Effect of user and firm-generated content on usage intention of sports brands across social media platforms

Social media (SM) has become integral to global communication, with a utilization rate of 59% worldwide as of January 2023 and over 4.59 billion users, projected to reach six billion by 2027 (Statista, 2023a, 2023b, 2023c). The rapid growth of Web 2.0 has propelled SM platforms forward, with companies increasingly leveraging these platforms to engage with stakeholders (Jha and Verma, 2024). Platforms like Instagram, Facebook, YouTube and X have transformed interactions between users and brands, influencing consumer behavior and buying decisions through interactive environments filled with marketing messages and peer opinions (Goh et al., 2012). SM is a powerful tool for fostering fan engagement and loyalty in the sports industry. Sports brands’ managers use SM to interact with customers and fans, recognizing its significant role in brand promotion (Seng and Keat, 2014; Vale and Fernandes, 2018).

User-generated content (UGC), including likes, comments, shares, reviews and ratings, and firm-generated content (FGC), like SM advertising, SM promotion and SM interactive marketing, is crucial for brand engagement (BE) across SM platforms. Consumers trust UGC more than traditional marketing messages, as they perceive it as authentic and trustworthy (Nikbin et al., 2022). UGC is vital for sports organizations’ marketing strategies, leveraging SM’s reach to attract fans and customers (Geurin and Burch, 2017). The relationship between UGC and sports brands is complex, with fans sharing knowledge and experiences, discussing games and showcasing fan-created artwork, all contributing to establishing a genuine identity for the sports brands (Mathur et al., 2022). FGC significantly impacts business performance and consumer behavior (Tunçel and Yılmaz, 2020). Although UGC provides authenticity and credibility, FGC offers authoritative and well-organized brand messages, informing about brand standards and explaining product details (Aljarah et al., 2022). In today’s digital age, combining UGC and FGC can enhance online marketing strategies for maximum customer engagement.

The impact of SM is particularly pronounced among young people, who are increasingly engaged in online groups and are more likely to be attracted to sports brands (Yang et al., 2021). Despite the growing popularity of UGC and FGC in SM, research on their effects on the intention to use sports brands is limited. This study aims:

• to explore the dimensions of UGC and FGC relating to sports brands across SM platforms;

• to study the effect of UGC and FGC dimensions on brand trust (BT) and BE; and

• to investigate the mediating role of BT and BE between UGC and FGC dimensions and brand usage intention (BUI) among sports brands users across SM platforms.

The schema of presentation of this study includes, first, a literature review section (section 2) that covers the review of SM and sports brands, the theory of planned behavior (TPB), UGC, FGC, BT, BE and BUI, thereby developing hypotheses and a conceptual model grounded in the TPB for validation. Second, the proposed conceptual model is tested using AMOS 21.0 structural equation modelling with the 945 voluntary responses collected using convenience sampling (section 3,4). Third, the findings of the study show that UGC and FGC dimensions directly affect BT and BE, which also affects the usage intention of sports brand users across SM platforms (section 5). Fourth, the main contribution of the study is to bridge the void in the literature by examining the intricate relationships of the dimensions of UGC and FGC on BUI through the mediators BT and BE (section 6). Finally, the limitations, future research directions and conclusions are presented (section 7).

SM encompasses a set of online tools and platforms rooted in the principles and technology of Web 2.0 (Kaplan and Haenlein, 2010), which facilitate the creation and sharing of UGC and FGC. Communication and sharing of information through SM have radically changed how consumers behave and relate to brands; therefore, companies must pay more attention to SM (Vale and Fernandes, 2018). Consumers widely use SM to engage with the brand, which is of greater interest to marketers (Liadeli et al., 2023). SM enables individuals to proactively gather information and voice their viewpoints (Jha and Verma, 2024). People are no longer passive recipients of product details; they become dynamic content generators and disseminators, using various mediums such as videos, text and audio, and possess the power to influence other consumers’ consumption behaviors to an unprecedented extent (Ayertey et al., 2021). As SM has transformed consumer behavior and engagement, companies must focus on SM strategies (Tyrväinen et al., 2023; Yuen et al., 2023). Many brands have developed a strong SM presence, allowing them to engage directly with their customers (Liadeli et al., 2023). The sports sector, characterized by product inconsistency, multiple stakeholders and the high emotional involvement of fans, relies heavily on consumer loyalty (Machado et al., 2020). Sports brands leverage SM platforms like Facebook and Instagram to build strong fan relationships through UGC and FGC content, enabling cost-effective global promotion and influencing consumer behavior (Raji et al., 2020; Machado et al., 2020). Official fan pages and FGCs on SM platforms help establish and strengthen fan connections, fostering engagement and loyalty (de Vries et al., 2012). Sports brands leverage SM to showcase behind-the-scenes moments, share player insights and promote events, enhancing the fan experience and driving engagement (Yang et al., 2019). Sports marketers focus on creating appealing content to increase BE through UGC and FGC (Osokin, 2018).

