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  • 标题:Exploring fantasy baseball consumer behavior: examining the relationship between identification, fantasy participation, and consumption.
  • 作者:Shapiro, Stephen L. ; Drayer, Joris ; Dwyer, Brendan
  • 期刊名称:Journal of Sport Behavior
  • 印刷版ISSN:0162-7341
  • 出版年度:2014
  • 期号:February
  • 语种:English
  • 出版社:University of South Alabama
  • 摘要:From a spectator sport perspective, identity theory plays a significant role in the fan connection to sport, and this framework has been used in various forms to explain sport consumer behavior. Previous research provides evidence that identification influences consumption of sport-related products and services (Lavarie & Arnette, 2000; Madrigal, 1995; Trail, Anderson, & Fink, 2000, 2005; Trail, Fink, & Anderson, 2003). Additionally, fans appear to identify with multiple aspects of sport (e.g., team, individual players, the sport). These distinct points of attachment help explain individual consumption behavior (Robinson & Trail, 2005; Trail, Robinson, Dick, & Gillentine, 2003).
  • 关键词:Baseball;Consumer behavior;Fantasy sports leagues;Professional sports

Exploring fantasy baseball consumer behavior: examining the relationship between identification, fantasy participation, and consumption.


Shapiro, Stephen L. ; Drayer, Joris ; Dwyer, Brendan 等


Identification is the process of linking an individual's experience and internal information processing to social networks created through interactions with others (Callero, 1985). This connection between "self" and "society" is the basis for identity theory which suggests that through experience and social interaction, individuals create various role-identities which influence future behaviors (Ervin & Stryker, 2001; Stryker, 1980; Stryker & Burke, 2000). Commitment to one's social network through experience and social interaction impacts identity salience which in turn influences individual behavior (Ervin & Stryker, 2001; Stryker, 1980).

From a spectator sport perspective, identity theory plays a significant role in the fan connection to sport, and this framework has been used in various forms to explain sport consumer behavior. Previous research provides evidence that identification influences consumption of sport-related products and services (Lavarie & Arnette, 2000; Madrigal, 1995; Trail, Anderson, & Fink, 2000, 2005; Trail, Fink, & Anderson, 2003). Additionally, fans appear to identify with multiple aspects of sport (e.g., team, individual players, the sport). These distinct points of attachment help explain individual consumption behavior (Robinson & Trail, 2005; Trail, Robinson, Dick, & Gillentine, 2003).

Despite the increased attention this area has received from researchers, there have been limited investigations regarding the role identification plays in the consumptive habits of fantasy sport participants. Previous research has identified relationships between identification and motives for fantasy participation and differing levels of identification between a participant's favorite team and fantasy team (Spinda, Wann, & Sollitto, 2012). However, the impact of identification on consumption for fantasy participants has not been explored. Residing primarily in a virtual world yet tied to real-world statistics, the activity of fantasy sport allows participants to own and manage a roster of professional athletes. The outcomes of this activity have been found to result in enhanced professional media consumption primarily in the form of television viewership of live games, televised sport programming, and internet usage (Dwyer, 2011a; Nesbit & King, 2010b). However, although the focus of fantasy sport is on the statistical output of individual athletes as opposed to teams, recent research has determined the activity is actually complementary to traditional professional sport fandom (Dwyer & Drayer, 2010; Dwyer, Shapiro, & Drayer, 2011). In other words, a fantasy participant can engage in the media consumption of his/ her fantasy players in addition to the consumption of his/her favorite team without having to sacrifice one for the other.

Despite these findings, little is known about a fantasy sport participant's points of attachment with professional sport. Spinda et al.'s (2012) findings demonstrate some distinct differences in points of attachment between team, individual, and sport. With additional opportunities to consume the product compared to non-participating sports fans (e.g., favorite team, fantasy players, opponent's fantasy players), examining various points of attachment relative to consumption habits will provide insight into this rapidly growing form of sport random. The population of fantasy sport participants is also an avid consumer of technology due to the nature of mediated participation in fantasy activities (Comeau, 2007; Farquhar & Meeds, 2007; Smith, Synowka, & Smith, 2010). This may impact both traditional forms of sport consumption (e.g., attendance, merchandise purchases) and mediated consumption (e.g., television, internet). Additional research regarding the various consumptive habits of this population of sport consumers is warranted. In particular, a deeper understanding of the antecedents of consumption would help media providers, team marketers, and league officials more completely meet the needs of this ever-expanding group of sport consumers. Taken together, the purpose of this study was to examine the identification of fantasy sport participants as it relates to traditional and mediated consumption of professional sport.

