Introduction And Annotated Bibliography A brief introduction describing the specific topic you selected to investigate (within the broad context of viral a

A brief introduction describing the specific topic you selected to investigate (within the broad context of viral advertising). Make sure you take into account the comments/suggestions and feedback you received in Assignment I. This is your chance to improve and refine it.

Select three (3) sources from the bibliographic list and write annotation for all three according to the Guide to Annotated Bibliography 

Each annotated bibliography should be under 120-words 

  • Write your annotation in paragraph format
  • Provide a summary of the scope, main points, and central theme of the article
  • Describe any conclusions that can be drawn from the article
  • Comment on the intended audience
  • Compare or contrast this source with another you have cited
  • Point out any notable biases or gaps you detect
  • Evaluate and explain why this source is relevant or suitable for your topic

Length and format of paper:

A Word doc, double-spaced 12 pts.

The introduction of your selected topic for research should be under one (1) page long.

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Journal of Interactive Marketing 28 (2014) 43–54

Consumer Decision-making Processes in Mobile Viral Marketing Campaigns

Christian Pescher & Philipp Reichhart & Martin Spann ⁎

Institute of Electronic Commerce and Digital Markets, Ludwig-Maximilians-Universität München, Geschwister-Scholl-Platz 1, D-80539 München, Germany

Available online 22 November 2013

Abstract

The high penetration of cell phones in today’s global environment offers a wide range of promising mobile marketing activities, including
mobile viral marketing campaigns. However, the success of these campaigns, which remains unexplored, depends on the consumers’ willingness to
actively forward the advertisements that they receive to acquaintances, e.g., to make mobile referrals. Therefore, it is important to identify and
understand the factors that influence consumer referral behavior via mobile devices. The authors analyze a three-stage model of consumer referral
behavior via mobile devices in a field study of a firm-created mobile viral marketing campaign. The findings suggest that consumers who place
high importance on the purposive value and entertainment value of a message are likely to enter the interest and referral stages. Accounting for
consumers’ egocentric social networks, we find that tie strength has a negative influence on the reading and decision to refer stages and that degree
centrality has no influence on the decision-making process.
© 2013 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Keywords: Mobile commerce; Referral behavior; Sociometric indicators; Mobile viral marketing

Introduction

The effectiveness of traditional marketing tools appears to be
diminishing as consumers often perceive advertising to be
irrelevant or simply overwhelming in quantity (Porter and
Golan 2006). Therefore, viral marketing campaigns may provide
an efficient alternative for transmitting advertising messages to
consumers, a claim supported by the increasing number of
successful viral marketing campaigns in recent years. One
famous example of a viral marketing campaign is Hotmail,
which acquired more than 12 million customers in less than
18 months via a small message attached at the end of each
outgoing mail from a Hotmail account informing consumers
about the free Hotmail service (Krishnamurthy 2001). In addition
to Hotmail, several other companies, such as the National
Broadcasting Company (NBC) and Proctor & Gamble, have
successfully launched viral marketing campaigns (Godes and
Mayzlin 2009).

In general, a viral marketing campaign is initiated by a firm that
actively sends a stimulus to selected or unselected consumers.
However, after this initial seeding, the viral marketing campaign

⁎ Corresponding author.
E-mail addresses: pescher@bwl.lmu.de (C. Pescher),

p.reichhart@bwl.lmu.de (P. Reichhart), spann@spann.de (M. Spann).

1094-9968/$ -see front matter © 2013 Direct Marketing Educational Foundat
http://dx.doi.org/10.1016/j.intmar.2013.08.001

ion, In

relies on peer-to-peer communications for its successful
diffusion among potential customers. Therefore, viral market-
ing campaigns build on the idea that consumers attribute higher
credibility to information received from other consumers via
referrals than to information received via traditional advertising
(Godes and Mayzlin 2005). Thus, the success of viral marketing
campaigns requires that consumers value the message that they
receive and actively forward it to other consumers within their
social networks.

Mobile devices such as cell phones enhance consumers’
ability to quickly, easily and electronically exchange informa-
tion about products and to receive mobile advertisements
immediately at any time and in any location (e.g., using mobile
text message ads) (Drossos et al. 2007). As cell phones have the
potential to reach most consumers due to their high penetration
rate (cf., EITO 2010), they appear to be well suited for viral
marketing campaigns. As a result, an increasing number of
companies are using mobile devices for marketing activities.

