Effects of the spectator's emotional attachment to esports players on the sponsoring brand

Fernando Navarro-Lucena (PhD Programme in Economics and Business, Faculty of Economics and Business, University of Malaga, Malaga, Spain)
Sebastian Molinillo (Department of Business Management, University of Malaga, Malaga, Spain)
Rafael Anaya-Sánchez (Department of Business Management, University of Malaga, Malaga, Spain)

Academia Revista Latinoamericana de Administración

ISSN: 1012-8255

Article publication date: 26 November 2024

Issue publication date: 3 December 2024

338

Abstract

Purpose

The purpose of this study is to understand whether the spectator’s emotional attachment to esports’ players is key for the sponsoring brand’s outcomes. A theoretical model based on the attachment, social influence and brand communities’ literature is proposed.

Design/methodology/approach

Data were collected through an online survey from a sample of 1,355 regular esports viewers. The proposed conceptual model was evaluated using partial least squares-structural equation modeling (PLS-SEM).

Findings

The results showed that emotional attachment to esports players exerts a large effect on the viewer’s engagement with the community and his or her intention to view its content for longer. These two variables are key in explaining the viewer’s intention to perform positive behaviors toward the sponsoring brand, such as recommendation, purchase intentions and co-creation.

Originality/value

This study improves the understanding about the effects of the viewer’s emotional bond with esports players and the bond’s impact on the development of positive behaviors toward the sponsoring brand.

Propósito

El objetivo de este estudio es comprender cómo el apego emocional del espectador hacia el jugador de esports es determinante para los resultados de la marca patrocinadora. Para ello se propone un modelo teórico basado en la literatura sobre el apego, la influencia social, y las comunidades de marca.

Diseño/metodología/enfoque

Se recopilaron datos de una muestra de 1.355 espectadores habituales de esports mediante una encuesta online. El modelo conceptual propuesto se evaluó con la técnica de ecuaciones estructurales por el método de mínimos cuadrados parciales (PLS-SEM).

Hallazgos

Los resultados muestran que el apego emocional hacia el jugador de esports ejerce un gran efecto tanto en el compromiso del espectador con la comunidad como en su intención de permanecer más tiempo visionando sus contenidos. Estas dos variables son clave para explicar la intención del espectador de realizar comportamientos positivos hacia la marca patrocinadora como son la recomendación, la intención de compra y la cocreación.

Originalidad

Este estudio contribuye a mejorar la comprensión sobre los efectos del vínculo emocional del espectador con los jugadores de esports y su impacto en el desarrollo de comportamientos positivos hacia la marca patrocinadora.

Keywords

Citation

Navarro-Lucena, F., Molinillo, S. and Anaya-Sánchez, R. (2024), "Effects of the spectator's emotional attachment to esports players on the sponsoring brand", Academia Revista Latinoamericana de Administración, Vol. 37 No. 4, pp. 513-528. https://doi.org/10.1108/ARLA-05-2024-0094

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Fernando Navarro-Lucena, Sebastian Molinillo and Rafael Anaya-Sánchez

License

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


1. Introduction

Esports are competitive electronic games that are organized into leagues and tournaments. These games attract sponsors and spectators and the players, grouped into teams, seek to outperform their rivals through cognitive skills (Zhong et al., 2022). Butcher and Teah (2023) highlight parallels between esports and traditional sports in terms of their technological evolution, motor and cognitive skills, interpersonal interactions, teamwork and brand management. However, unlike traditional sports, esports viewers primarily watch competitions via live streaming platforms instead of traditional media. According to Stream Hatchet (2024), the three predominant live streaming platforms are Twitch, YouTube, AfreecaTV and Kick, with Twitch being the most popular. Twitch is no longer just a video game streaming platform – it has become a live audiovisual entertainment space that offers diverse content and uses innovative advertising formats (Gamir-Ríos et al., 2024).

