Attracting Facebook 'fans': the importance of authenticity and engagement as a social networking strategy for professional sport teams.

Pronschinske, Mya ; Groza, Mark D. ; Walker, Matthew 等

Attracting Facebook 'Fans': The Importance of Authenticity and Engagement as a Social Networking Strategy for Professional Sport Teams

The meteoric rise of Facebook usage has been evidenced since 2009, which marked a turning point in terms of how people use the Internet (Hennig-Thurau et al., 2010). For the first time in history, the number of people communicating via social network sites (SNS) outpaced the number communicating through email (Nielsen Media, 2009). This shift in user preferences has not gone unnoticed and in recent years, many sport teams have both extended and repositioned their marketing efforts through this still emerging medium. Wallace, Wilson, and Miloch (2011) noted that, given the value of social media, reframing existing marketing strategies to include SNS in marketing, communications, and brand-management practices has become the norm.

After its launch in 2004 as a site designed to connect students on college campuses, Facebook extended its reach by allowing commercial organizations to create pages. By 2006, nearly 22,000 organizations created Facebook profiles (Smith, 2006). Today, Facebook boasts over 500 million active users who spend over 700 billion hours a month on the site (Facebook, 2011). While an increasing number of sport organizations have imbedded Facebook content into their marketing strategies, little empirical information is available on Facebook as a fan attraction mechanism. Most professional sport teams devote considerable time and resources to cultivating relationships with their fans, and the marketing literature is replete with examples of how and why consumers identify with teams (e.g., Crawford, 2004; James, Walker, & Kuminka, 2008; Pritchard, Stinson, & Patton, 2010). While traditional marketing strategies have helped teams realize their potential as a point of fan attachment, SNS now provide an opportunity to create new and expand existing relational bonds.

Beyond a traditional approach to marketing largely considered a goods-dominant approach, Vargo and Lusch (2004) posited that marketers are evolving into a service-dominant logic, which recognizes that all value is co-created. Further, the authors suggested that value is created through the interaction that occurs between the customer and the firm. Sport teams have utilized technologies that allow for these interactions, for example, team chat rooms (i.e., two-way communication with other fans) and e-newsletters (i.e., one-way communication from the organization to the fan). However, SNS allow users to go a step further and engage directly with the team (i.e., two-way communication) by entering into relationships through friending individuals with similar interests and becoming a fan of a team's Facebook page. It is not that social networking is a new form of marketing but rather is adapting to the times in which consumers desire to be a part of the marketing process. Facebook is an especially enticing medium to sport marketers in this regard because costs are minimal, targeting specific fan groups is simple, product and service information can be conveniently distributed, and information that can be used over extended periods is easily posted and stored (Walker, Kent, & Vincent, 2011). For these benefits to be realized, however, individuals must be drawn to, and engaged in a team's SNS. That is, a sport team cannot reach Facebook users unless the user establishes an SNS relationship with the team by liking the team's page. Based on this commentary and the widespread use of Facebook by professional sport teams to distribute information and connect with their fans, the research question developed to guide our investigation is as follows:

RQ: How can professional sport teams manage their Facebook page to maximize the number of individuals that 'follow' the team on Facebook?

While a substantial body of literature on the Internet as a viable communication medium in sport exists (e.g., Brown, 2003; Suh & Pedersen, 2010), there is limited research on SNS usage by professional sport teams. That said, there is a small (albeit growing) body of work in the broad area of sport communication (e.g., Clavio, 2011; Clavio & Kian, 2010; Wallace, Wilson, & Miloch, 2011; Williams & Chinn, 2010), which has shed light on the usage and preference patterns of individuals. Much of the existing Facebook research has focused on personal identity, privacy, temporal usage patterns, cultural exchanges, and friendship articulation (e.g., Deighton & Kornfeld, 2009; Peltier, Milne, & Phelps, 2009). In contrast to this individual user research, we adopted a meso-level organizational approach to understand how sport teams present themselves on Facebook and use this presentation in a relationship marketing capacity. An analysis of Facebook page attributes is intended to improve our limited understanding of this still-emerging medium. As such, this study advances the sport marketing literature by building and testing an econometric model predicting what Facebook attributes lead to fan participation.

Relationship Marketing

While SNS help launch products and strengthen existing brands (Waters, Burnett, Lamm, & Lucas, 2009), little is known about how sport organizations use these applications to cultivate relationships (Bee & Kahle, 2006). Defined by Morgan and Hunt (1994) as "... all marketing activities directed toward establishing, developing, and maintaining successful relational exchanges" (p. 22), relationship marketing refers to developing long-term relationships with organizational stakeholders. Theoretically, Bee and Kahle (2006) provided a functional perspective of relationship marketing in which compliance, identification, and internalization guide attitude change in sport consumers. This has been found to lead to favorable financial outcomes for sport organizations (Palmatier, 2008). From a practitioner perspective, sport teams and leagues have become proactive in brand management and embraced relationship marketing due (in part) to innovations in technology, new developments in sport marketing research, and increased options to gather sport and entertainment information (Groza, Cobbs, & Schaefers, 2012; McDonald & Milne, 1997). To enhance the team-fan relationship and foster relational exchanges, sport teams utilize online marketing activities, which include traditional websites, chat rooms, blogs, and message boards (Filo & Funk, 2005; Kim & Trail, 2011), because the "... potential value and benefits of using social media to meet relationship-marketing goals [in sport] is significant" (Williams & Chinn, 2010, p. 423). However, research on fan engagement through SNS has been slow to evolve. Waters, Burke, Jackson, and Buning (2010) maintained this is potentially problematic for sport marketers since sport fans are often more invested in the organization-public relationship than the average consumer.

