Abstract
This study investigates the factors that influence sport fans’ intentions to purchase a mixed reality headset, specifically the Apple Vision Pro. A cross-sectional survey of 272 US-based sport fans was conducted via Prolific Academic. Structural equation modeling was used to test a conceptual model integrating the technology acceptance model (TAM) with six dimensions of team identification (TID). Private evaluation and public evaluation (dimensions of TID) had indirect positive effects on purchase intention via perceived usefulness, perceived ease of use, and attitude. Attitude mediated the relationship between TAM constructs and purchase intention. Findings highlight the importance of social and emotional identity in shaping sport fans’ adoption of mixed reality technologies. By demonstrating that fan identity influences core TAM belief constructs, the study offers theoretical and practical insights for promoting emerging fan engagement technologies.
Keywords
The sport consumption experience is dynamic (Potwarka et al., 2025), and technology is affording sport marketers with new ways to enhance those experiences (Yim et al., 2021). One such technology reshaping the sport fan experience is extended reality (Burton & Schlieman, 2021). Extended reality is the catch-all term encompassing virtual reality (VR; e.g., Chang et al., 2024), augmented reality (AR; e.g., Goebert & Greenhalgh, 2020), and mixed reality (MR; e.g., Westmattelmann et al., 2021).
AR has gained traction as a compelling tool for enhancing the fan experience in diverse sport marketing contexts. Goebert (2020) postulates that AR has been employed by major sport organizations such as the National Basketball Association (NBA), National Football League, and Major League Baseball to activate fan engagement through advertising, product interaction, and customer service. These activations include AR-enhanced merchandise and immersive stadium experiences (Goebert, 2020). By blending digital content with real-world environments, AR, VR, and MR can facilitate deeper fan interaction and brand immersion, often turning passive spectators into active participants.
Building on these developments, MR technologies are now pushing the boundaries of immersive fan engagement even further (Aquino, 2024). The Apple Vision Pro has emerged as an exciting MR headset that exemplifies the convergence of spatial computing, real-time interactivity, and immersive multimedia (Apple, 2024). These capabilities respond to a growing trend in which fans seek more personalized, immersive, and emotionally engaging sport experiences.
For instance, recent work by Chang et al. (2024) demonstrates how VR technologies can evoke flow states and emotional connection, particularly among low-involvement fans, thereby expanding the reach and satisfaction of digital sport experiences. The term flow state refers to a deeply immersive psychological experience in which an individual becomes fully absorbed in an activity, characterized by focused attention, intrinsic enjoyment, and a distorted sense of time (Csikszentmihalyi, 1990). Moreover, research has also shown that AR-based sport broadcasting can heighten visual engagement and sensory immersion, especially among viewers with lower prior sport involvement (Ahn & Ko, 2024). This reinforces the broader trend toward hybrid, tech-enabled sport experiences that capture fans’ attention through dynamic and emotionally resonant features.
As sport continues to evolve alongside rapid technological advancement (Ratten, 2020), understanding how and why fans adopt emerging technologies has become a critical area of inquiry. Technologies such as AR, VR, and MR are altering how sport content is consumed. It is also redefining the nature of the fan experience, blurring the lines between physical attendance, digital interaction, and emotional connection. These innovations have implications for fan engagement, revenue generation, sponsorship activation, and data-driven personalization. Indeed, these are core pillars of modern sport marketing and management.
Yet, despite their growing prominence, adoption of these technologies is not automatic. It depends on how fans perceive their usefulness, usability, and relevance to their identities and routines. Therefore, studying technology adoption enables sport scholars and practitioners to anticipate consumer behavior, optimize fan engagement strategies, and ensure that investments in innovation align with fans’ needs and expectations.
While prior research has frequently used the technology acceptance model (TAM) to explain sport fans’ adoption of digital innovations (e.g., Gómez-Ruiz et al., 2022; Ha et al., 2017; Hur et al., 2012; Schneiders & Rocha, 2022), TAM focuses primarily on individual-level cognitive belief, namely perceived usefulness and perceived ease of use. However, sport is not just a functional or rational activity; it is highly emotional, social, and identity driven (Ashmore et al., 2004; Branscombe & Wann, 1992). Fans often form deep psychological connections with their teams (Ashmore et al., 2004; Branscombe & Wann, 1992), and these attachments can significantly influence how they perceive and evaluate new sport-related technologies.