The TPB proposes that intention is influenced by attitudes, subjective norms and perceived behavioral control (Ajzen, 1991). Within the TPB framework, an individual’s intention to use a brand is significantly influenced by their emotional and cognitive engagement. Shared user experiences on SM platforms sustain interest and engagement, increasing consumers’ likelihood of developing strong BUI (Elly et al., 2024; Seng and Keat, 2014). UGC, comprising likes, shares, comments, reviews, ratings and SM posts created by consumers (Santos, 2021), acts as electronic word-of-mouth. Positive UGC enhances consumers’ attitudes toward a brand through authentic and relatable experiences (Yu and Ko, 2021), which in turn fosters BT and BE as consumers feel more secure and connected to the brand (Demba et al., 2019; Nikbin et al., 2022). FGC, which includes SM advertising, SM promotions and SM interactive marketing (Raji et al., 2020), significantly shapes consumers’ attitudes and perceived behavioral control. FGC can create a favorable brand image and provide essential information and incentives, building BT and enhancing BE (Kitirattarkarn et al., 2019; Kumar et al., 2016). BT and BE are pivotal behavioral intentions that shape consumer actions (Osei-Frimpong and McLean, 2018), influenced by attitudes, subjective norms and perceived behavioral control. BT encompasses the confidence consumers place in a brand’s reliability and integrity (Chaudhuri and Holbrook, 2001), whereas BE refers to the emotional and cognitive commitment consumers have toward a brand (Hollebeek et al., 2014), manifested through interactions and participation in brand-related activities. High levels of BE indicate a strong, positive connection with the brand, often leading to loyalty and advocacy (Erdoğmuş and Tatar, 2015). In the context of SM, UGC and FGC shape consumer attitudes and perceptions, building BT and fostering BE. When integrated with the TPB framework, they comprehensively understand how SM content influences consumer behavior, providing valuable insights for effective marketing strategies.

UGC is defined as text, information or activities created by digital platform users and shared through various channels, impacting communication individually or collectively (Santos, 2021). UGC is produced by individuals who share data or multimedia content online, often for free and without compensation (Jiao et al., 2018). UGC actively fosters personal opinions, social interactions and knowledge sharing and is regarded as trustworthy, genuine and less biased (Hochstein et al., 2023; Qin et al., 2024). UGC is quantified using likes, comments, shares, reviews and ratings.

Liking is a quick and effortless way for users to acknowledge brand content, reflecting consumers’ inclination to endorse and distribute brand-related content, which can lead to BT and BE (Ibrahim et al., 2022; Swani and Labrecque, 2020). Comments require more effort and cognitive thinking, leading to deeper BE and influencing other customers’ preferences and the company’s online popularity (George et al., 2023). Sharing experiences on SM platforms acts as viral marketing, endorsing trust in the brand (Ibrahim et al., 2022; Yuki, 2015). Shares, especially when customized by the user, create more BE, with more engaged users tending to share brand content (Swani and Labrecque, 2020). Reviews and ratings reflect consumer opinions on product quality and service, affecting purchasing decisions and BT (Chakraborty and Bhat, 2018). Post-usage views on product quality and features are encouraged by online retailers on e-commerce platforms as they are crucial for influencing purchase decisions and are more credible than FGC (Thakur, 2018). Sports brands leverage UGC on SM to create BT and BE with fans (Assaker, 2020). These dimensions of UGC thus enhance BT, BE and BUI (Demba et al., 2019; Nikbin et al., 2022). Therefore, we posit that:

