Creating a written outline for a workshop based on communications theories

Pre-Work Activity:

– asks the audience questions like

A. Do you and your friends follow the same influencers and content creators on social media platforms? Example: Instagram, Tik Tok, YouTube.

B. How much time do you and your friends spend while watching the influencers/content creators on social media?

https://www.communicationstudies.com/communication…

  Available online at www.sciencedirect.com
Journal of Interactive Marketing 26 (2012) 198 – 208
www.elsevier.com/locate/intmar
Social Media Peer Communication and Impacts on Purchase Intentions:
A Consumer Socialization Framework
Xia Wang a,⁎ & Chunling Yu b & Yujie Wei c
a
Department of Marketing, Renmin University, Beijing, China
Department of Marketing, Tsinghua University, Beijing, China
c
Department of Marketing & Real Estate, Richard College of Business, The University of West Georgia, GA, USA
b
Available online 27 April 2012
Abstract
Consumer socialization through peer communication using social media websites has become an important marketing issue through the development and increasing popularity of social media. Guided by a socialization framework, this article investigates peer communication through social media
websites; individual-level tie strength and group-level identification with the peer group as antecedents; and product attitudes and purchase decisions as
outcomes. Survey data from 292 participants who engaged in peer communications about products through social media confirm that the two
antecedents have positive influences on peer communication outcomes. Online consumer socialization through peer communication also affects
purchasing decisions in two ways: directly (conformity with peers) and indirectly by reinforcing product involvement. In addition, consumer’s
need for uniqueness has a moderating effect on the influence of peer communication on product attitudes. These findings have significant theoretical and managerial implications.
© 2012 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved.
Keywords: Peer communication; Online socialization; Social media; Product attitude; Purchase intention
Introduction
The Internet and especially social media have changed how
consumers and marketers communicate (Hennig-Thurau et al.
2004; Nambisan and Baron 2007). Social media websites attract millions of users, many of whom integrate the sites into
their daily lives and business practices (Lueg et al. 2006;
Muratore 2008; Okazaki 2009). Moreover, social media allow
users to connect with peers by adding them to networks of
friends, which facilitates communication, particularly among
peer groups (Ahuja and Galvin 2003; Zhang and Daugherty
2009). The resulting new, unconventional channel for consumer
socialization through the Internet is changing consumer behavior
(Lueg et al. 2006; Muratore 2008; Okazaki 2009).
⁎ Corresponding author at: Department of Marketing, School of Business,
Renmin University of China, 59 Zhong Guan Cun Rd., Beijing 100872, China.
E-mail addresses: wangxia@ruc.edu.cn (X. Wang),
yuchl@sem.tsinghua.edu.cn (C. Yu), jwei@westga.edu (Y. Wei).
The change prompted by the emergence of social media also
applies to the consumer decision making process and marketing
communications (Hennig-Thurau et al. 2011; Shankar and
Malthouse 2007). For example, social media websites provide
a public forum that gives individual consumers their own
voices, as well as access to product information that facilitates
their purchase decisions (Kozinets et al. 2010). Usergenerated online product reviews have proliferated through social media, with great impact on marketing (e.g., HennigThurau et al. 2004; Trusov, Bodapati, and Bucklin 2010).
Such communal word-of-mouth (WOM) not only increases
marketing messages but also alters consumer information processing (Casteleyn, Mottart, and Rutten 2009; Kozinets et al.
2010). In particular, peer communication through social
media, a new form of consumer socialization, has profound impacts on consumer decision making and thus marketing strategies (Casteleyn, Mottart, and Rutten 2009; Okazaki 2009).
Consumer socialization refers to the process by which individual consumers learn skills, knowledge, and attitudes from
others through communication, which then assist them in
1094-9968/$ -see front matter © 2012 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved.
doi:10.1016/j.intmar.2011.11.004
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
functioning as consumers in the marketplace (Ward 1974).
Conventional socialization occurs among consumers who
know one another, such as parents and children, colleagues, relatives, friends, and neighbors (e.g., Kim, Lee, and Tomiuk 2009;
Moschis and Moore 1984; Mukhopadhyay and Yeung 2010).
However, online social media enable socialization through virtual
communities among both people who know one another and
strangers (Lueg et al. 2006; Muratore 2008; Okazaki 2009). Although peers are widely acknowledged as key forces affecting
consumer socialization (e.g., Moschis and Churchill 1978), peer
communication in online socialization processes has received
limited research attention (Ahuja and Galvin 2003). Particularly,
the influence of peer communication through social media websites on consumers’ purchase decisions rarely has been investigated (Iyengar, Han, and Gupta 2009; Trusov, Bodapati, and
Bucklin 2010). To fill this gap, we investigate consumptionrelated peer communication through social media and its impacts
on consumers’ product attitudes and purchase intentions, from a
consumer socialization perspective.
Peer communication initially was defined as overt peer interactions among adolescents, focused on goods and services
(Moschis and Churchill 1978). In social media, such peer communication entails interactions about products/services among
individual consumers through computer-aided social networks
(Dhar and Chang 2009), also referred to as virtual communities
of consumption (Kozinets 1999). We use the term “peers” to
capture “the richness of this interpersonal communication construct” in an online context (Lueg and Finney 2007, p 29). Thus
our focus is on how an individual becomes socialized through
positive interactions on a social media website to use some
product/service. Hereafter, we refer simply to peer communication, instead of consumption-related peer communication on
social media.
By investigating the influence of peer communication on
consumer behavior, this research contributes to existing literature in three ways. First, the results can help scholars and interactive marketing practitioners understand the role of social
media for consumer behavior and marketing. Second, we investigate the influence of preselected antecedents of peer communication and outcomes of the consumer socialization process,
which can expand the application scope of socialization theory
to an online setting and provide theoretical implications for
scholars. Third, by testing the moderating effect of consumer
characteristics, such as need for uniqueness, we provide insights into how consumer characteristics might strengthen or
weaken the influence of peer communication on consumer behavior through social media.
Theoretical Background
Consumer Socialization through Social Media
Consumer socialization theory predicts that communication
among consumers affects their cognitive, affective, and behavioral attitudes (Ward 1974). Through socialization, consumers learn
consumption-related skills, knowledge, and attitudes in the marketplace. The widely applied socialization framework delineates
199
consumer learning processes and how people perform their
roles as consumers in society (e.g., Churchill and Moschis
1979; De Gregorio and Sung 2010; Moschis and Churchill 1978).
Consumer socialization theory also offers two theoretical
perspectives for understanding and predicting consumer-toconsumer information transmission: a cognitive development
model and social learning theory (Moschis and Churchill
1978). The former, focused on cognitive/psychological processes regards socialization as a function of qualitative stages
in cognitive development which occur between infancy and
adulthood (Kim, Lee, and Tomiuk 2009). The latter instead emphasizes external, environmental sources of learning, or “socialization agents” (peers), which transmit norms, attitudes,
motivations, and behaviors to learners (Köhler et al. 2011;
Moschis and Moore 1984; Shim 1996). This perspective has
been adopted to explain consumer socialization processes
among adult populations, particularly among non-family members (e.g., Ahuja and Galvin 2003; De Gregorio and Sung
2010; Taylor, Lewin, and Strutton 2011). For example, De
Gregorio and Sung (2010) find that adult consumers’
placement-related attitudes and behaviors always are subject
to the influence of circles of friends and acquaintances; they
also show that peer communication is the strongest predictor
of product placement attitudes and behaviors.
Social media, especially social network sites, provide a virtual space for people to communicate through the Internet,
which also might be an important agent of consumer socialization (Köhler et al. 2011; Lueg and Finney 2007; Lueg et al.
2006; Muratore 2008; Zhang and Daugherty 2009). Social
media provide three conditions that encourage consumer socialization among peers online. First, blogs, instant messaging, and
social networking sites all provide communication tools that
make the socialization process easy and convenient (Muratore
2008). For example, in virtual communities Ahuja and Galvin
(2003) find that new members can be socialized easily into virtual groups through electronic communication and quickly
learn task-related knowledge and skills through their interactions with other members. Second, increasing numbers of consumers visit social media websites to communicate with others
and find information to help them make various consumptionrelated decisions (Lueg et al. 2006). Third, social media facilitate education and information because they feature multitudes
of friends or peers who act as socialization agents and provide
vast product information and evaluations quickly (Gershoff
and Johar 2006; Taylor, Lewin, and Strutton 2011). Drawing
on the consumer socialization framework, Taylor, Lewin, and
Strutton (2011) find that online consumers’ attitudes toward social network advertising depend greatly on socialization factors
(i.e., peers). Lueg and Finney (2007) further reveal that peer
communications online can influence consumers so strongly
that they convert others into Internet shoppers. They suggest retailers should encourage such communication by setting up tella-friend functions on websites.
On the basis of socialization theory and this previous research, we thus establish a model of consumer socialization
through social media to explain consumer social learning processes through peer communication and the outcomes of these
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X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
processes (Fig. 1). The main elements of the model consist of
antecedents, socialization agents, socialization processes, and
outcomes (De Gregorio and Sung 2010; Moschis and
Churchill 1978).
Socialization Agent: Peers
Interactions with peers are fundamental human acts, arising
from psycho-physiological and sociological need gratification
(Ward 1974). Consumer socialization literature indicates that
peers are the primary socialization agents, beyond family members (Köhler et al. 2011; Moschis and Churchill 1978; Shim
1996). Consumers tend to interact with peers about consumption matters, which greatly influence their attitudes toward
products and services (Churchill and Moschis 1979;
Mukhopadhyay and Yeung 2010). The influence of reference
group peers on consumer behavior also has been well documented (e.g., Bearden and Rose 1990). Previous research consistently has shown that peer communication has a strong
impact on attitudes toward advertising (De Gregorio and Sung
2010), shopping orientations (Lueg et al. 2006; Mangleburg,
Doney, and Bristol 2004), and consumer decision-making
(Shim 1996; Smith, Menon, and Sivakumar 2005). For example, more frequent communication with peers about consumption matters leads to stronger social consumption motivations
(Moschis and Moore 1984; Shim 1996). Agent–learner communication patterns, such as the level of interpersonal communication, also affect various consumer behaviors (e.g., De
Gregorio and Sung 2010). In line with socialization theory,
we argue that peers act as socialization agents through social
media and that newcomers are influenced by peers through
communication, as a result of a social learning process.