Review of Literature

Fantasy Sport

Within the last two decades, fantasy sport has developed into a multi-billion dollar industry with over 32 million participants in the United States and Canada alone (Fantasy Sports Trade Association [FSTA], 2011). In parallel with the explosion of the internet, fantasy sport participation has evolved into a substantial connection point for sports fans where participants are provided an opportunity to interact with professional sport in a manner not offered through other, more traditional forms of sport random (Dwyer & Kim, 2011). In addition to the large number of participants, the demographic composition (25-41, highly-educated, income > $75,000) and consumption behavior of this group is highly-coveted by advertisers and corporate partners as it outpaces other sport fans and the general population (Fisher, 2008). According to Zeitchick (2005), for perhaps the first time in history, the fantasy sports subculture is driving strategy at the country's biggest broadcasters.

As a result of this popularity, academic researchers have been drawn to the motives of fantasy participants as well as the behavioral and consumptive outcomes of participation (Drayer, Shapiro, Dwyer, Morse, & White, 2010; Dwyer, 2011b; Dwyer & Kim, 2011; Farquhar & Meeds, 2007). This research suggests participatory drivers range from psychological, social, and market-controlled factors, and for the most part, increased consumption habits have been linked to several media formats (Drayer et al., 2010; Dwyer, 2011a; Nesbit & King, 2010b).

In terms of fantasy participation motives, Farquhar and Meeds (2007) and Dwyer and Kim (2011) developed and validated distinct motivational scales for fantasy football participation with several overlapping drivers including entertainment, social interaction, competition, arousal, escape, and surveillance. Spinda and Haridakis (2008) also explored the motives of fantasy participants, and discovered the following motivational dimensions: ownership, achievement/self-esteem, escape/pass time, socialization, bragging rights, and amusement. Ultimately, the authors suggested fantasy sport participation is "a purposive, instrumental, and active media-use endeavor [sic]" (p. 196).

The importance of establishing motives has been well documented, as motives have been found to influence consumer behavior from a spectator sport perspective (Kim & Trail, 2010; Trail et al., 2003) and more notably within the realm of fantasy sport participation (Drayer et al., 2010; Dwyer et al., 2011). Drayer et al. (2010) developed a framework through the application and extension of Fazio, Powell, and Herr's (1983) attitude-behavior relationship. The authors found fantasy football participation activated additional attitudes and perceptions with regard to the National Football League (NFL) product that, combined with traditional sport fandom, resulted in enhanced mediated consumption of the NFL. Dwyer et al. (2011) developed a market segmentation of fantasy sport participants based on motives. Within each segment of fantasy motives various aspects of fantasy sport consumption differed, which included consumption through mediated platforms such as television, internet, and mobile phones. These findings suggest consumption patterns differ based on motives for participation.

Additional fantasy consumption research identified increases in attendance for fantasy participants (Nesbit & King, 2010b) and different levels of consumption based on varying levels of interest in an individual's favorite team and/or fantasy team (Dwyer & Drayer, 2010). Additionally, Dwyer (2011 a) found fantasy football participants were not only attracted to their fantasy football players, but were also aware of their opponent's players, and as a result, intentionally watched and followed the live games of both sets of players in addition to their favorite team and its rivals. In an attempt to explore the team loyalty effects of fantasy football participation, Dwyer (2011b) discovered that although fantasy football appears to be a complementary activity to traditional (favorite team) random, it may result in an incongruent disconnect between a participant's highly-developed attitudinal team loyalty and his/her viewership behavior of that team. Although the literature focused on attitudes and behaviors of fantasy sport participants is growing, the relationship between identification and traditional and mediated sport consumption for fantasy participants is limited (Karg & McDonald, 2011).

Identification and Consumption

The importance of the relationship between identification and sport-related consumption has been acknowledged in the literature (Trail et al., 2000, 2005; Trail et al., 2003; Trail & James, 2001; Warm & Branscombe, 1993). Originally, research focused on team identification exclusively; however, Trail et al. (2003), developed the Points of Attachment Index (PAI), which segments identification based on specific types of fan connection: team, player, coach, sport, community, and level of play. These different forms of identification have been shown to influence various consumption behaviors distinctively.

Support for measuring identification as distinct categories can be found in the work of Robinson and Trail (2005), who identified considerably higher levels of team and sport identification compared to player, coach, level of sport, and community. Additionally, Kwon, Trail, and Anderson (2006) found that various points of attachment differed in their influence on future intentions to attend games, purchase merchandise, and purchase clothing with specific team logos.

