Abstract
Purpose
With the remarkable advancements in information and communication technologies, comprehending online sport fan communities is being pushed further up in the agenda of sport teams worldwide. Based on social identity theory, the main purpose of this research paper is to test the mechanism of how horizontal relationships developed through online communities lead to vertical relationships such as team identification and behavioural intentions.
Design/methodology/approach
Using a sample of online baseball fan community members in South Korea (N = 400) and employing structural equations modelling, the current research examined the structural relations among online community identification, team identification, behavioural intention and WOM intention while testing moderating effect of perceived authenticity.
Findings
This study finds that online community identification has a significant positive impact on team-level consumer outcomes: team identification, behavioural intention and WOM intention. Team identification is verified as a significant determinant of both behavioural intention and WOM intention. Moreover, the partial mediating role of team identification in the relationships between online community identification and behavioural intentions are corroborated.
Originality/value
The present study furnishes essential information for identifying the underlying mechanism of how fan-to-fan horizontal relationships cultivate team-to-fan vertical relationships in the context of the virtual fan community.
Keywords
Citation
Kim, S. and Manoli, A.E. (2023), "From horizontal to vertical relationships: how online community identification fosters sport fans’ team identification and behavioural intentions", International Journal of Sports Marketing and Sponsorship, Vol. 24 No. 1, pp. 1-19. https://doi.org/10.1108/IJSMS-09-2021-0188
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited
Introduction
Sport fans are co-creators of teams’ value, not passive consumers anymore (Hedlund, 2014; Uhrich, 2014). With the development of Internet-based communication technologies, the power has shifted from marketers to sport consumers (Brogi, 2014) and thus consumers’ voice has become a crucial aspect to consider in the decision-making process of brands (Black and Veloutsou, 2017). The expansion of individuals’ influence on brands' decision-making processes and brand management has been witnessed (Bi, 2019). As a result, online communication platforms should be a vital element of the marketing mix of any sport organisation as they can play a significant role in the sport consumer behaviour patterns of modern age sport fans.
It is worth noting that online communities are inherently different from traditional brand communities. Firstly, online fan communities allow for the transcendence of physical barriers of time and distance, making online communities a powerful platform to build fan-to-fan relationships. The fundamental power of an online community resides in the ability of its members to interact with each other without a time or space restriction (Brogi, 2014). Secondly, beyond the obvious differences, the concept of an online sport fan community in the current study is distinguished from other types of communities in terms of ownership since the community was created and operated by fans voluntarily, and is thus not a company-sponsored channel. An increased interest in differentiating between brand-created and user-generated media platforms has emerged recently (e.g. Bruhn et al., 2012). Thirdly, the fan-to-fan relationship does not merely stay online. Online communities often transition into offline groups and gatherings based on the developed sense of community and trust (Abfalter et al., 2012). Over the years, considerable research attention has been devoted to investigating the underlying mechanism of electronic-to-face interactions (e.g. Zhang et al., 2020). Thus, the online community should be viewed as a key focal point of a team in understanding sport fans’ actual behaviour. However, few studies have explicitly explored how the subgroup membership in an online environment (i.e. online community identification) starts to develop a connection to the superordinate level (i.e. a sport team) outcomes (Katz et al., 2020), creating a number of research gaps regarding the features of online sport fan communities.
The first research gap is the overlooking of online community identification in the sport marketing literature, despite the prominent role of online communities in facilitating fan-to-fan interactions in the digital era. Although sport marketing scholars have studied community identification (e.g. Katz et al., 2020; Yoshida et al., 2015a; Yoshida et al., 2015b), they have only focused on these communities offline in face-to-face environments. As Katz et al. (2020) pointed out, Katz et al. (2018) only identified consumer-company identification, not consumer-community identification, and while Yoshida et al. (2015b) differentiated between team identification and community identification, they did not examine the relationship between the two constructs. Previous sport management research does not, as of yet, furnish satisfactory insights into how fan-to-community identification within an online fan community platform is important in strengthening fan-to-team identification. This gap is also associated with the impacts of online community identification on fans' behaviour. An effort to uncover the outcomes of online community identification has yet to be made in the context of sport fans (Yoshida et al., 2015a).
The use of social media platforms is a powerful modern trend in that two-thirds of the public in some countries already use social media platforms to learn the news (Pew Research Center, 2021). As information dissemination has become faster than ever before, a sport team’s authenticity in marketing communication should be a central element in the digital era (Kim and Manoli, 2022; Pronschinske et al., 2012). This idea leads to the second research gap of the current study. Brand managers have increasingly recognised the pivotal role of authentic brand behaviour and considered authenticity as a desirable brand characteristic (Guèvremont and Grohmann, 2016). The perception of authenticity is reported to be a significant antecedent of brand trust (Portal et al., 2019; Schallehn et al., 2014), brand attachment (Morhart et al., 2015), relationship quality (Fritz et al., 2017), brand loyalty (Lu et al., 2015) and positive WOM (Morhart et al., 2015). Consumers often make a purchase decision when the product or brand values are congruent with their own values, and this conformity may determine the authenticity of a brand (Schallehn et al., 2014). Despite this significant influence of brand authenticity on consumer behaviour, the exploration of a sport team’s authenticity is in its early stage (Cho et al., 2020). Given that authenticity is a primary element that can perpetuate the business orientation in a crisis or erosion of brand trust (Napoli et al., 2016), efforts to understand how sport teams’ authenticity can affect fans’ behaviour are essential in the ever-changing market.