A relational exchange is the foundation for SNS and research on relationship development (i.e., though virtual channels) provides insight on how social networking can be used to promote relationship growth (Kelleher, 2006). As social media usage increases, so too does the potential for sport teams to connect with individuals not normally reached through traditional marketing channels. This is a result of SNS being available, free to the subscriber, and because they provide the most up-to-date information on the team, they tend to serve active information seeking audiences rather than passive ones reached through traditional media (Walker et al., 2011). In addition, highly identified fans are now (more than ever before) able to broadcast their loyalty to other fans throughout their social network. Literature on sport fans has, in the aggregate, noted that fans tend to possess numerous shared feelings, which include sympathy, support, identity, and camaraderie with the teams they support, as well as with referent others (e.g., Depken, 2001; Giulianotti, 2002; Tapp & Clowes, 2002). Given the high level of meaning attached to the aforementioned feelings, it is not altogether surprising to see differences between sport consumers and traditional consumers in the marketplace. The key distinguishing factor is that sport fans frequently share these experiences in social group/gathering scenarios (i.e., brand communities), which are closely tied to various social networks (Benigni, Porter, & Wood, 2009).

Sport teams have the unique opportunity to capitalize on social connections by implementing and utilizing SNS strategies to bolster their relationship marketing platform. This, however, is not without its challenges. To build and sustain such relationships, sport teams must deploy a SNS strategy that consistently evolves and adapts to fan patterns and preferences. Doing so will provide the teams with specific information about their fans, which will help them tailor messages based on certain needs, wants, and behaviors. Although research has examined the impact of many SNS communication cues, three (in particular) have been deemed critical for relationship cultivation: (1) disclosure, (2) involvement, and (3) information dissemination.

Research investigating SNS strategies of non-profit organizations, for example, have confirmed that disclo sure, involvement, and information dissemination are among the most salient Facebook features affecting user participation (see Waters et al., 2009).

[FIGURE 1 OMITTED]

Professional sport teams are, however, fundamentally different from non-profits and other for-profit organizations. For example, non-profits and traditional for-profit businesses may not have to deal with imitation in online environments. Many fans of popular sport teams have taken advantage of the user-centric nature of SNS by creating unauthentic pages, which divert individuals away from the actual profile page of their favorite team. Thus, page authenticity is included to account for imitation practices prevalent in the SNS environment among professional sport fans. As depicted in Figure 1, we predict that the number of likes a professional sport team's Facebook page has is a function of the degree to which the page (1) communicates authenticity, (2) discloses details about the business aspect of the sport organization, (3) engages fans, and (4) disseminates information regarding the sport aspect of the organization. The theoretical justification for these predictions is outlined next.

Hypothesis Development

Authenticity

Leigh, Peters, and Shelton (2006) note the importance of authenticity in marketing campaigns, which typically occurs within transparency and organizational legitimacy discussions. In order to evoke authenticity, message cues engendering trust must be embedded within the marketing strategy (Brown, Kozinets, & Sherry, 2003). This is especially true when forming new team fan relationships. In these situations, trust plays an intermediary role in relationship marketing because it refers to one party having confidence in the other and is a key mechanism to reduce complexity in situations of uncertainty (Morgan & Hunt, 1994). In sport, Filo, Funk, and Alexandris (2008) noted the mediating role of brand trust with regards to brand loyalty. Trust has also been recognized as a construct affecting relationship quality (Kim & Trail, 2011). However, building trust through online content is challenging because consumers can be skeptical of messages due to the open-centric nature of the Internet (Schlosser, White, & Lloyd, 2006). In professional sport, many fans have created fake team pages, thereby compromising the number of potential fans drawn to the actual team site. This represents a critical barrier to fan participation for the authentic team Facebook page and limits the overall impact of the page.

Evidenced by the number of team and organizational websites and online fan portals, nearly every sport team has found it important to be represented on the Internet to attract fans, increase team awareness, and sell team-related merchandise. However, advancing online consumers from attention to action has proven difficult. One reason for this behavioral gap is the lack of faith that exists between organizations and increasingly cautious Internet consumers. As a result, trust represents both a short-term issue and a significant long-term barrier for realizing full consumer engagement with an entity on the Web (Suh & Pedersen, 2010). Therefore, the authentic nature of a Facebook page is necessary to convey an official presence, which can assuage user skepticism and evoke involvement.

H1: The authenticity attributes contained in an organization's Facebook page will positively influence the number of fans.

Disclosure

In a modern sport business climate fraught with dubious business practices (e.g., Nike, FIFA, etc.) it is not surprising that critics have depicted many sport organizations as purely self-interested. This heightened scrutiny toward organizational behavior underscores the need for empirical robustness to guide organizational disclosure (Basu & Palazzo, 2008; Varadarajan & Yadav, 2002). As the need for information increases so too has sport consumer demand for transparency. Consequently, many sport fans now look to the Internet to provide the most up-to-date and detailed information on teams and organizations with which they have a high degree of affinity. This heightened attention (i.e., from the media and consumer groups) means that any sport organization behavior (whether positive or negative) can be quick to reach the public.