Despite this, existing TAM-based research in sport management has rarely incorporated social identity variables, limiting its explanatory power in emotionally charged domains like sport fandom. For instance, Ha et al. (2017) examined smartphone use among sport fans, finding that beyond general perceptions of ease of use and usefulness, sport-specific and device-specific factors (e.g., sport involvement, personal attachment to smartphones) significantly predicted adoption intentions. Their findings highlight the argument that sport consumption behaviors are shaped by a collection of psychological and contextual influences that extend beyond traditional TAM constructs. Yet, even as sport marketing research increasingly engages with these broader variables, few studies have systematically integrated team identification into predictive models of technology acceptance.
This study responds to that gap by proposing a TAM model that incorporates multidimensional team identification as an antecedent to perceived usefulness and ease of use. By doing so, the model better reflects the social, affective, and symbolic dimensions of fandom that influence how technologies like the Apple Vision Pro are evaluated and adopted. This extension not only enhances the theoretical richness of TAM in sport settings but also aligns with emerging calls to account for fan identity and psychological connection in explaining sport consumer behavior (Funk & James, 2006). We argue that team identification can shape fans’ beliefs about sport technology, such as how useful or easy it seems, which ultimately impacts their attitudes and intentions to adopt.
By integrating team identification into the TAM, this study offers a more holistic and contextually grounded model of sport fans’ technology acceptance. Integrating team identification addresses this psychological complexity by accounting for how social identity processes can shape perceptions of a technology's relevance and value. For instance, a highly identified fan may perceive a team-branded MR headset as more useful not only because of its features, but also because it deepens their symbolic relationship with the team. This extension of TAM moves beyond individual cognition to incorporate social meaning, thereby increasing the model's explanatory power in contexts where emotional and symbolic factors are central to adoption decisions. It also enables sport managers to segment and target fan groups more effectively based on identity-driven motivations, leading to more tailored technology engagement strategies. Therefore, the purpose of this study is to extend the TAM by incorporating multidimensional team identification to explain sport fans’ adoption of MR technology.
Theoretical Framework and Hypothesis Development
Technology Acceptance Model (TAM)
TAM has become one of the most influential frameworks for explaining why individuals choose to adopt or reject new technologies (Davis, 1989). TAM was chosen for this study because of its parsimony, empirical robustness, and widespread applicability across various domains, including sport contexts. Compared to extended versions of TAM such as TAM2 (Venkatesh & Davis, 2000), TAM3 (Venkatesh & Bala, 2008), and the unified theory of acceptance and use of technology (Venkatesh et al., 2003), the original TAM provides a theoretically grounded yet flexible framework that is well-suited for parsimonious modeling and integration with contextually relevant constructs, such as team identification. While these extended models introduce additional variables (e.g., subjective norms, facilitating conditions, computer anxiety), many of these factors are more applicable to organizational or mandatory-use settings rather than voluntary, emotionally driven consumer contexts like sport fandom. In contrast, TAM centers on perceived usefulness and perceived ease of use. These are constructs that remain highly salient in high complexity, emotionally charged domains. Importantly, TAM's simplicity allows for targeted theoretical extensions, such as the inclusion of multidimensional team identification, to better capture the social identity dynamics central to sport fan behavior (Davis, 1989; Venkatesh & Davis, 2000).
TAM originated from the theory of reasoned action (TRA) and the theory of planned behavior (TPB; Ajzen, 1991), both of which emphasize that behavior is primarily driven by an individual's attitudes and intentions. TRA posits that behavioral intention results from a combination of one's attitude toward the behavior and subjective norms (perceptions of social expectations), while TPB extends this logic by adding perceived behavioral control to account for situational constraints on behavior. Davis (1989) adapted these concepts to technology adoption by proposing that two cognitive beliefs, namely perceived usefulness and perceived ease of use serve as key attitudinal determinants of users’ behavioral intentions to adopt new technologies. In contemporary research, TAM continues to evolve as a specialized extension of TRA and TPB, retaining their focus on volitional behavior but contextualizing it for technology-based decision-making (Ajzen, 2020; Venkatesh & Davis, 2000). This conceptual lineage underscores that technology adoption is not merely a rational evaluation of functionality but also a process influenced by attitudinal, normative, and control-related beliefs.