The esports audience comprised 532 million viewers worldwide in 2022 and is projected to grow to 640.8 million by the end of 2025 (Statista, 2024). Thus, the sector is undergoing rapid growth in terms of participation, media coverage, sponsorship and marketing (Jordan-Vallverdú et al., 2024). These figures have attracted the attention of the scientific community. Authors, such as Scholz (2019) and Taylor (2012), highlighted that esports represent a complex and diverse ecosystem that warrants study. Jordan-Vallverdú et al. (2024) argued that esports research has focused on the differential characteristics of the industry, gambling, player performance and spectator behavior. They also found that research into spectators’ behaviors has mainly analyzed viewing motives, effects on viewers’ behaviors and preferences, the creation of online communities and the viewer’s learning. Technological acceptance theories, such as the Unified Theory of Acceptance and Use of Technology (UTAUT), and frameworks used with the consumption of audiovisual products, e.g. Uses and Gratifications Theory, have been applied (Hamari and Sjöblom, 2017; Hilvert-Bruce et al., 2018; Qian et al., 2022). Recently, some authors have begun to study the effects on sponsoring brands, analyzing brand awareness (De Zoeten and Könecke, 2023), brand identity (Calapez et al., 2024) and the sponsorship of endemic and non-endemic brands (Abbasi et al., 2023; Cuesta-Valiño et al., 2022; Rogers et al., 2020).

The esports audience is more highly engaged, digitally connected and tech-savvy (Butcher and Teah, 2023) than other viewer profiles. In addition, the communities generated have a great capacity to influence their members’ behaviors (Kohls et al., 2023). So far, research on esports has focused primarily on studying consumer behavior in live streaming within the framework of the theories of technology acceptance (e.g. UTAUT) and the consumption of audiovisual products (e.g. Uses and Gratifications Theory) (Hamari and Sjöblom, 2017; Hilvert-Bruce et al., 2018; Qian et al., 2022). Additionally, studies have explored brand awareness (De Zoeten and Könecke, 2023), brand identity (Calapez et al., 2024) and sponsorship (Abbasi et al., 2023; Cuesta-Valiño et al., 2022; Mohammadi et al., 2023; Alonso-Dos-Santos et al., 2024). However, few papers have studied how emotional attachment with a player may influence spectator behavior toward the sponsoring brand (see Flegr and Schmidt, 2022; Rietz and Hallmann, 2023).

In this sense, players and teams continuously generate content that is consumed by their followers and spectators, both from brands related to video games and from other sectors of interest to their audiences. Additionally, they create links and relationships with their audiences, achieving high levels of social identification between viewers and players (Soares et al., 2023). For these reasons, esports players can be considered as influencers (Jordan-Vallverdú et al., 2024; Roth et al., 2023).

The literature related to live streaming indicates that the viewer’s attachment to the streamer generates positive behaviors towards the sponsoring brands (e.g. Shao, 2024). In this context, authors, such as Soares et al. (2023), emphasize the importance of understanding how attachment to esports players generates emotional and cognitive states among viewers, ultimately favoring positive behaviors towards sponsoring brands. Among the beneficial viewer states for players and brands are stickiness and engagement with the streamer’s community of followers. These viewer states have been highlighted as key factors by research in the field of branding in online environments (e.g. social commerce and online brand communities) (see Martínez-López et al., 2020; Molinillo et al., 2021), as well as in studies specific to live streaming (see Jiao et al., 2023; Kim and Kim, 2022; Li et al., 2021). Both states can be achieved more easily when the viewer feels a strong attachment with the content creator (Li and Han, 2021; Li et al., 2021).

This study has two primary objectives: (1) to analyze how the emotional attachment of the spectator with the esports player favors commitment to the community built around the player and a sense of stickiness and (2) to understand how these spectator states lead to various favorable behaviors, such as positive electronic word-of-mouth (eWOM), purchase intention and co-creation intention, towards sponsoring brands. To this end, this research is based on Attachment Theory (Ainsworth and Bowlby, 1991) and Social Influence Theory (Kelman, 1974). Attachment Theory describes how emotional bonds foster loyalty, while Social Influence Theory details how the audience adopts attitudes and behaviors by identifying with and internalizing the streamers' values. Combining the two theories could enable a holistic understanding of the emotional and social dynamics that underpin the influence of esports players on their audiences. Thus, this research analyzes, for the first time, how attachment with esports players influences viewer behaviors that are favorable to sponsoring brands.