These relationships have not been explored within the population of fantasy consumers. Karg and McDonald (2011) found differences in attachment to sport, team, players, and coach between fantasy and non-fantasy players who are fans of Australian football, providing evidence of unique attitudes for fans who participate in fantasy sport. Spinda et al. (2012) found that participants of Strat-O-Matic Baseball (SOMB), a baseball simulation game similar to fantasy baseball, had stronger identification with their favorite MLB teams compared to their SOMB team. Additionally, participation motives such as knowledge acquisition and enjoyment predicted various levels of identification, confirming the relationship between motives and identification from a fantasy sport perspective. However, the specific relationship between various points of attachment and aspects of sport consumption has yet to be addressed.

Technological advancements have provided a multitude of consumption opportunities for the sport consumer. These opportunities include traditional forms of consumption and mediated consumption. Furthermore, fantasy sport participants may be motivated to consume sport based on favorite team interests and/or fantasy team interests. This distinction in consumption has not been examined and may be important given the vast growth of fantasy sport and the elevated consumption levels of its participants. The role of sport identification on these various forms of consumption is needed from both a practical and theoretical standpoint. Additionally, due to the avid use of technology by fantasy sport participants, identification may influence traditional and mediated consumption differently for this population of sport consumers.

Finally, identification with fantasy sport specifically has not been explored. Drayer et al. (2010) suggested that fantasy sports participants have two distinct avenues through which to attach to professional football: fantasy team and favorite team. The authors concluded that there were specific behavioral differences associated with each of these distinct aspects of football consumption. Further, they found that participants' perceptions of the NFL were expanded as a result of fantasy sports resulting in heightened levels of interactivity and heightened levels of interest in individual players. However, within their small qualitative sample, they did not explore specific points of attachments. Their findings suggest that the nature of fantasy participation might create an attachment to fantasy sport that is different from the traditional forms of attachment. Additional research is needed to confirm these findings.

In summary, the fantasy sport research suggests a link between fantasy participation, attitudes about sport, and consumption of sport-related products and services. Additionally, previous literature has highlighted the influence of identification on attendance (Lavarie & Arnette, 2000; Trail, Anderson, & Lee, 2006) and other various consumption behaviors (Trail et al., 2003; Trail et al., 2005; Trail et al., 2006). However, the research on identification within the population of fantasy sport participants is limited, particularly in terms of its effect on traditional and mediated consumption.

In addition, the context of fantasy baseball, as opposed to fantasy football, has been neglected for the most part despite its place as the second most popular fantasy sport activity (> 9 million participants; FSTA, 2008). Based on the growth of fantasy sport as a complementary activity, and the important role identification plays on sport consumer behavior, two research questions were developed to guide the current study:

RQ 1: How do baseball consumer points of attachment influence traditional consumption for fantasy baseball participants?

RQ2: How do baseball consumer points of attachment influence mediated consumption for fantasy baseball participants?

Method

Sample & Procedure

The target population for this study was current fantasy baseball participants over the age of 18. A sample of 1,500 potential respondents was randomly selected from a group of 3,400 FSTA members to participate in the study. An online survey was developed and distributed through email to the random sample of FSTA members. A follow up email was sent two weeks after the initial distribution in an effort to increase response rate. A total of 253 usable surveys were collected for a response rate of 16.9%, which is common in online survey methodology (Shapiro & Dwyer, 2011).

Instrumentation

The survey instrument contained four sections with a total of 37 items. The first section of the survey focused on fantasy participation (3 items), measuring the number of years of participation, number of teams owned, and time spent participating in fantasy baseball. The second section of the survey measured multiple points of attachment for fantasy baseball participants. A five factor, 15 item adapted version of Trail et al's (2003) PAI was used to measure attachment to players, team, community, and sport. Additionally a 3 item sub-dimension was developed to measure specific attachment to fantasy sport. The third section of the survey was comprised of various sport consumption behaviors (7 items) which included measures of attendance, merchandise purchases, and mediated consumption. The final section focused on participant demographics (8 items) to profile the typical respondent.

Data Analysis

A confirmatory factor analysis (CFA) was initially conducted on the adapted PAI to examine the factor structure of the attachment construct based on the pooled sample of respondents. Previous theory on points of attachment and scale development of the PAI (Robinson & Trail, 2005; Trail et al., 2003) drove specification of the factor model. Therefore, CFA was the most appropriate factor analytic technique (Brown, 2006). Construct validity was assessed due to the fact that the PAI had not been used to examine fantasy baseball participants, and a new sub-dimension (Fantasy Attachment) was included.