Perceived usefulness is defined as the degree to which an individual believes that using a particular system will enhance their performance or help them achieve their goals (Davis, 1989). In the context of sport consumption, this construct captures how much value fans believe a technology adds to their experience, such as through improved engagement, better access to content, or enhanced enjoyment. Prior research in sport settings has found perceived usefulness to be a key predictor of adoption behavior.
For instance, Gómez-Ruiz et al. (2022) demonstrated that perceived usefulness significantly influenced consumers’ intention to adopt fitness apps, highlighting its continued relevance in digital sport contexts. Their findings suggest that users actively assess whether a technology contributes meaningful value to their experience, whether by enhancing access to content, increasing enjoyment, deepening their connection to a team, or supporting performance-related goals (Gómez-Ruiz et al., 2022). In sport technology environments, usefulness often reflects the degree to which an innovation adds functional, emotional, or experiential benefits that justify adoption.
This study includes perceived usefulness to capture how fans evaluate the practical and psychological rewards offered by emerging technologies such as the Apple Vision Pro. As a multifunctional and immersive device, the Vision Pro enables new forms of sport consumption through features like spatial replays, interactive overlays, and real-time data engagement. These capabilities invite users to reflect on how the technology improves (not just supplements) their overall sport experience. Assessing perceived usefulness allows researchers to measure whether fans recognize these features as enhancements that align with their motivations and expectations.
Moreover, consistent with the foundational logic of TAM (Davis, 1989), perceived usefulness serves as a central belief that shapes behavioral intention. It reflects a cost–benefit appraisal in which users weigh the anticipated gains of adoption against their time, effort, and financial investment. Thus, the following hypotheses were formulated:
Perceived ease of use refers to the degree to which an individual believes that using a system will be free of effort (Davis, 1989). Technologies that are user-friendly and intuitive are more likely to be accepted by consumers, especially those with less technological expertise. This relationship has been supported in sport-specific contexts. For instance, Ha et al. (2017) applied TAM to investigate factors influencing sport fans’ use of smartphones for consuming sport-related content. Their findings revealed that perceived ease of use significantly influenced behavioral intention, whereas perceived usefulness showed a comparatively weaker relationship (Ha et al., 2017). This suggests that for mobile-based technologies, fans may prioritize convenience, simplicity, and seamless interaction over direct performance benefits.
In digital sport environments where fans engage with content quickly and often on the go, usability may carry more weight than functional utility (Ha et al., 2017; Kim et al., 2017). Fans might not necessarily adopt a sport technology because it helps them achieve a measurable goal (e.g., enhancing knowledge or improving performance), but rather because the experience is intuitive, enjoyable, and requires minimal effort to navigate (Davis, 1989; Venkatesh & Davis, 2000). This distinction is particularly important in the case of emerging or immersive technologies such as MR headsets, where perceived complexity can serve as a barrier to entry and negatively influence attitudes toward adoption (Gómez-Ruiz et al., 2022; Ratten, 2020; Yoshida et al., 2023).
By highlighting the outsized role of perceived ease of use in influencing sport fans’ technology adoption decisions, Ha et al.'s (2017) findings reveal the importance of designing and marketing sport technologies that are not only feature-rich but also cognitively and physically accessible. Their study lends further empirical support to our use of perceived ease of use as a central construct in this model, especially in a context like the Apple Vision Pro, which may be unfamiliar or intimidating to less tech-savvy users. Thus, the following hypotheses were formulated:
While both constructs have shown strong predictive power in technology adoption research, most applications of TAM in the sport context have focused on relatively basic or familiar technologies such as apps, websites, and social media platforms (Ha et al., 2017; Hur et al., 2012). For instance, Schneiders and Rocha (2022) applied TAM to examine how Formula 1 viewers respond to technological innovation in televised sport content. Their findings showed that perceptions of innovation influenced satisfaction and commitment to viewing behavior, particularly through indirect pathways (Schneiders & Rocha, 2022). This highlights the importance of mediated relationships within TAM-based models.