Kumar et al. (2016) define FGC as content companies share on their official SM pages. Through continuous customer interactions, FGC enhances corporate credibility and trust (Osei-Frimpong and McLean, 2018). Traditionally, FGC has been significant in advertising, reaching the target audience directly (Keller, 2016). Technological advancements have changed the communication between sports brands and customers, making SM an interactive platform for direct interaction and revolutionizing BE (Osei-Frimpong and McLean, 2018). Sports brand managers use SM platforms to engage fans with their brands by creating and sharing content due to the trust gained for FGC (Achen, 2020a, 2020b; Wang and Zhou, 2015). Through ongoing engagement with a brand’s FGC, viewers can transform from occasional or intermittent followers into loyal brand enthusiasts (Wei, 2024). The present study explores FGC using SM advertising, SM promotion and SM interactive marketing (Raji et al., 2020).

SM advertising is a powerful tool for sports brands, using channels like social networking sites, blogs and microblogging to communicate with customers, market products and cultivate brand advocates (Ebrahim, 2020; Erdoğmuş and Tatar, 2015). SM promotions offer short-term incentives to influence consumer behavior, thus impacting consumer behavior and engagement (Raji et al., 2020; Tufa and Workineh, 2022). Interactive marketing on SM is crucial for sports businesses as it allows direct and engaging connections with customers and fosters fan loyalty (Kim and Ko, 2012; Raji et al., 2020). Active involvement in interactive marketing initiatives like debates, events, live broadcasts and personalized content enhances fan engagement, brand visibility and revenue (Kumar et al., 2024; Raji et al., 2020). Thus, SM advertising, SM promotion and SM interactive marketing are vital components of modern marketing communications for sports brands, driving BT and BE, and hence we hypothesized that:

Trust in a brand provides a competitive edge by enhancing consumer receptiveness and approval of a brand (Yang and Battocchio, 2020). Consumer trust is defined as the willingness to rely on the brand’s capability to fulfill its expected responsibilities (Chaudhuri and Holbrook, 2001). In the context of SM, BT is the degree to which users perceive a brand as honest and secure (George et al., 2023). Trust and brand knowledge influence consumers’ responses to brand interactions, with SM interactions playing a crucial role in nurturing BT (Chen and Cheng, 2019). As BT grows, it becomes easier for sports brands marketers to convey marketing messages and create positive brand impressions (Ebrahim, 2020). Online trust significantly influences consumers’ behavior (Jadil et al., 2022). Unlike previous research on BT that measures BT as a unidimensional construct (Gong et al., 2022; Kim et al., 2023), this study finds that BT can be measured differently by considering the interactive effects of its multiple dimensions: perceived benevolence, perceived credibility and perceived reputation (Chan-Olmsted and Kim, 2022; Lassoued and Hobbs, 2015).

Perceived benevolence is perceived when consumers believe a brand’s products offer health, social and environmental benefits without significant risks (Lassoued and Hobbs, 2015; Li et al., 2008). Perceived credibility, characterized as the “believability” of product information, enhances perceived quality and value, influencing BT (Erdem et al., 2006). Perceived reputation, the belief that a brand consistently delivers high-quality products, fosters consumer trust through the cumulative impact of a firm’s past activities (Lassoued and Hobbs, 2015). SM activities and trust within SM platforms significantly influence usage intentions (Attar et al., 2020). Customers are more likely to believe that a brand can meet their substantial needs if its intentions prioritize customer well-being. In addition, existing literature reveals a positive relationship between BT, consumer engagement and customer loyalty (Hsieh and Chang, 2016). Hence, the multiple dimensions of trust contribute to building BT among consumers, increasing engagement among sports brand users and influencing usage intention. Thus, we hypothesize that:

Previous research highlights that BT is influenced by UGC and FGC (Kitirattarkarn et al., 2019) and BT leads to people’s intention to use a brand’s product (Nikbin et al., 2022). When people trust a brand, they will likely want to use it (George et al., 2023), and it is crucial in making people feel good about a brand (Xue et al., 2020). The content created by users can make a brand seem genuine and honest, which builds trust and leads to usage intention (Chari et al., 2016). UGC and FGC create trust in a brand, where UGC has more impact than FGC in building trust among the users (Hochstein et al., 2023; Qin et al., 2024; Tyrväinen et al., 2023). Sports brands always use UGC (Geurin and Burch, 2017) and FGC (Checchinato et al., 2015) to create trust among the users, which leads to the usage intention of sports brands (Nikbin et al., 2022). Hence, the literature shows that BT mediates the relation of UGC and FGC on BUI:

Engagement is a promising concept in marketing literature, potentially increasing brand loyalty (Habibi et al., 2014; Hollebeek et al., 2014). Sports marketers and managers increasingly use SM as a cost-effective marketing tool for consumer BE (Machado et al., 2020). Consumer BE is defined as a consumer’s favorable blend of thoughts, emotions and actions linked to a brand during interactions, influenced by their thoughts, emotions and actions during brand interactions (Hollebeek et al., 2014). SM platforms allow sports brands to connect with consumers and fans beyond traditional offline marketing to communicate brand identity and associations effectively (Thompson et al., 2014). SM enables brands to encourage continuous consumer interaction and engagement through UGC and FGC (Ibrahim et al., 2022; Machado et al., 2020). The volume of reactions an SM post generates is a crucial indicator of user engagement (Grosso et al., 2024). BE in SM is classified as consuming and contributing, where consuming UGC consists of streaming/viewing videos/pictures or reading comments related to the brand, and contributing involves creating content (Machado et al., 2020). BE is considered as a crucial predictor of BUI, because engaged customers are more likely to have a higher intention to use the brand due to their positive experiences and emotional connection with it (Kitirattarkarn et al., 2019). Consumers with higher levels of engagement exhibit greater commitment and repeated usage of the brand (Erdoğmuş and Tatar, 2015). Thus, we posit that:

Past studies indicate that BE mediates the relationship between UGC, FGC and consumers’ intention to use branded products (George et al., 2023; Kitirattarkarn et al., 2019). Higher BE leads to a stronger intention to use the brands’ products, with engaged consumers exhibiting higher BT (Erdoğmuş and Tatar, 2015). BT, driven by UGC and FGC, enhances BE and impacts usage intention (Osei-Frimpong and McLean, 2018). UGC and FGC contribute to BE, influencing BUI (Machado et al., 2020). Hence, we hypothesize that:

Ajzen’s (1991) TPB emphasizes that attitudes toward using a brand, subjective norms related to brand usage and perceived behavioral control over brand use collectively shape BUIs. Thus, behavioral intention is crucial for predicting or driving behavior (Laksamana, 2018). Interaction-driven customer value plays a vital role in shaping continuance intentions (Zhou et al., 2013), indicating that positive interactions and experiences with the brand can enhance intentions to continue using it. Based on engagement, experience and knowledge, consumers’ preferences for brands on SM define BUI. Hence, brand perception impacts usage intention and enjoyment (Kumar and Nayar, 2021). An active sports brand presence on SM fosters brand loyalty and usage intention (Seng and Keat, 2014). BT fosters online purchase intentions (Rietveld et al., 2020). The conceptual model (Figure 1) examines the effect of UGC and FGC dimensions on BT and BE and how these factors influence consumers’ intention to use sports brands.

A quantitative survey was used to evaluate the conceptual model illustrated in Figure 1. Research on consumer behavior of sports brands in the context of SM requires considering regional, national and cultural differences (Filo et al., 2015). Considering the growth and engagement of sports fans in metropolitan cities (World Football Report, 2023), the data was collected from Indian cities, as they exhibit substantial enthusiasm for SM and use them extensively to purchase sports brands’ products (Thomas and Jain, 2022). India is expected to have approximately 1.5 billion active SM users by 2040 (Statista, 2023a, 2023b, 2023c). Metropolitan cities like Bangalore, Mumbai, Chennai and Kochi were selected, as these cities boast diverse populations representing various regions of the country and are also the central sports hub of the different sports leagues such as the Indian Premier League, Indian Super League, Premier Badminton League, Pro-Kabaddi and Hockey Indian League. The initial phase of empirical validation for the conceptual model involved the development of a questionnaire to study the influence of UGC and FGC dimensions on the usage intentions of sports brands users across SM platforms.

