Understanding Willingness to Pay for Social Network Sites

Abstract

The authors investigate how perceived customer value can be translated into economic returns for online social network sites (SNS). The (joint) impact of two value propositions, social capital and entitativity, is assessed. Perceived economic and social customer value are investigated as outcomes of these propositions. Two studies reveal that entitativity and social capital impact members’ willingness to pay (WtP) membership fees, either directly or indirectly. Moreover, the predictive ability of perceived economic and social customer value regarding WtP depends on the type of membership and the type of social network. SNS providers are advised to emphasize the benefits their users actually take advantage of. While for professional SNS, it seems advisable to stress both social and economic value, particularly for premium members, in socially oriented SNS premium members seem to be driven more by social value. Other theoretical and managerial implications are discussed.

Keywords

entitativity online social networks social capital upselling willingess to pay

A recent comScore report (2011) is just one of the many market surveys that confirms that online social network use is still increasing rapidly. Social network sites (SNS) are online communities that facilitate communication and interactions among members and allow them to share personal content (Trusov, Bucklin, and Pauwels 2009). While some global SNS dominate the market, there is a multitude of smaller, more focused networks. For instance, there are SNS set up to reconnect with (former) friends (e.g., Classmates.com) and those that serve the purpose of networking professionally (e.g., LinkedIn). In view of this diversity and increased competition, knowledge with regard to sustainable business models for online social networks is needed. While many SNS services are currently free, providers’ desire to capitalize on members’ online interactions is leading to the adoption of alternative business models. One example is the “freemium” strategy, where basic service is available to consumers for free, whereas upgraded, premium services are only accessible against payment of a subscription fee (Ritzer and Jurgenson 2010). The freemium strategy is applied by both professional business SNS and more socially oriented networks. Insights on the economic returns, however, are inconclusive. While Enders et al. (2008, p. 209) suggest that revenue models for SNS based on paid subscriptions depend on a “critical mass of users,” little is known about mechanisms that drive such models. As SNS providers are looking for value propositions to attract and retain members profitably, this article explores how value can be translated into willingness to pay (WtP) for SNS.

Our study identifies two value propositions that positively affect members’ WtP subscription fees, either directly or indirectly. To begin with, social capital has been described as relationships between and within groups that can be regarded as a resource for social action (Nahapiet and Ghoshal 1998). As a resource, it creates value for members of a social network, for instance, in the form of information or solidarity (Adler and Kwon 2002). Past research has suggested the existence of a genuine community based on strong feelings of “we-ness” (Mathwick, Wiertz, and de Ruyter 2008), but explicit research on this phenomenon has remained underexposed. In order to assess whether people perceive a SNS as a coherent entity, we posit that the concept of entitativity may serve as a value proposition complementary to social capital. Furthermore, we introduce economic value in addition to social and functional value propositions that have hitherto been considered in the context of online collectives. The consideration of consumers’ economic benefits seems critical when studying their WtP membership fees, particularly when considering SNS with different, namely professional and social, purposes. Our study aims to make three important contributions.

First, we introduce the concept of entitativity, which has been described as “(t)he degree to which a collection of persons are perceived as being bonded together in a coherent unit” (Lickel et al. 2000, p. 224), or simply the “groupness” of a group (Hamilton, Sherman, and Castelli 2002, p. 140). To our knowledge, entitativity has not hitherto been applied in the context of online social networks. Second, we examine the impact of entitativity, alongside social capital on WtP, and hence economic value for SNS providers. In addition to such a direct influence, we examine potential indirect routes incorporating social, economic, and functional value as consequences of entitativity and social capital. Finally, we account for heterogeneity by differentiating between free and upgraded, fee-paying members, as we expect their motivations for investing in memberships fees to differ. Also, we examine the aforementioned issues across two different SNS (i.e., social vs. professional focus). To achieve these contributions, the remainder of this article is structured as follows. The next section addresses the theoretical background and research hypotheses, followed by a description of the two empirical studies. The last section discusses the findings and implications of the study, including directions for future research.

Theoretical Background

SNS and WtP

SNS represent only one type of social media, which is an umbrella term that also includes content communities (e.g., YouTube), blogs, collaborative projects (e.g., Wikipedia), virtual social worlds (e.g., Second Life), and virtual game worlds (e.g., World of Warcraft). While some SNS focus more on networking, thereby connecting new people online, others primarily help members to (re-)connect to existing relations who are already part of their offline networks. The strength of connections among members may hence differ across networks and can range from loose associations that provide valuable information to members, to strong ties, including close friends or family members (van Noort, Antheunis, and van Reijmersdal 2012). For instance, some SNS were set up as professional business networking sites (e.g., LinkedIn, Xing), while others represent socially organized SNS which aim to (re-)connect existing and close relationships (e.g., Facebook, Classmates.com). This research investigates both types of SNS to provide a more comprehensive picture.

Despite a growing number of studies on SNS, research on consumers’ WtP for SNS use has been scarce. SNS members’ WtP relates to both members’ intention to upgrade their current free accounts to a fee-based account, and their intention to extend their paid membership period. While many academic studies have discussed consumers’ WtP in the context of e-commerce or online brand communities, they paid considerably less attention to users’ WtP for online content, not to mention to the specific case of SNS, where users themselves cocreate value. Different from traditional marketing contexts, the peculiarities of online content or value as a paid product (e.g., lack of uniqueness, many alternatives, and little differentiation) constitute challenges for online service providers. The few studies available on this topic either focused on price promotions and marketing communications, the quality of the content or service (e.g., up-to-date, superior, or exclusive content), or the perceived risks with regard to online credit card use or unknown brands (Pauwels and Weiss 2008; Wang et al. 2005). While online content providers can reasonably control most of these factors, operators of online SNS depend on the value proposition of connectivity, and have to rely on members’ willingness to contribute to the group and to stay loyal and/or pay subscription fees. Surprisingly little is known regarding how to transform social interactions in online social networks into benefits for profit-oriented providers, a process that requires “a deep understanding of the economic and social motivations of the participants” (Balasubramanian and Mahajan 2001, p. 104). An exploratory case study investigation by Enders et al. (2008) suggests that the success of paid subscription models for SNS may, among more functional factors, also depend on members’ trust in other users and the platform, as well as on their social interactions and network ties. As social capital and entitativity reflect these factors, we will argue that both concepts will drive SNS members’ WtP. We develop a rationale for this argument in the next section.