Research on mobile marketing has thus far devoted limited
attention to viral marketing campaigns, particularly with respect to
the decision-making process of consumer referral behavior for
mobile viral marketing campaigns, e.g., via mobile text messages.
Thus, the factors that influence this process remain largely
unexplored. The literature on consumer decision-making suggests
that consumers undergo a multi-stage process after receiving a

c. Published by Elsevier Inc. All rights reserved.

44 C. Pescher et al. / Journal of Interactive Marketing 28 (2014) 43–54

stimulus (e.g., a mobile text message) and before taking action
(e.g., forwarding the text message to friends) (Bettman 1979; De
Bruyn and Lilien 2008). At different stages of the process, various
factors that influence consumer decision-making can be measured
using psychographic, sociometric, and demographic variables as
well as by consumer usage characteristics. Whereas previous
studies have mainly focused on selected dimensions, our study
considers variables from all categories.

De Bruyn and Lilien (2008) analyzed viral marketing in an
online environment and discussed relational indicators of
business students who had received unsolicited e-mails from
friends. This study provided an important contribution and
amplified our understanding about how viral campaigns work.
The present paper differs from the work of De Bruyn and Lilien
(2008) and goes beyond their findings in four important ways:
actor, medium, setting, and consumer characteristics. The first
difference is the actor involved. In viral campaigns, the
initiator, usually a company, sends the message to the seeding
points (first level). Next, the seeding points forward the
message to their contacts (second level), and so on. Whereas
De Bruyn and Lilien (2008) focused on the second-level actors,
the present study focuses on the first-level actors, e.g., the direct
contacts of the company. We believe that for the success of a
campaign, additional insights into the behavior of first-level
actors are very important because if they do not forward the
message, it will never reach the second-level actors. The second
difference is the medium used in the campaign. Although we
cannot explicitly rule out that participants of De Bruyn and
Lilien’s (2008) campaign used mobile devices, they conducted
their campaign at a time when the use of the Internet via mobile
devices was still very uncommon. Therefore, it is reasonable to
assume that at least the majority of their participants used a
desktop or a laptop computer when they participated in De
Bruyn and Lilien’s (2008) campaign. In contrast, the present
study explicitly uses only text messages to mobile devices. In
addition, mobile phones are a very personal media which is
used in a more active way compared to desktop or laptop
computers (Bacile, Ye, and Swilley 2014). The third difference is
the setting in which the viral campaign takes place. Whereas the
participants in the study by De Bruyn and Lilien (2008) were
business students from a northeastern US university, we conduct
a mobile marketing campaign in a field setting using randomly
selected customers. The fourth and most important difference is
that De Bruyn and Lilien (2008) focused exclusively on relational
characteristics. In addition to relational characteristics, this
paper also considers variables that describe demographic factors,
psychographic factors, and usage characteristics. As these
variables yield significant results, the study and its findings go
beyond the findings of De Bruyn and Lilien (2008).

The main goal and contribution of this work is, first, to
analyze consumers’ decision-making processes regarding their
forwarding behavior in response to mobile advertising via their
cell phone (i.e., text messages) in a mobile environment using a
real-world field study. To analyze consumers’ decision-making
processes, we use a three-stage sequential response model of
the consumer decision-making process. Additionally, we inte-
grate consumers’ egocentric social networks into a theoretical

framework to consider social relationships (e.g., tie strength,
degree centrality) when analyzing mobile viral marketing
campaigns. Thus, to understand referral behavior, we integrate
psychographic (e.g., usage intensity) and sociometric (e.g., tie
strength) indicators of consumer characteristics. We are then able
to determine the factors that influence a consumer’s decision to
refer a mobile stimulus and are able to identify the factors that
lead to reading the advertising message and to the decision to
learn more about the product.