Peer Communication as a Social Learning Process
Socialization theory suggests that a consumer develops
consumption-related attitudes and behaviors by learning from
socialization agents, through interactions with them (Churchill
and Moschis 1979; Lueg and Finney 2007). Consumers learn
values, attitudes, and skills by observing others or various
media, including social media. The process can take three
forms: modeling, reinforcement, or social interaction. Each represents a different mechanism by which the individual is socialized
to adopt particular behaviors or intentions (Moschis and Churchill
1978). In the modeling process, a mechanism of imitating or
mimicking the socialization agent exists because the agent’s behavior appears meaningful or desirable to the learner (Moschis
and Churchill 1978). A reinforcement process implies that the
learner is motivated to adopt (or not) some behaviors or intentions
because of a reward (or punishment) offered by the socialization
agent. This reward reinforcement can be delivered via written
communication and social media. Finally, the social interaction
mechanism involves interactions with socialization agents in social contexts, which may combine modeling and reinforcement
(Moschis and Churchill 1978).
In a social media setting, the consumer learns attitudes and
purchase behaviors through written messages that peers send
(i.e., peer communication). Previous research indicates that
learning processes through social media involve modeling, reinforcement, and social interaction mechanisms simultaneously
(e.g., Lueg and Finney 2007). Peers’ ownership of a certain
product or service constitutes a modeling process; to be like
peers, the consumer can buy the same brand or avoid other
brands (Lueg and Finney 2007). The potential for peer pressure
also motivates the focal consumer to like or purchase the product,
which can prompt rewards (e.g., more intimate relationships)
Fig. 1. Consumer socialization framework through social media.
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
from peers, whereas a lack of purchase can lead to punishment
(e.g., exclusion from the group). For this learning process, peers
exert influences in written messages, such as positive and negative reviews, comments, suggestions, discussions, or experiences.
In summary, in the course of the ongoing peer communication
process, a consumer becomes socialized to adopt some product
that is new to him or her; peers (socialization agents) also provide
models to be matched, rewards to be pursued, and punishment to
be avoided.
Consumer Socialization Outcomes: Involvement, Attitude, and
Purchase Intention
Peer communication is associated with learning about consumption, such as brand preferences, involvement, or purchase
intentions. Consumer behaviors or attitudes tend to result from
learning acquired through interactions between the consumer
and socialization agents. Involvement, a psychological construct
that occurs during a buyer’s decision-making process, refers to
the perceived relevance of an object, based on the consumer’s
needs, values, or interests (Zaichkowsky 1985). Consumer involvement with products motivates reactions to marketing and
advertising stimuli, such that high involvement consumers are
more interested in and more likely to purchase a product
(Karmarkar and Tormala 2010; Kim, Haley, and Koo 2009).
Interpersonal influence research also identifies two forms of
peer influence: normative and informational (Bearden,
Netemeyer, and Teel 1989). We believe they intertwine with
peer communication and produce different outcomes. Normative
influences push people who choose to be affiliated to some social
group to conform with group norms and modify their attitudes
and behaviors based on peers’ expectations (Bearden,
Netemeyer, and Teel 1989). Conformance thus emerges in social
media and other online communities (e.g., De Bruyn and Lilien
2008; Iyengar, Han, and Gupta 2009; Trusov, Bodapati, and
Bucklin 2010). Members of a social networking group face conformity pressures when they make purchase decisions. Informational influences instead drive people to learn about some
product/service by seeking information from peers. They might
search for information from knowledgeable peers or learn by observing others’ behavior. Informational influences thus affect
consumer decision processes and product evaluations. Social
media provide a new channel to acquire product information
through peer communication, from many peers or third parties
(Kozinets 1999) at a very low or no cost.
In turn, we propose that through peer communication, socialization agents influence newcomers both directly and indirectly.
The direct influence stems from the normative influence manifested by conformity with peers (agents); the indirect influence
moves from the informational influence through product involvement. When newcomers face normative pressures, they conform
with group norms by exhibiting like or dislike for some product
or services (Trusov, Bodapati, and Bucklin 2010). When newcomers are under an informational influence, they instead rely
on what they have learned or observed from peers (agents) to
determine their product involvement, which ultimately may
affect their attitudes toward the product or purchase decisions
201
(Lord, Lee, and Choong 2001; Lueg et al. 2006). With more
information obtained from agents, newcomers become more
interested in a product, as well as more eager to learn about it
(Franke, Keinz, and Steger 2009). High involvement newcomers
thus are more likely to show positive attitudes toward the product
(Kim, Haley, and Koo 2009) and purchase it than are those with
low involvement (Martin and Stewart 2000; Zaichkowsky 1985).
Therefore, we suggest:
H1. Product attitude is positively associated with purchase
intention.
H2. Consumption-related peer communication on social media
is positively associated with product attitude.
H3. Consumption-related peer communication on social media
is positively associated with product involvement.
H4. Product involvement is positively associated with product
attitude.
Consumer Socialization Antecedents: Tie Strength and
Identification with the Peer Group
The social setting in which learning takes place is particularly important for explaining learning processes, which can directly and indirectly affect learning (Moschis and Churchill
1978). Consumer socialization is a product of several antecedent
variables, including social class, gender, and family size (e.g., De
Gregorio and Sung 2010; Shim 1996). Relationships (networks)
built through social media also may have strong influences on
communication with peers (Kozinets 1999; Okazaki 2009;
Zhang and Daughety 2009). In line with prior literature, we suggest that peer communication through social media depends on
tie strength with peers and identification with the peer group.
Tie Strength with Peers. We define tie strength with peers as
to the degree to which a person is willing to maintain some relationship with peers through some social media. The relationship may be very close, such as dear friends, or very casual,
such as with acquaintances or strangers. Tie strength offers significant explanatory power regarding the influence of WOM
communications (Brown, Broderick, and Lee 2007; De Bruyn
and Lilien 2008). Strong ties are more likely to transfer useful
knowledge (Levin and Cross 2004) and thus have more influence on receivers than do weak ties (De Bruyn and Lilien
2008; Smith, Menon, and Sivakumar 2005). We therefore propose that in the context of social media, a strong tie between an
individual and his or her peers is more likely to lead to communication about a product than is a weak tie.
H5. Tie strength with peers is positively associated with peer
communication.
Identification with the Peer Group. Identification with the
peer group refers to the conception of the self, in terms of
“the defining features of a self-inclusive social category that
renders self stereotypically interchangeable with other ingroup members” (Hogg 1992, p 90). Identification with the
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X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
group is a key determinant of virtual community participation
(Dholakia, Bagozzi, and Pearo 2004), such that when identification with a group has been established, the person develops
we-intentions and wants to maintain a positive, self-defining relationship with the group (Bagozzi and Dholakia 2002), places
greater value on relationships with the community (Nambisan
and Baron 2007), and is willing to engage in community activities (Algesheimer, Dholakia, and Herrmann 2005).
Moreover, the tie between an individual and peers precedes
and contributes to his or her identification with the peer group
(Algesheimer, Dholakia, and Herrmann 2005). Therefore, a
harmonious relationship with peers should lead consumers to
seek out and interact with other similar members of the group
(Algesheimer, Dholakia, and Herrmann 2005). Thus we predict:
H6. Identification with the peer group is positively associated
with peer communication.
H7. Tie strength with peers is positively associated with identification with the peer group.
Moderating Role of Need for Uniqueness
Marketing literature demonstrates that consumer product
preferences always depend on need for uniqueness (e.g.,
Irmak, Vallen, and Sen 2010; Tian, Bearden, and Hunter
2001). The social influence of other members of a community
affects an individual’s decisions because of that individual’s
concern about the impressions his or her behavior gives other
people (Amaldoss and Jain 2005). Consumer’s need for uniqueness also affects willingness to generate WOM (Cheema and
Kaikati 2010) or comply with others’ preferences (Irmak,
Vallen, and Sen 2010).
We propose that the impact of peer communication on product
attitude should be moderated by consumer’s need for uniqueness.
In the consumer socialization process, need for uniqueness has a
significant moderating effect on consumer evaluations; when
others serve as a reference point, high-uniqueness consumers
are less likely to be influenced by those others’ opinions or purchase the product than low-uniqueness consumers (Irmak,
Vallen, and Sen 2010). The former also are less willing to conform and less likely to be affected by peer communication. As
Tian, Bearden, and Hunter (2001) show, among high uniqueness
consumers, peer reviews or recommendations even can activate
“counterconformity motivations” if they sense a threat to their
identity, such as when they think others are too similar to them.
Thus, we propose:
H8. Need for uniqueness moderates the association between peer
communication and product attitude: High (versus low) uniqueness consumers are less likely to conform to peers’ influence.
Method
Sample
The data collection focused on Chinese consumers who are
frequent users of social media websites. In recent years, the
number of Internet users has increased dramatically in China;
recent predictions suggest that the number of social network
users also will more than double from 207 million in 2010 to
488 million in 2015 (Emarketer Report 2011). New online network websites appear every day, and Chinese enterprises have
taken advantage of this technological trend to promote products
and brands to various social media users (Harrison and Hedley
2011). To find the most frequent users of social media websites,
we chose the largest Internet portal, www.sina.com, to collect
our data. The website serves more than 95.3% of the Internet
users in China. With the permission from the website, we
built a link on its front page to our online survey. When participants clicked the link, they were directed to an invitation and instructions page. A screening question excluded unqualified
participants who had never used any social media websites:
“Did you visit one of the listed social network websites in the
past six months to acquire information on some products, services, or activities you were interested in?” Those who clicked
“yes” were invited to continue the survey; those who chose
“no” were told to stop. The listed social media websites included
QQpengyou, Renren.com, Kaixin.com, and 51.com because
these websites are among the most frequently used by Chinese
consumers (China Internet Network Center Report 2009)—
similar to Facebook in the United States. Participants who
completed the survey had a chance to win a laptop as an
incentive.