The measurement scale (Supplementary Material – Appendix A), to assess various constructs of the study, was adapted from prior research and modified to suit the specific context of the study. A five-point Likert scale that ranged from “strongly agree” to “strongly disagree” was employed. To ensure the questionnaire’s credibility, a panel of six experts, comprising two academicians with notable publications in SM and three practitioners experienced in managing SM of reputed sports brands, were selected (Thakur, 2018). Content validity was ensured by the ratings these experts gave for the measurement items on a five-point scale. In the evaluation by these experts, the item-level construct reliability exceeded the minimum of 0.7, indicating satisfactory content validity (Hew and Syed Abdul Kadir, 2016). To eliminate any potential ambiguities, the questionnaire was initially administered to 15 postgraduate commerce students, who were asked to complete it without any clarifications. Subsequently, the items were explained to them, and they were requested to complete the questionnaire again to evaluate any alterations in their replies. A paired sample t-test was employed to analyze the significant differences before and after the explanation. Based on the t-test results, a few items were revised to address the identified variances. The expert panel reviewed the modified questionnaire again and piloted it among 50 participants. Based on the findings from the pilot study, modifications were made to enhance the validity and reliability of the questionnaire before the final survey.

The study was conducted in June 2023 using the convenience sampling method to target users of sports brands in SM platforms. Three thousand questionnaires were distributed to users across various SM platforms, including Facebook, Instagram, YouTube and X, who have purchased multiple sports brands’ products over the past six months. To ensure the authenticity of the purchases, the self-reported details of the products bought by customers were cross-checked. Out of the 990 voluntary responses received, 45 were incomplete, which were excluded, and the remaining 945 valid responses were used for further analysis, making a response rate of 33%. The collected sample size exceeded the recommended minimum of 10 times the maximum number of inner and outer links associated with any latent variable in the model, ensuring statistical robustness (Bentler, 2016; Hair, 2009). Several steps were taken in this study to mitigate the potential issue of common method bias (CMB) arising from the usage of self-reported data (Podsakoff et al., 2003). Initially, the scale questions about the variables were distributed throughout the questionnaire. Second, respondents were assured of their anonymity, and third, they were encouraged to respond truthfully by emphasizing the pure academic nature of the research. Moreover, Harman’s single-factor test (Harman, 1976) was conducted, and the variance explained by the single-factor was found to be 31.19%, which is less than the recommended minimum of 50% (Podsakoff et al., 2003), indicating the absence of CMB. To address the limitation of failure to control for CMB in Harman’s single-factor test, the CFA-based unmeasured latent method construct test was used. This test specifies a latent construct without uniquely observed indicators that capture shared variance between method and substantive constructs (Podsakoff et al., 2003). As a rule of thumb, if the difference between estimates with and without a common latent factor exceeds 0.20, the construct is retained in the model (Afthanorhan et al., 2021). In this study, the difference for all constructs measured was below 0.20, further reinstating the absence of CMB (Supplementary Material – Appendix A).

The demographic characteristics of the participants are listed in Table 1, which aligns with the characteristics of the current sports brands users across various SM platforms (Statista, 2023a, 2023b, 2023c).