Multiple measures of fit were used to examine the factor structure of the PAI. Overall goodness of fit was assessed using a robust chi-squared test; however, according to Hu and Bentler (1999), this test can be sensitive to sample size arid should not be used exclusively in determining model fit. Therefore, standardized root mean square residual (SRMR), root mean square error of approximation (RMSEA), and the comparative fit index (CFI) were examined to provide additional sources of fit that are widely accepted in applied research and have shown satisfactory performance in model simulation analyses. According to Hu and Bentler, SRMR values close to .08 or below, RMSEA values close to .06 or below, and CFI values close to .95 or greater provide evidence of an adequate model fit.

Additional measures of validity and reliability were assessed. Convergent validity was evaluated through the application of Fornell and Larcker's (1981) Average Variance Extracted (AVE) test. A third validity measure was used exclusively on the new Fantasy Attachment sub-dimension. To assess predictive validity, the scores for the Fantasy Attachment factor were regressed simultaneously onto three measures of fantasy participation selected due to both theoretical and practical relevance (DeVellis, 1991). Finally, alpha coefficients were examined within each factor of the PAI to assess reliability-related evidence. Means and standard deviations were subsequently calculated for each point of attachment in the scale.

To examine the relationships between identification and both traditional and mediated consumption, multiple regression analyses were conducted. Three regression models were developed to analyze RQ1 and four regression models were developed to analyze RQ2. Multiple linear regression assumptions were examined for these equations (Linearity, Independence, Normality, and Equality of Variances). Descriptive statistics, residual plots, and statistical tests for normality and equality of variances showed that none of the assumptions were violated in the regression equations. In addition, potential multicollinearity issues within the model were examined through variance inflation factors and tolerance statistics. The results suggested there were no significant multicollinearity issues in any of the regression equations used in the analysis.

Results

Fantasy Participation

The 253 respondents appeared to be avid fantasy participants. On average, participants had played fantasy baseball for approximately seven years (M = 7.04, SD = 4.90). The average number of fantasy teams owned (of any kind) was 4.30 (6.224). The standard deviation is large for this variable due to the fact that some participants were outliers with a significant amount of fantasy teams owned over the course of a year. Finally, participants spent 14.04 (10.63) hours per week playing fantasy sport, which includes conducting research, preparing rosters, and making lineup changes throughout the season.

Points of Attachment Index

CFA identified a five factor, 14 item solution for the adapted PAl scale. One item was deleted from the Fantasy Attachment factor due to poor factor loading. The final solution was found to be satisfactory [X.sup.2] (67) = 94.53, p <.001, RMSEA = .040, CFI = .99, NNFI = .99, and SRMR, .043. Additionally, AVE scores ranged between .689 and .810 and Cronbach's alpha scores ranged between .77 and .89. Finally, results of the predictive validity assessment on the Fantasy Attachment sub-dimension showed that fantasy participation had an influence on respondents' identification with fantasy sport F(3, 249) = 5.33, p = .001. Two of the three predictor variables, number of years playing fantasy baseball (p = .001) and hours per week participating in fantasy baseball (p = .014), had a significantly positive relationship with fantasy sport attachment. Table 1 provides a summary of validity and reliability-related evidence for the adapted PAI.

Regression Analyses

Multiple regression analyses were subsequently conducted. For RQ1, all three regression models were found to be significant. Traditional consumption included attendance F(5,247) = 11.63, p = <.001, general merchandise purchases F(5,247) = 9.65, p = <.001, and favorite team merchandise purchases F(5,247) = 18.27, p = .001. Attachment to team and community were the only significant variables in these models. Table 2 provides a detailed summary of regression results for RQ1.

For RQ2, all four regression models were also found to be significant. Mediated consumption based on favorite team included television F(5,247) = 13.07, p = <.001 and internet F(5,247) = 12.14, p = <.001. Only attachment to team was significant in these models. Mediated consumption for fantasy purposes included television F(5,247) = 5.43, p = <.001 and internet F(5,247) = 3.37, p = .006. Attachment to team, sport, and fantasy team were significant variables in the internet model. Only attachment to team significantly influenced television consumption for fantasy purposes. Table 3 provides a detailed summary of regression results for RQ2.