Value Propositions for SNS

Entitativity

As mentioned above, entitativity depicts to what extent aggregates of people can be described as a single meaningful and ongoing entity, being bonded together in a coherent unit (Lickel et al. 2000). The degree of entitativity differentiates perceptions of mere aggregates or collections of individuals, such as people waiting at a bus stop (Igarashi and Kashima 2011) from unified groups that are perceived as meaningful entities, such as a football team (Lickel et al. 2000). Drawing on Gestalt principles, Campbell (1958) identified several characteristics that influence individuals’ perceptions of entitativity, such as similarity and proximity among individuals, sharing a common fate (e.g., collective goals) and collective movement. In addition, Lickel et al. (2000) reports that the degree of interaction among group members and the importance assigned to the group by its members drives entitativity perceptions. In contrast, certain group demographics, such as size and tenure of existence, have been reported to be either unrelated to the level of perceived entitativity or to cause conflicting results (cf. Hamilton, Sherman, and Castelli 2002; Lickel et al. 2000).

Based on the level of perceived entitativity, scholars have categorized groups along a continuum ranging from high to low levels of entitativity, namely intimacy groups, social categories, task groups, and loose associations. Typical examples comprise members of a family, friends, or romantic relationships for intimacy groups; a common nationality, ethnic, or professional background for social categories; an airline flight crew or a company committee for task groups; and people at a bus stop or a queue at the bank for loose associations (Lickel et al. 2000; Sherman, Hamilton, and Lewis 1999). Lickel et al. (2000) suggested that social rules governing interactions among members may differ for these groups in a way that intimacy groups may be dominated by communal exchange principles, whereas task groups may be regulated by equity principles.

The conceptualization of entitativity strongly builds on literature describing how individuals perceive groups they do not belong to (i.e., out-groups), as it mainly aimed to understand how perceivers judge to what extent a collection of individuals constitutes a group (Sherman, Hamilton, and Lewis 1999). This is different from other concepts of group perceptions, such as social identification, which derived from studies on in-group–out-group differentiation with a primary focus on one’s in-group (Sherman, Hamilton, and Lewis 1999). Social identification, which has been described as “the perception of oneness with or belongingness to some human aggregate” (Ashforth and Mael 1989, p. 21), thus primarily focuses on the self, and provides little information about the relationships among other group members, and is thus conceptually different from entitativity.

This is corroborated by empirical evidence. Previous studies detected a positive correlation between the concepts, but also found evidence for their distinctiveness after applying confirmatory factor analysis¹ (e.g., Castano et al. 2002; Lickel et al. 2000). Recent studies support the conceptualization of identification as an outcome of entitativity (e.g., Lickel et al. 2000). It has been empirically confirmed that there is a causal link from entitativity to social identification (e.g., Correll and Park 2005; Jans, Postmes, and van der Zee 2011). Furthermore, a full mediational role of entitativity between the concept’s antecedents and social identification has been reported. For instance, a study by Castano, Yzerbyt, and Bourguignon (2003) found that the extent to which respondents perceived the European Union as an entity influenced their identification with it. The concept of entitativity can thus help ascertain the motives for identification (Castano, Yzerbyt, and Bourguignon 2003).

Other group concepts used in extant studies, such as in-group homogeneity, only constitute one dimension of entitativity, and are hence conceptually different (Castano, Yzerbyt, and Bourguignon 2003; Hogg et al. 2007). It has even been suggested that homogeneity might be a less important component of entitativity (Hogg et al. 2007), a notion that finds support in a study by Jans, Postmes, and van der Zee (2011). The authors found that for the specific case of inductively formed groups (i.e., groups that are formed by the contributions of individuals), it is individual distinctiveness among members, and hence the opposite of similarity or homogeneity, that drives entitativity perceptions. Again, other studies in the field of online (brand) communities referred to a strong group feeling, weness or consciousness of kind, a characteristic that is regarded as the most important of the three traditional characteristics or markers of communities (Muniz and O’Guinn 2001).

In view of the variety of group concepts used in previous studies, the added value of entitativity can be found in its use as a theoretical umbrella concept that helps to understand “a series of otherwise disparate phenomena in stereotyping, impression formation, and intergroup relations literature” over the last decade (Castano, Yzerbyt, and Bourguignon 2003, p. 735; see also Castano et al. 2002). Online SNS differ widely in terms of size or purpose and may hence range from tight-knit entities to loose aggregates of anonymous members. Entitativity, to our knowledge, has not been applied to research on online social networks. Igarashi and Kashima (2011) studied entitativity from the perspective of offline social networks, with individuals judging other groups based on the representation of abstract network graphs. Their findings suggest that network entitativity depends strongly on the level of interaction among members. Moreover, the authors conclude that in very small networks (i.e., up to five members) perceptions of entitativity may be based mainly on ties among dyads, whereas for larger networks (i.e., up to 150 members), entitativity perceptions depend on how social connections are organized into a meaningful unit. These findings underline the importance of considering the concept of entitativity in research on SNS, as it extends the idea of relationship dyads, which has received considerable attention by researchers who focused on tie strength in online contexts. Moreover, the distinctive scope denoted by a highly entitative group could serve as an important value proposition for SNS, and may hence be key for a successful online revenue model.