The survey did not ask participants to specify the products,
services, or activities they had communicated about on social
media; instead, our focus centered on the peer communication
process. We also did not examine the agent–learner interactions
in reference to the type of learning (e.g., modeling, reinforcement) because a cross-sectional design is not suitable for studying the processes, though it facilitates an investigation of the
extent of agent–learner interactions (Moschis and Churchill
1978).
To specify the peer communication, each participant indicated
a website on which he/she engaged in peer communication; the
members with whom they had communicated; topics that they
had communicated about with those peers; the types of their relationships with the peers (e.g., friends, strangers) and the importance of those relationships to them; frequencies with which
they communicated with peers; and the extent to which they
were affected by the communications. Other questions pertained
to surfing behavior on social media websites and demographics,
such as age, gender, income, and education. After completing
the survey, participants provided additional personal information
for the prize drawing.
Data
The data were collected in December 2010, over a period of
approximately three weeks. A total of 935 participants clicked
the survey link, and 421 of them passed the screening question
and took the survey. To clean the data, we removed incomplete
responses or responses submitted from the same computer Internet protocols, leaving a usable sample of 292 questionnaires
for the analysis. Approximately 33.9% of participants were
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
frequent users of the social media website QQPengyou and
sought product information through interactions with the peer
members; 29.5% had used Renren.com; 17.8% used Kaixin.
com; and approximately 18.9% of the participants had used
51.com or other social media websites. Among the complete
and usable responses, 61% of the participants were men. The
average age of the respondents was 29.5 years. Most (85.6%)
had college degrees, and about 70.8% of the participants
reported a monthly income of less than 5000 Yuan (RMB). Regarding social media website usage, approximately 15.5% of
the participants spent more than 3 h on their chosen social
media website per day, 11.9% spent 2–3 h per day, 43.3%
spent 1–2 h per day, and 29.2% spent less than an hour per
day. The demographic characteristics of the sample thus indicated
a higher level of education and younger respondents, relative to
the total population of China, but they were consistent with social
media users in the country (i.e., 52.9% men, 52.6% between 20
and 29 years of age, 59.1% with college degrees; China Internet
Network Center Report 2009).
Measure Development
We adopted the construct items from published articles, with
some minor changes to accommodate the social media context
of our research. We measured the exogenous variable, tie
strength with peers, using four items adapted from the validated
scale proposed by De Bruyn and Lilien (2008). Identification
with the peer group was measured with five items adapted
from the scale for measuring community identification by
Algesheimer, Dholakia, and Herrmann (2005). We also used
adaptations of existing measures for peer communication
(Moschis and Churchill 1978), product involvement
(Zaichkowsky 1985), product attitudes (Crites, Fabrigar, and
Petty 1994), and purchase intentions (Taylor, Houlahan, and
Gabriel 1975). The moderating variable, consumer’s need for
uniqueness, was measured using a scale adapted from Tian,
Bearden, and Hunter (2001). The items were scored on sevenpoint Likert scales, ranging from strongly disagree (1) to
strongly agree (7), except for the measure of tie strength with
peers, which ranged from very unlikely (1) to very likely (7).
The questionnaire was first drafted in English and then translated
into Chinese using a translation and back-translation procedure
(Myers et al. 2000). Table 1 contains the final pool of items and
their reliability values.
The confirmatory factor analysis for the measurement
models relied on LISREL 8.80 (Jöreskog and Sörbom 1996),
which can deal with a wide variety of models to analyze latent
variables (Anderson and Gerbing 1988). We investigated the
measurement model, incorporating all study constructs. The results (Table 1) reveal a satisfactory fit (Chi-square = 734.66,
df = 329, non-normed fit index [NNFI] = .97, confirmatory fit
index [CFI] = .98, incremental fit index [IFI] = .98, root mean
square error of approximation [RMSEA] = .065). The overall
fit was acceptable, and all relevant loadings were substantial
and highly significant. Moreover, construct reliability values
exceeded the recommended threshold of .60 (Bagozzi and Yi
1988). Construct reliability ranged from .84 for need for
203
Table 1
Item statistics and measurement model results.
Loading Construct Average
reliability variance
extracted
Tie strength with peers
How likely would you share personal
confidences with your peers?
How likely would you spend some free
time socializing with your peers?
How likely would you perform a large
favor for your peers?
How likely would your peers perform a
large favor for you?
Identification with the peer group
I am very attached to the peer group on
social media.
My peers on social media and I share the
same objectives.
The friendships I have with my peers mean
a lot to me.
If my peers planned something, I’d think of it
as something “we” would do rather than
“they” would do.
I see myself as a part of the peer group on
social media.
0.85
0.94
0.80
0.93
0.72
0.92
0.70
0.90
0.91
0.91
0.86
0.81
0.90
0.82
0.86
Peer communication
I talked with my peers about the product on
social media.
I talked with my peers about buying the
product on the Internet.
I asked my peers for advice about
the product.
I obtained the product information from
my peers.
My peers encouraged me to buy the product.
0.81
Product attitude
Dislike–like
Bad–good
Undesirable–desirable
0.91
0.92
0.93
0.95
0.85
Purchase intention
Unlikely–likely
Uncertain–certain,
Definitely not–definitely
0.88
0.86
0.91
0.92
0.79
Product involvement
Uninterested–interested
Not involved–highly involved
Of no concern–of concern to me
Unimportant–important
Irrelevant–relevant
0.87
0.92
0.93
0.91
0.83
0.95
0.80
0.84
0.63
0.87
0.90
0.87
0.74
Need for uniqueness
I actively seek to develop my personal
0.83
uniqueness by buying special products
or brands.
The products and brands that I like best
0.86
are the ones that express my individuality.
I have often violated the understood rules
0.68
of my social group regarding what to buy
or own.
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X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
uniqueness to .95 for product involvement and product attitude.
We assessed discriminant validity by comparing the average
variance extracted (AVE) values with the squared correlation
between each pair of constructs and constructing 95% confidence intervals around the inter-construct correlations (Fornell
and Larcker 1981). In support of discriminant validity, the
AVE for each construct exceeded the squared correlation between the construct and any other construct; in addition, the
AVE for each latent construct exceeded the .50 threshold, ranging
from .63 to .85, and the item factor loadings for the latent constructs all were greater than .6. Therefore, the scale items provided
a good representation of the constructs. The correlation matrix of
latent variables is in Table 2.
Results
We used LISREL 8.80 software with maximum likelihood
estimation to test the hypothesized relationships. Tie strength
with peers provided an exogenous variable; the other constructs
were endogenous variables. According to the existing thresholds
(e.g., Hu and Bentler 1999), the model exhibits good fit to the
data (Chi-square = 674.20, df= 268, NNFI = .97, CFI = .98,
IFI = .98, RMSEA = .072), as the results in Table 3 show.
All the hypotheses were supported (p b .01). Regarding the
main effects, peer communication affected product attitudes,
which in turn enhanced purchase intentions (H1). Furthermore,
both the direct effect of normative impact (conformity with
peers) (H2) and the indirect effect of informational impact
through product involvement (H3 and H4) were confirmed in
their direct (β = .26, p b .01) and indirect (β = .31, p b .01) effects
on product attitudes. We also found a significant indirect effect
of peer communication on purchase intention (β = .45, p b .01).
The analyses of the antecedents revealed that tie strength
with peers and identification with the peer group had positive
influences on peer communication (H5 and H6). Tie strength
also related positively to identification with the peer group
(H7).
Table 3
Structural equation modeling results for hypotheses.
Hypothesized effect
Standardized tpConclusion
coefficient
Value Value
H1: Product attitude →purchase
intention
H2: Peer communication→ product
attitude
H3: Peer communication→ product
involvement
H4: Product involvement → purchase
intention
H5: Tie strength with
peers→peer communication
H6: Identification with the peer
group →peer communication
H7: Tie strength with
peers→identification with
the peer group
0.79
15.43 b0.01 Supported
0.26
2.61 b0.01 Supported
0.82
15.28 b0.01 Supported
0.38
3.88 b0.01 Supported
0.44
5.76 b0.01 Supported
0.26
3.50 b0.01 Supported
0.70
12.21 b0.01 Supported
and product attitude. To test this moderating effect, we first divided the participants into two subgroups, according to their
scores on the need for uniqueness scale, using cluster analysis
approach (Dickinger and Kleijnen 2008). The cluster solution
yielded two subgroups: 137 participants who scored high on
need for uniqueness, and 155 participants who scored low.
We conducted a multiple group analysis to examine the moderating effects. In addition, we tested the structural model with free
parameter estimates and a model with an equality constraint imposed on the path between peer communication and attitude simultaneously. A poorer fit, indicated by a higher chi-square,
would confirm a significant difference between the models for
the high versus low need for uniqueness groups. As we show in
Table 4, the moderating effect of need for uniqueness is significant (Δχ 2 = 30.77, Δdf = 1). The estimated coefficient of peer
communication on attitude decreased from .50 (low need for
uniqueness, t = 3.78, p b .01) to −.15 (high need for uniqueness,
t = −1.10, p N .05). That is, the direct effect of peer communication on attitude appeared more evident for consumers who scored
low in their need for uniqueness.
Moderating Effect of Need for Uniqueness
Discussion
We have proposed that consumers’ need for uniqueness
would moderate the relationship between peer communication
Table 2
Means, standard deviations, and correlation matrices.
Mean SD
1. Tie strength
with peers
2. Identification with
the peer group
3. Peer
communication
4. Product attitude
5. Purchase intention
6. Product
involvement
7. Need for
uniqueness
1
2
3
4
5
6
7
4.99
1.45 1.00
4.69
1.21 0.65 1.00
4.88
1.56 0.54 0.50 1.00
5.23
4.75
4.96
1.45 0.49 0.54 0.51 1.00
1.39 0.44 0.43 0.46 0.74 1.00
1.54 0.55 0.56 0.77 0.56 0.46 1.00
4.59
1.32 0.51 0.59 0.40 0.44 0.28 0.42 1.00
This research models the antecedents and outcomes of peer
communication through social media from the perspective of
a consumer socialization framework. The results support all
our hypotheses, and these findings provide unique insights
into peer communication and its impact on consumer attitudes
in an online consumer socialization process. Peer communication
Table 4
Moderating effect of need for uniqueness.