2. Theoretical framework

2.1 Social Influence Theory and Attachment Theory

The considerable adoption of social networks has resulted in the emergence of public figures or celebrities who possess significant persuasive and influential power. These influencers are people who use social networks to generate knowledge and share it with their followers and/or audiences. Generally, the audience is attracted to the influencer’s content because the influencer is usually regarded as a reference in a particular subject or area (Lou and Yuan, 2019; Martínez-López et al., 2020). The content usually addresses various topics, including aspects of their personal lives, and is communicated through text, images or videos. The relationships created and strengthened through social networks with influencers can assist commercial brands in implementing marketing strategies (Shiau et al., 2018; Uribe et al., 2022). In this way, the influencers can be “aligned” with the company’s objectives in exchange for compensation (Abidin, 2016).

Social Influence Theory (Kelman, 1961, 1974) offers a useful theoretical framework to understand the underlying mechanisms of influencers' relationships with their followers (Tafesse and Wood, 2021). Followers accept influencers' recommendations on social networks to the extent that they perceive them as popular, credible, relatable and/or experts in a particular field (Schouten et al., 2020). Furthermore, as influencers strive to attract, retain and engage followers, these followers become increasingly attached to them and their communities (Ki et al., 2020). This attachment helps influencers achieve brand marketing and commercial success. In this sense, follower engagement and stickiness in consuming shared content have been shown to be important variables in the success of influencer marketing and branding actions in social networks (see Argyris et al., 2020; Tafesse and Wood, 2021; Zhang et al., 2017).

The impact of these influencers on the public is often due to factors, such as authenticity, experience or knowledge, which position them as opinion leaders (Childers et al., 2018); this explains that influencers have crucial and influential knowledge in the followers’ purchase decision process (Bao and Chang, 2014). Thus, they serve as a powerful tool for advertising products, services or brands by fostering a close relationship between users and brands (Shiau et al., 2018).

2.2 Development of hypotheses

2.2.1 Effects of emotional attachment with the esports player/streamer

The literature defines a follower’s emotional attachment as a “parasocial” interaction, where the follower engages in a self-defined relationship with the influencer (Dibble et al., 2015). If followers perceive that this relationship is maintained satisfactorily, they will be more likely to accept the opinions and values transmitted by the influencer (Sánchez-Fernández and Jiménez-Castillo, 2021). This can ultimately enhance positive aspects of the follower’s engagement within the community centered around the streamer.

By actively participating in the player/streamer’s online community (e.g. through comments, subscriptions and private memberships), the audience can establish or deepen emotional connections with the streamer. These communities, because they allow their members to make more informed decisions and reduce their financial and time costs, play a key role in promoting the consumption of live streaming content and in brand sponsorship (Kohls et al., 2023). Similar to findings in other studies of online communities (e.g. Martínez-López et al., 2017), this emotional connection can lead to a greater intention to interact within the brand’s community and positively influence the sense of belonging to it. Community members who identify with the community are incentivized to interact continuously with other members (Baldus et al., 2015; Hollebeek et al., 2016). Recent studies have demonstrated that emotional attachment is crucial for building effective online (Li and Han, 2021; Sohail, 2022) and offline (Tang et al., 2024) community strategies. Therefore, the following hypothesis is proposed:

H1.

The viewers’ emotional attachment with the player/streamer positively influences their engagement with the community.

The ability of the player or streamer to consistently attract and retain their audience, whether through live or recorded content, is also a significant area of study. Within the context of online commerce communities, the concept of stickiness intention is defined as the time a customer spends on a social medium, either during a single visit or over the course of several visits (Molinillo et al., 2020; Zhang et al., 2017). In the context of esports, this refers to the intention of the audience to spend more time on videos, groups, forums or the online community in general (Hu et al., 2020).