Social capital

Social capital has been identified as an important value proposition of online communities (e.g., Chiu, Hsu, and Wang 2006; Wasko and Faraj 2005). The concept has been the subject of much debate and a variety of definitions have been developed. A common dominator is that social capital essentially reflects that relationships between and within groups can be regarded as a resource for social action (Nahapiet and Ghoshal 1998). This is central to the widely used definition that was introduced by Nahapiet and Ghoshal (1998, p. 243): “the sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit.” Research has confirmed that people use their personal contacts, and hence the social capital endowed in these relations, to find jobs, exchange resources, or for product innovations and entrepreneurship (Adler and Kwon 2002).

Social capital is often defined in terms of attributes, such as social trust, norms and sanctions (e.g., the norm of voluntarism), obligations and expectations (e.g., the obligation to reciprocate), identification, and commitment, which various studies have combined in different ways (Coleman 1988; Nahapiet and Ghoshal 1998; Wasko and Faraj 2005). While these dimensions differ conceptually, they are connected, as members of a social collective are willing to provide favors to other members, even to strangers (i.e., voluntarism), as they believe (i.e., trust) that those favors will be returned by some community member in the future (i.e., reciprocity). In other words, trust, which is safeguarded by established community norms and sanctions for free riders, facilitates exchanges between members.

In an online context, several studies have focused on social capital as a driver of knowledge sharing. For instance, Wasko and Faraj (2005), who investigated an online network linking members of a legal professional association in the United States, concluded that online social capital can spur knowledge exchange. Similarly, Chiu, Hsu, and Wang (2006) found that tie strength, reciprocity, and identification all enhanced the quality of knowledge shared, while trust only had a positive impact on the quality of knowledge contributed to a professional online community. Mathwick, Wiertz, and de Ruyter (2008) took a different outcome focus. They studied the impact of social capital on the values derived for the members of a peer-to-peer problem-solving community, and how those benefits in turn influenced their commitment toward the group.

Hypotheses Development

The Direct Route

Entitativity and willingess to pay (WtP)

Due to the meaningfulness and coherence that highly entitative groups convey, individuals generally perceive them as very stable, controllable, and predictable. These characteristics are generally highly valued by group members (Sherman, Hamilton, and Lewis 1999). Therefore, past research suggests that highly entitative groups serve their members better than groups that one perceives as low in entitativity (Yzerbyt et al. 2000). As members strive for continuity and permanence of groups from which they derive value, they are likely to be committed and willing to invest in groups they perceive as highly entitative (Sherman, Hamilton, and Lewis 1999). Or as Yzerbyt et al. (2000, p. 286) put it: “Clearly, entitativity cements the members to their group.” Drawing on this reasoning, we expect members of a SNS who perceive their network as a meaningful and ongoing entity to commit time and resources to safeguard the valuable group feeling. As in the freemium business model, advanced functionalities and possibilities for interaction are usually restricted to upgraded members who pay subscription fees, thus we anticipate that members with high entitativity perceptions show higher WtP for SNS use to ensure multiple and sustained interactions with their network:

Hypothesis 1a: Entitativity will positively impact SNS members’ intentions to pay for online social network use.

Social capital and WtP

Scholars have argued that social trust enhances communication, resource exchanges, and cooperation (Bolino, Turnley, and Gloodgood 2002). Enders et al. (2008) report that trust is a main driving force for online financial transactions. On the basis of this, we expect trust to be an important factor impacting SNS members’ decision whether to pay subscription fees or not. If members do not trust the site operator or other members in the social network, they will perceive a higher risk with regard to committing financial resources when paying subscription fees. A second social capital dimension, reciprocity, is regarded as a norm of mutual indebtedness. The internalization of this norm obliges the person or the party that has received a benefit to repay the favor at some time (Gouldner 1960), which ensures a stream of ongoing exchanges, including favors that may be returned to the sender directly, or the community more generally. The latter notion, also termed generalized exchange or reciprocity, assumes that each member of a social network gives to another. Finally, community voluntarism, which has been described as “proactive engagement in community life” (Mathwick, Wiertz, and de Ruyter 2008, p. 834), includes the voluntary provision of time and effort with the intent to benefit others. The dimensions reciprocity and voluntarism are both likely to drive social interactions as SNS members perceive a moral duty to reciprocate the value they receive by volunteering their time or efforts. These moral obligations ensure an ongoing stream of interactions, which, according to Enders et al. (2008, p. 207), may create “unique customer value” and hence positively affect members’ WtP subscription fees. Therefore, we hypothesize:

Hypothesis 1b: Social capital will positively impact SNS members’ intentions to pay for online social network use.

The Indirect Route

We also propose an indirect route, suggesting that entitativity and social capital will result in specific value for members, which in turn will favorably affect their WtP. Recent studies on online networks have identified a variety of drivers for user participation, including social, functional/informational, and hedonic benefits (e.g., Dholakia et al. 2009; Wang and Fesenmaier 2004). Social benefits are derived from socializing and building relationships with others, and may result in an increased social network and the enjoyment of communication. Functional benefits, on the other hand, are mostly associated with users’ access to valuable information provided by other community members (e.g., Dholakia et al. 2009), and have also been termed informational value in previous research. Interestingly, despite an acknowledgment of members’ instrumental motivations for participating in online communities, recent research has largely neglected the explicit notion of economic motives.

Entitativity and social value

Perceived social value or benefit has been defined as the perceived utility acquired through one’s association with specific social groups (e.g., based on demographics, socioeconomic, or cultural-ethnic factors). Perceived social value is reflected by social support, intimacy, and friendship, which is acquired through one’s communication and involvement with others (e.g., Dholakia, Bagozzi, and Klein Pearo 2004; Wang and Fesenmaier 2004). The utility inherent to perceived social value has been described as “the knowledge that the entire community is there to be tapped, should the need arise” (Mathwick, Wiertz, and de Ruyter 2008, p. 836). Relationships yielding such benefits are usually characterized by a high level of closeness, group solidarity, expectations that exchanges will be continued in the future, and strong prevailing norms of giving and receiving for the group’s well-being (Gassenheimer, Houston, and Davis 1998). Groups perceived as high in entitativity due to high degrees of interaction, common goals and outcomes should derive higher value for their members compared to less entitative groups (cf. Sherman, Hamilton, and Lewis 1999). As studies on entitativity have associated high entitativity with intimacy and friendship, we hypothesize a positive influence of entitativity on perceived social value.