Discussion

The size and purchasing power of the fantasy sport population has been well documented (Fisher, 2008; FSTA, 2011). As a result, sport managers and marketers must account for the unique attitudes and behaviors of these individuals to properly package and deliver sport products and services. For instance, the NFL recently directed all teams to display real-time fantasy football statistics at all home games starting in the 2011 season (McCarthy, 2011). As the industry continues to mature, fantasy participants are becoming a highly valued segment of the sport consumer population. Thus, from a marketing perspective, the investigation into attitudes and consumption habits of participants is vital.

From a theoretical perspective, the current findings support identity theory by providing evidence that social interaction through fantasy participation influences various role-identities, which in turn impacts consumption of sport-related products and services. Results indicate identification with one's favorite team, community, and sport appear to be the most ubiquitous connection points for fantasy baseball participants, as these points of attachment were found to be significant across varying forms of consumption. Identification with one's fantasy team significantly influenced consumption modes more specific to the activity, yet tied to the media representation of MLB. These results also support Robinson and Trail's (2005) and Trail et al.'s (2003) findings wherein distinct points of attachment differed across groups, between sports, and resulted in varying consumptive outcomes. In addition, the current study's authors suggest identification with fantasy team should be considered in the future application of the PAI (with respect to fantasy participants) as it validates the burgeoning landscape of professional sport and media consumption. This finding is supported by Spinda et al. (2012), who also examined fantasy-specific identification and found significant relationships, though in a different context.

These findings also confirm previous spectator consumption behavior research which suggests attachment to team remains the most influential with respect to television consumption (Dwyer, 2011a; Mahony & Howard, 1998; Mahony & Moorman, 1999, 2000), as well as attendance and future merchandise purchase intentions (Kwon et al., 2006). Additionally, the importance of attachment to team does not appear to be negatively affected by fantasy participation, which is also consistent with previous research (Dwyer, 2011a; Dwyer, 2011b) and supports Drayer et al's (2010) assertion that fantasy sport participation complements traditional (favorite team-focused) sport consumption behavior. This finding is noteworthy for professional teams and leagues looking to leverage fantasy sport participation into additional consumption without detracting from traditional (favorite team) attachment and consumption.

A notable component to these findings is the specific influence of the newly created attachment to fantasy team sub-dimension. Attachment to fantasy team appears to be a source enhanced internet usage. This is supported by previous fantasy sport investigations (Drayer et al., 2010; Dwyer & Drayer, 2010). However, attachment to fantasy team did not influence watching television for fantasy purposes, which is contrary to previous research (Drayer et al., 2010; Dwyer, 2011a; Dwyer & Drayer, 2010; Nesbit & King, 2010b). These previous studies, however, examined fantasy football. Thus, the contradiction could be due to the uniqueness of baseball and the lack of nationally televised games and/or the fact that fantasy baseball would not necessarily be a reason to watch a local broadcast. In addition, attachment to one's fantasy team did not influence the more traditional forms of sport consumption (e.g., attendance and merchandise purchases) which contradicts findings from Nesbit and King (2010a). Additional research in this area is advised.

With regard to the future application of the PAI, a few modifications may need to be addressed when accounting for fantasy sport participation. Given fantasy baseball's focus on individual player statistics, one could have hypothesized that attachment to individual players would have been more influential. Yet, it was the only attachment factor that had no significant relationship with either traditional or mediated consumption. This finding may have occurred for two reasons. First, Drayer et al. (2010) determined that attraction to individual players was shallow and less enduring due to the short time span of ownership (one year); thus, a fantasy participant's attachment to individual players may be lessened. Second, the wording of two of the attachment items were related to individual players across the league although one was related to individual players on the participant's favorite team. Given the processes of fantasy baseball participation, these may represent two completely different forms of individual player fandom and may require instrument adjustment. Regardless of the reasoning, further investigation into individual player attachment is suggested, specifically with regard to fantasy participation.

Similarly, the newly-created fantasy baseball attachment items may also need re-examination. If in fact fantasy baseball participation is a complementary activity as suggested by these findings, the wording of the fantasy baseball attachment items may need to be addressed. Namely, the items are worded so that fantasy participation is one's only attachment to the league. Based on this study's findings wherein team, community, and sport attachment were highly influential, this attachment may need to be less polarizing. Once again, further psychometric testing on additional samples is suggested.