In the context of live shopping or live commerce, there seems to be a relationship between the emotional attachment of the audience with the streamer and the intention to watch the content for a longer time (Li et al., 2021; Madina and Kim, 2021). Therefore, extrapolating to this study, the greater the emotional attachment of the audience or community with the streamer, the greater their attachment with the streamer’s content. This implies that, if an emotional attachment is established, the audience’s content consumption behavior would become more frequent, and they would dedicate more time to it.

H2.

The emotional attachment of the viewer with the player/streamer positively influences the consumer’s intention to view the content for longer.

2.2.2 Generation of favorable behaviors towards the sponsoring brand

As Qian et al. (2022) point out, value co-creation, purchase intentions and intentions to recommend are some of the outcomes of live streaming services, favored by engagement and long-lasting, meaningful relationships between consumers and stakeholders. In this research, eWOM, purchase intentions and intention to co-create, identified as key behaviors in social media (Molinillo et al., 2020, 2021), stand out as favorable actions towards the brand.

The term eWOM refers to traditional WOM communication in online media (Liu et al., 2024). Molinillo et al. (2020) demonstrated that consumer engagement is a predictor of several favorable brand behaviors, including positive eWOM. Similarly, engagement with brands on social media has been found to influence intention to engage in positive eWOM (Osei-Frimpong and McLean, 2018; Srivastava et al., 2023). A community of followers is usually generated around streamers' social media platforms and networks (Kapoor et al., 2018). The engagement generated in the audience, through their interactions with esports streamers, can lead them to disseminate positive WOM about the streamers and about the sponsoring brands (Abbasi et al., 2023). Therefore, the following hypothesis is stated:

H3.

Viewer engagement with the online community positively influences positive eWOM towards the sponsoring brand.

The intention to purchase sponsoring or player-recommended brands is a crucial variable due to its impact on brand revenue. Purchase intention appears to be related to viewer engagement with the community (Jibril et al., 2019; Tiruwa et al., 2016). This relationship has been tested in the context of live streaming (e.g. Dua, 2023; Sun et al., 2019) and social media purchases (Akram et al., 2021; Borges-Tiago et al., 2019). Similarly, Abbasi et al. (2023) argued that engagement with esports leads viewers to purchase relevant products. Therefore, the following hypothesis is proposed:

H4.

Community engagement positively influences the intention to purchase the sponsoring brand.

According to Liu et al. (2022), in live esports games, highly engaged spectators contribute to the creation of other users' experiences through co-creation, similar to how brands and players/streamers do. In this sense, Molinillo et al. (2020) found that, in the field of social commerce, one of the outcomes of community engagement was the intention to co-create. Co-creation is understood as the intention to exchange information, assist other members, solve difficulties or suggest new ideas to improve the product or service. Similarly, Abbasi et al. (2023) showed that consumer engagement with esports favors the co-production of ideas. In the context of esports, the following hypothesis is proposed:

H5.

Community engagement positively influences the intention to co-create.

Customer stickiness to a given website occurs when customers develop a positive attitude toward that website’s content, features, products and services, leading them to stay for a longer time on that site and consume its content (Wu et al., 2010). Zhang et al. (2017) stated that when consumers feel stickiness toward content offered through social networks, they will be more likely to subsequently engage in positive WOM for the concerned brand. Barta et al. (2023) argued that stickiness intention motivates live streaming users, when the experience is positive, to recommend the content viewed. Therefore, it is considered that when viewers spend a significant amount of time consuming content generated by the streamer, they will have a higher propensity to recommend it. Consequently, the following hypothesis is proposed:

H6.

The viewer’s intention to watch the content for an extended period of time positively affects the eWOM towards the sponsoring brand.

As Hu et al. (2020) pointed out, the ability of streamers to convert their followers into paying customers is highly dependent on stickiness. Hsu and Lin (2016) highlighted stickiness as an antecedent of purchase and repurchase intentions in mobile apps. Lee et al. (2021) and Hsu and Hu (2024) demonstrated the positive effect of stickiness on repurchase intention in social commerce. Liu et al. (2023) argued that live-streaming followers are stimulated by their interactions with streamers and other viewers, which increases their intention to continue watching the content and generates greater purchase intentions for the promoted products. Based on the above, the following hypothesis is proposed:

H7.