To fill these research gaps, the aim of the current study is threefold. While the core element of online communities is the brand (i.e. team) itself, an online community exists and persists because of the relationships among members and their memberships (Jang et al., 2008). Therefore, investigating whether fan-community identification (subgroup identity) is associated with fan-team identification (superordinate identity) is the first purpose of the study. The second aim of the current study is to explore the mediating role of team identification between online community identification and attendance intention and WOM intention. Third, the authors will explore how perceived authentic behaviour of sport teams affects the connections between online community identification and fan-to-team relationships of community members (i.e. team identification, attending intention and positive WOM intention).
Literature review and hypotheses development
Identifications within online fan communities
Drawing on Lock and Heere’s (2017) study, both online community identification and team identification are founded on social identity theory (SIT). SIT has been successfully applied in sport marketing literature as a theoretical basis and is considered a useful framework for investigating sport fan behaviour (Heere and James, 2007; Yoshida et al., 2015b). SIT is defined as “the individual’s knowledge that he or she belongs to certain social groups together with some emotional and value significance to him or her of this group membership” (Tajfel, 1982, p. 31). By categorising themselves as members of a certain social group, individuals create their own social identity to establish self-esteem and show favourable bias toward the social group to which they belong (Mael and Ashforth, 1995).
Although sport fans’ SIT studies primarily focused on team identification in the past, recent studies have explored other identities that are embedded within team identification (Katz et al., 2020). In other words, it is now generally accepted that sport fans can belong to various subgroups under the superordinate identity while they anchor their identification with sport teams as a focal point (Lock and Heere, 2017). Lock and Funk’s (2016) Multiple In-Group Identity Framework (MIIF) support this idea. Applying the MIIF to the current study, team identification used in this study corresponds to a superordinate level and online community identification is equivalent to a subgroup membership (Lock and Funk, 2016). An important premise regarding the two identities is that the subgroup identity slightly overlaps the superordinate identity, rather than a separate and unique social identity that is entirely independent of the team identification.
Regarding the notion of fans interacting with other fans, online sport fan communities have been born in a virtual setting, specifically Web 2.0; that is, the interaction between fans is a distinctive feature of the online community. Communication technologies have shifted the emphasis on sport fans’ ways of Internet use from getting information to user-generated content and information sharing (Quinton, 2013). The digital world offers an ideal platform to promote not only the interaction between a brand and its consumers, but also interaction among consumers. Connectivity and participation are two keywords to explain the consumers’ or members’ interaction (Wu and Fang, 2010). The virtual communities allow fans to connect with each other without the restriction of time and place through chat rooms and discussion forums, while participation enables them to share emotions by exchanging and sharing information about their team. These features of online communities can play an important role not only in enhancing a strong connection between members but also in building a solid relationship with brands (Brogi, 2014).
Members of an online community can strengthen a sense of belonging with the community through sharing their common interests and expressing their passion and love, while these social interactions among members ultimately affect members’ relationships with the brand (Popp and Woratschek, 2017; Zhou et al., 2012). Online fan communities tend to create a strong sense of fellowship with other members since their identity as fans of a specific team is represented and strengthened by the community (Kim and Kim, 2017). This idea is also supported by Muniz and O’Guinn’s (2001) brand community triad. Based on the brand community triad, which emphasises both the brand-customer relationship and the customer-customer relationship, sport fan communities are considered strong examples of brand communities (Katz et al., 2018). It is worth noting that online sport fan communities are different from other online brand communities. Research suggests that members of a sport fan community have higher levels of self-esteem, positivity, collective unity, social opportunities, and inclusiveness, and they thus experience an increase in social capital (Mastromartino et al., 2020; 2020). Unlike any other brand, sport has the advantage of being widely broadcasted, producing content (i.e. matches and news) almost every day, further enhancing the experiences of their members. Therefore, it is worth noting that both community identification and team identification coexist within online communities. Thus, efforts to understand the role of the online community as a channel for nurturing team identification and consumption behaviour are required.
Impact of online community identification
A considerable amount of sport marketing research has demonstrated the relationship between community identification and team identification in an offline setting. Yoshida et al. (2015b) corroborated the positive link between community attachment and team identification focusing on an offline community setting (i.e. loyalty program participation). Heere et al. (2011) tested the relationships between multiple community identities (university identity, city identity and state identity) and team identity. They confirmed the association between the multi-community identity and college football team identification. Although an extensive amount of the existing sport marketing literature well expands the understanding of sport fans’ community identifications in offline settings, there is still a notable paucity of knowledge regarding online sport fan communities.
The importance of consumers’ interaction and membership in building strong customer-brand relationships is underpinned by many scholars (e.g. Bi, 2019; Hedlund, 2014). For example, Bi (2019) argued that interpersonal interactions and customer-community relationships in online communities link the members together, which results in cultivating loyal customers. In the sport marketing literature, Uhrich (2014) argued that “the importance of customer-to-customer interactions is particularly obvious in the team sport” (p. 26). Katz and Heere (2015) proposed a sport fans’ brand community model that explains the salience of fans’ social relations with other fans, arguing that fan-to-fan relationships are an important component of brand community formation. In the same vein, Katz et al. (2018) asserted that horizontal relationships should be the focal point for sports marketers while highlighting multiple connections' integration. This study, thus, suggests that covering both fan-to-community and fan-to-team relationships in the investigation of a sport fan community provides a more in-depth insight into understanding sport fans’ behaviours. However, it is not the authors’ intention to assume which concept occurs first since scholars verified the effect of in-group memberships on fans’ identification with and behaviour towards the superordinate group, such as team identity (Lock and Funk, 2016).