Hypothesis 2a: Entitativity will positively impact SNS members’ perceived social value.

Social capital and social value

Among the benefits to be derived from social capital that the literature has discussed most frequently are (1) access to a variety of information sources, which may enhance the quality, importance and timeliness of information and (2) solidarity, which is strengthened by strong social norms and a high degree of closure² (Adler and Kwon 2002). While such benefits are most frequently mentioned in the context of social capital created offline (e.g., in neighborhood communities, company networks), informational and perceived social benefits have also been identified as an outcome of social capital by Mathwick, Wiertz, and de Ruyter (2008) in the context of online communities. Therefore, we hypothesize:

Hypothesis 2b: Social capital will positively impact SNS members’ perceived social value.

Entitativity and economic value

We posit that the benefits and value to be derived from high levels of entitativity will not only be restricted to the social sphere, but encompass economic advantages (i.e., direct and indirect financial benefits) for group members as well. The entitativity literature suggests that for high entitativity, perceptions of the in-group are positively biased in a way that members perceive the group as more capable of realizing positive achievements relative to in-groups low in entitativity (Sherman, Hamilton, and Lewis 1999). Yzerbyt et al. (2000) argued that high entitativity perceptions may increase members’ expectations that the group will act upon its intentions and that it is more likely to accomplish its goals. According to the authors, it is this potency and efficacy of groups that attracts members to join, not only the desire of belonging to a group. It is therefore expected that the positive bias toward a highly entitative in-group with regard to its perceived efficiency, potential, and readiness to act will influence SNS members’ evaluations of the economic value they realized by participating in the group. Moreover, a study by Grayson (2007) demonstrated that friendship relations, which are representative of high levels of entitativity (Lickel et al. 2000; Sherman, Hamilton, and Lewis 1999), can have a favorable impact on business outcomes. The author attributed this positive effect partly to high levels of loyalty, helpfulness, and openness among friends. Drawing on the reasoning above we hypothesize:

Hypothesis 3a: Entitativity will positively impact SNS members’ realized economic value.

Social capital and economic value

In the literature on economic sociology, it has been argued that embeddedness of relations in social networks can positively impact trust and reciprocity, which facilitate the exchange of private resources that otherwise might be difficult to get hold of through market relationships (cf. Uzzi 1999). We argue that access to information about job opportunities, special offers or business contacts will increase SNS members’ likelihood of realizing actual economic benefits. Hence, we hypothesize that social capital will have a positive impact on SNS members’ realized economic value.

Hypothesis 3b: Social capital will positively impact SNS members’ realized economic value.

The Moderating Role of Member Heterogeneity in Online Social Networks

We argue that heterogeneity in the membership base of a SNS (i.e., free vs. fee-paying) is likely to influence the effects of social and economic value on WtP. Falk, Hammerschmidt, and Schepers (2010), for instance, show that functional-utilitarian benefits to be derived from e-service sites are more important for inexperienced users. For experienced, long-term users, on the other hand, higher-order benefits (e.g., hedonic benefits) gain increasing importance. Other studies support this stating that instrumental benefits are essential for consumers’ first visit or choice of online service channels or communities (Dholakia, Bagozzi, and Klein Pearo 2004). Drawing on the relationship characteristics of both types of relationship, Gassenheimer, Houston, and Davis (1998) suggest that transactional exchanges are associated rather with economic value, whereas social value is more important for relational/communal relationships. Therefore, we argue that SNS members’ motivations to pay subscription fees will differ between member types. In particular, we believe that premium members’ relationships in online networks will be based rather on relational exchanges, relative to regular members, as the fact that they are already paying subscription fees is likely to be associated with increased use of the SNS. Their relationships with other SNS members are hence likely to be communal, being described by a feeling of sincere concern for the exchange partner’s welfare. This is corroborated by Bhattacharya (1998) who concluded that tangible benefits such as discounts or not having to pay fees does not drive willingness to renew subscriptions. Regular members’ relationships, on the other hand, may rather be based on transactional exchanges. In freemium-based business models, the functionalities of SNS available to regular members are limited. Regular members’ interactions in the online network will therefore be less frequent and intense and hence characterized by the principle of exchange relationships. As exchange partners do anticipate future exchange, but do not expect to receive monetary repayment in return for their help according to the communal principle (Ryu and Feick 2007), we expect economic value to be a stronger driver of WtP for regular members, relative to premium members. Moreover, premium members enjoy the social benefits of more personalized interactions due to premium functionalities associated with an upgraded account. Therefore, we hypothesize:

Hypothesis 4: Social value will have a more positive impact on WtP for premium members, compared to regular members.

Hypothesis 5: Economic value will have a more positive impact on WtP for regular members, compared to premium members.

Study 1

Sample and Procedure

We conducted Study 1 among registered members of an online SNS with the primary purpose of helping members find and interact with former classmates and friends. The SNS hence principally serves a social purpose. Registered members need to indicate the educational institutions they attended, which directs their connections to former classmates, and hence to a network of people they may know. Registered members can create a personal profile, upload photos and other personal information, and use the online service either for free, or upgrade their account against payment of an annual fee. Premium members enjoy certain benefits that are not available to nonpaying, so-called regular members, such as sending personalized messages or being able to see who has viewed one’s profile.