All interactions between a sport team and its consumers through different contact points are potential sources of information. However, if this information exists in disparate form, it can impede communication because of the lack of trust this instills. Alongside general trust concerns, it is also important to account for the specific context of an interaction. Many sport teams may not actually adopt a disclosure strategy. Instead, in the context of human-computer interaction, they regulate information disclosure based on the dynamics of an ongoing interaction and by including costs/benefit calculation of the disclosure (Tufekci, 2008).

Website analyses have found that general organizational information, history, a list of officers, mission statements, and products and service listings have been the most common disclosure features (Robbins & Stylianou, 2003). While SNS contain much of this information, they also present other elements unique to this medium. For example, many sport teams use Facebook to create a distinctive organizational-presentation (i.e., profile page). In theoretical parlance, this social representation is referred to as technologically mediated sociality (Tufekci, 2008). Analyses of this idea should account for the public/private boundaries in social interactions between the team and its fans. In addition, specific attention should be paid to the dissimilarities between the social Internet and the commercial and informational Internet.

H2: The disclosure attributes contained in an organization's Facebook page will positively influence the number of fans.

Engagement

A marketing strategy that allows for fan engagement should contribute significantly to relationship building for professional sport teams. For example, researchers (in and outside of sport) have noted the more consumers feel like they are part of the organization the more identified they become and the more likely they are to form a lasting relationship with the organization (e.g., Bhattacharya, Rao, & Glynn, 1995; Kwon & Armstrong, 2006). Since "... preserving, supporting, and improving the organization proceeds naturally from identification" (Ahearne, Bhattacharya, & Gruen, 2005, p. 577), it is reasonable to understand how sport teams are particularly interested in the cognitive, affective, and behavioral (i.e., engagement) responses of their fans. For example, identification has been examined in multiple sport contexts, including attachment to various event aspects (Robinson & Trail, 2005) and the strength of commitment through team identification (Funk & James, 2001). These studies add further support to the importance of identity in the engagement process underlined by the relationship marketing paradigm.

Relationship building through identity formation is not, however, immediate. Identification is formed over time, subjectively, though repeated engagement with a team and other fans of the team. Engagement gives the impression of commitment because it entails practices to positively involve consumers in organizational activities (Greenwood, 2007). When a team shows commitment to its fans through policy and practice, the more accountable and responsible the team appears. Morgan and Hunt (1994) noted that with regard to relationship marketing, commitment is one of the most salient concepts for marketers to capture. Intuitively, understanding the reciprocal relationship between the team and the consumer is easy (i.e., without fans, the team ceases to exist). Consequently, it is important for sport teams to demonstrate (back to the fans) the importance of a committed relationship.

Research has suggested that sport organizations engaging in active communication with consumers and fans may indirectly enhance commitment through a felt sense of involvement (Walker, Sartore, & Taylor, 2009). Similarly, Berry and Parasuraman (1991) contend that "... relationships are built on the foundation of mutual commitment" (p. 139). Thus, when reciprocal commitment is established and interactivity occurs (i.e., two-way dialogue), fan engagement in a virtual environment should increase (Sawhney, Verona, & Prandelli, 2005). In our model, engagement refers to the team's efforts to demonstrate commitment and appeal to the fans. In turn, this committed image should enhance the consumer's motivation to interact with the team and other social members.

H3: The engagement attributes contained in an organization's Facebook page will positively influence the number of fans.

Dissemination

As mentioned, one of the primary foundations for SNS usage by sport teams is relationship building. SNS technology can neither create nor destroy relationships; rather, it is the technology in use that influences relationships. One of the most attractive functions of Facebook for professional sport is the ability for fans to openly and actively disseminate information, since the utility of SNS are predicated on the information distributed and the communication between members (Shankar & Malthouse, 2007). The dissemination process encompasses specific routines that teams use to manage the flow of information to establish relationships. Academic research on information use has emphasized the important role organizations play in the information exchange process (Jayachandran, Sharma, Kaufman, & Raman, 2005).

The ability to use Facebook for disseminating real-time information to fans provides the team with an added communication strategy. According to the cascade diffusion model (see Goldenberg, Libai, & Muller, 2001), information dissemination usually occurs through surprisingly weak-ties. However, with the rapid advancement in how SNS collect, process, and distribute information, content now flows freely between much stronger ties (i.e., from fans directly to the team itself). Connectivity and constant access has created a real-time flow of information among social networks, and since Facebook satisfies the fan's desire for real-time information, the following hypothesis is proposed:

H4: The dissemination attributes contained in an organization's Facebook page will positively influence the number of fans.

Controls

A number of factors independent of a team's SNS are expected to influence participation. In order to isolate the hypothesized effects, other variables must be controlled for in the econometric model. Prior research has suggested that individuals possess a desire to associate with organizations they perceive as successful (Bhattacharya, Rao, & Glynn,1995) and regardless of identification, success is viewed as a form of legitimacy. Thus, team success controls were included because of their variability and temporal influence. Additionally, the market size the team operates in is also very likely to influence the number of SNS fans a team attracts. For example, a team in a large market (e.g., New York City) will presumably have contact with more individuals than a team operating in a smaller market (e.g., Milwaukee). The final control is the length of time the SNS has been operative. Although Facebook has existed since 2004, not all teams began using the medium concurrently. Therefore, a time control was included. Controlling for these variables reduces the likelihood of omitted variable bias and enhances statistical robustness.