Related Literature

Viral Marketing and Factors that Influence Consumer Referral
Behavior

Viral marketing campaigns focus on the information spread of
customers, that is, their referral behavior regarding information or
an advertisement. Companies are interested in cost-effective
marketing campaigns that perform well. Viral marketing cam-
paigns aim to meet these two goals and can, accordingly, have a
positive influence on company performance (Godes and Mayzlin
2009). Companies can spread a marketing message with the
objective of encouraging customers to forward the message to their
contacts (e.g., friends or acquaintances) (Van der Lans et al. 2010).
In this way, the company then benefits from referrals among
consumers (Porter and Golan 2006). Referrals that result from a
viral marketing campaign attract new customers who are likely to
be more loyal and, therefore, more profitable than customers
acquired through regular marketing investments (Trusov, Bucklin,
and Pauwels 2009).

Two streams of research can be identified. The first is the
influence of viral marketing on consumers, and the second is
research that has analyzed the factors that lead to participating
in viral marketing campaigns. First, previous research identified
that viral marketing influences consumer preferences and pur-
chase decisions (East, Hammond, and Lomax 2008). Further, an
influence on the pre-purchase attitudes was identified by Herr,
Kardes, and Kim (1991). In addition, viral marketing also
influences the post-usage perceptions of products (Bone 1995).

Second, previous research has identified satisfaction,
customer commitment and product-related aspects as the most
important reasons for participating in viral marketing campaigns
(cf., Bowman and Narayandas 2001; De Matos and Rossi 2008;
Maxham and Netemeyer 2002; Moldovan, Goldenberg, and
Chattopadhyay 2011). With respect to psychological motives,
self-enhancement was identified as a motive for consumers to
generate referrals (De Angelis et al. 2012; Wojnicki and Godes
2008). The importance of self-enhancement in addition to social
benefits, economic incentives and concern for others was identified
as a motive behind making online referrals (Hennig-Thurau et al.
2004). Referrals can be differentiated into positive and negative
referrals. Anxiety reduction, advice seeking and vengeance are
factors that contribute to negative referrals (Sundaram, Mitra, and
Webster 1998).

Within the referral process, the relationships and social
network position of the consumer are also influential. For
example, Bampo et al. (2008) found that network structure is

45C. Pescher et al. / Journal of Interactive Marketing 28 (2014) 43–54

important in viral marketing campaigns. Furthermore, it has
been determined that consumers are more likely to activate
strong ties than weak ties when actively searching for
information (Brown and Reingen 1987) because strong ties
tend to be high-quality relationships (Bian 1997; Portes 1998).
In addition, targeting consumers who have a high degree
centrality (e.g., quantity of relationships) leads to a higher
number of visible actions, such as page visits, than do random
seeding strategies (Hinz et al. 2011). Kleijnen et al. (2009)
analyzed the intention to use mobile services using sociometric
variables and evaluated how consumers’ network positions
influence their intentions to use mobile services. However, the
previous study contributes to the literature by analyzing a different
research question than is examined in our paper. Specifically,
Kleijnen et al. (2009) focused on the intention to use services,
while our study focuses on consumers’ decision-making processes
until they make a referral. In summary, previous research focused
on the consumers’ psychographic constructs or relationships and
social networks to explore why consumers participate in viral
marketing campaigns and why they make referrals, two constructs
that are rarely analyzed together. Iyengar, Van den Bulte, and
Valente (2011) used both constructs jointly and found that
correlations between the two are low. However, this study did
not take place in an online or mobile context but rather in the
context of referrals for new prescription drugs between specialists.
In contrast, our study analyzes both aspects together within a
mobile viral marketing campaign.