The emergence of MR headsets like the Apple Vision Pro introduces a fundamentally different kind of sport consumption experience; one that is immersive, multisensory, and potentially more demanding cognitively and financially. As such, applying TAM in this new technological landscape provides the necessary baseline for testing the impact of team identification. Moreover, while later versions of TAM (e.g., TAM2; Venkatesh & Davis, 2000) excluded the “attitude” construct to streamline the model and improve parsimony in organizational and utilitarian contexts, this study retains attitude for both theoretical and contextual reasons. First, Davis’ (1989) original model included attitude as a mediating mechanism between cognitive beliefs (i.e., perceived usefulness and perceived ease of use) and behavioral intention. This structure remains particularly relevant in consumer contexts where decisions are influenced not only by functionality but also by evaluative affect toward the product. In emotionally charged settings like sport fandom, attitude serves as a meaningful psychological bridge that connects perceived value with behavioral intent. Recent sport technology research (e.g., Gómez-Ruiz et al., 2022; Kim et al., 2017) has also continued to include attitude to capture the evaluative dimension of consumers’ responses to innovations. Therefore, attitude is retained in the model to capture the evaluative dimension of consumers’ responses to innovations. This is especially important when evaluating complex and emotionally resonant technologies like MR devices. Thus, the following hypothesis was formulated:
While these TAM relationships provide a foundational model, they largely assume a rational, utilitarian process. Yet, in the context of sport fandom, consumer behavior is deeply shaped by emotional, social, and identity-based factors. To better account for these dynamics, we extend the TAM with the concept of team identification. As Ratten (2020) notes, the literature on sport technology adoption remains in an early theoretical stage, often lacking conceptual depth despite widespread digital transformation in the sport industry. This emphasizes the need to move beyond models that focus only on practical or performance-related reasons for adopting technology and instead incorporate social and psychological factors (i.e., team identification) that reflect the emotional and symbolic nature of sport consumption.
Team Identification as an Extension to TAM
The concept of team identification originates from social identity theory (SIT), regarded as how the subjective perception of the self is perceived by others (Brown, 2000; Funk et al., 2022). SIT has made notable contributions in four key areas, namely in-group bias, responses to status inequality, intragroup homogeneity and stereotyping, and changing intergroup attitudes through contact (Brown, 2000). Specifically, SIT has helped inform our understanding of why a group prefers itself (in-group) over other groups (out-group). This preference reveals itself in different ways, such as the approaches individuals use to perceive, assess, and engage with members of their own group compared to those from different groups (Brown, 2000).
Researchers regard the central tenants of SIT in the context of sport with a concept known as team identification, defined as “the degree to which a consumer feels a sense of belonging to and connection with other spectators and fans of a sports team” (Funk et al., 2022, p. 229). Similarly, Branscombe and Wann (1992) defined it as “the extent to which individuals perceive themselves as fans of the team, are involved in the team, are concerned with the team's performance, and view their team as a representative of themselves” (p. 3). Researchers have examined the role team identification plays in a variety of sport consumer behaviors. For instance, Yoshida et al. (2023) demonstrated that team identification positively predicted subjective vitality, both directly and indirectly through behavioral engagement such as stadium attendance. Their findings emphasize the psychological value of fandom, suggesting that fans’ sense of identity with a team can energize them and enhance well-being through meaningful sport consumption experiences.
Most of the previous studies that have examined the role team identification plays in sport consumer behavior have predominately used a one-dimensional measure or qualitative approaches (Delia et al., 2021). Scholars have noted conceptual inconsistencies in how team identification has been defined and operationalized across studies (Lock & Heere, 2017). Specifically, Lock and Heere (2017) argued that much of the research conflates the distinct perspectives of identity theory and the social identity approach, leading to theoretical ambiguity. To address these conceptual gaps, scholars have increasingly advocated for a multidimensional and network-based approach to studying team identification that recognizes how fans connect not only with the team itself but also with subgroups, supporter clubs, and peer communities that reinforce this identity (Katz et al., 2020). Building on their analysis, this study adopts a multidimensional perspective of team identification to capture the full complexity of fan identity and its influence on technology adoption.