We posted a link to an online survey in a newsletter sent out to registered members during a period of 2 weeks. After the omission of missing values, our sample consisted of 5,738 usable responses, including 3,458 regular and 2,280 premium members. In both subsets, there are slightly more female respondents (regular: 54% and premium: 63%). With regard to age, the distribution of the sample is skewed toward higher age categories (regular: 61% > 45 years old and premium: 68% > 45 years), which corresponds with the distribution of the SNS’s actual member base, as the focus is on helping individuals to reconnect with former classmates and share memories of the past.

Measures

With the exception of economic value, our measures are based on past studies and were adapted to fit the context of our study. We used 7-point Likert-type scales for all items, anchored by strongly disagree/agree. We measured entitativity with 3 items, asking respondents to what extent they perceived that users of the SNS (1) formed an entity, (2) had a bond, and (3) were a unity. Social capital was measured by the three components trust, reciprocity, and volunteerism. We developed 3 items for trust, 3 for reciprocity (e.g., importance of giving and receiving on the SNS, contributing to the SNS), and 5 for voluntarism (e.g., helping others to find information). We modeled social capital as a formative latent construct determined by three reflective dimensions. The perceived social value measure (3 items) was adapted from Mathwick, Wiertz, and de Ruyter (2008). We identified potential economic benefits to be derived from SNS by browsing various SNS. Based on members’ activities on SNS such as LinkedIn, Facebook, and others, we identified several categories, such as job- or study-related aspects, finding accommodation or receiving advice with regard to products. Many SNS even include separate sections for searching and advertising jobs, internships, apartments, or for buying and selling goods or services, reflecting existing demand for such services. Since these are reflective of financial gains that members may derive, from these, we developed a 4-item measure for economic value. WtP was measured with a single item which was phrased differently for regular and premium members. For all items, see the Appendix.

Measurement Model and Analysis Approach

We employed partial least squares-structural equation modeling (PLS-SEM). Different from covariance-based (CB-) SEM techniques (e.g., Lisrel, AMOS), PLS is more prediction oriented and aims to maximize the explained variance in the dependent outcomes (Henseler, Ringle, and Sinkovics 2009). While PLS-SEM is generally regarded as an alternative and sometimes complementary technique to CB-SEM, PLS-SEM is explicitly recommended for models including formative measurement constructs. This is particularly the case for second-order molar models, where a second-order formative latent construct (in our case social capital) is formed by several first-order reflective latent constructs (i.e., reciprocity, voluntarism, trust). We modeled the second-order construct by using the hierarchical component model, where the indicators of the first-order reflective constructs are repeated to measure the second-order formative construct.

We conducted our analyses with SmartPLS 2.0 software (Ringle, Wende, and Will 2005).³ We followed the advocated two-step procedure of evaluating the measurement model first, followed by an estimation of the structural model. While the results of the measurement model resemble the outcomes of principal component analyses, the path coefficients calculated as part of the structural model can be interpreted in a similar way as the β coefficients in an ordinary least squares regression.

Results—Measurement Model Evaluation

In order to assess the psychometric properties of the multiple item scales, we estimated the measurement model by calculating individual indicator reliabilities, composite reliability (CR), convergent validity, and discriminant validity (e.g., Henseler, Ringle, and Sinkovics 2009). To do so, we ran the PLS algorithm (path weighting scheme) and bootstrapping procedure (500 samples).

To assess the reliability of individual items, we checked whether the loading of each item on its respective latent construct was higher than the recommended threshold of .7. While 1 item loading fell slightly below this threshold, all loadings were significant (t-statistic > 1.96) and hence retained. The literature recommends removing reflective items only if their loadings are smaller than .4 (Henseler, Ringle, and Sinkovics 2009). To assess the internal consistency, we evaluated the CR scores for each latent construct. They all exceeded the recommended threshold of .7, which is considered satisfactory (Table 1). CR scores are interpreted in a similar way as Cronbach’s α, which PLS calculates as well. AVE scores (average variance extracted) indicate the level of convergent validity as they specify the amount of shared variance between reflective measurement items and their respective latent construct. All AVE scores in Study 1 are higher than .5 (Table 1). We assessed discriminant validity in two ways: first, according to the Fornell-Larcker criterion, each latent construct should share more variance with its own block of indicators than with any other latent variables from the model. Therefore, the AVE score of a latent variable should be higher than the construct’s squared correlation with any other latent variable, which is confirmed for our models. As a second test to assess discriminant validity, we observed that each indicator’s loading was higher than all of its cross-loadings with other latent variables. Overall, our assessment supports the reliability and validity of our reflective measurement model. As suggested for formative measurement models, we also examined the degree of multicollinearity among the three social capital components. We calculated the variance inflation factor (VIF = 1 / [1 − R²]), which should be lower than 10, and ideally lower than 5. Calculations showed that multicollinearity was not a problem as the mean VIF for social capital was 1.37.⁴

Table 1.

Composite Reliability (CR), Average Variance Extracted (AVE), Cronbach’s α (CA), Correlations.

	CR	AVE	CA	ENT	EV	RECIP	SV	TRUST	VOLUNT	WtP
Entitativity (ENT)	.95	.88	.93	.936
Economic value (EV)	.99	.95	.98	.355	.974
SC reciprocity (Recip)	.83	.62	.69	.339	.097	.785
Social value (SV)	.93	.81	.88	.498	.141	.412	.902
SC trust	.85	.66	.74	.330	−.012	.382	.562	.811
SC voluntarism (Volunt)	.90	.64	.86	.446	.199	.495	.613	.431	.801
Willingness to pay (WtP)	1	1	1	.402	.164	.337	.402	.237	.390	1

Note. Numbers in boldface refer to the square root of AVE scores.