In addition to offline- or online-based viral marketing activities,
an increasing number of companies are conducting marketing
campaigns using mobile phones, and promising approaches
include mobile viral marketing campaigns. Research on mobile
viral marketing is relatively unexplored because most research in
the field of mobile marketing analyzes marketing activities such as
mobile couponing (Dickinger and Kleijnen 2008; Reichhart,
Pescher, and Spann 2013), the acceptance of advertising text
messages (Tsang, Ho, and Liang 2004) or the attitudes toward
(Tsang, Ho, and Liang 2004) and the acceptance of mobile
marketing (Sultan, Rohm, and Gao 2009). In the context of mobile
viral marketing research, Hinz et al. (2011) studied mobile viral
marketing for a mobile phone service provider and determined that
the most effective seeding strategy for customer acquisition is to
focus on well-connected individuals. In contrast to our study, their
referrals were conducted via the Internet (i.e., the companies’
online referral system) rather than via a mobile device (i.e.,
forwarding the text message immediately). Nevertheless, generat-
ing referrals using a mobile device can affect referral behavior.
Palka, Pousttchi, and Wiedemann (2009) postulated a grounded
theory of mobile viral marketing campaigns and found that trust
and perceived risk are important factors in the viral marketing
process. In comparison to our study, they used qualitative methods
and did not conduct a real-world field study. Okazaki (2008)
identified, for Japanese adolescents, consumer characteristics such
as purposive value and entertainment value are the main factors
in mobile viral marketing campaigns and that these factors
significantly influence the adolescents’ attitudes toward viral
marketing campaigns. Furthermore, both purposive value
and entertainment value are influenced by the antecedents’

group-person connectivity, commitment to the brand, and
relationship with the mobile device. In contrast to our study,
Okazaki (2008) did not analyze whether referrals were made,
nor did he analyze the referrals that were directly made via a
mobile device by forwarding the mobile text message. Instead, he
analyzed the general viral effect in the form of telling or
recommending the mobile advertising campaign. Further, our
field study analyzes the entire consumer decision-making process
for a mobile viral marketing campaign via text messages across
the three stages: from stage one, reading, to stage two, interest, to
stage three, decision to refer.

To summarize, in contrast to the existing studies in the field
of mobile viral marketing, we analyze consumers’ egocentric
networks via measures such as tie strength and degree
centrality. These sociometric factors are analyzed jointly
with psychographic constructs across the three stages in the
decision-making process. Thus, our study uses a real-world
mobile viral marketing campaign and enables us to test the
relative importance of social embeddedness and consumer
characteristics with respect to consumers’ decision to forward
mobile messages.

Decision-making Process and Specifics of the Mobile Environment

Consumer decision-making is a multiple-stage process
(Bettman 1979; De Bruyn and Lilien 2008; Lavidge and
Steiner 1961). In a viral marketing campaign, the final goal is to
generate a high number of referrals. Therefore, our model of
consumer forwarding behavior is designed for the specific
situation of mobile viral marketing campaigns.

The process and first stage begin with the consumer reading
a mobile advertising text message on his or her mobile phone.
If this text message sparks the consumer’s interest and the
consumer wants to learn more about the offered product, he/she
enters the interest stage, which is the second stage of the model.
If the consumer finds the product interesting after learning
about it, he or she makes a referral, which is the third stage of
our model (decision to refer).

In this study, we analyze the stages of the consumer
decision-making processes within a mobile environment, i.e.,
within a mobile viral marketing campaign. There are several
differences between mobile viral marketing and online or
offline viral marketing. A mobile text message is more
intrusive than an e-mail because it appears immediately on
the full screen. Consumers usually carry their mobile phone
with them and a mobile message may also reach them in a
private moment. Contrary, consumers may need to purposely
look into their e-mail accounts to receive e-mails. Therefore a
mobile message can be more personal compared to an e-mail.
In comparison to offline face-to-face referrals, mobile referrals
do not possess this personal aspect and can be transmitted
digitally within a few minutes to several friends in different
places simultaneously. This is not possible in the offline world.
Additionally, a mobile referral can reach the recipient faster
than an e-mail or an offline referral. Thus, the mobile device
may influence the referral behavior due to its faster digital
transmission of information.

46 C. Pescher et al. / Journal of Interactive Marketing 28 (2014) 43–54

Development of Hypotheses

While the factors that influence the stages of the decision-
making process can be divided into two groups, we analyze
them jointly in this study. The first group consists of the
psychographic indicators of consumer characteristics, thus
focusing on each consumer’s motivation to participate in the
campaign and his or her usage behavior. The second group of
factors includes sociometric indicators of consumer character-
istics, thus providing information about the type of relationship
that the consumer has with his or her contacts and his or her
resulting social network.