Hypothesized relationship
Group
Standardized
coefficient
Δχ2
Δdf
Peer communication → product
attitude
High need
for uniqueness
Low need
for uniqueness
− 0.15
30.77
1
⁎ p b .01.
0.50 ⁎
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
through social media positively influences purchase intentions in
two ways: a direct influence through conformity and an indirect
influence by reinforcing product involvement. This finding is in
line with previous research (Bearden, Netemeyer, and Teel
1989), which suggests that socialization theory can be applied effectively to a social media setting. Moreover, peer communication on social media can be promoted by strengthening both
individual-level tie strength with peers and group-level identification with a peer group. In our examination of the direct impact of
peer communication on product attitude, we also confirm the
moderating effect of need for uniqueness. The findings provide
both theoretical and managerial insights.
Theoretical Implications
The emergence of virtual communities of consumption has
transformed consumer information search processes into “a
source of community and understanding” (Kozinets 1999, p
254). This study has set out to examine the impact of peer communication through social media on consumer product attitudes
and purchase intentions from a socialization theory perspective.
Previous research mainly focused on the impact of four consumer socialization agents—parents, mass media, school, and
peers (Moschis and Churchill 1978). The primary contribution
of our findings to theory is that consumption-related peer communications through social media are becoming increasingly
relevant for consumer socialization issues and can significantly
influence newcomers’ attitudes toward the product. By incorporating more variables into the socialization framework
(Moschis and Churchill 1978), we have created a model that
describes socialization processes that take place in virtual communities of consumption. Our model incorporates interaction
attributes (individual-level tie strength, group-level identification with the peer group) related to peers as socialization
agents, which enhances understanding of the antecedents of
peer communication. It also includes product attitudes and purchase intentions as outcomes of the online socialization process. Perhaps most important, our finding that online peer
communication drives consumer behavior through conformity
and informational routes extends the socialization framework
proposed by Moschis and Churchill (1978). The moderating
role of need for uniqueness also helps account for the impact
of virtual agent–consumer interactions; other moderators also
might exist in online socialization process. Our findings suggest that the social learning process in virtual communities remains a complex process that features multilevel variables,
beyond the scope of traditional socialization theory. Marketing
researchers should build their future research plans accordingly.
Managerial Implications
Ahuja and Galvin (2003) suggest a need for organizational
mechanisms that focus on virtual member socialization. The
findings of this research indicate that understanding consumer
online socialization processes—and specifically the influence
of peer communication—is vital. The findings also provide
205
meaningful implications for interactive marketing practitioners,
online advisers, and social media website operators.
Implications for Marketers
Social media websites provide an opportunity for businesses
to engage and interact with potential consumers, encourage an
increased sense of intimacy with consumers, and build allimportant relationships with potential consumers (Mersey,
Malthouse, and Calder 2010). Marketers should take advantage
of consumer participation through active communication to
strengthen their relationships (Brown, Broderick, and Lee
2007; Kozinets 1999). They also should examine the extent to
which they can assist members of prominent social media websites by connecting them with more other people they know and
identifying with other media users with whom they would not
otherwise have made contact. In particular, firms should sponsor online communities on influential social media websites
and offer consumers the ability to develop relationships with
others who share similar interests so they can exchange product
information and experiences, which should effectively generate
product interest among many people.
Corporate social networking websites also should allow consumers to not only exchange information about products or services but also engage in “participating and socializing”
experiences, across both current and potential consumers
(Mersey, Malthouse, and Calder 2010). Kozinets (1999) divides members of virtual communities of consumption into
four types—tourists, minglers, devotees, and insiders—according
to the strength of their relations with the consumption activity and
with the virtual community. Only insiders maintain strong social
ties and strong personal ties to the consumption activity. Thus,
marketers should target this group and attempt to turn others
into insiders. With a good understanding of their visitors, social
media websites can use structural and content features to stimulate visitors’ desire to learn more about a product or think more
about the product category, whether by highlighting the values
of their offerings, the commonalities between the reviewer and
the reader, or the need for empathy with the reviewer. As
Kozinets (1999, p 255) suggests, websites should make the social
contact through peer communication “a valuable reinforcement”
mechanism that stresses “longer-term personal gain through cooperation with other communities of consumption members.”
Marketers then can take measures to build trust between the reviewer and the reader and especially aim to increase the trustworthiness of active reviewers who contribute most to the site by
developing effective tools to enhance the persuasive effects of
their peer communication.
Finally, marketers who use social media tools should actively monitor peer communication by target consumers, audit the
effectiveness of the two routes from peer communication to
brand attitude and purchase intention, and handle with care
any negative peer communication about products and services
transmitted by written messages. They must be sensitive to
changes in consumer behavior patterns, identify new areas of
consumer values and interest, and integrate the values, needs,
and wants that consumers express in writing. Experienced employees might be deployed to deal with negative opinions or
206
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
service failures. By tracking the potential for positive social effects of social media use, marketers also might experiment with
more effective ways to stimulate peer communication among
consumers who are less socially connected, which can lead to
benefits through WOM about products. Although great efforts
should focus on enriching the social experience of social
media users, special care must be taken to ensure that peer communication does not mislead or overwhelm those users who
prefer less complex message exchanges through social media.
Implications for Online Advertisers
The findings of this study also provide implications for advertising. The literature shows that online advertising effectiveness is related to consumer engagement with a website, as
manifested in “finding a basis for conversation and social interaction” (Calder, Malthouse, and Schaedel 2009, p 323). Online
advertisers therefore should work with companies that operate
social media websites to increase the persuasive effects of interactivity, make advertised products more intangible for potential
consumers, identify the most important attributes, and use these
attributes in advertising. Increased interactivity in the user-touser domain may encourage visitors to build new kinds of relationships with the sponsoring corporation. It also could provide
customers with the ability to share opinions and information
through social media, spread opinions about the company or
advertised brand, and improve the relationship between the
brand/company and the user who regards the website as interactive. An advertiser that can use social media to respond effectively to consumer commentary on review sites gains a great
advantage because it can engage customers in conversations
to understand their needs and build relationships throughout
the purchase and after-purchase process (Bronner and de
Hoog 2010).
Implication for Social Media Website Operators
Social media operators should study the importance of both
their social and informational functions, then provide some additional support for the key functions through their website design. For example, a social media website can provide users
with the ability to share their consumption-related experiences,
opinions, and knowledge with others with similar interests.
Therefore, the website designers must ensure they can acquire
the information at their own pace and refer back to online discussions to absorb even more personal information. Users
would be able to see what they want, as well as write comments
or rate products or services. Operators also should ensure their
online social media forums offer credibility, relevance, and the
ability to evoke empathy through WOM communication. Advanced technology and safety mechanisms should be in place
and constantly upgraded to ensure high-quality peer communication and trust-based interactions among peers.
Limitations and Directions for Further Research
Despite these interesting implications, this study has several
limitations that also provide salient future research issues. First,
the social websites included in our sample were Chinese, which
enabled us to study a linguistically homogenous sample. These
respondents likely differ from consumers with other cultural
backgrounds, especially Western consumers. For example,
Singh, Zhao, and Hu (2005) find that local websites in India,
China, Japan, and the United States differ significantly in
their cultural dimensions. Therefore, additional research should
test our proposed model in other cultural contexts. Second, we
focused on positive impacts of peer communication on product
attitudes. Yet in many cases, peer communication yields negative
product reviews or feedback. Previous research has indicated that
even a small amount of negative information from a few postings
can have substantial impacts on consumer attitudes (Schlosser
2005). Further research should investigate this impact on consumer attitudes, as well as how to minimize or mitigate undesired
effects. Third, the participants were not asked to specify a product
category, but consumer interest in peer communication may vary
with product categories. Thus, we call for research that integrates
the product/service category into the model tests. Fourth, our
study did not include other potentially influential variables,
such as trust, empathy, or website credibility. Researchers should
explore the roles of those variables in terms of creating and sustaining interest in peer communication, to help identify more
moderators that have significant impacts on peer communication
outcomes.
Acknowledgments
This research work is supported by the National Natural Science
Foundation of China (70772018/71072146), the Fundamental
Research Funds for the Central Universities, and the Research
Funds of Renmin University of China (10XNK137). The authors
are grateful to the referees for their suggestions and comments
that improve the quality of this paper.
References
Ahuja, Manju K. and John E. Galvin (2003), “Socialization in Virtual Groups,”
Journal of Management, 29, 2, 161–85.
Algesheimer, René, Utpal M. Dholakia, and Andreas Herrmann (2005), “The
Social Influence of Brand Community: Evidence from European Car
Clubs,” Journal of Marketing, 69, 19–34.
Amaldoss, Wilfred and Sanjay Jain (2005), “Pricing of Conspicuous Goods: A
Competitive Analysis of Social Effects,” Journal of Marketing Research,
42, 1, 30–42.
Anderson, James C. and David W. Gerbing (1988), “Structural Equation
Modeling in Practice: A Review and Recommended Two-step Approach,”
Psychological Bulletin, 103, 3, 411–23.
Bagozzi, Richard P. and Youjae Yi (1988), “On the Evaluation of Structural
Equation Models,” Journal of the Academy of Marketing Science, 16, 1,
74–94.
——— and Utpal M. Dholakia (2002), “Intentional Social Action in Virtual
Communities,” Journal of Interactive Marketing, 16, 2, 2–21.
Bearden, William O., Richard G. Netemeyer, and Jesse E. Teel (1989), “Measurement of Consumer Susceptibility to Interpersonal Influence,” Journal
of Consumer Research, 15, 4, 473–81.
——— and Randall L. Rose (1990), “Attention to Social Comparison Information: An Individual Difference Factor Affecting Consumer Conformity,”
Journal of Consumer Research, 16, 461–71.
Bronner, Fred and Robert de Hoog (2010), “Consumer-generated Versus
Marketer-generated Websites in Consumer Decision Making,” International
Journal of Market Research, 52, 2, 231–48.
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
Brown, Jo, Amanda J. Broderick, and Nick Lee (2007), “Word of Mouth Communication within Online Communities: Conceptualizing the Online Social
Network,” Journal of Interactive Marketing, 21, 3, 2–20.
Calder, Bobby J., Edward C. Malthouse, and Ute Schaedel (2009), “An Experimental Study of the Relationship between Online Engagement and
Advertising Effectiveness,” Journal of Interactive Marketing, 23, 321–31.