Evidence of the relationship between online community identification and team identification can be found in brand research. For instance, Zhou et al. (2012) verified that online brand community identification directly influences brand identification. Interestingly, consumer commitment towards an online brand community did not affect brand commitment. Instead, they found that the online community commitment becomes brand commitment through attachment and emotion (Zhou et al., 2012). These results indicate that online community identification might translate into team identification without the cultivation of fans' attachment. The current study posits that an online community may enhance sport fans’ team recognition and attitude, thus strengthening their identification with the team. As a result, the following hypothesis is posed:
Online community identification is positively associated with team identification.
In addition to the impact of online community identification on team identification, the current study also aims to investigate the effect of online community identification on team-level behavioural intentions (i.e. attendance and positive WOM intentions). The relationship between online sport fan community identification (membership) and attitude (e.g. Alonso Dos Santos et al., 2016) and behaviour outcomes (e.g. Mastromartino et al., 2020) has been explored. Their results show that identification with online fan community translates into a favourable attitude and behaviour toward the team and sponsor brand. A similar result was noted by Yoshida et al. (2015a), yet their research was not on the online community context. Therefore, how online community identification predicts a fan's positive WOM intention, which is an important driver of expanding a fan base, remains unanswered, while the relationships should be investigated within other cultural contexts, as Alonso Dos Santos et al. (2016) and Mastromartino et al. (2020) conducted their studies in western cultures. In the brand management context, empirical results generally indicate that securing online community identification is considered to be a key driver of the positive effect on customer behaviour. Specifically, Popp and Woratschek (2017) confirmed that there was a substantial influence of customers’ online brand community identification on positive WOM and attitudinal loyalty. Support for linking online community identification and behavioural intentions is also found in the work of Kim and Kim (2017) who delineated that online fan community identification has a significant impact on loyalty (e.g. purchase intention and positive WOM intention) towards both the celebrity and the community. These results can be extended to the sporting context. Theoretically, SIT could underpin the mechanism by which online fan community identification could influence behavioural intentions of sport fans, since identified community members would develop the in-group favouritism and out-group bias, ultimately increasing their loyal behaviour to harmonise their value with the social group’s value (Mael and Ashforth, 1995). Based on the existing literature and SIT, the authors propose the following hypotheses:
Online community identification is positively associated with attendance intention.
Online community identification is positively associated with WOM intention.
Impact of team identification and its mediating role
When it comes to a consequence of sport fans’ team identification, the concept has been acknowledged to be a powerful driver of consumption behaviour (Heere et al., 2011). Team identification was found to positively affect loyalty (Heere and James, 2007) and positive WOM intentions (Chang et al., 2018). Moreover, identification with a team was found to be a more robust antecedent of sport fans’ attendance than satisfaction (Trail et al., 2003; Trail et al., 2003) and it largely determines psychological factors of sport fans such as forming self-esteem and loyalty (Wann et al., 2000). Results of empirical studies show that the more sport fans categorise themselves in a particular team and identify themselves as fans of the team, the more likely they are to behave favourably and be committed towards the team.
In addition, the link between team identification and behavioural intention is well explained by SIT, which helps to understand the influence of sport fans’ group membership towards a team on consumer behaviour (Lock and Heere, 2017). The manifestation of identity begins when an individual who has an identity in the “in-group” discovers a difference with someone who is an “out-group” (Abrams and Hogg, 1988). Turner et al. (1987) explained the mechanism of identity with the terms; in-group favouritism and out-group bias, suggesting that individuals are more discriminatory towards the relevant out-group than the irrelevant out-group. This finding can help illustrate the phenomenon of sport fandom since the existence of team sports is often based around being classified as having a team one supports and one or many teams they are against.
While the impact of team identification on consumer outcomes has been widely reported, the present study is different from previous research in the sense that it examined team identification through an online interface. The current study is one of the first studies to examine the influence of online-based fan-to-fan ties on team-level outcomes. Also, the sample is collected from a different and understudied region and sport league (i.e. professional baseball league) that would contribute to extending previous knowledge on sport fan behaviour. The clear empirical evidence led the current study to establish the following hypotheses:
Team identification is positively associated with attendance intention.
Team identification is positively associated with WOM intention.
The mediator effect of team identification has been examined in various contexts, for instance, team identification mediated the effect of dissimilarity on conflict (Hobman and Bordia, 2006) and the effect of fans’ satisfaction on attitudinal loyalty (Bodet and Bernache-Assollant, 2011). Furthermore, Heere et al. (2011) confirmed that the relationship between group identities (city, state, and university identities) and behavioural consequences is fully mediated by team identification. Since team identification has been considered to be a primary driver of behavioural intention and positive WOM intention (Chang et al., 2018), it is logical to assume that the more fan-to-fan horizontal relationships are established, the more they feel that their fan-to-team vertical relationships reflect their self-concept, which will lead to positive behavioural intentions. Strong fan-to-fan relationships in an online community allow for fans to feel superior to other fan groups, strengthening their team identification and giving them a reason to be committed and willing to spread positive words about the team. Therefore, we hypothesise that:
Team identification will partially mediate the relationship between online community identification and behavioural intention.
Team identification will partially mediate the relationship between online community identification and positive WOM intention.
Perceived authenticity
Unlike traditional marketing communication (e.g. advertisement) or brand-created social media, information diffusion of negative (e.g. issues and scandals) content about sport teams can also be swift within the online community context (Bruhn et al., 2012). In this light, authentic brand behaviour that can be both positive and negative content in an online setting might be useful for sport consumers in terms of attendance decisions and positive word-of-mouth. Existing literature shows that any inconsistent behaviour of sport teams can lead to deviations from the expected brand core values, resulting in an increased likelihood of brand reputation and trust deterioration (Portal et al., 2019).