Results—Hypotheses Testing

We expected that social capital, modeled as a formative second-order latent construct, would be formed by three first order, reflective constructs. We tested this assumption together with Hypotheses 1–3. We specified a structural model in PLS and ran the PLS algorithm as well as the bootstrapping procedure to obtain path coefficients, their respective t-values, and R² coefficients of the endogenous constructs. Similar to multiple regression, the quality of PLS models is evaluated based on the directions and significance of path coefficients, and the magnitude of R², which signifies the amount of variance in a construct that is explained by the model (Götz, Liehr-Gobbers, and Krafft 2010). While some experts suggest that there is no generally acceptable threshold for the size of R² (cf. Götz, Liehr-Gobbers, and Krafft 2010), a value of .20 is considered high in consumer behavior studies.

Our results are shown in Figure 1. They confirm the three-dimensional structure of social capital, which is formed by voluntarism, trust, and reciprocity (refer to Table 2 for β coefficients and t-values). In line with Hypotheses 1a and 1b, entitativity and social capital positively impact SNS members’ WtP. The estimation of our structural model also confirmed Hypotheses 2a and 2b, which suggested that entitativity and social capital will positively impact SNS members’ perceived social value. The explained variance in social value accounted for by entitativity and social capital is R² = .51. We also expected a positive effect of entitativity and social capital for economic value (Hypotheses 3a and b). However, our results only confirm our hypothesis for entitativity (Hypothesis 3a), while the effect of social capital on economic value (Hypothesis 3b) is nonsignificant. We hence reject Hypothesis 3b. For economic value, entitativity and social capital account for a R² value of .13, which is considerably lower than the one for social value.

Figure 1.

The influence of social capital and entitativity on willingness to pay (WtP) in a socially oriented social network sites (SNS).

Table 2.

Hypotheses Testing—Path Analyses (β, t-Value).

Path Analyses
Hyp.	Path	β	t-Value	Hypotheses
	SC Voluntarism -> Social Capital	.719	116.37
	SC Trust -> Social Capital	.339	57.56
	SC Reciprocity -> Social Capital	.142	49.00
Hypothesis 1a	Entitativity -> WtP	.221	13.26	Supported
Hypothesis 1b	Social Capital -> WtP	.191	11.48	Supported
Hypothesis 2a	Entitativity -> Social Value	.217	19.00	Supported
Hypothesis 2b	Social Capital -> Social Value	.586	58.38	Supported
Hypothesis 3a	Entitativity -> Economic Value	.366	26.45	Supported
Hypothesis 3b	Social Capital -> Economic Value	−.024	ns	Rejected
Hypothesis 4	Interaction SV × Member type	.06	6.00	Supported
Hypothesis 5	Interaction EV × Member type	−.09	8.70	Supported

To test Hypotheses 4 and 5, we extended our structural model by including interaction terms for membership type (i.e., regular vs. premium member) and social/economic value, respectively. We used the stepwise product term approach that is recommended for reflective measurement models. In line with Hypothesis 4, the impact of social value on WtP is moderated by membership type in a way that social value is a more important driver for premium members compared to regular members. Finally, our results suggest that economic value is more important for regular members, relative to premium members, lending support for Hypothesis 5 (Table 2).

The combined variance in WtP explained by our model, including entitativity , social capital, and social and economic value, resulted in a R² value of .23. While the predictive quality of the model slightly deteriorates when the indirect factors social and economic value are excluded (R² = .22), the effect size⁵ of this difference is weak. Observing the total effects (Table 3), it can be concluded that entitativity and social capital contribute approximately evenly to WtP. Moreover, the total effect of social value on WtP appears to be somewhat higher compared to the total effect of economic value.

Table 3.

Total Effects of Latent Constructs on WtP.

	Total Effect	t-Value
Entitativity -> WtP	.267	18.62
Social captial -> WtP	.281	21.26
Econ. value -> WtP	.034	2.73
Soc. value -> WtP	.155	8.86

Study 2

Sample and Procedure

For Study 2, data were collected among members of a professional SNS with the primary purpose of finding jobs, people, business opportunities, or recommending others. The SNS enables members, for instance, to post comments, join special interest groups and to view others’ profiles. Moreover, employers can list jobs and search for potential candidates. The SNS offers free services (for a group we call regular members) in addition to several paid upgrading-options for various target groups (whom we collectively call premium members). Our sample consists of 462 members, including 302 regular and 160 upgraded, premium members. The distribution of gender and age across regular and premium members is somewhat skewed toward lower age categories (regular members: 54% female, 13% > 45 years old and premium members: 22% female, 3% > 45 years old). This is reflective of the membership base of this SNS.

Measures and Measurement Model

We adopted the measures from Study 1 and adapted them to the context of the professional SNS. To get a more comprehensive picture of entitativity, we extended the measure from Study 1 with 3 items (6 items in total) based on Stenstrom et al. (2008). We extended economic value with 2 items (6 items in total) to capture the context of Study 2. Finally, to widen the array and examine the viability of different value propositions, we added functional value as a new construct to our measurement model (in addition to social and economic value). For an overview of items used, refer to the Appendix. Moreover, structural relationships and the analysis approach were kept identical to Study 1.

Results—Measurement Model Evaluation

Also for Study 2, we calculated the individual indicator reliabilities, CR, convergent validity, and discriminant validity. First, all item loadings exceeded the threshold of .7, except for 1 item of entitativity, which was retained, however, due to its relatively high loading (i.e., .67) and significance. All other items significantly loaded on their respective latent construct as well (t-statistic > 1.96). The internal consistency and convergent validity of our measures proved satisfactory, as all CR scores exceeded the threshold of .7, and all AVE scores were higher than .5 (Table 4). Discriminant validity was satisfactory as well: First, the AVE score of each latent variable exceeded the construct’s squared correlation with any other latent variable (Fornell-Larcker criterion). Second, each indicator’s loading was higher than all of its cross-loadings with other latent variables. The reliability and validity of our reflective measurement model is hence supported. Similar to Study 1, we calculated the VIF for the formative measurement model (i.e., social capital). Calculations showed that multicollinearity was not a problem as the mean VIF for social capital was 1.91,⁶ which is considerably lower than the recommended threshold of 10.