Casteleyn, Jordi, André Mottart, and Kris Rutten (2009), “How to Use Facebook in Your Market Research,” International Journal of Market Research,
51, 4, 439–47.
Cheema, Amar and Andrew M. Kaikati (2010), “The Effect of Need for Uniqueness on Word of Mouth,” Journal of Marketing Research, 47, 3, 553–63.
China Internet Network Center Report (2009), “Social Network Users in China,”
Available online at: http://www.cnnic.cn (accessed on March, 2011).
Churchill Jr., Gilbert A. and George P. Moschis (1979), “Television and Interpersonal Influences on Adolescent Consumer Learning,” Journal of Consumer Research, 6, 23–35.
Crites Jr., Stephen L., Leandre R. Fabrigar, and Richard E. Petty (1994), “Measuring the Affective and Cognitive Properties of Attitudes: Conceptual and
Methodological Issues,” Personality and Social Psychology Bulletin, 20, 6,
619–34.
De Bruyn, Arnaud and Gary L. Lilien (2008), “A Multi-stage Model of Wordof-Mouth Influence through Viral Marketing,” International Journal of Research in Marketing, 25, 151–63.
De Gregorio, Federico and Yongjun Sung (2010), “Understanding Attitudes
Toward and Behaviors in Response to Product Placement: A Consumer Socialization Framework,” Journal of Advertising, 39, 1, 83–96.
Dhar, Vasant and Elaine Chang (2009), “Does Chatter Matter? The Impact of
User-generated Content on Music Sales,” Journal of Interactive Marketing,
23, 4, 300–7.
Dholakia, Utpal, Richard P. Bagozzi, and Lisa Klein Pearo (2004), “A Social
Influence Model of Consumer Participation in Network- and Small-groupbased Virtual Communities,” International Journal of Research in Marketing, 21, 3, 241–63.
Dickinger, Astrid and Mirella Kleijnen (2008), “Coupons Going Wireless: Determinants of Consumer Intentions to Redeem Mobile Coupons,” Journal of
Interactive Marketing, 22, 3, 23–39.
Emarketer Report (2011), “China Social Media Marketing,” Available online at:
http://www.emarketer.com (accessed March 2011).
Fornell, Claes and David F. Larcker (1981), “Evaluating Structural Equation
Models with Unobservable Variables and Measurement Error,” Journal of
Marketing Research, 18, 39–50.
Franke, Nikolaus, Peter Keinz, and Christoph J. Steger (2009), “Testing the
Value of Customization: When Do Customers Really Prefer Products Tailored to their Preferences?” Journal of Marketing, 73, 103–21.
Gershoff, Andrew D. and Gita Venkataramani Johar (2006), “Do You Know
Me? Consumer Calibration of Friends’ Knowledge,” Journal of Consumer
Research, 32, 496–503.
Harrison, Matthew and Mark Hedley (2011), “Marketing and Selling to Chinese
Businesses, Available online at: http://www.b2binternational.com. (accessed
August 2011).
Hennig-Thurau, Thorsten, Kevin P. Gwinner, Gianfranco Walsh, and Dwayne
D. Gremler (2004), “Electronic Word-of-Mouth Via Consumer Opinion
Platforms: What Motivates Consumers to Articulate Themselves on the Internet?,” Journal of Interactive Marketing, 18, 38–52.
———, Edward C. Malthouse, Christian Friege, Sonja Gensler, and Lara
Lobschat (2011), “The Impact of New Media on Customer Relationships,”
Journal of Service Research, 13, 3, 330–1.
Hogg, Michael A. (1992), The Social Psychology of Group Cohesiveness: From
Attraction to Social Identity. New York: New York University Press.
Hu, Li-tze and Peter M. Bentler (1999), “Cutoff Criteria for Fit Indices in Covariance Structure Analysis: Conventional Criteria versus New Alternatives,” Structural Equation Modeling, 6, 1, 1–55.
Irmak, Caglar, Beth Vallen, and Sankar Sen (2010), “You Like What I Like, but
I Don’t Like What You Like: Uniqueness Motivations in Product Preferences,”
Journal of Consumer Research, 37, 3, 443–55.
Iyengar, Raghuram, Sangman Han, and Sunil Gupta (2009), “Do Friends Influence
Purchases in a Social Network?” Working Paper No. 09-123, Harvard Business
School.
207
Jöreskog, Karl G. and Dag Sörbom (1996), LISREL 8: Structural Equation
Modeling. Chicago: Scientific Software International.
Karmarkar, Uma R. and Zakary L. Tormala (2010), “Believe Me, I Have No
Idea What I’m Talking About: The Effects of Source Certainty on
Consumer Involvement and Persuasion,” Journal of Consumer Research,
36, 6, 1033–49.
Kim, Chankon, Hanjoon Lee, and Marc A. Tomiuk (2009), “Adolescents’ Perceptions of Family Communication Patterns and Some Aspects of their
Consumer Socialization,” Psychology & Marketing, 26, 10, 888–907.
Kim, Sora, Eric Haley, and Gi-Yong Koo (2009), “Comparison of the Paths
from Consumer Involvement Types to Ad Responses between Corporate
Advertising and Product Advertising,” Journal of Advertising, 38, 3, 67–80.
Köhler, Clemens F., Andrew J. Rohm, Ko de Ruyter, and Martin Wetzels
(2011), “Return on Interactivity: The Impact of Online Agents on Newcomer Adjustment,” Journal of Marketing, 75, 2, 93–108.
Kozinets, Robert V. (1999), “E-tribalized Marketing? The Strategic Implications of Virtual Communities of Consumption,” European Management
Journal, 17, 3, 252–64.
———, Kristine de Valck, Andrea C. Wojnicki, and Sarah J.S. Wilner (2010),
“Networked Narratives: Understanding Word-of-Mouth Marketing in Online Communities,” Journal of Marketing, 74, 2, 71–89.
Levin, Daniel Z. and Rob Cross (2004), “The Strength of Weak Ties You Can
Trust: The Mediating Role of Trust in Effective Knowledge Transfer,” Management Science, 50, 11, 1477–90.
Lord, Kenneth R., Myung-Soo Lee, and Peggy Choong (2001), “Differences in
Normative and Informational Social Influence,” Advances in Consumer Research, 28, 280–5.
Lueg, Jason E., Nicole Ponder, Sharon E. Beatty, and Michael L. Capella
(2006), “Teenagers’ Use of Alternative Shopping Channels: A Consumer
Socialization Perspective,” Journal of Retailing, 82, 2, 137–53.
——— and R. Zachary Finney (2007), “Interpersonal Communication in the
Consumer Socialization Process: Scale Development and Validation,” Journal of Marketing Theory & Practice, 15, 1, 25–39.
Mangleburg, Tamara F., Patricia M. Doney, and Terry Bristol (2004), “Shopping with Friends and Teens’ Susceptibility to Peer Influence,” Journal of
Retailing, 80, 101–16.
Martin, Ingrid M. and David W. Stewart (2000), “The Differential Impact of
Goal Congruency on Attitudes, Intentions, and the Transfer of Brand Equity,” Journal of Marketing Research, 38, 471–84.
Mersey, Rachel Davis, Edward C. Malthouse, and Bobby J. Calder (2010), “Engagement with Online Media,” Journal of Media Business Studies, 7, 2,
39–56.
Moschis, George P. and Gilbert A. Churchill Jr. (1978), “Consumer Socialization: A Theoretical and Empirical Analysis,” Journal of Marketing
Research, 15, 4, 599–609.
——— and Roy L. Moore (1984), “Anticipatory Consumer Socialization,”
Journal of the Academy of Marketing Science, 12, 4, 109–23.
Mukhopadhyay, Anirban and Catherine W.M. Yeung (2010), “Building
Character: Effects of Lay Theories of Self-Control on the Selection of Products
for Children,” Journal of Marketing Research, 47, 2, 240–50.
Muratore, Isabelle (2008), “Teenagers, Blogs and Socialization: A Case Study
of Young French Bloggers,” Young Consumers, 9, 2, 131–42.
Myers, Matthew B., Roger J. Calantone, Thomas J. Page Jr., and Charles R.
Taylor (2000), “An Application of Multiple-group Causal Models in Assessing Cross-cultural Measurement Equivalence,” Journal of International
Marketing, 8, 4, 108–21.
Nambisan, Satish and Robert A. Baron (2007), “Interactions in Virtual
Customer Environments: Implications for Product Support and Customer
Relationship Management,” Journal of Interactive Marketing, 21, 2,
42–61.
Okazaki, Shintaro (2009), “The Tactical Use of Mobile Marketing: How Adolescents’ Social Networking Can Best Shape Brand Extensions,” Journal
of Advertising Research, 49, 1, 12–26.
Schlosser, Ann E. (2005), “Posting versus Lurking: Communicating in a
Multiple Audience Context,” Journal of Consumer Research, 32, 2, 260–5.
Shankar, Venkatesh and Edward C. Malthouse (2007), “The Growth of Interactions and Dialogs in Interactive Marketing,” Journal of Interactive
Marketing, 21, 2, 2–4.
208
X. Wang et al. / Journal of Interactive Marketing 26 (2012) 198–208
Shim, Soyeon (1996), “Adolescent Consumer Decision-making Styles: The
Consumer Socialization Perspective,” Psychology and Marketing, 13, 6,
547–69.
Singh, Nitish, Hongxin Zhao, and Xiaorui Hu (2005), “Analyzing the Cultural
Content of Web Sites: A Cross-national Comparison of China, India, Japan,
and US,” International Marketing Review, 22, 2, 129–45.
Smith, Donnavieve, Satya Menon, and K. Sivakumar (2005), “Online Peer and
Editorial Recommendations, Trust, and Choice in Virtual Markets,” Journal
of Interactive Marketing, 19, 3, 15–37.
Taylor, David G., Jeffery E. Lewin, and David Strutton (2011), “Friends, Fans,
and Followers: Do Ads Work on Social Networks? How Gender and Age
Shape Receptivity,” Journal of Advertising Research, 51, 1, 258–76.
