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ScienceDirect 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: [email protected] (C. Pescher),

[email protected] (P. Reichhart), [email protected] (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 …

Forster 17

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