Table 4.

Composite Reliability (CR), Average Variance Extracted (AVE), Cronbach’s α (CA), Correlations.

	AVE	CR	CA	EV	ENT	FV	Recip	SV	Trust	Volunt	WtP
Economic value (EV)	.70	.93	.91	.835
Entitativity (ENT)	.62	.90	.87	.591	.784
Functional value (FV)	.75	.92	.89	.551	.487	.867
SC reciprocity (Recip)	.75	.90	.83	.333	.335	.536	.865
Social value (SV)	.71	.91	.86	.678	.679	.515	.354	.843
SC TRUST (Trust)	.73	.89	.82	.373	.407	.549	.517	.521	.856
SC Voluntarism (Volunt)	.70	.90	.86	.426	.415	.646	.701	.444	.566	.836
Willingness to pay (WtP)	1	1	1	.611	.466	.394	.245	.562	.320	.329	1

Note: Numbers in boldface refer to the square root of AVE scores.

Results—Hypotheses Testing

In line with Study 1, our results confirm the three-dimensional structure of social capital, formed by voluntarism, trust, and reciprocity (Table 5). Different from Study 1, however, entitativity and social capital did not have a significant, direct impact on WtP. We therefore reject Hypotheses 1a and 1b for Study 2. Our results did confirm Hypotheses 2a and 2b, however, which suggested a positive impact of entitativity and social capital on social value. The explained variance in social value accounted for by entitativity and social capital is R² = .52. Our analysis also confirmed a positive effect of entitativity and social capital on economic value (R² = .39), confirming Hypotheses 3a and 3b. Functional value (R² = .51), which we included in Study 2, was significantly and positively affected by entitativity and social capital as well (Figure 2).

Figure 2.

The influence of social capital and entitativity on willingness to pay (WtP) in a professional social network sites (SNS).

Table 5.

Hypotheses Testing—Path Analyses (β, t-Value).

Path Analyses
Hyp.	Path	β	t-Value	Hypotheses
	SC voluntarism -> Social capital	.565	36.61
	SC trust -> Social capital	.407	25.94
	SC reciprocity -> Social capital	.183	18.29
Hypothesis 1a	Entitativity -> WtP	.052	ns	Rejected
Hypothesis 1b	Social Capital -> WtP	.029	ns	Rejected
Hypothesis 2a	Entitativity -> Social Value	.548	13.76	Supported
Hypothesis 2b	Social Capital -> Social Value	.279	5.93	Supported
Hypothesis 3a	Entitativity -> Economic Value	.479	11.47	Supported
Hypothesis 3b	Social Capital -> Economic Value	.238	5.16	Supported
Hypothesis 4	Interaction effect SV * Member type	.068	2.05	Supported
Hypothesis 5	Interaction effect EV * Member type	.105	3.42	Rejected

To test Hypotheses 4 and 5, we extended our structural model by including interaction terms for membership type (i.e., regular vs. premium member) and social/economic value, respectively. In line with Hypothesis 4 and Study 1, the impact of social value on WtP is moderated by membership type in a way that social value is a more important driver for premium members compared to regular members (Table 5). Different from Study 1, however, our results for Study 2 suggest that economic value is a more important driver for premium members, compared to regular members. We hence reject Hypothesis 5 for Study 2. Finally, we find similar effects for functional value, which seems to be a more important driver for premium members’ WtP (interaction effect functional value and member type: β = .14, t-value = 4.57). The combined variance in WtP explained by our model, including entitativity, social capital, social, economic, and functional value, resulted in an R² value of .42. The predictive quality of the model deteriorates when the indirect factors social, economic, and functional value are excluded (R² = .22), and the effect size⁷ of this difference appears to be strong (i.e., .35). When considering the total effects (Table 6), it can be concluded that the total effect of entitativity on WtP is somewhat higher than the total effect of social capital. Moreover, while the total effect of functional value on WtP appears to be nonsignificant, the total effect of economic value is significant and somewhat higher than the total effect of social value, which is significant as well.

Table 6.

Total Effects of Latent Constructs on WtP.

	Total Effect	t-Value
Entitativity -> WtP	.376	8.48
Social captial -> WtP	.193	4.77
Econ. value -> WtP	.406	7.54
Funct. value -> WtP	.006	.11
Soc. value -> WtP	.233	3.57

Discussion and Implications

The aim of this study was to expand our understanding of viable value propositions for different members of SNS and investigate how these can be translated into economic returns. We find that entitativity and social capital impact members’ WtP memberships fees, either directly or indirectly. Moreover, whether perceived economic and social customer value can explain this willingness depends on the type of customer relationship, as well as on the type of the social network. This study contributes to the academic literature in several ways. First, it adds insights to the literature on value propositions for online social networks by introducing entitativity. By linking entitativity to members’ perceptions of increased social and economic value as well as their WtP subscription fees, our results confirm that the concept is an important value proposition for SNS. Differences exist, however, across types of SNS. While in the more socially oriented network (Study 1) entitativity exhibited a direct effect on members’ WtP, in the professional network (Study 2), the perception of being a member of a meaningful entity only seems to increase WtP among members indirectly, through the social, economic, and functional value. Interestingly, the same pattern also emerged for social capital in Study 2. Although our hypotheses regarding the direct effects of entitativity and social capital on WtP were not supported by Study 2, our findings do seem plausible. As professional SNS, such as LinkedIn or Ryze, focus more on economic purposes and exchanges, social group phenomena, including relational norms and entitativity, may be less pronounced, which might explain the lack of a direct effect on WtP. Extending existing research on entitativity which has been conducted primarily in offline contexts (e.g., Igarashi and Kashima 2011), our study demonstrates the viability of the construct in an online setting.