The viewer’s intention to watch the content longer positively affects the intention to buy the sponsoring brand.

Finally, it is necessary to determine how actors co-create value through their mutual interactions, given their exchange of services in the context of esports (Kunz et al., 2022). Previous research has shown how stickiness positively influences brand–consumer relational variables. For example, Thakur and AlSaleh (2018) examined the effect of stickiness on the sense of belonging to the community created around a blog, while Liu et al. (2021) demonstrated the effect of stickiness on intentions to interact with other consumers in social commerce purchases. Therefore, the following hypothesis is proposed:

H8.

The viewer’s intention to view the content for a longer period of time positively affects the intention to co-create.

Figure 1 shows the proposed theoretical model.

3. Methodology

3.1 Measuring instrument and data collection

The scales for measuring the constructs of the proposed model (see Appendix) have been adapted from previous studies. All items were measured using seven-point Likert scales (1 = strongly disagree and 7 = strongly agree). The variable “emotional attachment” was measured using a five-item scale adapted from Sánchez-Fernández and Jiménez-Castillo (2021). The construct, “community engagement,” was measured with a four-item scale adapted from Martínez-López et al. (2017). The variable, “stickiness intention,” was measured using a three-item scale from Molinillo et al. (2020). “Positive eWOM toward the brand” and “intention to buy the sponsoring brand” were measured using three-item scales adapted from Sánchez-Fernández and Jiménez-Castillo (2021).

The questionnaire was disseminated via email and social media to esports influencers, such as gamers, teams, content creators, community owners, forums, Discord communities and industry entrepreneurs.

3.2 Sample

The target audience for this questionnaire comprised esports followers and players. To ensure the relevance of responses, a screening question was included at the beginning of the questionnaire to filter out the individuals not fitting the target demographic. A total of 1,367 questionnaires were collected, with 1,355 of these considered valid. The vast majority of participants (82%) were between the ages of 21 and 35. Most respondents were men (95.6%). In terms of occupation, 66% were employed and 23% were students. The predominant levels of education among respondents were university degrees (40.1%), vocational training (23.2%) and postgraduate degrees (22.4%).

4. Results

The data were analyzed using the partial least squares structural equation modeling technique, employing the SmartPLS software version 3.3.3 (Henseler et al., 2018; Ringle and Sarstedt, 2016). The evaluation process consisted of two phases. In the first, the reliability of the measures and constructs, as well as convergent and discriminant validity, were assessed. In the second, the validity of the hypotheses within the structural model was assessed.

In order to analyze the reliability of measures, the loadings (λ) of each item were examined relative to their construct. Carmines and Zeller (1979) proposed that λ values should be equal to or greater than 0.707. In our study, all items met this reliability criterion, with the exception of item EA05 of the emotional attachment variable, with a value of 0.695, although this was only slightly below the 0.707 threshold. To assess reliability at the construct level (Table 1), the Cronbach’s alpha (α) indicator was used. In this case, all values were above 0.85, well exceeding the minimum acceptable level of 0.7 (Cronbach, 1951). Furthermore, the composite reliability (ρC) values, according to Werts et al. (1974), were above 0.9, and in the Dijkstra–Henseler (ρA) analysis (Dijkstra and Henseler, 2015), all levels were above 0.86. Thus, all indicators of construct reliability were within acceptable levels (Nunnally and Bernstein, 1994). Convergent validity, which indicates the degree to which a construct explains the variance of its indicators (Hair et al., 2019), was measured through the average variance extracted (AVE) (Fornell and Larcker, 1981). This value must be greater than or equal to 0.5, which our model satisfies.

Two methods were employed to assess discriminant validity. First, inter-construct correlations should be less than the square root of the AVEs (Fornell and Larcker, 1981). Second, the heterotrait-monotrait ratio (HTMT) between any two reflective constructs should be less than 0.8 (Henseler et al., 2015). All values fell within the recommended limits (Table 2). Therefore, the measurement model demonstrates discriminant validity.