Competition in the sport market is driving sport teams to find different approaches to the business, and authenticity represents one way in which a sustainable relationship with key stakeholders (i.e. sport fans and the public) can be built by providing them with a distinctive experience (Cho et al., 2020). More importantly, informed consumers demand more authentic brand behaviour than ever before, and they refuse to accept unauthentic brand behaviours (Schallehn et al., 2014). By putting a brand’s values at the centre of its initiatives and by implementing these initiatives that align with the values, consumers are likely to perceive a brand’s authenticity, which, in turn, can result in brand trust (Portal et al., 2019). Thus, authenticity should be positioned as a primary factor that makes a brand distinct from other brands in today’s competitive world (Schallehn et al., 2014).
Regarding the concept of authenticity, a brand is considered authentic when they act genuinely and do not manipulate customers (Portal et al., 2019). Cho et al. (2020) defined sport team authenticity with three conditions, “whether the team’s value is consistent, whether the team’s value is congruent with individual values, and how much the team is oriented toward the fan” (p. 152). However, the current study holds a slightly different point of view in defining authenticity. Given that brand authenticity can be achieved by communication strategies (Quinton, 2013), the present study situated the perceived authenticity in relationship management through strategic communication. As the feedback function of online-based communication technologies blurs the boundaries of traditional one-way relationships from a message sender (e.g. sport teams) to a message receiver (e.g. sport fans), strategic communication in achieving brand authenticity has become more critical than ever before. For these reasons, this study adopts Shen and Kim’s (2012) concept of perceived authenticity who hold a relationship management point of view. They identified truthfulness, transparency and consistency as key components that form the basis for an organisation’s authenticity. Another core element of perceived authenticity is sport fans’ evaluation. There is a consensus that the concept is an assessment of a particular object evaluated by consumers from their personal experiences rather than an intrinsic attribute of an object (Grayson and Martinec, 2004). Projecting this emphasis on consumers’ evaluative attribute and the three factors of Shen and Kim’s (2012) definition into this study, the authors view authenticity as the perception of a sport fan’s subjective evaluation of the various experiences associated with a team’s level of truthful, transparent and consistent communication with fans.
The moderating effects of perceived authenticity
One of the objectives of this research is to uncover the intermediate mechanism moderating online sport fan community’s effects on team-level outcomes (i.e. team identification, attendance intention and WOM intention) relationships. In the relationship between online community identification and team level outcomes, this study postulates that authenticity is to act as a moderator. Recent tourism literature has hinted at the moderating effect of perceived authenticity. Meng and Han (2019) empirically corroborate that the perceived authenticity of tourists significantly moderates the relationship between place identification and destination loyalty. Their result indicated that tourists’ authentic perception foster the influence of attachment (i.e. place identification) on destination loyalty. Yet, it should be noted that Meng and Han’s (2019) concept of perceived authenticity refers to tourism authenticity that is concerned with the originality of toured objects, while the current study views perceived authenticity as authentic organisational communication and behaviour (Shen and Kim, 2012). Meng and Choi’s (2017) study verified that perceived authenticity significantly moderates the relationship between communicative staging (a type of servicescape) and customer emotion and the relationship between customer emotion and satisfaction. Considering the fact that identification can be seen as a type of emotional attachment (affective perception), their study also offers some guidelines.
The consequences of brand authenticity illustrate that perceived authentic perception has a beneficial effect on consumers’ psychological outcomes and behavioural intention variables (Morhart et al., 2015). It is, thus, logical to assume that sport fans are likely to feel the increased attendance intention and positive WOM intention when they perceive that a sport team’s communication and behaviour is congruent with its values and beliefs, while the effects of team identification and online community identification on perceived authenticity remain uncertain. This assumption meets the requirement of testing the moderation effect of authenticity on the relationship between identification with the online community and team identification and positive behavioural intentions (Baron and Kenny, 1986). Following the discussion, the present study proposes that the magnitudes of hypothesised relationships between sport fans’ identifications and behavioural intentions might differ by perceived authenticity. Hence, the following hypotheses are established:
Perceived authenticity will moderate the relationship between online community identification and team identification.
Perceived authenticity will moderate the relationship between online community identification and attendance intention.
Perceived authenticity will moderate the relationship between team identification and positive WOM intention.
Figure 1 illustrates the proposed research model for the current study.
Methodology
Sampling and data collection
The data used in this study were collected from members of an online sport fan community by carrying out web-based questionnaire surveys with a non-probability quota sampling method. As an online sport fan community, an online community that supports Samsung Lions baseball club, which is affiliated with the Korea Baseball Organisation (KBO), was selected. The Samsung Lions online fan community was founded in 2006 and had over 7,300,000 posts and 58,400 members as of 15th June 2021. The online sport fan community is based on “NAVER:, the largest research engine in South Korea; it is regarded as a representative online sport fan community, while it was also awarded the “Community of the year: field of sport/leisure” award in 2016.
Supported by the community managers, the survey was posted on the notice board of the main page of the community, which enabled every member of the community to access it. The questionnaire was posted between 30th May to 13th June 2021. To mimic the demographic characteristics of the sample population (i.e. the fanbase of the KBO), the current study applied a quota sampling technique setting quotas regarding key demographics: gender and age. The quota sampling approach has been previously applied in studies in the context of mega sport events (e.g. Funahashi et al., 2020; Ouyang et al., 2017), being welcomed as a response to the limitations of non-probability sampling, and was thus adopted in our study. As a result, the fan demographic data at the league based on the game attendance behaviour of the 2019 season (Prosports data portal, 2021) and the online fan community demographics were compared and matched. 400 sample targets were stratified by a distribution equivalent to KBO overall fanbase characteristics regarding key demographics. In addition, small prize vouchers were offered to participants in order to encourage participation, while all participants were also informed of the study’s aims.