Psychographic Indicators of Consumer Characteristics

As mentioned in the related literature section, according to
Okazaki (2008), in viral marketing campaigns, purposive value
and entertainment value are the primary value dimensions for
consumers. This insight is based on the finding that consumers
gain two types of benefits from participating in sales promotions:
hedonic and utilitarian benefits (Chandon, Wansink, and Laurent
2000). Hedonic benefits are primarily intrinsic and can be
associated with entertainment value. Consumers participate
voluntarily and derive value from the fun of interacting with
peers by forwarding a referral (e.g., an ad might be of interest to
peer recipients) (Dholakia, Bagozzi, and Pearo 2004). A previous
study found that the entertainment factor influences intended use
in mobile campaigns (Palka, Pousttchi, and Wiedemann 2009).
Okazaki (2008) found that in a mobile viral marketing campaign,
the entertainment value directly influences the recipient’s attitude
toward the campaign, which, in turn, influences the recipient’s
intention to participate in a mobile viral campaign. Phelps et al.
(2004) showed that the entertainment value is a factor that
increases consumers’ forwarding behavior in viral marketing
campaigns conducted via e-mail. Thus, we may presume that
consumers who place high importance on the entertainment value
of exchanging messages are more likely to enter the reading and
interest stages than consumers who do not value entertainment to
the same degree. Additionally, the entertainment value can
also influence the decision to refer (i.e., forwarding) behavior
because a text message that addresses consumers who place
high importance on entertainment value causes the recipient to
think about forwarding the text message and motivates them
to forward the mobile advertisement to friends (i.e., decision
to refer stage).

H1. Consumers who place high importance on the entertainment
value of a message are more likely to a) enter the reading stage,
b) enter the interest stage and c) enter the decision to refer stage.

As utilitarian benefits are instrumental and functional, they
can be associated with purposive value (Okazaki 2008).
Dholakia, Bagozzi, and Pearo (2004) analyzed the influence
of purposive value in network-based virtual communities and
found that purposive value is a predictor of social identity and
a key motive for an individual to participate in virtual
communities. With respect to the mobile context, previous
research found that purposive value has a direct, significant

influence on a consumer’s attitude toward a mobile viral marketing
campaign and that this attitude significantly influences the
intention to participate in mobile marketing campaigns (Okazaki
2008). For some consumers, forwarding a (mobile) advertisement
in a viral marketing campaign can have a personal and a social
meaning (e.g., doing something good for friends by forwarding the
ad). Thus, we hypothesize that consumers who place high
importance on the purposive value of exchanging messages will
display a greater likelihood to enter the reading and interest stages.
We also hypothesize that consumers who place high importance on
the purposive value of a message are more likely to make the
decision to forward the message.

H2. Consumers who place high importance on the purposive
value of a message are more likely to a) enter the reading stage,
b) enter the interest stage and c) enter the decision to refer stage.

The intensity of usage (e.g., a high quantity of written text
messages) positively influences the probability of trial and
adoption (Steenkamp and Gielens 2003). Thus, consumers with
high usage intensities are more likely to actively participate in a
mobile viral marketing campaign. As mobile viral marketing
campaigns are a fairly new form of advertising, consumers with
high usage intensities are more likely to participate in mobile
viral marketing campaigns and are more likely to forward
messages than consumers with low usage intensities. Therefore,
we propose that usage intensity has an effect on the decision to
forward a mobile advertising text message. The likelihood of
deciding to forward the mobile advertisement increases with
the usage intensity of mobile text messages. This proposition is
consistent with Neslin, Henderson, and Quelch (1985), who
found that the promotional acceleration effect is stronger for
heavy users than it is for other consumers. Godes and Mayzlin
(2009) analyzed the effectiveness of referral activities and
argued that the sales impact from less loyal customers is
greater, but they also highlighted that this greater sales impact
does not mean that the overall referrals by less loyal customers
have a greater impact than those by highly loyal customers.
They concluded that companies who want to implement an
exogenous referral program to drive sales should focus on both
less loyal and highly loyal customers because focusing only on
highly loyal or less loyal customers is not necessarily the
cornerstone of a successful viral marketing campaign. In the
online context, a previous study found that experience with the
Internet influences channel usage behavior (Frambach, Roest,
and Krishnan 2007). Thus, as consumers with high usage
intensity are used to communicating with mobile phones, they
know how to write, read and forward mobile text messages.
Accordingly, it is likely that the threshold to forward a text
message is lower for consumers with high usage intensity than
it is for other consumers and that such consumers are thus more
inclined to refer. Further, the minimal effort required to directly
forward a mobile text message via a cell phone increases the
decision to refer. Thus, we hypothesize that heavy mobile users
will be more likely to refer than will light users.