The bootstrapping technique (Dijkstra and Henseler, 2015), with 10,000 subsamples, was used in SmartPLS to assess the structural model. The results are shown in Table 3, which indicates that seven of the eight hypotheses are statistically significant (p-value<0.001). Therefore, emotional attachment positively affects community engagement (β = 0.549; p < 0.001) and stickiness intention (β = 0.526; p < 0.001), thereby supporting hypotheses H1 and H2. On the other hand, the results demonstrate that community engagement significantly influences positive eWOM for the brand (β = 0.381; p < 0.001), intention to purchase the sponsoring brand (β = 0.390; p < 0.001) and intention to co-create (β = 0.550; p < 0.001), thereby supporting hypotheses H3, H4 and H5. Additionally, the positive effect of stickiness intention on positive eWOM of the brand (β = 0.207; p < 0.001) and purchase intention (β = 0.243; p < 0.001) was confirmed, supporting hypotheses H6 and H7. However, the relationship between stickiness intention and intention to co-create was not significant (β = −0.001; p > 0.05); therefore, hypothesis H8 was not supported. It is important to mention that the relationship between community engagement and intention to co-create is the strongest in the whole model (β = 0.550), followed by those between emotional attachment and community engagement (β = 0.549) and between emotional attachment and stickiness intention (β = 0.526).

The coefficient of determination (R2) suggests that the community engagement and stickiness intention variables explain 30 and 28% of the variance, respectively. The final variables of the model explain the following explained variances: positive eWOM of the brand (28%), intention to purchase the sponsoring brand (32%) and intention to co-create (30%). It is worth noting that the total effect produced by the community engagement variable is greater than that produced by stickiness intention. Finally, the standardized root mean square residual value was 0.041, which is below the recommended maximum threshold of 0.08, indicating a good overall fit of the model (Henseler et al., 2015).

5. Discussion and conclusion

5.1 Theoretical implications

While research on esports is at an early stage, there is a growing interest in understanding consumer behavior and responses toward sponsoring brands (see Cuesta-Valiño et al., 2022; Macey et al., 2022). Various studies have analyzed the viewer’s emotional attachment with streamers, analyzing its effects on their behavioral intentions (e.g. Li et al., 2021, 2023). However, few studies have analyzed the emotional attachment of the spectator with esports’ players and its effects on the sponsoring brand (Soares et al., 2023) or the role played by the community of spectators (Abbasi et al., 2023). The present study aims to explore the relationship between a spectator’s emotional attachment to an esports player, his/her commitment to the community generated around the player and a sense of stickiness as antecedents of positive eWOM towards the sponsoring brand, purchase intention and co-creation intention. To this end, a theoretical framework combining Attachment Theory, Social Influence Theory and the literature on brand communities was utilized.

A number of theoretical implications of interest to esports players and sponsoring brands can be drawn from the results obtained. First, the emotional attachment that the audience has with the esports player enhances engagement with the fan community. Engagement with the community has previously been identified as key to the success of branded virtual communities (Martínez-López et al., 2017; Wagner, 2023). This relationship had been proposed in the context of other communities (Li and Han, 2021; Sohail, 2022), and the results extend this to communities centered on esports players. Similarly, emotional attachment positively influences the viewer’s intention to spend more time viewing content or participating in their community. This indicates that the bonds established between the player and the audience are of vital importance for enhancing community performance and maintaining viewer interest in the content. These findings are in line with the proposal of Li et al. (2021) regarding other types of live broadcasts.

Second, the viewers’ level of engagement with the community influences their behaviors, fostering positive attitudes towards the recommended brand. Previous studies (e.g. Abbasi et al., 2023) have proposed that viewer engagement with the overall esports ecosystem influences purchase and recommendation intentions, but the effects of the viewer community’s engagement have not been specifically examined in the esports context. In this way, community engagement favors the intentions to recommend the brand mentioned during broadcasts, extending findings from the field of videogames (e.g. Chang and Hsu, 2022). Moreover, community engagement influences the intention to co-create. That is, the audience co-creates content and value within the community, helping the influencer spot trends, fill gaps and even acquire and disseminate knowledge to the entire community. These results reinforce the conclusions of Martínez-López et al. (2020) in influencer marketing, applying them to the esports sector. Likewise, community engagement positively affects the intention to purchase sponsoring brands featured during the games. Feeling engaged with the community suggests that viewers will align their tastes, aspirations and intentions with the player and other viewers, trying to identify with them (Martínez-López et al., 2017). This alignment facilitates the purchase of brands endorsed by the players or their community of followers.