Method

Sample

All teams comprising the four major North American professional sport leagues were used as the research context to test which Facebook attributes attract the most fans. Investigating multiple teams in multiple leagues enhances the generalizability of the results, which provide important substantive implications to sport marketers. The cultivation of an affective connection to the team is critical to marketers in professional sport. Similarly, sport fans exhibit heightened emotional reactions toward their favorite teams and are willing to make their allegiances known to outsiders (Filo & Funk, 2005). As such, affect represents an important element to how the typical sport fan may utilize a team's Facebook page. Studying Facebook pages allows for the use of objective data in the form of actual user behavior (i.e., the number of likes) as opposed to perceptual or intention based data.

Data Collection

The study population consisted of all teams from the four main leagues housed in the professional sport industry in North America (N = 122): National Football League (NFL; n = 32), National Basketball Association (NBA; n = 30), National Hockey League (NHL; n = 30), and Major League Baseball (MLB; n = 30). Each team website and Facebook account was visited and coded for the presence or absence of an official Facebook page. To ensure that the official Facebook page was used, the coders began from each team's official website and proceeded to click the links until reaching the official Facebook page. Of the 122 teams, eight did not have an official Facebook presence at the time of the data collection and were not used in the subsequent analyses. This delimitation resulted in a sample size of N = 114.

In order to identify and code the Facebook page attributes, we adopted a qualitative content analysis approach (Hsieh & Shannon, 2005), which is a systematic technique for examining communication methods (Berger, 2000). Qualitative content analysis was appropriate since existing theory and research literature on a Facebook usage is limited in the sport marketing discourse. This initial analysis made it possible to code each team's Facebook page according to four primary page attributes. As the coders visited the assigned team page, they consulted a 22-item codebook to assist with the coding of the page attributes. The codebook was created though a review of relevant trade publications and the social media literature on how organizations use SNS and the Internet as marketing tools (Waters et al., 2009). The authors also used an expert panel of social media and sport marketing scholars to ensure the codebook accurately reflected Facebook page attributes found in the professional sport context. Continually consulting the codebook, specific text section(s) detailing the page attributes of each professional team were archived in a spreadsheet to facilitate the coding process.

Coding the Variables

Page authenticity (Authentic) was determined by the following four attributes: (1) username and any login information on the welcome page, (2) official page statement, (3) official logo and copyright statements, and (4) a statement that the site is monitored with security measure descriptions. Disclosure (Disclosure) was determined by the following five attributes: (1) organizational affiliation, (2) organization overview (e.g., founded, location, etc.), (3) mission statement, (4) organizational description, and (5) a link to the organization's website. Engagement (Engagement) was determined by the following six attributes: (1) listing of team events, (2) discussion board, (3) wall used for dialogue between the organization and fans, (4) creation of other applications (e.g., ticket and merchandise sales portals), (5) presence of an official email, and (6) and other relevant contact information. Information dissemination (Information) was determined by the following four attributes: (1) news links from the organization, (2) notes from the organization, (3) photographs posted by the organization, and (4) videos uploaded by the organization.

Inter-coder reliability checks were performed at regular intervals throughout the coding. By using Holsti's (1969) coefficient of reliability, agreement between coders was above 90% after coding 10% (n = 11) of the sample and Scott's (1955) Pi Percentage of agreement corrected for chance agreement between coders, which was all above .90 Given the coding scheme's objective measures, the high level of inter-coder reliability and sample size, the coders divided the sample and coded each part independently. Any coding ambiguities were discussed and resolved, with the primary author being the final arbiter for reliability. Additionally, content analyzing the page attributes, the number of registered Facebook fans of each organization (i.e., the dependent variable), as well as the date in which the page was created were recorded. This was accomplished by scrolling back through the wall feature to locate the initial post.

The Econometric Model

To estimate the relationship between the page attributes and the number of Facebook fans (i.e., likes), a series of two hierarchical regression models were tested. This analytical approach was used in order to assess if the hypothesized independent variables explain variance in the dependent variable beyond the variance explained by the control variables. The first model (i.e., base model) is as follows:

[LogFBFans.sub.ij] = [[beta].sub.0] + [[beta].sub.1] [Pop.sub.ij] + [[beta].sub.2] [Weeks.sup.2.sub.ij] + [[beta].sub.3][Winpct.sub.ij] + [[beta].sub.4][PostPlay.sub.ij] + [[beta].sub.5][DLeague.sub.j] + [e.sub.ij] (1)

LogFBFan represents the number of registered Facebook fans on team i from league j's page at the time of the analysis. The dependent variable was log transformed because the absolute number of fans was positively skewed violating the assumption of normality necessary for Ordinary Least Squared (OLS) regression (Hair et al., 2010). Pop is the metropolitan population of team i and was gathered from Forbes (2010). [Weeks.sup.2] represents the number of weeks in which the organization hosted an official Facebook page (i.e., from the date of page creation to the date of the content analysis). This variable was squared because of the diminishing return of time. That is, when an organization initializes the page there is likely a great deal of activity from individuals who are key stakeholders of the organization. After a certain amount of time, the number of new fans will likely diminish. Winpct is the winning percentage of team i during the previous season and PostPlay is a dummy variable that takes the value of "1" if the team played in the postseason the prior season and "0" if they did not. These two variables were designed to control for the success of each individual organization. The data for both variables were gathered from each league's official website. The final set of control variables is DLeague, which is a vector of dummy variable representing the league team i is a member of. This control was necessary because there may be systematic variations in popularity across the four leagues. Inclusion of these dummy variables (i.e., fixed effects method) is intended to control for these differences. Finally, is an independent randomly distributed error term. The descriptive statistics, as well as variables correlations, are contained in Tables 1 and 2, respectively. The descriptive statistics and correlations revealed that no violations of normality or multicollinearity existed.