Taylor, James W., John J. Houlahan, and Alan C. Gabriel (1975), “The Purchase Intention Question in New Product Development: A Field Test,”
Journal of Marketing, 39, 1, 90–2.
Tian, Kelly T., William O. Bearden, and Gary L. Hunter (2001), “Consumers’
Need for Uniqueness: Scale Development and Validation,” Journal of Consumer Research, 28, 1, 50–66.
Trusov, Michael, Anand V. Bodapati, and Randolph E. Bucklin (2010), “Determining Influential Users in Internet Social Networks,” Journal of Marketing
Research, 47, 4, 643–58.
Ward, Scott (1974), “Consumer Socialization,” Journal of Consumer Research, 1,
2, 1–14.
Zaichkowsky, Judith Lynne (1985), “Measuring the Involvement Construct,”
Journal of Consumer Research, 12, 3, 341–52.
Zhang, Jie and Terry Daugherty (2009), “Third-person Effect and Social Networking: Implications for Online Marketing and Word-of-Mouth Communication,” American Journal of Business, 24, 2, 53–63.
Xia Wang is an Assistant Professor of Marketing, School of Business, Renmin
University (China). She received her Doctoral Degree in Business Administration with a major in Marketing at Tsinghua University. Her major research area
is in word-of-mouth marketing, and consumer behavior.
Chunling Yu is an Associate Professor of Marketing, School of Management,
Tsinghua University (China). She received her Doctoral Degree in Business
Administration with a major in Marketing at Tsinghua University. Her research
has appeared in many academic journals including: The Journal of Product &
Brand Management, and Journal of Brand Management. Dr. Yu’s major research area is in consumer social interaction, and consumer behavior.
Yujie Wei is an Assistant Professor of Marketing, University of West Georgia
(U.S.A). He received his Master’s Degree in Linguistics at the University of
Science and Technology Beijing and Doctoral Degree in Business Administration
with a major in Marketing at Georgia State University. His research has appeared
in many academic journals including: The Journal of Business Research,
Journal of Electronic Commerce Research, Journal of Product & Brand
Management, and Journal of Asia Business Studies. Dr. Wei’s major research
area is in international marketing, e-commerce, and consumer behavior.
SOCIAL MEDIA, A NEW REVOLUTION IN THE FIELD OF MARKETING: THE
EFFECT OF INFORMATION SHARING, PEER PRESSURE, ENTERTAINMENT
AND EMOTIONAL CONNECTION ON THE ATTITUDE TOWARDS THE BRAND
AND IN TURN THE PRUCHASE INTENTIONS FROM THE BRAND
by
Sradha Narendra Sheth
Bachelors of Commerce
Mysore Education Society College of Arts, Commerce & Science, 2007
Master in Business Administration
Institute of Chartered Financial Analysts of India Business School, 2010
__________________________________________
Submitted in Partial Fulfillment of the Requirements
For the Degree of Master of Science in
Retailing
College of Hospitality, Retail and Sport Management
University of South Carolina
2013
Accepted by:
Jiyeon Kim, Director of Thesis
Jung-Hwan Kim, Reader
Jeffrey Campbell, Reader
Joohyung Park, Reader
Lacy Ford, Vice Provost and Dean of Graduate Studies
i
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ii
ACKNOWLEDGEMENTS
Behind every achievement lies an unfathomable sea of gratitude to those who
accentuated it and without them it would not have come into existence. Here I want to
express and record my heart felt feeling of gratefulness to all those who directly or
indirectly helped me in this work.
My academic career at University of South Carolina has been an extremely
fruitful experience. I am indebted to everyone at the College of HRSM for their
contributions to my academic and personal growth over these two years.
I wish to thank Dr. Jiyeon Kim (thesis mentor) for her advice, motivation and
continual guidance with my thesis. I thank her for her support and criticisms offered for
the successful completion of my thesis.
Finally, I would like to thank my thesis committee members, Dr. Jeffery
Campbell, Dr. Joohyung Park and Dr. Jung-Hwan Kim for their precious time, effort
and the valuable inputs that helped make my thesis even more consistent.
iii
ABSTRACT
Social Media has today become one of the fastest and strongest networking and
communication tools. Companies realizing the importance of this new marketing
revolution have also ventured into the world of social media. Thus, the purpose of this
study is to examine the effect of social media marketing on user’s attitude towards the
brand present on social media and their purchase intentions from the brand. The
relevance of this study will provide great insights to retailers with regard to using
multiple social media sites and their features to successfully market their products, retain
and grow their customer base.
iv
TABLE OF CONTENTS
ACKNOWLEDGEMENTS………………………………………………………………………………….. iii
ABSTRACT……………………………………………………………………………………………………….. iv
LIST OF TABLES……………………………………………………………………………………………… vii
LIST OF FIGURES …………………………………………………………………………………………… viii
CHAPTER 1: INTRODUCTION …………………………………………………………………………… 1
Social media for companies ……………………………………………………………………………….. 3
Social media for users ……………………………………………………………………………………….. 5
CHAPTER 2: REVIEW OF LITERATURE……………………………………………………………. 8
Theoretical Background …………………………………………………………………………………….. 8
CHAPTER 3: CONCEPTUAL MODEL AND HYPOTHESES ………………………………. 12
Hypotheses …………………………………………………………………………………………………….. 12
Conceptual Model …………………………………………………………………………………………… 13
CHAPTER 4: METHOD …………………………………………………………………………………….. 21
Data Collection and Sample characteristics ………………………………………………………… 21
Survey Development ……………………………………………………………………………………….. 22
CHAPTER 5: DATA ANALYSIS ……………………………………………………………………….. 24
Reliability and validity …………………………………………………………………………………….. 24
v
Pearson Correlation Coefficients ………………………………………………………………………. 24
Hypotheses testing…………………………………………………………………………………………… 27
CHAPTER 6: DISCUSSION……………………………………………………………………………….. 31
CHAPTER 7: IMPLICATIONS, LIMITATIONS & FUTURE RESEARCH…………….. 35
REFERENCES ………………………………………………………………………………………………….. 37
APPENDIX A: QUESTIONNAIRE……………………………………………………………………… 46
APPENDIX B: DESCRIPTIVE STATISTICS ………………………………………………………. 55
vi
LIST OF TABLES
Table1.1 Consumer engagement with brands …………………………………………………………….5
Table 4.1: Social Media Usage on a daily basis ………………………………………………………21
Table 5.1: Reliability Statistics ……………………………………………………………………………..25
Table 5.2: Pearson Correlation Coefficients …………………………………………………………….25
Table 5.3: Hypotheses Testing and Regression ……………………………………………………….28
Table 5.4: Customer-brand engagement ………………………………………………………………….29
Table 5.5: Products discussed and recommended of social media ……………………………..30
vii
LIST OF FIGURES
Figure 3.1 Social Media Marketing – Purchase Intention Model………………………………..13
Figure B.1 Gender ……………………………………………………………………………………………….54
Figure B.2 Age ……………………………………………………………………………………………………54
Figure B.3 Number of log-in on daily basis ……………………………………………………………55
Figure B.4 Number of Hours spent per visit…………………………………………………………….55
viii
CHAPTER 1
INTRODUCTION
Internet has been a medium for communication, information sharing and
entertainment since the 1990s. The migration to Web 2.0 has enabled instant
communications. Through applications such as Facebook, Twitter and other social
networking sites (SNS), users can create, publish and share content, data and information.
Social media is a virtual landscape that facilitates quick and easy transmission of content
in the form of words, pictures, videos, and audios. It allows users to form groups or
communities, share common interests or goals, exchange opinions or suggestions and
form relationships with other users on that platform. Social media growth trajectory has
reached approx. 1 Billion and continues to project an upward trend (Leplan, 2010).
Though the primary goal of social media is to facilitate networking among the users, it
has found its use in marketing. Social media marketing appears to have changed the way
people discover, read and share news, information and content (Solis, 2007).
Diane Hessan, President and CEO of Communisplace said,
“Customers are demanding to be more engaged with the companies that affect their lives.
Booming trends like blogging, online communities, flash mobbing, buzz agents, and
MySpace show that customers have a lot to say – they want to be asked and they want to
be involved. ”
1
The structural and interactive features of social media encourages ongoing
conversations between marketers and consumers for all three stages of the marketing
process: prepurchase (i.e., information search), purchase (i.e., sales promotion), and
postpurchase (i.e., customer services) (Kaplan and Haenlein, 2010).
Although previous studies researched the attitude of the users towards social
media advertising (Taylor, Lewin, & Strutton, 2011), the effect of social media
advertising on the user’s attitude towards the brand is yet to be examined. It is crucial to
study the user’s attitude towards the brand to understand the user’s purchase intentions.
Lee & Ma (2011) evaluated the intention to share news over social media but how the
news or information shared and exchanged affects the attitude is an important and
unexplored path. Another study found that personification of brands using verbal and
non-verbal cues helped build long term customer-brand relationships (Kwon & Sung,
2011). However, they did not examine how the attitude developed due to brand
personification affects the user’s purchase intentions. Moreover, his study is important to
understand how the members of a group or peers in the social network shape the attitude
of the other users thereby, influencing their purchase intentions. Since the attitude is
expected to be a strong predictor of purchase intention, it is important for marketers to
understand how to shape the attitude of the customers using social media that will
provide an opportunity to the retailers to reach out to the mass market. Thus, the purpose
of this study to examine the effects of information sharing, peer pressure, entertainment
and emotional connection in a social media setting on the user’s attitude toward a brand
present in social media thereby influencing their purchase intention from the brand.