Recent advances in the sport management literature emphasize the value of conceptualizing team identification as a multidimensional construct rather than a singular or unidimensional form of fan attachment. Heere and James (2007) developed the TEAM × ID scale grounded in SIT, identifying six core dimensions that collectively capture the diverse ways fans psychologically associate with a sport team: private evaluation, public evaluation, interconnection of self, sense of interdependence, behavioral involvement, and cognitive awareness. These dimensions move beyond surface-level allegiance and instead reflect a range of identity-driven processes, including how fans evaluate their team privately, how they believe others view their fandom, the extent to which their self-concept overlaps with team membership, and how they act on and think about their team affiliation. By articulating these distinct but interrelated facets, the TEAM × ID framework enables researchers to assess the depth of fan identity with greater specificity and explanatory power.
Building on this structural approach, James et al. (2019) offered a critical refinement to the measurement of team identification. They argued that previous studies often conflated nonfans with weakly identified fans, which introduced ambiguity into interpretations of fan behavior and distorted the underlying distribution of identification across samples. Their work advocated for more nuanced measurement tools that distinguish clearly between the levels of identification and account for both the presence and absence of fan identity. These methodological insights have advanced the precision and validity of team identification research, particularly in studies where identity strength may moderate or mediate psychological or behavioral outcomes.
In this study, we adopt a multidimensional approach to measuring team identification to better capture the complexity of fan identity and its influence on technology adoption behavior. By using the TEAM × ID scale, we are able to isolate which specific facets of identification (i.e., private evaluation, behavioral involvement, etc.) correspond most strongly with perceptions of a new sport technology's usefulness or ease of use. This approach enhances the explanatory value of the extended TAM framework by allowing for a more granular analysis of how social identity shapes fan cognition and decision-making. Rather than assuming that identification exerts a uniform effect, we test how different identity dimensions interact with core TAM constructs, offering a richer and more contextually grounded model of sport fan behavior. In doing so, we contribute both theoretical refinement and empirical insight to the intersection of fan psychology and technology acceptance in sport.
Moreover, the extension of TAM with team identification is grounded in the theoretical convergence of SIT (Tajfel, 2010) and technology acceptance research. TAM posits that technology adoption is driven by perceived usefulness and perceived ease of use, beliefs often treated as cognitive and rational. However, in emotionally charged settings like sport, these beliefs may be shaped by affective and identity-relevant factors. Research in SIT suggests that group membership influences not only attitudes and behavior, but also information processing, evaluation of stimuli, and decision-making (Abrams & Hogg, 2004; Ashforth & Mael, 1989). This implies that fans’ identification with a team may alter how they perceive the relevance, utility, or complexity of sport technologies.
Each of the team identification dimensions may shape how fans interpret a technology's relevance, utility, and usability. One of the team identification dimensions, private evaluation, reflects the internalized sense of pride and positive self-esteem derived from one's association with a team (Heere et al., 2011). Fans who hold strong private evaluations perceive their team affiliation as integral to their self-concept and may view technologies that reinforce this bond, such as MR tools offering immersive team-related experiences as particularly meaningful. Thus, the following hypotheses were formulated:
Conversely, public evaluation captures how fans believe others perceive their team affiliation (Heere et al., 2011). Fans who think their team is well respected may see adopting innovative technologies as a way to enhance or display this positive image, aligning with prior work suggesting that social visibility and prestige can drive technology use in sport settings (Filo et al., 2015). Thus, the following hypotheses were formulated:
The interconnection of self with the group describes the perceived overlap between personal identity and group membership (Heere et al., 2011). When fans perceive high overlap, technological engagement can feel like an extension of their collective identity. Similarly, sense of interdependence reflects the extent to which fans believe their actions or emotions affect the team's outcomes. This shared psychological investment may heighten responsiveness to technologies that simulate presence, participation, or collective experience. For example, MR features that provide interactive viewing or shared spatial experiences may appeal strongly to interdependent fans seeking deeper group connectedness. Thus, the following hypotheses were formulated:
Finally, behavioral involvement captures the degree of active participation in fan-related activities (e.g., attending games, following social media, purchasing merchandise), while cognitive awareness refers to knowledge of the team's history, players, and organizational structure (Heere & James, 2007). Fans high in behavioral involvement may adopt MR devices to extend their engagement repertoire (e.g., virtual replays, interactive team environments), whereas those high in cognitive awareness may critically evaluate the utility and authenticity of such innovations before adoption. By considering these six dimensions simultaneously, this study not only recognizes the complexity of fan identity but also identifies which aspects of identification most strongly shape perceptions of technology usefulness, ease of use, and eventual purchase intention. Thus, the following hypotheses were formulated:
Figure 1 shows a visual representation of the hypotheses that will be tested.