Measurement
All measurement scale items were adapted from existing research that has been empirically tested. To measure both online community identification and team identification, five items established by Algesheimer et al. (2005), which contain cognitive and affective components, were adapted. The scale was considered appropriate to assess fans’ identification from the online community context since the validity and generalisability of Algesheimer et al.’s (2005) scale have been well established in previous studies (e.g. Hsu et al., 2012; Zhou et al., 2012). Furthermore, the scale has been used before to effectively measured the association between consumer-community identification and consumer-brand identification simultaneously (e.g. Popp and Woratschek, 2017), making it the ideal scale for our study. Next, in line with the operationalisation and conceptualisation of perceived authenticity in the current study, measures of perceived authenticity were used from the seven-item scale by Shen and Kim (2012). The measurement scale evaluates sport fans’ perception of authentic brand (team) behaviour, covering trustfulness, transparency and consistency aspects, in line with how perceived authenticity is conceptualised in our work. Finally, attendance intention and positive WOM intention were measured using six items from the scale used by Algesheimer et al. (2005) and Brown et al. (2005) since the measurement items have been used in similar contexts before (e.g. Popp and Woratschek, 2017), making them the best fitting scales for our research.
Participants were asked to provide their responses on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Two scholars, who are familiar with this research domain and bilingual in both English and Korean, translated and reviewed the questionnaire using the back-translation strategy (Brislin, 1970). Several revisions were made, such as possible ambiguities in the wording of the questions. Then, two community leaders and eight randomly selected online community members reviewed the questions. Then survey could move on to the next analysis.
Results
Sample profile
Table 1 presents the characteristics of the respondents that also matched with fan demographic data at the league level in terms of age and gender. More detailed information is presented in Table 1.
Analysis of measurement model
Before assessing the psychometric properties of the measurement tools, this study conducted a preliminary analysis to identify the univariate and multivariate normality. The univariate normality of the data was examined by employing skewness and kurtosis. Skewness statistics ranged from −0.89 to −0.16, and kurtosis statistics ranged from −1.07 to 1.09. These results indicate that the data was univariate normal (Pallant, 2010). The current study detected outliers using Mahalanobis distance (Pallant, 2010). The results showed that 14 responses with Mahalanobis distance values ranging from 12.92 to 34.12 were detected as outliers at p < 0.01 level. The significance level and the values were determined by chi-square distribution. The 14 cases were eliminated for the next phase of the analysis.
The internal consistency reliability of the data was identified using Cronbach’s alpha values and standardised factor loadings. The result revealed that Cronbach’s alpha values of all constructs are above the 0.70 threshold, ranging from 0.82 to 0.91 (Bagozzi and Yi, 2012). The subsequent confirmatory factor analysis showed that the standardised factor loading of all observed variables from five constructs met the Bagozzi and Yi’s (2012) suggested threshold of 0.70. Also, t-values of each observed variable were significant (at p < 0.001 level), suggesting that the measuring items have adequate construct validity. The overall measurement model fit indices met the criterion by Hair et al. (2010): χ2/df = 2.62, p < 0.001, RMR = 0.06, GFI = 0.90, NFI = 0.92, IFI = 0.95, TLI = 0.94, CFI = 0.95, RMSEA = 0.06, indicating that items within each construct are more associated with each other than items from other constructs.
Next, convergent validity and composite reliability (CR) was confirmed. Assessing convergent validity in the present study was based on the average variances extracted (AVE). Items measuring five constructs showed CR value ≥ 0.82 and AVE value ≥ 0.61, indicating that the values were above Bagozzi and Yi’s (2012) recommended standards of 0.70 (CR) and 0.50 (AVE). All the values, therefore, indicated an adequate convergent validity of the items. Furthermore, discriminant validity was identified based on Fornell and Larcker’s (1981) criterion, which posits that the discriminant validity is secured when correlations do not exceed the square root of AVE values. Table 3 reveals that all the square roots of AVE were above the coefficients representing its correlation with other constructs, and thus discriminant validity was achieved. Tables 2 and 3 summarise the psychometric properties of the data.
Common method bias
Since the current study collected data for all variables cross-sectionally, common method bias could be an issue. To address the potential bias, Podsakoff et al. (2003) recommended applying procedural strategies and/or statistics strategies. As a way of procedural strategies, respondents are guaranteed their anonymity while being informed about the purpose of the study and the fact that there are no right or wrong answers to the questions. In terms of statistics strategies, the sample was analysed employing Harman’s single factor test. Using factor analysis, the main factor explained 41.34% of the variance; so, no single factor explained more than 50% of the variance (Podsakoff et al., 2003). This result indicates that common method variance bias is not a significant issue with the data.