2
Social media for companies
Social media is a new revolution in the field of marketing. Companies now
subscribe to social networking sites and encourage interested parties to join their virtual
or online groups in order to increase exposure and traffic, conduct market research,
generate leads and potential business partners and improve sales. For example, Publix
uploads downloadable coupons on a daily basis which would help the followers take
advantage of various discounts and promotional offers. They also send out invitations to
try out their new products or participate in various on-campus cooking events as an
attempt to attract a lot of homemakers or those who enjoy cooking. Publix has a team
dedicated to marketing over social media and has approximately 1 million likes and
79,000 talking. They continually respond to their customer’s queries, issues or concerns
or even general comments and product requests. Similarly, Nike has more than 10 million
followers. With such a huge fan base, they had to create multiple online communities,
each community dedicated to a different sport. Nike ensures that they inform all their
followers about new products launched and latest technology and expertise used in
enhancing the product quality. They invite followers to discuss different sports,
celebrities and other prize winning events. Nike also encourages users to comment, give
opinions and feedback on their stores, products and services. This acts as a strong tool to
build relationships with their fan base. Many other companies and brands have increased
their presence on social media. Social media would also be a potent tool for the start-ups
and new entrepreneurs to introduce their products and brands to the mass market. Thus,
social media has become an important source for marketers to predict customer’s needs
and wants; target mass market; advertise their products or services; resolve issues and
3
grievances; obtain feedback and suggestions; build strong relationships; influence
attitudes towards the brand and ultimately affect the purchase intentions.
The 2012 social media marketing industry report ranked the top 5 social networking
sites based on the marketing features as follows:
1. Facebook: Social networking site known for its wall post and networking feature
2. Twitter – Micro-blogging site to post short messages not more than 140 words.
3. LinkedIn – Business networking site to send business invitations, tenders &
quotations.
4. Blogs – Personal published journal that helps personify a brand.
5. Youtube – Content community to create and upload any video for the world to
see.
This shows how different social networking sites can be used by marketers to
market their products For example, Ikea can depend on YouTube to demonstrate how
easy it is for the customers to put together their products (do-it-yourself products), while
brands like Apple can tell apple stories to their fans through blogs. Moreover, it has been
observed that 56% of the internet users in America feel a stronger connection with
companies and feel better served by companies who use social media to interact with
consumers (Cone, 2012). The more a customer interacts with a brand, the more likely it is
to affect the user’s attitude towards the brand (Francella, 2011). This may affect their
thinking or liking towards the brand which may result in a developing a favorable attitude
towards the brand or may even result in a purchase-related decision. The Economist
Intelligence Unit (2007) interviewed 311 executives to understand how customers engage
with a brand (see. table 1.1). “Sensing a variety of potential benefits, marketers also have
4
ventured into the world of social media to use them for sales, customer service,
promotions, and human resource tactics” (Kwon & Sung, 2010).
Table1.1: Consumer engagement with brands
Attributes that describe an engaged customer
Percentage of respondents
Recommends products/services to others
79
Frequently purchases products/services
64
Provides frequent feedback on product/services
61
issues
Participates in product/service design
38
Is actively involved in online communities or user
11
groups
Source: The Economist Intelligence Unit, 2007
Social media for users
Social media provides a platform for the users who seek to gratify their status and
information seeking needs by sharing information (Lee & Ma, 2011); recommendations,
suggestions and various product, brand or store experiences and in turn expect their peers
or other users to reciprocate in the form of appreciation, or criticisms. Almost everybody
today is digitally connected to their friends, families, acquaintances via the social media
sites and online activities.
5
As has been rightly quoted by Safko & Brake (2009), “Technology has enabled
everyone to function as citizen journalists or market mavens.” By discussing products
and services among their group members, users unintentionally start endorsing a brand.
Users tend to trust such sources as the information is coming from a third party rather
than the company or the marketer (Chi, 2011). Thus, relating personal experiences may
influence the attitude of the other users or followers of the brands. Users join various
facebook or virtual brand communities primarily for entertainment and socialization.
Research has also supported that by making the search process easy, interactive and fun,
companies can generate favorable attitude towards the brands. Moreover, companies
offering updates, coupons and other benefits to the group members may motivate other
users to join brand-related groups to take advantage of such promotional activities.
Additionally, social media platforms like blogs or facebook allow marketers to personify
their brands, enabling users to easily relate with the brands. By matching the
characteristics, marketers can establish strong relationships and connection between the
user and a brand on social media (Kwon and Sung, 2011). The emotional connection so
formed can affect the attitude towards the brand on social media. Social media is an
extension of word-of-mouth marketing i.e. when users discuss or inform others about
their interactions with the brands on social media, they indirectly exert pressure on their
peers to be a part of such virtual brand communities and avail similar benefits. By
interacting, communicating and building relationships with the followers on social media
on a regular basis, marketers can enhance the brand perceptions (Phan, 2011) and attitude
towards the brand which may eventually affect the purchase intentions. Thus, social
6
media provides ample opportunities to marketers or companies who can influence the
conversations that consumers have with one another.
7
CHAPTER 2
REVIEW OF LITERATURE
Theoretical Background
The conceptual framework for this study is based on three well-received theories
in business, advertising, and psychology.
Uses and Gratification theory: Uses and gratification theory was developed to
understand why people actively seek out specific media to satisfy specific needs ( Herta
Herzog, 1944). The theory has been used to explain behavior of audiences being engaged
in various forms of media (i.e. listening to the radio or reading the newspaper). While the
traditional media theory nominates that the media has an effect on people, the use and
gratification theory focuses on what people do with the media, assuming active roles the
audiences are taking in choosing and using the media (West and Turner, 2007). With the
influx of Internet and mobile technologies, the use and gratifications theory serves as the
most appropriate paradigm to measure consumer’s need to use the new and modern tools
to make more informed decisions. This theory postulates that an individual’s social and
psychological needs motivate them to select a particular type of media to achieve the
goals. In other words, media users are motivated to expose themselves selectively to
media based on their needs and gratification-seeking motives purposefully attempting to
achieve those goals by using specific media channels and content (Taylor, Lewin, and
8
Strutton, 2011). The theory includes 5 categories namely; cognitive needs (acquiring
information, knowledge and understanding), affective needs (emotions, pleasure and
feelings), personal integrity needs (credibility, stability and status), social integrity needs
(familyand friends) and tension release needs (escape and diversion) that would affect the
use and gratification of a media (Katz, Gurevitch and Haas, 1973). Previous researchers
identified gratifications of using social and mobile media to achieve goals as follows:

Shao (2009) – Information, entertainment and mood management

Dunne, A., Lawlor, M., & Rowley, J. (2010) – Entertainment, information
search, peer acceptance and relationship management

Park, Kee, & Valenzuela (2009) – Information seeking, socializing,
entertainment, and self-status seeking.

Chiu, Hsu and Wang (2006) – Social interaction and socializing

Kim, Jeong and Lee (2010) – Information seeking and socializing
Although the media dependency and usage may vary, the common denominators
of the previous research regarding the user’s use of the social networking sites are the
following gratifications: information seeking, entertainment, and socializing/peer
acceptance. This may explain how the gratifications obtained through social media can
help consumers form a positive attitude toward a brand. The gratifications such as
availability of information, entertainment, recommendations/discussions, through social
media, etc. may affect the user’s brand choice which is represented by their attitude
toward a brand and in turn their purchase intention from the brand.
Stimulus-Organism-Response (SOR) Theory: The Stimulus-Organism-Response
9
(SOR) theory suggests that environmental stimuli (S) sparks an emotional reaction (O)
which in turn forces the consumer to respond (R) in a positive or a negative manner
(Mehrabian and Russell, 1974). Donovan and Rossiter (1982) examined the linkage
between organism (O) and response (R) obtained from a consumer and maintained that
pleasure is the determinant of the response (approach or avoidance) generated. Previous
studies confirmed that a high level of pleasure elicited by environmental stimuli in retail
stores and on web sites enhances satisfaction (Eroglu, Machleit, & Davis, 2003),
positively influences the brand choice (Eroglu, Machleit, & Davis, 2003; Hu & Jasper,
2006) in turn affecting purchase intention (Babin & Babin, 2001).
Based on the SOR theory, the stimulus (S) can be external to the person and
consist of various elements of the physical environment such as availability of
product/brand information, events or activities, polls, forums, an opportunity to interact
with the brands on a social networking site etc., and the organism (O) can be to the
internal processes intervening between stimuli external to the person and the final action
or response such as formation of an attitude towards the brands. The response (R) can be
the intention to buy from a brand present on social media as antecedents of
approach/avoidance behavior. The SOR paradigm is used in this study to support the
emotional connectivity between brands and users; affects their brand choice represented
by their attitude towards the brand, thereby increasing their purchase intentions.
Theory of Reasoned Action: Theory of reasoned action examines the determinants of
consciously intended behaviors. TRA assumes behavioral intention as a function of a)
belief related attitude i.e. an individual’s outlook towards performing a behavior and b)
10
subjective norm, i.e. the social and environmental pressures to perform a behavior. This
theory helps understand what (personal beliefs or social and environmental factors)
motivates an individual to behave in a particular fashion. While attitude consists of an
individual’s belief about the consequences of having performed behavior, subjective
norm explains how perceptions of the people around a person can influence his/her
intention and behavior (Ajzen & Fishbein, 1980). Attitude is an individual’s affective
response towards performing some behavior based on his/her positive (approach) or
negative (avoidance) valence of an event, object or situation. Subjective norm can be the
social pressure an individual experiences while considering and making the purchase
decision. Previous research found peer pressure being a strong influence on the student’s
online forum participation intention (Yang, Lee, Tan & Teo, 2007). Participating in
various online events encourages interaction which in turn may lead to establishment of
new social relationships. These interpersonal or social relationships exert social pressure
which influences the user’s brand choice represented by their attitude towards a brand
which may in turn help determine their purchase intentions.
11
CHAPTER 3
CONCEPTUAL MODEL AND HYPOTHESES
The Social Media Marketing-Purchase Intention conceptual model developed for
this study explains the effects of four external constructs (information sharing, peer
pressure, entertainment and emotional connection in a social media setting) on the user’s
brand choice is represented by the user’s attitude towards the brand which in turn the
purchase intentions from that brand (see figure 3.1).
Hypotheses
Information Sharing:
Information sharing refers to the exchange of relevant news via social media in a
timely fashion (Ko, Cho & Roberts, 2005; Luo, 2002). Social media allows users to
create, share, and seek content and at the same time facilitates communication and
collaboration among users and between brands and users (Kim, Jeong, & Lee, 2010;
Lerman, 2007). Thus, social media users today have become active producers of
information (Nov, Naaman, & Ye, 2010). Consumers today prefer to make an informed
purchase decision by collecting as much information as they can get, evaluating various
options available, conducting a cost-benefit analysis, etc. This makes it mandatory for
marketers to be present on the social media. Moreover, social media can shape user’s
attitude towards the brand through mutual, two-way communication (Najmi, Atefi, &
Mirbagheri, 2012).