H3. The usage intensity of the referral medium has a positive
influence on the likelihood of making the decision to refer.

47C. Pescher et al. / Journal of Interactive Marketing 28 (2014) 43–54

Sociometric Indicators of Consumer Characteristics

Sociometric indicators describe the interaction structure of
an individual consumer with his or her surroundings. When
consumers receive an interesting mobile advertising message, it
is likely that they want to find out more about it. Once the
consumer has visited the product homepage, he or she then
considers not only whether the message is worth forwarding but
also to whom it should be forwarded.

Sociometric indicators provide information about the social
network of each individual consumer. This individual network
influences the likelihood of knowing someone who may be
interested in the offered product. Thus, social networks have a
significant impact on the decision-making process in a viral
marketing campaign. The decision to forward the mobile
advertising message depends on two factors: the quality and the
quantity of relations, i.e., the tie strength and the degree centrality.

Tie strength is an important factor in viral marketing and
increases with the amount of time spent with the potential
recipient and with the degree of emotional intensity between
the sender and the potential recipient (Marsden and Campbell
1984). Consumers perceive strong ties to be more influential
than weak ties (Brown and Reingen 1987) because the strong
ties seem more trustworthy (Rogers 1995). Therefore, because
consumers are more motivated to provide high-value informa-
tion to strong ties (Frenzen and Nakamoto 1993), tie strength is
an indicator of the quality of the relationship.

Reagans and McEvily (2003) studied how social network
factors influence knowledge transfer at an R&D firm. To
measure the tie strength, they used two items that are analogous
to those that we used (Burt 1984). Their results indicated that
tie strength positively influences the ease of knowledge
transfer. Thus, network ties increase a person’s capability to
send complex ideas to heterogeneous persons. Overall, they
highlighted the importance of tie strength with respect to the
knowledge transfer process, and they postulate that tie strength
holds a privileged position. Other studies found that weak ties
make non-redundant information available (Levin and Cross
2004). In an online setting, participants were more likely to
share information with strong ties than with weak ties (Norman
and Russell 2006). With respect to viral marketing conducted
via e-mail, previous research has found that tie strength has a
significant influence on whether the recipient examines an
e-mail message sent from a friend (i.e., opens and reads the
message) (De Bruyn and Lilien 2008). Tie strength was also
determined to be less relevant in an online setting compared to an
offline setting (Brown, Broderick, and Lee 2007). In a non-mobile
or non-online context, stronger ties are more likely to activate the
referral flow (Reingen and Kernan 1986). Furthermore, tie
strength is positively related to the amount of time spent receiving
positive referrals (van Hoye and Lievens 1994).

As previously mentioned, research on word-of-mouth behav-
ior has shown that people engage in word-of-mouth for reasons
such as altruism (Sundaram, Mitra, and Webster 1998). However,
Sundaram, Mitra, and Webster (1998) did not control for the
quality of a relationship between sender and recipient. Research
concerning referral reward programs has identified that offering a

reward increases the referral intensity and has a particular impact
on weak ties (Ryu and Feick 2007). Brown and Reingen 1987
found that while strongly tied individuals exchange more
information and communicate more frequently, weak ties play
an important bridging role. Additionally, Granovetter (1973)
stated that one is significantly more likely to be a bridge in the
case of weak ties than in strong ties. In job search, when using
personal networks, it was found that weak ties have a higher rate
of effectiveness when addressing specialists for jobs compared to
strong ties (Bian 1997) and that the income of people using weak
ties was greater than those who used strong ties (Lin, Ensel, and
Vaughn 1981). At the information level, consumers who are
connected via strong ties tend to share the same information
that is rarely new to them, while consumers obtain important
information from weak ties who tend to possess information that
is “new” to them (Granovetter 1973). Consistent with this
finding, Levin …

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