Structural model and hypotheses testing
To examine the established hypotheses, structural equation modelling using AMOS software was adopted as it is suitable to test a two-step approach by assessing both the psychometric properties of the measures and the structural model (Byrne, 2016). The results of structural equation modelling showed that the proposed research framework fit the data well (χ2/df = 3.57, p < 0.001, RMR = 0.05, GFI = 0.94, NFI = 0.93, IFI = 0.93, TLI = 0.90, CFI = 0.93, RMSEA = 0.07). In terms of direct effects, the structural equation modelling supported all the direct effects of the hypotheses. The result found that online community and the horizontal ties that exist among fans were positively associated with team identification, supporting H1. The direct path linking online community identification to team identification was significant (β = 0.72, t = 20.35, p < 0.001), suggesting that sport fans’ community-level identification strongly connects to brand-level (i.e. team) identification. The direct effect from the online fan community identification to behavioural intention was significant (β = 0.25, t = 4.41, p < 0.001), while the path to positive WOM intention was also found to be significant (β = 0.22, t = 4.08, p < 0.001), and therefore, H2-1 and H2-2 were supported. H3-1 and H3-2 postulated that team identification influences attendance intention and WOM intention. The results illustrated that the effect of team identification to attendance intention was significant (β = 0.44, t = 7.79, p < 0.001), while the direct effect of team identification was also associated with WOM intention (β = 0.48, t = 8.95, p < 0.001), and therefore, H3-1 and H3-2 were accepted.
The present research explored whether online community identification indirectly influences brand-related attendance intention and positive WOM intention via team identification. A bias-corrected percentile bootstrap method was utilised to assess indirect effects' statistical significance and generate 2000 samples and 95% bias-corrected confidence intervals (CIs). According to the results, all the estimated coefficients within 95% bias-corrected CIs did not contain zero, suggesting that team identification's indirect effect is significant. Specifically, the indirect effect of online community identification on attendance intention via team identification was significant (β = 0.32, p < 0.001; Lower bounds of 95% CIs = 0.22; Upper bounds of 95% CIs = 0.41). A partial mediating role of team identification between online community identification and attendance intention was confirmed, supporting H4-1. The result of H4-2 indicated a partial mediating role of team identification in the relationship between online community identification and positive WOM intention (β = 0.35, p < 0.001; Lower bounds of 95% CIs = 0.26; Upper bounds of 95% CIs = 0.44).
Regarding the moderating effects, moderation analysis was conducted based on Baron and Kenny’s (1986) procedures. This study determined the moderating effects of authenticity according to the significance of the interaction conditions (Baron and Kenny, 1986). However, no significant moderating role of authenticity was found between online community identification and behavioural intentions (attendance intention: β = −0.09, t = −1.79, p = 0.07; WOM intention: β = −0.10, t = −1.99, p = 0.05), and between online community identification and team identification (β = −0.07, t = −1.96, p = 0.05), failing to support H5-1 to H5-3. Table 4 illustrates the results of hypotheses testing.
Discussion
Theoretical implications
This study explored the underlying mechanism of how online community identification cultivates team-to-fan relationships in the context of the virtual sport fan community. Overall, the results show that sport fans’ online community identification is a significant driver of all constructs: team identification, attendance intention and positive WOM intention. Also, the partial mediating role of team identification was confirmed.
Based on the results, this study offers the following theoretical implications. First, one of the most crucial theoretical contributions to the current knowledge is the exploration of the effects of community-level identification (i.e. subgroup online community identification) on brand-level identification (i.e. superordinate team identification) for the first time. Two contradictory views exist on the relationship between community identification and brand identification. Some studies suggest that brand identification affects brand community identification (e.g. Algesheimer et al., 2005), while others assert that brand community identification may reinforce their identification with the brand (e.g. Bagozzi and Dholakia, 2006). The findings of our study successfully reveal how fan-to-community identification enhances fan-to-team identification, extending the area of fan community identification to the online context. This finding is partly consistent with Katz and Heere (2015) and Lock and Funk (2016), who identified that both superordinate identification and subgroup identification have an impact on sport consumer behaviours, yet new in exploring this phenomenon in an online sport fan community context, thus offering novel insights in the context of sport. This theoretical implication can be elucidated by the fact that sport fans’ community identification serves as a platform to express self-imagery, strengthening the social value, cohesion, and extra-role prosocial behaviour of baseball fans. As Lock and Funk (2016) noted, given that satisfaction through the multifaceted need for identity and a sense of belonging are solid motivations for individuals, sport can provide a wide range of identity-related benefits for people, and the online community furnishes a perfect platform to pursue and materialise their identities. Thus, the first and primary theoretical contribution of the present research to the existing literature is the additional variance explained by uncovering the mechanism of how online platform-based identification contributes to team-level identification.
Second, this study extends multi-identifications research by demonstrating that a subgroup of the virtual environment affects actual behaviour intentions. Online community identification engenders behavioural intentions towards the team (attendance intention and positive WOM intention about the team) even though those relationships are not as strong as the link between online community identification and team identification, highlighting the partial mediating role of team identification. The current study confirmed that fans’ relationships formed in an online platform represent an intensified example of a consumer-to-consumer framework within the context of sport fan behaviour. This idea supports the view that the sport fans’ decision to attend a game and spread positive WOM can rely on their collective feelings in an online community. The result is also supported by many brand community studies. For instance, Bi (2019) argued that online community members’ level of commitment was higher in individual-centred online communities where interpersonal interactions are focused than in product-centred or knowledge-centred online communities. It is reasonable to understand that the theoretical importance of social experiences in an online fan community is established in the sport marketing context.
Third, the perceived authentic behaviour of a sport team is shown to not have an impact on the relationship between online community identification and team identification and behavioural intentions. This counterintuitive result can be explained by SIT as one of the major assumptions of the theory is that individuals would alter their attitude to conform to group identification (Zhou et al., 2012). Building upon the SIT, sport fans change their attitude in the direction of favouring the team, protecting their identification with the team, even if the team’s behaviour is perceived to be un-authentic. As a result, this current study confirmed that perceived authenticity is not effective in explaining sport fans’ social identity and behavioral intentions.