Limitations with regard to the current study certainly exist. For instance, although enlightening with regard to varying points of attachment, this study was limited to a cross-section of fantasy baseball fans. An interesting extension would incorporate both fantasy baseball participants and non-participating MLB fans to compare and contrast points of attachment and consumption behavior. In addition, an extension to fantasy football and the other fantasy sports may be a fruitful line of research as would be a comparison between the media consumption habits of fantasy baseball and fantasy football participants. Rigorous inquiry of other well-researched attitudinal constructs (e.g., risk aversion, control) in conjunction with fantasy participation is always needed as the field is very much emerging and requires further exploration. Lastly, as mentioned above, future application of the PAl should consider the usage of the fantasy attachment items, as further psychometric validation is strongly suggested.

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Stephen L. Shapiro

Old Dominion University

Joris Drayer

Temple University

Brendan Dwyer

Virginia Commonwealth University

Address correspondence to: Stephen L. Shapiro, PhD. Old Dominion University, Student Recreation Center #2012 Norfolk, VA 23529. Email: sshapiro@odu.edu
Table 1--Reliability and validity testing for the adapted PAI

Factors and Items           Factor
                            Loading      t       SE      AVE    [alpha]

Attachment to Team            .79       --       --     -.754    0.86

--I consider myself to be
a "real" fan of (team)

--I would experience a        .92     20.12 *    .06
loss if I had to stop
being a fan of (team)

--Being a fan of (team)       .89     19.52 *    .06
is very important to me

Attachment to Players                           .810             0.89

--I am more a fan of          .79       --       --
individual players than
the (team) in general

--I am a big fan of           .93     17.69 *    .07
certain players more than
I am a fan of the (team)

--I consider myself to be     .97     19.34 *    .06
a fan of players rather
than a fan of the (team)

Attachment to Community                                 .789     0.89

--I feel connected to         .84       --       --
numerous aspects of the
community

--I feel a part of the        .96     19.34 *    .06
community in which the
(team) calls home

--I support the               .86     19.85 *    .05
city/region which is home
to the (team) as a whole

Attachment to Sport                                     .764     0.86

--First and foremost, I       .61       --       --
consider myself a
baseball fan

--Baseball is my favorite     .97     10.88 *    .15
sport

--Of all sports, I prefer     .99     10.57 *    .15
baseball

Attachment to Fantasy                                   .689     0.77

--Fantasy baseball is the     .85       --       --
reason for my interest in
MLB

--I would experience a        .81     21.08 *    .05
loss if I could not play
fantasy baseball

Note: * p <.05; [varies] = Cronbach's alpha coefficient;
AVE = Average variance extracted;
SE = Standard error; t = t-values

Table 2--OLS Regression Results--RQ1 (Traditional Consumption)

                                                  p-
DVs     Selection Variables   Rz       Beta    values

Game Attendance               .191
        Player                         -.006     .935
        Team                            .161     .030
        Community                       .192    <.001
        Sport                           .075     .099
        Fantasy Team                   -.023     .705

MLB Merchandise Purchase      .163
        Player                         -.040     .613
        Team                            .229     .009
        Community                       .123     .016
        Sport                           .073     .173
        Fantasy Team                   -.042     .563

Favorite Team
Merchandise Purchase          .270
        Player                          .069     .359
        Team                            .424    <.001
        Community                       .096     .047
        Sport                          -.004     .940
        Fantasy Team                   -.127     .065

Note: DV = Dependent Variable; Beta = Unstandardized
Beta Coefficient

Table 3--OLS Regression Results--RQ2 (Mediated Consumption)

DVs                Selection      [R.sup.2]    Beta       p-
                   Variables                           values
                                    .064
Internet           Player                      -.087     .366
Consumption        Team                         .261     .015
for Fantasy        Community                   -.040     .522
Purposes           Sport                        .150     .022
                   Fantasy Team                 .220     .013

Television                          .099
Viewership for     Player                       .456     .012
Fantasy            Team                         .646     .001
Purposes           Community                   -.043     .710
                   Sport                        .305     .012
                   Fantasy Team                 .184     .262

Internet                            .197
Consumption for    Player                      -.057     .738
Favorite           Team                         .836    <.001
Team Purposes      Community                   -.152     .164
                   Sport                        .056     .623
                   Fantasy Team                -.161     .299

Television                          .209
Viewership for     Player                       .197     .239
Favorite Team      Team                         .918    <.001
Purposes           Community                   -.012     .910
                   Sport                        .006     .959
                   Fantasy Team                -.267     .082

Note: DV = Dependent Variable;
Beta = Unstandardized Beta Coefficient
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