12
Conceptual Model
On Social Media
Information
sharing
H1
Brand Choice
H2
Attitude
towards
brands
Peer pressure
H5
Purchase
intention
H3a
Entertainment
H4
H3b
Emotional
connection
Figure 3.1: The Social Media Marketing – Purchase Intention Model
Users expect a dialogue with brands present on social media, in which the brand
listens to what a customer thinks, needs and wants rather than just pushing the product to
the customer (Brown, 2010). Consumers are joining various brand-related social media
groups or communities for opinion expression and information exchange, thereby
allowing the marketers to indirectly influence the user’s attitude towards their brands.
(Hair, Clark, & Shapiro, 2010). Studies have also supported that user’s love to discuss
their purchases and purchase experience on social media. Therefore, since the
13
information is coming from a third party, there is a positive influence on the user’s
attitude towards the brand (Chu, 2011). When users exchange information among each
other, they become the endorsers of the brand. Thus, marketers such as Target, Walmart,
Apple, Publix, Nike, Victoria’s Secret etc. actively participate on social media,
encouraging transmission of messages within and among users and the brands, thereby
shaping their attitude towards the brand (Chu, 2011). By being present on the social
media, marketers can facilitate communication and interaction among users. Chi, 2011
have supported that social media users trust virtual brand communities and have a
favorable attitude towards virtual brand communities. This kind of marketing and/or
advertising will influence the attitude towards the brand and in turn affect user’s purchase
intention (MacKenzie, Lutz, & Belch, 1986).
H1: Information sharing on social media will positively influence the attitude towards the
brand.
Peer Pressure:
Peer pressure can be defined as “group insistence and encouragement for an
individual to be involved in a group activity in a particular way” (Santor, Messervey, &
Kusumakar, 2000). In other words, it is the intentional or unintentional force that
members of a group impose on the other members, thereby encouraging them to act or
react in the similar fashion. Peer pressure is more common among youngsters who tend
to associate with the same group of people over a long period of time. Zhu, Huberman,
and Luon (2012) conducted an experiment to determine how social influence in online
recommender systems impacts user’s attitude towards the brand which would in turn
14
affects the final purchase intentions or decisions. The results of this study supported that
user’s opinions significantly sway other user’s own choices or are likely to reverse their
attitude towards the brand. When individuals choose to share information about products
and services with their friends, they tend to activate their strong- tie relationships
(Frenzen and Nakamoto 1993, Aral & walker 2011). Strong ties between group members
would indicate greater dependency on the other members for opinions and suggestions.
Narayan, Rao, Saunders (2011) mentioned that User’s attitude towards the brand is
shaped not just by the attributes of the products but also the preferences of other
consumers, such as peers. This may in turn influence their purchase intentions. Netzer,
Toubia, Bradlow, Dahan, Eveginou, Feinberg, Feit, Hui, Johnson, Liechty, Orlin, & Rao
(2008) has supported that customer’s attribute preference and attitude towards the brand
maybe influenced by the peers or the social group. According to Aral & walker (2011),
the tendency to accept the information from a known trusted source is more and the
tendency to respond is back is also greater due to the reciprocal relationship that the
group members share. When an individual notices their group members or family and
friends engage with a particular brand, they tend to get curious about the company and
the brand and this in turn may encourage them to associate with the similar brands
developing an attitude towards the brand. In a social media setting, consumers tend to
join different social groups. These social group members have common interest or likes
and prefer to take opinions, references and suggestions molding the attitudes of other
users towards the brand that may subsequently influence the purchase intentions.
H2: Peer pressure through social media will positively influence the attitude towards the
brand.
15
Entertainment:
Social networking sites have over the years gained importance due to its
entertainment quotient. Entertainment is a way of reducing or escaping pressure (Lee, &
Ma, 2012). According to Hair, Clark, & Shapiro (2010), users are heavily dependent on
the virtual brand communities to express their opinions and information exchange,
thereby influencing the attitude of the group members towards the brand. Previous
studies have supported that offering entertainment over social media evokes positives
emotions which influences the attitude towards the brand. According to McQuail, 2005,
the entertainment gratifications obtained through social media can be measured by its
ability to satisfy the user’s needs of escapism, enjoyment and anxiety relief. Frequenting
social networking sites have become a part of everyday life. Posting, commenting,
discussing, uploading photos/videos, etc. offer some kind of entertainment and relaxation
to the users (Hair, Clark, & Shapiro, 2010). Marketers are now using social media to
attract, entertain and to build long term relationships with users which would in turn
shape their attitude towards the brand. Novak, Hoffman & Yung (2000), in their study
supported that by making online search process fun and interactive; marketers can attract
customers, mitigate price sensitivity, and influence the attitude towards the brand.
Dawson, Bloch, and Ridgway (1990) and Pine & Gilmore (1999) have supported that
delivering experiences that are pleasurable, memorable, relevant and valued will linger in
the memory and influence the user’s attitudes and future purchase intentions. Once a user
develops a positive attitude towards the brand, they tend to favor and purchase those
brands over other brands. Hence, the following hypothesis can be developed:
16
H3a: Entertainment offered in a social media setting will positively influence the attitude
towards the brand.
It has also been supported that marketers now weave marketing content with
entertainment content in order to develop strong emotional connection between the
brands and the users (Hudson & Hudson, 2006). Moreover, when a user has positive
emotions (happy, excited, or satisfied), they tend to pass on the information to other
group members affecting their purchase intentions (Dobele, Lindgreen, & Beverland,
2007). Offering entertainment over social media pleases a user and may result in
developing strong liking or emotion towards the brand. For example, Nike conducts
various events such as discussing a product, game, sport personality or getting customer
feedback which grabs the attention of not only the loyal Nike customers but also that of
potential customers. This is Nike’s strategy to develop an emotional connection with their
customers. Furthermore, marketers use celebrities to endorse their brand which in turn
helps build an emotional connection between the brands and the users. For example,
when Michael Jordan endorses Nike, all Michael Jordan fans would be tempted to
support or patronize that brand. Similarly, by organizing virtual group activities such as
discussing sports or celebrity too may help evoke that emotional bond between users and
brand. Hence, an entertainment offered through social media may help develop an
emotional connection with the brand.
H3b: Entertainment offered in a social media setting will positively influence emotional
connection between the brands on social media and users.
17
Emotional connection
Emotional connection is defined as an informal amity among a group of people
(Chen, 2010) with common interests and goals. It is a dimension that helps us understand
the customer’s response or behavior. Kwon & Sung (2011) recommended that by being
present on the social media, marketers can motivate people’s tendency to
anthropomorphize brands. Characterizing brands on social media will attract users of
similar characteristics, thereby, influencing the purchase intentions from the brand (Kwon
& Sung, 2011). Moreover, giving brands a human face creates an emotional connection
between the brand and the user influencing their desire to purchase a brand. Murray
(1953), Maslow (1987) and Chen (2010) in their studies have supported that people today
depend on social networking sites to gratify their desire of belongingness and being
important to each other. Through social media users can form virtual brand groups to
share common interest, goals, discuss issues and opinions; groups can be secret i.e. only
the members have access to the group and they can decide if they want to be a closed or
an open group; the members get to approve or disapprove new members; and marketers
or group members can send mass or personalized messages to other members (Chu,
2011). The value subsequently obtained helps create an emotional connection which
strengthens relationships and influences user’s purchase intentions from the brand
(Deighton & Grayson, 1995). The more frequently a brand interacts with the users, more
likely is the user to purchase from that brand (Homans, 1950). Hence, the following
hypothesis was developed:
H4: Establishment of emotional connection in a social media setting will positively
influence the user’s purchase intentions from the brand.
18
Attitude towards brands and purchase intention:
Attitude towards a brand can be defined as audience’s positive (good, favorable or
happy) and negative (bad, unfavorable or unhappy) reactions to the advertised brands
(Najmi, Atefi, & Mirbagheri, 2012). In other words, attitude towards brands is formed
based on past experiences and the influence exerted by outsiders (such as friends, family,
peers, or other group members) forcing an individual to form a favorable/non-favorable
attitude towards the brand (Ranjbarian, Fathi, & Lari, 2011). Once the users join a brandrelated group on the social media sites, their attitude towards the brand and their purchase
intentions can be influenced by the information they mobilize from the other group
members (Chu, 2011). As mentioned earlier, information on social media is either
coming from or is backed by a third party, acting as the endorser of the brand. Thus, the
information is considered to be credible and trustworthy. Yoon, Kim, & Kim (1998)
supported that when the communication is coming from a trustworthy source, the
message sent will positively influence the attitude towards the brand in turn influencing
the purchase intentions. Moreover, since the information is coming from co-user, it
reduces the avoidance behavior and inculcates a feeling that the information may be true
and helpful for the current and future purchase intentions (Rojas-Mendez, Davies, &
Madran, 2009). Social media offer a platform for the users to discuss, share and seek
information of interest with members of their groups which helps shape their attitude
towards the brands. Thus, these conversations not only shape the attitudes but also impact
their confidence in evaluating the brand consequently influencing their purchase
intentions (Ranjbarian, Fathi, & Lari, 2011).
19
Purchase intention can be defined as an individual’s predisposition to purchase a
product or service (Belch, & Belch, 2004). Phelps & Hoy (1996) have supported that
purchase intention indicates the likelihood of an individual to purchase a brand. Many
studies have supported that a positive attitude towards brand positively influences the
purchase decisions. Social media platforms allow brands/marketers to present their
product and service in such a way that users tend build a positive perception and attitude
towards the brand.
H5: Attitude towards brands on social media will positively influence the purchase
intention.
20
CHAPTER 4
METHOD
A quantitative research method was adopted to gauge the effect of information
seeking and peer pressure on attitude towards brand and entertainment on both emotional
connection and attitude towards brand and in turn their influence on the user’s purchase
intentions from that brand.
Data Collection and Sample characteristics
The current study used a convenience sample consisting of students pursuing a
retailing degree from a large Southern University in the United States. College students
are considered to be an apt sample for this study since they are the heavy users of social
media. Survey invitations c…