Thirdly, the intention to spend more time viewing the content and/or interacting with the community (stickiness) positively affects positive eWOM. Thus, the more time viewers spend with the community and viewing the content, the greater their intention to spread positive eWOM about the brand. This result supports others obtained in other live-streaming contexts (e.g. Barta et al., 2023). Stickiness also positively affects intention to purchase sponsoring brands, supporting findings from other commerce activities on social media (e.g. Lee et al., 2021) and live streaming (Liu et al., 2023). Finally, the relationship between consumer intention to spend more time viewing content and the intention to co-create could not be validated. Thus, stickiness seems to be associated with seeking ideas for purchases and recommending content or brands when deemed useful. In contrast, stickiness does not favor more demanding behaviors, such as co-creation. Instead, community engagement seems to lead viewers to make such efforts.

5.2 Practical implications

Esports players/streamers exert significant influence on their viewers, making them valuable brand ambassadors. Commercial brands can leverage this relationship to recommend their products, although several factors need to be considered. Generally, such relationships tend to be more emotional than rational, necessitating a marketing strategy that feels as organic as possible to maintain the trust between the follower and the player/streamer. A lack of authenticity can damage both the commercial action as well as the player’s credibility, trust and follower base. Players/streamers are aware of this dynamic and seek brands that match their personality traits, lifestyle, tastes, culture and values. For marketing to be effective, the brand must approach the player/streamer to establish a relationship or emotional bond. This will enable the player/streamer to convey commercial content to their audience in a sincere and transparent manner.

The results of this study highlight several practical considerations within the esports ecosystem. Both the content and the selection of the professional player or streamer should be carefully analyzed. Their personality, lifestyle, values and culture should be considered to ensure alignment with the brand message. A congruent brand–player relationship fosters emotional attachment between the player and the audience, increasing the latter’s intention to participate in the community and spend more time watching videos. This will allow for sustainable growth in community size, viewership and engagement, thereby amplifying the impact of the player/streamer.

Moreover, community engagement directly and positively affects discussions about the product within the community, collaboration in content development with the player/streamer and, ultimately, purchase of the recommended product or brand. Commercial actions must be able to involve the player’s community, connecting the audience that identifies with the player with the brand or product as well. This will facilitate fluid and spontaneous communication about the products. Additionally, the audience members themselves can provide valuable insights into their needs, tastes and preferences, which companies can use to offer unique and personalized solutions. Effective community management by the player/streamer will positively affect purchase intention.

5.3 Limitations and future lines of research

This study has several limitations. First, the participation of women in the sample is low, although this fact is consistent with other studies in the sector, given the lower presence of women among esports viewers. Future work could aim to increase the representativeness of the sample by increasing the participation of women to around 25%, as has been suggested by some studies (Wink TTD, 2019). Secondly, the questionnaire was distributed through media channels, primarily targeting a Spanish audience. Future research could extend the study to include other countries and analyze potential differences among countries in order to increase the generalizability of the results.

Figures

Conceptual model

Figure 1

Conceptual model

Construct reliability and validity assessment

Cronbach αρAρCAVE
Community engagement (CE)0.8990.9070.9300.769
Emotional attachment (EA)0.8960.9020.9250.712
Intention to purchase sponsoring brands (IP)0.9260.9260.9530.871
Positive sponsoring brand eWOM (PBW)0.9000.9000.9380.834
Stickiness intention (ST)0.8540.8570.9110.774
Willingness to co-create (WTC)0.9610.9640.9720.896