The results of exploratory factor analysis exhibited significant loadings within the range of 0.619–0.922, and the Kaiser–Meyer–Olkin method for sample adequacy test was 0.799, surpassing the minimum threshold of 0.50 (Hair, 2009). Bartlett’s test of sphericity was significant (BTS < 0.001), meeting the necessary conditions (Tabachnick and Fidell, 2019). Before analysis, preliminary checks for normality were conducted, revealing acceptable skewness and kurtosis within ±1.5 for all variables (Hair, 2009). To assess the multicollinearity between the constructs, the variance inflation factor was measured and found to be within the threshold of <10 (Hair, 2009). The confirmatory factor analysis carried out using AMOS 21.0 to validate the variables indicated that the proposed measurement model demonstrated a good fit with the data (χ2/df = 1.428; RMR = 0.063, CFI = 0.954, AGFI = 0.864; RMSEA = 0.030), accurately representing the underlying structures in the observed data (Fornell and Larcker, 1981; Hair, 2009). Convergent validity was confirmed, as the average variance extracted (AVE) for each construct exceeded 0.50, which aligns with Fornell and Larcker (1981). Table 2 illustrates that the instrument also possesses discriminant validity, as the square root of the AVE for each latent variable is greater than the inter-construct correlations among these latent variables (Hair, 2009). Hence, it can be summarized that there is substantial support for the proposed theoretical model, and hypotheses can be tested.

In the subsequent phase of the study, the proposed structural model and the relationships underwent testing. The examination of the proposed structural model demonstrated a good fit with the data (χ² = 292.42, df = 120; p < 0.001; χ²/df = 2.43; CFI = 0.955, AGFI = 0.898, RMR = 0.061, RMSEA = 0.058) (Fornell and Larcker, 1981; Hair, 2009) (see Figure 2, validated model). Following this, the hypothesized paths were evaluated using standardized path coefficients in the model (see Tables 3 and 4). These standardized path coefficients affirmed the expected effects were used to measure the significance of the proposed paths (Bentler, 2016). Tables 3 and 4 explain the hypotheses examined and standardized regression weights of direct and indirect effects. All the nine dimensions have a significant effect on BT, BE and BUI, except for the indirect effect of SM Advertising (on BUI mediated through BT and BE), SM Promotion (on BUI mediated through BE), SM Interactive Marketing (on BUI mediated through BT). The R² values for BT, BE And BUI are 0.39, 0.32 and 0.27, respectively. The findings reveal that comments and shares have a positive direct and indirect effect on BT and BE. Also, BT and BE significantly contribute to BUI.

The indirect effects of UGC and FGC dimensions on BUI mediated through BT and BE were analyzed and found to be significant (see Table 4). All the proposed hypotheses were confirmed, except the indirect effect of the SM Interactive Marketing construct of FGC. The indirect influence of UGC dimensions [Likes (β = 0.47*), Comments (β = 0.54*), Shares (β = 0.52*) and Reviews and Ratings (β = 0.46**)] on BE through BT have a significant effect, validating the mediation hypotheses. Similarly, UGC dimensions, [Likes (β = 0.41**), Comments (β = 0.47*), Shares (β = 0.45**) and Reviews and Ratings (β = 0.40*)] have a significant indirect effect on BUI mediated through BT. The indirect effect of UGC dimensions [Likes (β = 0.47*), Comments (β = 0.48*), Shares (β = 0.45**) and Reviews and Ratings (β = 0.42*)] on BUI, when mediated by BE, was found to be significant, validating the mediation hypothesis. Also, the UGC dimensions [Likes (β = 0.31**), Comments (β = 0.37*), Shares (β = 0.35**) and Reviews and Ratings (β = 0.31*)] have a significant indirect effect on BUI through the combined mediation of BT and BE, further affirming the mediation hypotheses.

The study also analyzed the indirect effect of FGC dimensions [SM Advertising (β = 0.34*), SM promotion (β = 0.33**) and SM interactive marketing (β = 0.35*)] on BE through BT and found significant, which supported the mediation hypotheses. Similarly, the indirect effect of FGC dimensions, [SM Advertising (β = 0.30**), SM promotion (β = 0.29**), SM interactive marketing (β = 0.31)], on BUI, with BT as the mediator, was significant except for SM interactive marketing, affirming the mediation hypotheses. The indirect effect of FGC dimensions [SM Advertising (β = 0.29**), SM promotion (β = 0.28), SM interactive marketing (β = 0.29*)] on BUI, when mediated by BE, was found to be positive, except for SM promotion, thus supporting the proposed mediation hypotheses. Finally, the indirect effect of FGC dimensions [SM Advertising (β = 0.23), SM promotion (0.23*), SM interactive marketing (0.24*)] on BUI, through the combined mediation of BT and BE, was also positive and significant except for SM Advertising, further affirming the mediation hypotheses.