Model 1 creates the base line to compare Model 2 which includes the variables to test the study's hypotheses. Model 2 is as follows:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)

Model 2 is identical to Model 1 except for the inclusion of Authentic, Disclosure, Engagement, and Information. Each of these variables represent the percentage of authenticity, disclosure, engagement, or information indicators (as discussed above) present on team i's Facebook page at the time of the content analysis.

Results

The results of the OLS regressions for Model 1 and Model 2 can be found in Table 3. Model 1 contains the control variables Pop, Winpct, and PostPlay as well as the league fixed effects. The dummy variable 'NHL' was excluded and used as the base league because the NHL is the league with the fewest Facebook fans. Thus, the estimated coefficients for the variables MLB, NFL, and NBA can be interrupted as how many more Facbook fans those leagues have compared to the NHL. The variables included in Model 1 explained nearly 51% of the variance in the number of Facebook fans. The variance inflation factors (VIF) associated with the estimated coefficients are well below the 10.0 threshold suggesting multicollinearity is not an issue in the econometric model (Hair, Black, Babin, & Anderson, 2010). As predicted, winning percentage Winpct was significant (b = .52, p<.01), suggesting individuals are more likely to follow a successful organization. The significant coefficients among dummy variables (MLB: b = .77, p<.01; NFL: b = .79, p<.01) indicate statistically significant differences in the number of Facebook fans across leagues.

Model 2, which includes the coded Facebook attributes, explained a significantly greater proportion of the variance (i.e., 55%) compared to Model 1 (r2 A: p<.01). In addition to the significant change in the adjusted [r.sup.2], a test for joint significance (F-value= 3.80; p<.01) indicated that the additional variables added in Model 2 were important predictors for the number of a team's Facebook fans. All VIFs in Model 2 were well below the 10.0 level, again indicating that multicollinearity is not an issue. As in Model 1, Winpct (b = 1.63, p<.01) and two league dummy variables (MLB: b = .79, p<.01; NFL: b = .64, p<.01) were significant. In addition, authenticity (b = .49, p<.01) had a significant influence on the number of Facebook fans, thereby supporting [H.sub.1]. Those team pages that possessed more authenticity attributes had a higher number of fans. In support of [H.sub.2], Engagement was also significant (b = .36, p<.05), indicating that teams entering into a dialogic relationship with their stakeholders yielded a greater number of fans. Neither Disclosure nor Information was significant, failing to support [H.sub.3 or H4. Collectively, the results suggest that features of a professional sport team's SNS can be controlled by management and effect user participation. In the aggregate, the data suggests that authenticity and engagement influence SNS participation.

Discussion and Implications

Although the marketing literature has emphasized the importance of communication strategies in computer-mediated environments, research on social media has not kept pace (Varadarajan & Yadav, 2009). Sport teams began using Facebook pages in 2006; however, there has been little research regarding how sport organizations utilize the pre-defined pages, which could influence consumer participation. To address this void, we tested the supposition that Facebook attributes can catalyze fan engagement with an online Facebook community. Since communication through Facebook is a relatively new phenomenon, few guides exist to assist organizations develop SNS strategies. However, since nearly every team and sport organization would presumably like to occupy a larger and more visible place in the market, they must understand how to best utilize online mediums to increase consumer interest.

Prior work by Waters et al. (2009) provided a starting point to understand the current Facebook applications available to marketers. As well, by grounding the research in the relationship marketing framework, the results extend prior sport work by validating the suggested attributes and demonstrating their applicability as antecedents to team fan attraction. Additionally, this research extends the relationship marketing literature in sport through the introduction of service-dominant logic (Vargo & Lusch, 2004), highlighting that sport consumers may be actively seeking to engage with a team's marketing efforts. The idea of sought-after engagement moves beyond the predefined roles set forth by individual identification (Bee & Kahle, 2006); further, sport consumers desiring engagement pursue co-creation of content and the medium of Facebook satisfies this need. In addition, the results advance the literature on SNS usage by exploring the content contained in professional sport teams' Facebook pages and testing the coded variables' predictive ability on fan numbers.

Through the content analysis of professional sport teams' Facebook pages, we found that many teams have not fully utilized the capabilities of all possible Facebook applications. Exhaustively examining one aspect of the sport industry for the incorporation of authenticity, disclosure, engagement, and information dissemination, revealed that authenticity and engagement were the most important variables. The importance of these variables was underscored by a statistically significant number of fans for team pages. And although we predicted that components of information dissemination and disclosure would influence participation, overall they did not (statistically) impact the number of page fans. One possible reason for these variables not being significant is that the information coded is duplicated information typically found on the official team websites. Thus, there is nothing that SNS adds for these variables that cannot be communicated through a web 1.0 site.

Overall, two key variables impact the number of fans on a team's Facebook page. The results indicate that teams who are able to portray their Facebook page as official generated a higher number of fans. Having a Facebook icon link located on the team's website that allows the user to be directed to the official page is a great way to ensure that the fans are connecting with the team-created page. Also, advertising the official Facebook pages or Twitter accounts during in-game promotions is a great way to display that there are official pages formed and that the team would like to engage with their fans. Beyond professional sport, this finding is particularly apropos due to the open nature and creation of user-generated unofficial accounts on Facebook. The results also show that engagement strategies prompting fans to enter into a two-way dialogue are effective in attracting (and maintaining) users to the Facebook page. Fans respond favorably to discussion boards and the wall to communicate with other fans and the organization directly. Given the reported findings, this exchange relationship is not only important but necessary to increase Facebook fan numbers. Some practitioner-oriented ideas to generate engagement would be to ask fans to upload pictures of themselves at the game or watching from home, and during an in-game promotion period at the event. Not surprisingly, a higher regular season winning percentage (i.e., organizational success) resulted in a significantly greater number of Facebook fans. This finding aligns with social identity theory, which suggests that people are attracted to, and seek to identify with, successful organizations (Bhattacharya et al., 1995).