Managerial implications
Given that online fan community identification is a robust driver of team identification and behavioural intentions, sport marketers are advised to include online identification as a key objective. It should be noted that online fan community identification is “a form of self-expression and offers emotion-driven returns” (Kim and Kim, 2017, p. 241). Online community members may identify more deeply with the community over time, matching their values to the community. Sport marketers could then focus on enhancing this by encouraging sport players’ interactions with fans via the online community, or using elements of the teams’ history and values in their interactions with the online community and their members (Sutton et al., 1997). By enhancing the communal ties around a team through online communities, the team can retain existing fans by developing attendance intention and gathering new fans by developing positive WOM intention. Since sport fans may fulfil higher-order self-concept needs by identifying with other members in an online community which leads to team identification, the role of online communities and the fan-to-fan interactions need to be highlighted in sport management practice.
Currently, clubs in the KBO league are actively using social media channels such as YouTube as a method of interacting with fans, but online communities offer a better platform for eliciting fans’ social activities such as discussion, exchange of ideas and real-time reactions. The online community can be a virtual playground for sport fans. In this sense, sport marketers should pay particular attention to driving and rewarding user-generated online community members, potentially through teams’ promotional activities utilising the online community, which will also result in increased attendance and WOM for attracting new fans. By doing so, fans might have extra motivation to engage in community activities, which will result in identifying themselves further with the community. In addition, sport teams’ marketers need to optimise online fan communities as a means of two-way communication between the team and its fan. An interaction-oriented community design might encourage fans’ participation and sharing of their opinions. Moreover, if sport fans have more interaction opportunities directly with their team, the social interaction binds them together so that identification with both the community and the team might increase. Taking all the above into consideration, this study illustrates why building and maintaining online sport fan communities can be a meaningful and vital priority for sport management practice.
At the same time, given the direct effect and partial mediating role of team identification on the relationship between online community identification and behavioural intentions, sport marketers are advised to set team identification as their key objective to increase the loyalty of the online community members. Because the path from online community identification to team identification is strong, cultivating team identification is important to secure fans’ positive behavioural intentions. In order to strengthen team identification, sport marketers can develop and adopt marketing strategies with high fan-orientated value (Cho et al., 2020), such as encouraging fan rituals, group experiences and team history sharing (Wang and Tang, 2018). As more sport fans are expected to visit sport venues across the world after the COVID-19 pandemic, sport marketers should develop plans for generating meaningful attachments to venues (Cho et al., 2019) that are associated with team identification (Lee et al., 2017). In order to achieve that, they can utilise online communities to share information regarding the updated stadium environment (e.g. hygiene, parking space, and food service).
Limitations and future research
There are certain limitations of this study that need to be acknowledged. The first limitation is regarding the sample characteristics. The sample population of the current research is limited to one type of sport, using data collected from a single sport league (KBO league). As a result, the findings’ generalisability to other sports or other contexts with different features might be limited. Thus, considering other types of sports and leagues in future studies could help in dealing with the external validity and in offering further insights in this interesting field. Secondly, internal validity could be improved by adding control variables to rule them out as alternative explanations for the observed relationships between constructs. For instance, the present study did not take into account the fact that a team’s performance and income of a fan could affect the overall perception of fans toward their team and behavioural intentions, something that could be considered in future research. Thirdly, different cultures may have different attitudes toward the online community and sport team fandom. As such, the perceptions and environment of the online community in South Korea, the focus of this study, may be different from other countries. Comparative research across countries might generate more insights into the research model proposed in this study. At the same time, future investigations could apply a longitudinal design to capture the relationship between online community-level outcomes and team level outcomes and dynamics in more depth. Lastly, one of the dependent variables of this study is behavioural intention, which gauges fans’ intention to attend a game. Yet, behavioural intention is sometimes considered a weak predictor of future behaviour (for example, see Yoshida et al.’s (2015b) study). As a result, other variables as the outcome of sport fans’ identifications should be applied in future studies on the topic in order to account for this limitation.