The study explored the various dimensions of UGC and FGC created by sports brands across SM platforms, the direct effects of UGC and FGC dimensions on BT and BE, and the mediation effects of BT and BE between UGC and FGC dimensions and BUI. The findings affirm that the dimensions of UGC and FGC positively affect BT and BE. The results also indicate that the dimensions of UGC have a higher effect on BT and BE, in line with the findings of George et al. (2023) and Kitirattarkarn et al. (2019) than the dimensions of FGC. Among the dimensions of UGC, comments have the highest effect on BT and BE, indicated by the path coefficients of 0.75 and 0.70. The analysis of the indirect effect of UGC and FGC dimensions on BUI through BT and BE found that UGC dimensions have a higher effect on BUI than FGC dimensions, which necessitates the need for sports brands managers to prioritize UGC dimensions over FGC dimensions in their marketing initiatives.

The study found that the seven explored dimensions of UGC and FGC have a significant direct effect on BT and BE, reinstating the findings in the literature (Achen, 2020a, 2020b; Hollebeek and Macky, 2019; Wang and Zhou, 2015). UGC and FGC dimensions in SM allow users to connect with their favorite teams and athletes, share their passion and access exclusive content, promotions and real-time updates, enhancing their brand experience and loyalty. Among the dimensions of UGC, comments have a higher effect on BT and BE than other UGC dimensions, as commenting about sports brands provides a platform for users to express their opinions, share experiences and interact with the brand and other users, fostering a sense of loyalty to the brand. In sports brand marketing, the power of SM comments cannot be understated, as they are instrumental in building consumer trust (Lu et al., 2016) and creating a unique fan-driven environment. Sports brand managers can analyze the posts with high likes and comments, engage with consistent users who like the posts and comments, encourage discussions and create shareable content. For the dimensions of FGC, SM interactive marketing has the highest effect on BT and BE, fostering two-way communication between brands and users, which corroborates with the findings of Pagani and Mirabello (2011). SM interactive marketing strategies like live question and answer sessions, interactive polls and campaigns foster real-time interactions and community building among sports enthusiasts, enhancing BT and BE. Also, personalized responses and customer service through SM pages enhance perceived brand reliability and responsiveness, significantly contributing to BT and BE.

The findings of the study indicate that BT significantly affects BE, supporting the idea of Hsu et al. (2012), highlighting the importance of building long-term trust to enhance engagement with the sports brand. It was also found that BT and BE significantly affect the BUI among sports brand users across SM platforms in tandem with the findings of the previous studies (Chahal and Rani, 2017; Hsieh and Chang, 2016). BT instills confidence in consumers, encouraging them to choose and remain loyal to a brand, similar to how they would trust a friend’s recommendation. BE fosters an emotional connection through active interactions and meaningful relationships. Thus, BT and BE enhance a brand’s appeal, significantly increasing consumers’ likelihood of using its products or services. The present study also found that BT and BE mediate the relationships between UGC and FGC dimensions and BUI, which further reinstates the findings of Geng and Chen (2021) and Mathur et al. (2022). This suggests that UGC and FGC dimensions lead to consumers’ trust and engagement with the brand, thereby increasing usage intentions. Genuine user reviews (UGC) and brand posts (FGC) deepen consumers’ connection with the brand, fostering trust and engagement, which, in turn, drives consumers to use the brand’s products or services more frequently. UGC and FGC hence foster stronger fan relationships, enhance brand visibility and drive engagement and sales in a competitive market.