Many teams, especially in the current economic climate, lack both the financial and temporal resources to provide constant attention to a Facebook page. As a result, the engagement that fans desire may impact the propensity of additional fans wanting to like the team or it could drive current page fans to disassociate with the team. As mentioned, real-time information is one of the most attractive features of SNS. If the flow of information is sporadic, fans may become dissatisfied with the team and not frequent the Facebook page, thereby limiting the impact of the information transfer. Creating a page and not engaging in the dialogic communication with fans will not reap the relational benefits of SNS. When creating a Facebook page, some sport marketers tend to use the default attributes already prescribed by Facebook. In many situations, these defaults are not fully utilized thereby limiting their impact (e.g., having a video section with no videos). Further, this perceived inactivity can be strong enough to influence fans to not join or leave the group altogether (Waters et al., 2009).

Limitations and Future Research

In light of our findings, we recognize several study limitations. In particular, four are presented with applications to future research. First, the bracketed focus on Facebook is limiting because the features were only assessed in one social network medium. We recognize that social networks are just one component of the social media picture that organizations are utilizing to build stakeholder relationships. As such, future research should evaluate other popular network sites (e.g., Google+, LinkedIn, MySpace), microblogs (e.g., Twitter), wikis (e.g., Wikipedia), shared content (e.g., YouTube, Flickr, Digg), and social location platforms (e.g., Foursquare) to identify additional attributes that contribute to their marketing utility. Second, the sample used in this study consisted of a single aspect of a much larger professional sport industry. This delimitation was necessary for the manageability of data gathering and analysis. However, future research should extend this model to other aspects of sport to enhance the generalizability of the findings. Third, since the time of the data collection and subsequent coding, Facebook has included other features (e.g., dislike button) that could add to the reported findings. As Facebook continues to refine its platform and expand its applications, other aspects of the pages may be particularly enticing for fan attraction. Future researchers would be well-served to continually monitor Facebook looking for new applications to include in the proposed model. Fourth, while engagement was statistically significant, it could vary across the industry, as this characteristic (in isolation) is a relatively vague attribute. Further analyses should determine what levels of engagement are ideal for both the fan and the organization.

Future SNS research could also employ a case study approach that includes examples of successes and failures of SNS usage to strengthen theory in this area. Also, longitudinal investigations tracking fan fluctuations utilizing ethnographic techniques could prove useful to understand dialogic communication on SNS. The results of the current study suggest that simply creating a Facebook page is not enough to fully realize relationship marketing benefits. Rather, organizations should have a social media plan with clear strategies not only to reach new audiences but to develop relationships with current stakeholders. Another critique of SNS is the question of how can it be leveraged and monetized by sport organizations. Various professions have struggled with this fiduciary question and (beyond the anecdotal) have rarely been able to demonstrate a calculable return on investment from SMS. Critics have also raised concerns over how organizations are able to present content through SNS. This study offers an initial look at professional sport teams utilizing SNS for relationship marketing by identifying and measuring four specific antecedents. Future studies should continue to explore other variables that could influence a much broader range of organizational outcomes.

References

Ahearne, M., Bhattacharya, C. B., & Gruen, T. W. (2005). Antecedents and consequences of customer-company identification: Expanding the role of relationship marketing. Journal of Applied Psychology, 90, 574-585.

Basu, K., & Palazzo, G. (2008). Corporate social responsibility: A process model of sensemaking. Academy of Management Review, 33, 122-136.

Bee, C. C., & Kahle, L. R, (2006). Relationship marketing in sports: A functional approach. Sport Marketing Quarterly, 15, 102-110.

Benigni, V., Porter, L.V. & Wood, C. (2009). The rant: How online fan culture is revolutionizing college football. Electronic Journal of Communication, 19, 1-17.

Berger, A. A. (2000). Media and communication research methods: An introduction to qualitative and quantitative approaches. Thousand Oaks, CA: Sage.

Berry, L. L., & Parasuraman, A. (1991), Marketing services - Competing though quality. New York, NY: Free Press.

Bhattacharya, C. B., Rao, H., & Glynn, M. A. (1995). Understanding the bond of identification: An investigation of its correlates among art museum members. Journal of Marketing, 59(4), 46-57.

Brown, M. T. (2003). An analysis of online marketing in the sport industry: User activity, communication objectives, and perceived benefits. Sport Marketing Quarterly, 12, 48-55.

Brown, S., Kozinets, R. V., & Sherry, J. F. (2003). Teaching old brands new tricks: Retro branding and the revival of brand meaning. Journal of Marketing, 67(3), 19-33.

Claviro, G. (2011). Social media and the college football audience. Journal of Issues in Intercollegiate Athletics, 4, 309-325.

Clavio, G., & Kian, T. M. (2010). Uses and gratification of a retired female athlete's twitter followers. International Journal of Sport Communication, 3, 485-500.