Figures
Demographic characteristics
| Profile | Description | Responses (N = 400) | Percentage (%) |
|---|---|---|---|
| Gender | Male | 208 | 52.0 |
| Female | 192 | 48.0 | |
| Age group | 17–19 years | 73 | 18.3 |
| 20–29 years | 145 | 36.2 | |
| 30–39 years | 84 | 21.0 | |
| 40–49 years | 72 | 18.0 | |
| 50 years and above | 26 | 6.5 | |
| Occupation | Student | 142 | 35.5 |
| Part-time employee | 2 | 0.5 | |
| Full-time employee | 179 | 44.8 | |
| Self-employed | 34 | 8.5 | |
| Retired | 6 | 1.5 | |
| Other | 37 | 9.3 | |
| Highest educational qualification | Less than a high school diploma | 41 | 10.3 |
| Associate degree | 127 | 31.8 | |
| Bachelor’s degree | 207 | 51.7 | |
| Graduate degree | 25 | 6.3 | |
| Questions for sample behaviour | |||
| How long have you been Lions’ fan? | Less than one year | 23 | 5.8 |
| 1–3 years | 74 | 18.5 | |
| 4–6 years | 86 | 21.5 | |
| 7–9 years | 39 | 9.8 | |
| More than 10 years | 178 | 44.5 | |
| How many times do you visit the community? | 1–2 times | 89 | 22.3 |
| 3–4 times | 100 | 25.0 | |
| 5–6 times | 59 | 14.7 | |
| More than 7 times | 152 | 38.0 | |
Measurement scale properties and dimensionality
| Constructs and indicators (label) | M | SD | β (t-value) | α | CR | AVE |
|---|---|---|---|---|---|---|
| Online community identification | 0.90 | 0.88 | 0.71 | |||
| I am very attached to the Lions fan community (OCI1) | 5.32 | 1.07 | 0.87 (18.99) | |||
| I see myself as a part of the Lions fan community (OCI2) | 5.13 | 1.24 | 0.84 (18.21) | |||
| The friendship I have with other Lions fan community members means a lot to me (OCI3) | 5.10 | 1.29 | 0.82 (14.78) | |||
| Other Lions fan community members and I share the same objectives (OCI4) | 5.51 | 1.22 | 0.71 (14.86) | |||
| If Lions fan community planned something, I’d think of it as something ‘we’ would do rather than ‘they’ would do (OCI5) | 5.42 | 1.23 | 0.79 (14.22) | |||
| Team identification | 0.88 | 0.90 | 0.63 | |||
| I am very attached to the Samsung Lions (TI1) | 6.11 | 1.03 | 0.84 (15.10) | |||
| I see myself as a part of the Samsung Lions (TI2) | 5.22 | 1.71 | 0.81 (14.60) | |||
| The friendship I have with other Samsung Lions means a lot to me (TI3) | 5.76 | 0.98 | 0.77 (13.89) | |||
| Other Samsung Lions fans and I share the same objectives (TI4) | 5.93 | 1.05 | 0.84 (15.17) | |||
| If Samsung Lions planned something, I’d think of it as something ‘we’ would do rather than ‘they’ would do (TI5) | 5.73 | 1.12 | 0.71 (11.23) | |||
| Authenticity | 0.91 | 0.92 | 0.63 | |||
| This team always tells the truth (Auth1) | 4.60 | 1.37 | 0.76 (15.50) | |||
| I believe that this team’s actions are genuine (Auth2) | 4.83 | 1.32 | 0.82 (17.18) | |||
| I feel that this team is willing to admit to mistakes when they are made (Auth3) | 4.73 | 1.11 | 0.71 (14.45) | |||
| I feel that this team accepts and learns from mistakes (Auth4) | 5.07 | 1.37 | 0.79 (16.35) | |||
| I believe that this team’s behaviour matches its core value (Auth5) | 4.89 | 1.42 | 0.77 (11.41) | |||
| The team’s beliefs and actions are consistent (Auth6) | 4.90 | 1.41 | 0.89 (18.79) | |||
| I think this team marches the rhetoric with its action (Auth7) | 5.11 | 1.37 | 0.73 (14.63) | |||
| Behavioural (attendance) intention | 0.82 | 0.82 | 0.61 | |||
| I will attend more matches in the next few years (BI1) | 5.99 | 0.99 | 0.83 (14.40) | |||
| I will continue to attend matches even if tis prices increase (BI2) | 5.57 | 1.28 | 0.80 (14.05) | |||
| I will continue to attend matches even if experiencing a few problems such as traffic congestion (BI3) | 5.52 | 1.24 | 0.71 (12.36) | |||
| Positive WOM intention | 0.87 | 0.89 | 0.74 | |||
| I will comment positively about my Samsung Lions on the community (WOM1) | 5.76 | 1.05 | 0.81 (20.04) | |||
| I would recommend the community and the Samsung Lions to someone who asks my advice (WOM2) | 5.79 | 0.97 | 0.88 (23.21) | |||
| I will hardly miss an opportunity to tell others positive things about Samsung Lions (WOM3) | 5.80 | 1.15 | 0.89 (23.33) | |||
Note(s): χ2/df = 2.62, p < 0.001, RMR = 0.06, GFI = 0.90, NFI = 0.92, IFI = 0.95, TLI = 0.94, CFI = 0.95, RMSEA = 0.06
All loadings are significant (p < 0.001)
Discriminant validity
| Online community identification | Team identification | Authenticity | Behavioural intention | Positive WOM intention | |
|---|---|---|---|---|---|
| Online community identification | 0.84 | ||||
| Team identification | 0.78 | 0.80 | |||
| Authenticity | 0.61 | 0.72 | 0.80 | ||
| Behavioural intention | 0.66 | 0.77 | 0.67 | 0.78 | |
| Positive WOM intention | 0.65 | 0.76 | 0.66 | 0.71 | 0.86 |
Note(s): The italicised cells indicate squared root values of the AVE
Results of hypothesis testing
| Hypothesized paths | Direct effects | Mediation effects | Moderation effects | |||
|---|---|---|---|---|---|---|
| β | t-value | β | 95% CIs | β | t-value | |
| H1: OCI→TI | 0.72* | 20.35 | ||||
| H2-1: OCI→BI | 0.25* | 4.41 | ||||
| H2-2: OCI→WOM | 0.22* | 4.08 | ||||
| H3-1: TI→BI | 0.44* | 7.79 | ||||
| H3-2: TI→WOM | 0.48* | 8.95 | ||||
| H4-1: OCI→TI→BI | 0.32* | 0.22–0.41 | ||||
| H4-2: OCI→TI→WOM | 0.35* | 0.26–0.44 | ||||
| H5-1: OCI × Auth→ TI | −0.07 | −1.96 | ||||
| H5-2: OCI × Auth→ BI | −0.09 | −1.79 | ||||
| H5-3: OCI × Auth→ WOM | −0.10 | −1.99 | ||||
| Endogenous variables | SMC (R2) |
|---|---|
| Team identification | 0.54 (54%) |
| Behavioural intention | 0.43 (43%) |
| Positive WOM intention | 0.47 (47%) |
Note(s): χ2/df = 3.57, p < 0.001, RMR = 0.05, GFI = 0.94, NFI = 0.93, IFI = 0.93, TLI = 0.90, CFI = 0.93, RMSEA = 0.07
*p < 0.001 (two-tailed test)
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