Second, this study adds insights to the ongoing academic debate on whether and when subscription-based online business models are successful (e.g., Enders et al. 2008; Pauwels and Weiss 2008). While some researchers argue that it is almost impossible for online providers to capture economic value from SNS (Ritzer and Jurgenson 2010), others have called for research that explores ways of capitalizing on member interactions. So far, the focus has been on the quality of online content (Wang et al. 2005), or marketing practices (Pauwels and Weiss 2008). We extend extant insights by examining the joint impact of entitativity and social capital as direct and indirect predictors of SNS financial returns. Interestingly, the results of Study 1 suggest that in the case of the more socially oriented SNS the underlying logic for how economic and informational values are realized might differ. As suggested by Adler and Kwon (2002, p. 31), strong community norms may hamper entrepreneurial activity as members of tight-knit communities may feel obliged to share their resources with their closest members, which could hence “slow the accumulation of capital.” These authors (p. 30) refer to this phenomenon as “overembeddedness” and warn of possible backfire effects of social capital, which may be reflected by our findings from the socially oriented SNS. However, no such indication of backfire effects on realized economic value was detected, in the case of professional SNS.

Finally, our results underscore the importance of considering member heterogeneity and the type of network. The results of Study 1 suggest that regular members’ online interactions might be characterized by exchange relationships, which are mostly motivated by self-interest and thus by economic benefits (Gassenheimer, Houston, and Davis 1998). Premium members’ interactions, on the other hand, seem to resemble communal relationships, which are reflected by group solidarity and thus driven by social value (Gassenheimer, Houston, and Davis 1998). Surprisingly, in Study 2 social and economic value acted as more important drivers for premium members, relative to regular members. In a professional social networking context, the findings for economic value seem to be inconsistent with established relationship norms, according to which higher-order, psychological benefits are more important for more established customers, relative to functional-utilitarian benefits (e.g., Dholakia, Bagozzi, and Klein Pearo 2004). Although in the professional social network, social value appeared to be indeed more important for premium members, it seems that the predominantly economic purpose of the network also legitimates paying members’ expectations to receive economic rewards. More generally, it can be concluded that the paid membership fee option might raise overall higher expectations (social and economic) in professional online social networks. Such market or exchange relationship norms, which are triggered by economic benefits, seem to be accepted in a context that is driven primarily by economic motivations. Our study hence provides preliminary evidence that free and fee-paying members of subscription-based SNS seem to be guided by different relationship principles and hence seek out different sources of customer value.

Managerial Implications

This study offers actionable insights for SNS service providers who may wish to tailor their marketing approaches to different audiences, by considering the type(s) of social network(s) they serve, and types of members. In this way, SNS operators may positively influence members’ WtP membership fees. Our findings suggest that for SNS with a predominantly social focus it seems advisable to stress social benefits for paying members, and economic benefits for nonpaying audiences. Operators could consider providing more functionalities that lead to economic value, such as including website categories for job search, housing and for exchanging goods and services. For premium members, however, it seems advisable to reverse the focus by emphasizing group solidarity and the enjoyment of interacting with others, while downplaying communication of potential economic advantages. However, as changes in the benefits that regular and premium members seek are likely to be reflected by a gradual process rather than being induced by switching to an upgraded account, these recommendations should be adopted with caution. For SNS serving mainly professional or economic purposes, such as LinkedIn, operators should stress both economic and social benefits for both groups of members. It should be noted, however, that awareness of such benefits seems even more important for premium members, who also respond more positively to functional value.

To fuel perceptions of such values or benefits, SNS providers may wish to increase perceptions of entitativity and relational social norms. One possibility might be to identify and communicate aspects that highlight members’ common ground. The socially focused SNS we investigated in Study 1 does so in several ways: (1) it requests members to indicate any educational institutions they attended upon registration, so the focus is put on interactions with former classmates, (2) by focusing on stories, music, and fashion from the past, the social network invites active members to share common memories. In addition, many SNS encourage the formation of special interest groups that are only accessible for specific members. These groups are thus narrowly defined and often constitute niches within larger, global networks emphasizing close connections with a smaller audience in more purposeful networks. In this way, SNS providers may be able to increase perceptions of entitativity, which cements members to the group.

Limitations and Future Research

Like any other, this study is not without limitations. Future research should consider a broader variety and larger number of SNS or other social media collectives, such as TripAdvisor, in order to test the robustness of our approach. Moreover, actual behavioral data could provide valuable insights in addition to the WtP measures applied in our studies. Future research could also focus on specific dimensions or antecedents of entitativity to identify which ones might be most relevant in what type of network. In large, global networks similarity among members might not always be the case. Instead, it could be a high level of interaction that primarily drives perceptions of entitativity. By gaining more insight into the specific drivers of entitativity across different types of online social networks, and potentially also among different types of members, practical implications could be derived for SNS operators to stimulate members’ WtP. Moreover, it could be interesting to explore whether perceptions of entitativity differ for members joining narrowly defined special interest groups within broad, global networks. Another avenue for further research on the success factors of freemium business models are different types of social media, such as virtual game worlds. The rapid adoption of smartphones and tablet computers, in combination with a new global audience, is fueling the spread of freemium online games, where basic versions are available for free, whereas additional gaming features can be bought in the course of the game (Wakabayashi and Ante 2012). Finally, as economic value has been shown to encourage members to pay for SNS use, other factors that might complement entitativity and social capital in explaining how economic value is created could be explored in future research. The observation that entitativity only accounted for 13% of the variance in economic value in Study 1, the socially oriented SNS, suggests that there might be other, more influential aspects, which still need to be explored.

Footnotes

Appendix

Acknowledgments

The authors would like to thank Astrid Huijssoon and Dr. Debbie Keeling for their helpful input at earlier stages of this study. We appreciate the editor and two anonymous reviewers for their helpful insights and comments on earlier versions of the article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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