, R., Smith, D. C., & Park, C. W. (2001). Cross-functional product development teams,
creativity and the innovativeness of new consumer products. Journal of Marketing Research, 38,
73 – 85.
Shani, A., Wang, Y., Hutchinson, J., & Lai, F. (2010). Applying expenditure-based segmentation on
special-interest tourists: The case of golf travelers. Journal of Travel Research, 49, 337– 350.
Sharma, A., & Lambert, D. M. (1994). Segmentation of markets based on customer service.
International Journal of Physical Distribution & Logistics Management, 24, 50 – 58.
Shoham, A., & Ruvio, A. (2008). Opinion leaders and followers: A replication and extension.
Psychology and Marketing, 25, 280– 297.
Simonson, I., & Nowlis, S. M. (2000). The role of explanations and need for uniqueness in consumer
decision making: Unconventional choices based on reasons. (Research Paper No. 1610).
Stanford, CA: Graduate School of Business, Stanford University. Retrieved February 25, 2012,
from https://gsbapps.stanford.edu/researchpapers/library/rp1610.pdf
 Journal of Strategic Marketing 89

Steenkamp, J. -B. E. M., Hofstede, F., & Wedel, M. (1999). A cross-national investigation into the
individual and national cultural antecedents of consumer innovativeness. Journal of Marketing,
63, 55 – 69.
Turnbull, P. W., Leek, S., & Ying, G. (2000). Customer confusion: The mobile phone market.
Journal of Marketing Management, 16, 143– 163.
Vandecasteele, B., & Geuens, M. (2010). Motivated consumer innovativeness: Concept,
measurement, and validation. International Journal of Research in Marketing, 27, 308– 318.
Vanhamme, J., & Lindgreen, A. (2001). Gotcha! Findings from an exploratory investigation on the
dangers of using deceptive practices in the mail-order business. Psychology & Marketing, 18,
785– 810.
Venkataraman, M. P. (1991). The impact of innovativeness and innovation type of adoption. Journal
of Retailing, 67, 51 – 67.
Venkataraman, M. P., & Price, L. L. (1990). Differentiating between cognitive and sensory
innovativeness: Concepts, measurements and implications. Journal of Business Research, 20,
239– 315.
Venkatesan, M. (1973). Cognitive consistency and novelty seeking. In S. Ward & T. S. Robertson
(Eds.), Consumer behavior – theoretical sources (pp. 355– 384). Englewood Cliffs, NJ: Prentice
Hall.
Vigneron, F., & Johnson, L. W. (1999). A review and a conceptual framework of prestige-seeking
consumer behavior. Academy of Marketing Science Review, 1, 1 – 14.
Wahlers, R. G., Dunn, M. G., & Etzel, M. J. (1986). The congruence of alternative OSL measures
with consumer exploratory behaviour tendencies. Advances in Consumer Research, 13,
398– 402.
Wedel, M., & Kamakura, W. A. (1999). Market segmentation: Conceptual and methodological
foundations (2nd ed.). Boston, MA: Kluwer Academic.
Westbrook, R. A., & Oliver, R. A. (1991). The dimensionality of consumption emotion patterns and
consumer satisfaction. Journal of Consumer Research, 18, 84 – 91.
Wooder, S., & Baker, S. (2012). Extracting key lessons in service innovation. Journal of Product
Innovation Management, 29, 13 – 20.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and
synthesis of evidence. Journal of Marketing, 52, 2 – 22.