The current study provides significant theoretical support and expands the existing literature on UGC, FGC, BT, BE and BUI by incorporating multi-dimensional aspects of UGC and FGC and their influence on BT, BE and BUI, specifically within the sphere of sports brands across SM platforms. The theoretical framework of this study offers valuable insights for researchers by revealing how UGC and FGC dimensions influence BUI through BT and BE, with the integration of the TPB contributing to sports branding literature on SM. By aligning UGC and FGC with TPB constructs, the study elucidates how these content types influence consumer attitudes, perceived social norms and perceived behavioral control, shaping BUIs through BT and BE in the context of sports brands on SM platforms. The study contributes significantly to the literature by exploring the encompassing perceived benevolence, credibility and reputation thereby elucidating the complex pathways through which trust influences consumer engagement and usage intentions in sports brand SM marketing. Therefore, the theoretical model proposed in this study, which integrates the TPB with multiple dimensions of UGC, FGC and BT, represents a significant and novel contribution to the literature.

The research provides significant insights to sports brand managers and marketers on strategically using SM platforms. SM platforms offer unprecedented opportunities, such as affordability, widespread exposure and enhanced market awareness, which are crucial for sports brands’ ability to influence users. The research offers sports brand managers a practical approach to enhancing UGC and FGC by providing insights into content resonance, enabling them to tailor SM strategies that align with audience interests and preferences. Sports brands can enhance their presence and impact by strategically combining UGC and FGC, thus fostering a more robust connection with their audience. The research shows that sports brand managers must devise strategies that motivate consumers to recommend their products on SM platforms. As UGC and FGC dimensions significantly affect BT and BE, sports brands managers may encourage authentic UGC by promoting activities that increase customer engagement, such as rewarding post-purchase reviews, and also should use SM strategies such as interactive posts, contests and product showcases to interact with consumers. Managers can enhance brand perception and customer loyalty by ensuring high-quality, authentic fan-generated content that builds trust, deepens audience engagement, delivers relevant product information and drives positive brand experiences. As UGC and FGC have a strong relationship with BUI through BT and BE, sports brand managers may devise appropriate strategies that enhance trust and foster engagement to effectively translate positive content into increased usage intentions. Managers can ensure that when users post credible reviews, ratings and positive comments about a sports brand, they reinforce trust in the brand, thus increasing consumer engagement. Hence, managers may prioritize building trust through transparent communication and responsive interactions and actively engage with their audience to strengthen emotional connections.

The main limitation of the study is its focus on the sports brands’ consumer relationship within SM, which may limit its applicability to other market contexts. While the findings are helpful, caution should be exercised when applying the conceptual model to markets with different consumer behaviors and SM usage patterns. Future research should explore this model in varied consumer profiles and digital interaction patterns to broadly understand sports brands’ engagement and trust. Methodological concerns include using self-reported data and a nonprobabilistic sampling approach, which may introduce biases. Future research should also consider external market dynamics, technological developments like artificial intelligence and virtual reality and the role of influencer marketing in the sports industry. These areas could provide insights into innovative engagement strategies and the evolving landscape of sports brand marketing on SM.

The research offers a comprehensive analysis of the effect of UGC and FGC dimensions on BT and BE across SM platforms among sports brands. Using a quantitative methodology, the study surveyed 945 consumers and used structural equation modeling, revealing that UGC and FGC dimensions have a positive direct impact on BT and BE among sports brands users. Dimensions of UGC were found to have a higher effect than dimensions of FGC on BT and BE. The study also found that UGC and FGC dimensions have an indirect effect on the BUI of sports brands users through BT and BE. By integrating the TPB, the results of this study contribute substantially to the existing literature on brand management and SM marketing among sports brands. UGC and FGC dimensions have a pivotal role in enhancing BT and BE, underscoring the necessity for sports brands’ managers to actively participate in SM activities to develop and maintain consumer relationships. In an era where the digital landscape is continuously evolving, sports brands must innovate their SM engagement strategies to remain competitive. The insights provided by the study about the effectiveness of UGC and FGC in fostering BT, BE and BUI are invaluable, as they serve as a strategic guide for sports brands managers aiming to refine their digital engagement approaches to boost consumer interaction and foster enduring brand loyalty (see Table 5).

This paper is based on the lead author’s dissertation under the supervision of the second author.

Ethical statement: The study used survey responses collected anonymously through an online questionnaire. Participation was entirely voluntary and respondents provided their informed consent prior to completing the survey. No sensitive personal information was collected, ensuring confidentiality and compliance with ethical standards.

The supplementary material for this paper can be found online.