Crawford, G. (2004). Consuming sport: Fans, sport and culture. London, UK: Routledge.

Deighton, J., & Kornfeld. L. (2009). Interactivity's unanticipated consequences for marketers and marketing. Journal of Interactive Marketing, 23, 4-10.

Depken, C. A. (2001). Fan loyalty in professional sports: An extension to the national football league. Journal of Sport Economics, 2, 275-284.

Facebook (2011). Statistics. From http://www.facebook.com/press/ info.php?statistics

Filo, K., & Funk, D. C. (2005). Congruence between attractive product feature's and virtual content delivery for internet marketing communication. Sport Marketing Quarterly, 14, 112-122.

Filo, K., Funk, D. C., & Alexandris, K. (2008). Exploring the impact of brand trust on the relationship between brand associations and brand loyalty in sport and fitness. International Journal of Sport Management and Marketing, 3, 39-57.

Funk, D. C., & James, J. D. (2001). The Psychological Continuum Model (PCM). A conceptual framework for understanding an individual's psychological connection to sport. Sport Management Review, 4, 119-150.

Giulianotti, R. (2002). Supporters, followers, fans, and flaneurs: A taxonomy of spectator identities in football. Journal of Sport and Social Issues, 26, 25-46.

Goldenberg, J., Libai, B., & Muller, E. (2001). Talk of the network: A complex systems look at the underlying process of word-of-Mouth. Marketing Letters, 12, 211-223.

Grabner-Kraeuter, S. (2002). The role of consumers' trust in online-shopping. Journal of Business Ethics, 39(1-2), 43-50.

Greenwood, M. (2007). Stakeholder engagement: Beyond the myth of corporate responsibility. Journal of Business Ethics, 74, 315-327.

Groza, M. D., Cobbs, J. & Schaefers T. (2012). Managing a sponsored brand: The importance of sponsorship portfolio congruence. International Journal of Advertising, 31 1, 63-84.

Hair, J. F. Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall.

Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of Service Research, 13, 311-320.

Holsti, O. R. (1969). Content analysis for the social sciences and humanities. Reading, MA: Addison-Wesley.

Hsieh, H., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15, 1277-1288.

James, J. D., Walker, M., & Kuminka, B. (2008). Becoming a professional football team fan: Differences based on level of team internalization. International Journal of Sport Management, 10, 14-34.

Jayachandran, S., Sharma, S., Kaufman, P., & Raman, P. (2005). The role of relational information processes and technology use in customer relationship management. Journal of Marketing, 69, 177-192.

Kelleher, T. (2006). Public relations online: Lasting concepts for changing media. Thousand Oaks, CA: Sage.

Kim, Y. K., & Trail, G. T. (2011). A conceptual framework for understanding relationships between sport consumers and sport organizations: A relationship quality approach. Journal of Sport Management, 25, 57-69.

Kozinets, R. V. (2001). Utopian enterprise: Articulating the meanings of star trek's culture of consumption. Journal of Consumer Research, 28, 67-88.

Kwon, H., & Armstrong, K. (2006). Impulse purchase of sport team licensed merchandise: What matters? Journal of Sport Management, 20, 101-117.

Leigh, T. W., Peters, C., & Shelton, J. (2006). The consumer quest for authenticity: The multiplicity of meanings within the mg subculture of consumption. Journal of the Academy of Marketing Science, 34, 481-493.

McDonald, M. A., & Milne. G. R. (1997). A conceptual framework for evaluating marketing relationships in professional sport franchises. Sport Marketing Quarterly, 6(2), 27-32.

Melnick, J. (1993) Searching for sociability in the stands: A theory of sports spectating. Journal of Sport Management, 7, 44-60.

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38.

Nielsen Media. (2009). Report: Social media and video engagement reshapes the web. Retrieved from http://blog.nielsen.com/nielsenwire/nielsennews/online-global-landscape-0409/

Palmatier, R. (2008). Relationship marketing. Cambridge, MA: Marketing Science Institute.

Peltier, J., Milne, G. R., & Phelps, J. (2009). Information privacy research: Framework for integrating multiple public, information channels and responses. Journal of Interactive Marketing, 23, 191-205.

Pritchard, M. P., Stinson, J., & Patton, E. (2010). Affinity and affiliation: The dual-carriage way to team identification. Sport Marketing Quarterly, 19, 67-78.

Robbins, S. S., & Stylianou, A. C. (2003). Global corporate web sites: An empirical investigation of content and design. Information and Management, 40, 205-212.

Robinson, M. J., & Trail, G. T. (2005). Relationships among spectator gender, motives, points of attachment, and sport preference. Journal of Sport Management, 19, 58-80.

Sawhney, M., Verona, G., & Prandelli, E. (2005). Collaborating to create: The internet as a platform for customer engagement in product inovation. Journal of Interactive Marketing, 19(4), 1-15.

Schlosser, A. E., White, T. B., & Lloyd, S. M. (2006). Converting web site visitors into buyers: How web site investment increases customer trusting beliefs and online purchase intentions. Journal of Marketing, 70, 133-148.

Shankar, V., & Malthouse, E. C. (2007). The growth of interactions and dialogs in interactive marketing. Journal of interactive Marketing, 21(2), 2-4.

Scott, W. A. (1955). Reliability of content analysis: The case of nominal scale coding. Public Opinion Quarterly, 19, 321-325.

Slack, T. and Parent, M.M. (1997) Understanding sport organizations. The application of organization theory. Champaign, IL: Human Kinetics.

