Características de la población de la comunidad de San Juan

Desire for social interaction, concern for other customers, the motivation for economic incentives, and the potential to enhance one’s own self-worth have been established and accepted as primary motivations for engaging in eWOM (Hennig-Thurau et al., 2004). While “The marketplace is an important domain for everyday helping behavior” (Price et al., 1995, p. 262), “our willingness to share is motivated by our basic human need to be helpful by giving advice” (Smith et al., 2007, p. 387).

It is well-established in the literature that people perceive consumer recommendations as more trustworthy than those of experts (Huang and Chen, 2006). In their influential work, Feick and Price (1987) identified the concept of a “market maven” who is an individual with general marketplace knowledge or expertise. A market maven’s influence is in direct contrast to an opinion leader with product-specific knowledge or

expertise. “Research suggests that consumers are able to identify market mavens, use them in making consumption decisions, and distinguish them from individualswith product-based expertise” (Feick and Price, 1987, p. 94). With an ability to differentiate between expert and consumer online recommendations (Huang and Chen, 2006), it is with confidence and common enjoyment that people seek out valuable information (Smith et al., 2007). Therefore, online consumers have confidence in the validity of consumer-provided information online, enjoy interacting with other consumers online, and rely on a network of consumers with marketplace knowledge or expertise to guide their purchase decisions.

Motivation Key studies Social network site studies

Social benefits Hennig-Thurau et al. (2004): social benefits Daugherty et al. (2008): social function Nadkarni and Hofmann (2012): need to belong

Chu and Kim (2011): trust, normative influence Self-enhance ment Hennig-Thurau et al. (2004): extraversion/self-enhan cement Daugherty et al.

Nadkarni and

Hofmann (2012): need for self presentation

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(2008):

Extraversion Hennig-Thurau et al. (2004): extraversion/self-enha ncement Dissonance reduction Altruism Daugherty et al. (2008): ego-defensive Hennig-Thurau et al. (2004): concern for other consumers Economic incentives Hennig-Thurau et al. (2004): economic incentives

Table 6 Motivations of WOM

Note: The “Motivation” column shows the present study’ categorization of eWOM motivation constructs for creating eWOM volume based on literature review. The location of the citations indicates the motivation and the context studied. The term following each citation is the specific term used in that study.

Hennig-Thurau et al.’s (2004) analysis showed that the fre- quency of platform visits and comment writing are correlated with different sets of motivations. This hints that individual eWOM behaviors might correspond to different sets of motivations, which is likely in the context

of media choice. Schindler and Bickart (2005) argued that consumers’ choice of an online platform for reading eWOM varies based on the consumer’s motivation. Since posters are also readers, the type of site is likely to be important when posters are deciding where to post reviews (Bronner and de Hoog, 2011). The eWOM content and where to post the eWOM are intrin- sically linked (Wilson et al., 2012).

Based on a review of 42 academic studies on Facebook use, Nadkarni and Hofmann (2012) concluded that the need to belong and the need for self-presentation are the primary motivations for using Facebook. Chu and Kim (2011) argued that a key motivation for engaging in eWOM on social network sites may be establishing and maintaining personal social networks. Wilson et al. (2012) also found that posting on social network sites is positively correlated to wanting to share experiences, especially positive ones, with friends.

Seeding strategy

Marketers may control is how to start the viral campaign in social website—what usually is referred to as the “seeding strategy.” A seeding strategy involves determining how many initial consumers (“seeds”) are needed to disseminate a viral message to and what types of consumers to choose as seeds.

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According to Hinz et al. (2011), to achieve successful WOM campaign, firms must consider four critical viral marketing success factors: (1) content, in that the attractiveness of a message makes it memorable (Berger and Milkman 2011; Berger and Schwartz 2011; Gladwell 2002; Porter and Golan 2006); (2) the structure of the social network (Bampo et al. 2008); (3) the behavioral characteristics of the recipients and their incentives for sharing the message (Arndt 1967); and (4) the seeding strategy, which determines the initial set of targeted consumers chosen by the initiator of the viral marketing campaign (Bampo et al. 2008; Kalish, Mahajan, and Muller 1995; Libai, Muller, and Peres 2005). This last factor is of particular importance because it falls entirely under the control of the initiator and can exploit social characteristics (Toubia, Stephen, and Freud 2010) or observable network metrics.

The conventional wisdom adopts the influentials hypothesis, which states that targeting opinion leaders and strongly connected members of social networks (i.e., hubs) ensures rapid diffusion Iyengar, Van den Bulte, and Valente 2011). However, recent findings raise doubts. Van den Bulte and Lilien (2001) show that social contagion, which occurs when adoption is a function of exposure to other people’s knowledge, attitudes, or behaviors (Van den Bulte and Wuyts 2007), does not

necessarily influence diffusion, and yet it remains a basic premise of viral marketing. Such contagion frequently arises when people who are close in the social structure use one another to manage uncertainty in prospective decisions (Granovetter 1985). However, in a computer simulation, Watts and Dodds (2007) show that well-connected people are less important as initiators of large cascades of referrals or early adopters. Their finding, which Thompson (2008) provocatively summarizes by implying “the tipping point is toast,” has stimulated a heated debate about optimal seeding strategies, though no research offers an extensive empirical comparison of seeding strategies. Van den Bulte (2010) thus calls for empirical comparisons of seeding strategies that use sociometric measures (i.e., metrics that capture the social position of people). In response, Hinz et al (2011) undertook an empirical comparison of the success of different seeding strategies for viral marketing campaigns and identify reasons for variations in these levels of success and suggest that seeding to well-connected people is the most successful approach because these attractive seeding points are more likely to participate in viral marketing campaigns.

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2.2.2 NETWORK TOPOLOGY AND THE DEVELOPMENT OF