Source(s): Authors’ own elaboration

Discriminant validity

CEEAIPPBWSTWTC
CE0.8770.6070.5740.5500.6320.587
EA0.5490.8440.5670.5980.6010.436
IP0.5250.5160.9330.8230.5160.433
PBW0.4960.5350.7520.9130.4770.459
ST0.5550.5260.4590.4190.8800.333
WTC0.5500.4050.4090.4280.3050.947

Note(s): In italics, the square roots of the AVEs; below the main diagonal, the results of the Fornell-Larcker criterion; above the main diagonal, the HTMT values

Source(s): Authors’ own elaboration

Bootstrap data and contrast hypotheses

Original sample (O)Sample mean (M)Standard deviation (STDEV)T statistic (|O/STDEV|)p valuesResults
H1. EA → CC0.5490.5490.02125.8370.000Supported
H2. EA → ST0.5260.5260.02224.0800.000Supported
H3. CE → PBW0.3810.3810.02913.1120.000Supported
H4. CE → IP0.3900.3900.02714.2120.000Supported
H5. CE → WTC0.5500.5500.02423.2550.000Supported
H6. ST → PBW0.2070.2080.0297.2620.000Supported
H7. ST → IP0.2430.2430.0288.7500.000Supported
H8. ST → WTC−0.001−0.0010.0240.0300.976Not Supported

Source(s): Authors’ own elaboration

Appendix

Table A1

Table A1

Measurement scales

ConstructsItemsAuthors
Emotional attachmentEA1 I feel emotionally connected to the esports player/team/streamer that I followSánchez-Fernández and Jiménez-Castillo (2021)
EA2 I feel a bond with the esports player/team/streamer that I follow
EA3 I am very attached to the esports player/team/streamer that I follow
EA4 The esports player/team/streamer that I follow are special to me
EA5 I miss the esports player/team/streamer that I follow when they do not post an entry or I cannot view their posts
Community engagementCE1 I benefit from following the community’s rulesLaroche et al. (2012) and Martínez-López et al. (2017)
CE2 I am motivated to participate in the activities because I feel good afterward and because I like them
CE3 I am motivated to participate in the community’s activities because this supports other members
CE4 I am motivated to participate in the community’s activities because I can achieve personal goals
Stickiness intentionST1 I will stay for a long time browsing this esports player/team/streamer channelMolinillo et al. (2020)
ST2 I intend to prolong my stays on this esports player/team/streamer channel
ST3 I will visit this esports player/team/streamer channel frequently
Positive sponsoring brand eWOMPBW1 I am likely to recommend the brands suggested by the esports player/team/streamer that I follow to other peopleSánchez-Fernández and Jiménez-Castillo (2021)
PBW2 I am likely to encourage friends and relatives to buy the brands recommended by the esports player/team/streamer that I follow
PBW3 I am likely to say positive things about the brands recommended by the esports streamer/team/player that I follow to other people
Intention to purchase sponsoring brandsIP1 I would purchase a brand based on the advice I am given by the esports player/team/streamer that I followSánchez-Fernández and Jiménez-Castillo (2021)
IP2 I would follow brand recommendations from the esport player/team/streamer that I follow
IP3 In the future, I will purchase the products of brands recommended by the esports player/team/streamer that I follow
Willingness to cocreateWTC1 I intend to work with this player/team/streamer to co-create valueMolinillo et al. (2020)
WTC2 I will co-develop products/services with this player/team/streamer
WTC3 I will work to co-design products/services with this player/team/streamer
WTC4 Overall, I will cooperate with this player/team/streamer in co-creating value

Source(s): Authors’ own elaboration

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Acknowledgements

The authors express their gratitude to the editor and reviewers for their constructive feedback during the revision process. They would also like to acknowledge all the participants who took part in the study and the infrastructure and support of the Consumer Behaviour Lab (LICCO), located in the Faculty of Economics and Business Management of the University of Malaga.

Funding: This research was funded by the Andalusian Plan for Research, Development and Innovation (PAIDI) of the Andalusian Government (No: SEJ-567) (Spain).

Corresponding author

Sebastian Molinillo can be contacted at: smolinillo@uma.es

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