Smith, N. C. (2003). Corporate social responsibility: Whether or how? California Management Review, 45(4), 52-76.

Smith, J. (2006). Updated lists of all companies and regions on facebook. Retrieved from http://www.insidefacebook.com/2006/11/15

Suh, Y. I., & Pedersen, P. M. (2010). Participants' service quality perceptions of fantasy sports websites: The relationship between service quality, customer satisfaction, attitude, and actual usage. Sport Marketing Quarterly, 19, 78-87.

Tapp, A. & Clowes, J. (2002). From "carefree casuals" to "professional wanderers": Segmentation possibilities for football supporters. European Journal of Marketing, 36, (11/12), 1248-1269

Tufekci, Z. (2008). Grooming, gossip, facebook and mySpace. Information, Communication and Society, 11, 544-564.

Varadarajan, P. R., & Yadav, M. S. (2002). Marketing strategy and the internet: An organizing framework. Journal of the Academy of Marketing Science, 30, 296-312

Varadarajan, P. R., & Yadav, M. S. (2009). Marketing strategy in an internet-enabled environment: A retrospective on the first ten years of JIM and a prospective on the next ten years. Journal of Interactive Marketing, 23, 11-22.

Vargo, S. L., & Lusch, R. F. (2004, January). Evolving to a new dominant logic of marketing. Journal of Marketing, 68, 1-17.

Walker, M., Kent, A., & Vincent, J. (2011). CSR communication among professional sport organizations: Stakeholder information and involvement strategies. Sport Marketing Quarterly, 19, 125-131.

Walker, M., Sartore, M., & Taylor, R. (2009). Outsourcing marketing: It's the communication that matters. Management Decision, 47, 895-918.

Wallace, L., Wilson, J. & Miloch, K. (2011). Sporting Facebook: A content analysis of NCAA organizational sport pages and Big 12 Conference athletic department pages. International Journal of Sport Communication, 4, 422-444.

Waters, R. D., Burke, K. A., Jackson, Z. H., & Buning, J. D., (2011). Using stewardship to cultivate fandom online: Comparing how National Football League teams use their web sites and Facebook to engage their fans. International Journal of Sport Communication, 4, 163-177.

Waters, R. D., Burnett, E., Lamm, A., & Lucas, J. (2009). Engaging stakeholders through social networking: How nonprofit organizations are using Facebook. Public Relations Review, 35, 102-106.

Williams, J. & Chinn S.J. (2010). Meeting relationship-marketing goals through social media: A conceptual model for sport marketers. International Journal of Sport Communication, 3, 422-437.

Mya Pronschinske, is a doctoral student of marketing in the Department of Management & Marketing at the University of Wyoming. Her research interests include consumer behavior with an emphasis on self-presentation strategies in online and offline environments.

Mark D. Groza, PhD, is an assistant professor in the Department of Marketing at Northern Illinois University. His research interests include corporate sponsorship, personal selling, and customer relationship management.

Matthew Walker, PhD, is an assistant professor in the College of Health at the University of Southern Mississippi. His research focuses on business strategy with particular emphasis on organizational ethics and social responsibility. Table 1 Descriptive Statistics Variables Minimum Maximum M SD Facebook Fans 1995 1142337 118526 167490 Log FB Fans a 3.3 6.06 4.79 .53 Metro Population 303000 19007000 5294138 4736107 Weeks2 64 11025 3380 2529 Winning Percentage .063 .875 .513 .14 Post Play 0 .42 .50 Authentic 0 .57 .23 Engagement .17 .51 .22 Disclosure .13 .63 .33 .16 Information 0 .47 .22 Major League Baseball 0 .26 .44 National Basketball Association 0 .25 .44 National Football League 0 .24 .43 National Hockey League 0 .25 .43 (a) Due to positive skewness of the data, and in accordance with the suggestions of Hair et al. (2010), a "Log" transformation was performed on the absolute number of Facebook fans. Log FB Fans is used in the regression analysis. Table 2 Correlation of Study Variables 1 2 3 4 1. Log Fans 1 2. Metro Population .051 1 3. Weeks (2) .000 .089 1 4. Winning Percentage .395 ** .030 .021 1 5. Post Play .245 ** .078 .055 .670 ** 6. Authentic .387 ** -.005 -.238 * -.116 7. Engagement -.218 * .005 .047 -.032 8. Disclosure -.211 * .027 -.100 .056 9. Information -.121 .048 -.064 -0.63 5 6 7 8 9 1. Log Fans 2. Metro Population 3. Weeks (2) 4. Winning Percentage 5. Post Play 1 6. Authentic -.198 * 1 7. Engagement -.069 -.217 * 1 8. Disclosure -.231 * -.218 * .337 ** 1 9. Information -.022 -.063 .433 * .199 * 1 * p < .05 (two-tailed); ** p < .01 (two-tailed) Table 3 Hierarchical Regression Variables Hypothesis Model 1 Model 2 Intercept .195 ** 2.92 ** Metro Population .0000001 .0000001 Weeks (2) .00002 .00002 * Winning Percentage 1.52 ** 1.63 ** Post Play .12 .12 MLB .77 ** .79 ** NFL .65 ** .64 ** NBA .08 .16 Authentic [H.sub.1] .49 ** Disclosure [H.sub.2] .04 Engagement [H.sub.3] .36 * Information [H.sub.4] -.05 [R.sup.2] adjusted .514 .547 (a) * p < .05; ** p < .0 a Change in [R.sup.2] significant at the p < .05 level