Hypothesized model 1: Associations of the dimensions of team identification with purchase intention mediated by perceived usefulness, perceived ease of use, and attitude.
Method
Participants and Procedure
Participants for this study were recruited using a convenience sampling method. Data were collected through an online survey administered via Qualtrics and distributed on Prolific Academic, a reputable crowdsourcing platform commonly used in behavioral research across various disciplines (Tandon et al., 2021, 2022). Eligibility criteria restricted participation to individuals residing in the United States. To ensure that responses reflected the perspectives of genuine sport consumers, inclusion criteria required participants to self-identify as sport fans. During the screening stage, participants were asked the question: “Do you consider yourself a sport fan?” Only those who selected “yes” were permitted to proceed to the main survey. This self-identification approach is consistent with prior research that defines fandom based on individuals’ self-perceived connection and involvement with sport (Funk et al., 2022; Lock & Heere, 2017).
Additionally, the focus on American sport fans is theoretically aligned with the study's context, as the United States represents one of the largest and most commercially advanced sport markets where digital innovation such as MR technologies is being actively deployed. Therefore, sampling from this population enhances the practical relevance of the findings. To ensure consistency across responses, participants were shown a brief description of the Apple Vision Pro and video that emphasized its MR capabilities and its potential for enhancing the sport fan experience.
The purpose of this stimulus was to ensure all participants had a basic and consistent understanding of MR capabilities, given that familiarity with such technologies varies among consumers. The video was designed to be descriptive rather than promotional, avoiding persuasive language or brand endorsements to minimize bias in participants’ evaluations. Similar neutral stimuli have been used in prior research to establish context without significantly influencing attitudinal responses (Yoo et al., 2025).
While the Apple Vision Pro is a multipurpose device capable of supporting other domains such as education, entertainment, and productivity, our interest lay in understanding how fans evaluate its potential use for sport consumption. Participants were explicitly instructed to assess the device as it pertains to their sport media experiences. No manipulation check was used; however, the survey included screening criteria that required participants to identify as sport fans and to reflect on their consumption of sport content while evaluating the product. We acknowledge that broader perceptions of the Apple Vision Pro may be influenced by its nonsport features, and we address this drawback in the limitation section.
Measures
Perceived Ease of Use, Perceived Usefulness, Purchase Intention, Attitude
Using a 7-point Likert scale with responses ranging from 1 “strongly disagree” to 7 “strongly agree” (Joshi et al., 2015), respondents were asked whether they agree or disagree with several statements. For instance, statements such as “The Apple Vision Pro will be easy to use” was used to assess perceived ease of use; statements such as “The Apple Vision Pro can improve my experience of watching sports” was used to assess perceived usefulness; statements such as “I intend to purchase the Apple Vision Pro within the foreseeable future” was used to assess purchase intention; and statements such as “My impression of purchasing the Apple Vision Pro is bad-good” was used to assess attitude. Attitude toward the Apple Vision Pro was measured using a semantic differential scale (Heise, 1969), which differs from the Likert-type format used for the other constructs. Participants evaluated their overall impression of the product using five bipolar adjective pairs: good–bad, positive–negative, satisfactory–unsatisfactory, favorable–unfavorable, and unpleasant–pleasant. These items are commonly used in attitude measurement to capture evaluative judgments along affective dimensions (Ajzen & Fishbein, 1972). To maintain scoring consistency across the scale, the “unpleasant–pleasant” item was reverse-coded prior to analysis. All five items demonstrated strong factor loadings and contributed to a reliable, unidimensional attitude construct, as indicated by the high composite reliability (CR) reported in Table 1. The items used to measure these variables were adapted from Davis (1989) and Venkatesh and Davis (2000) and Dodds et al. (1991) to ensure reliability and validity. These items were then modified to better reflect the context of the study.
Means (M), Standard Deviations (SD), Factor Loadings (λ), and Composite Reliabilities (CRs).
Team Identification
Team identification was measured using items adapted from the Group Identity Scale developed by Heere and James (2007). This multidimensional measure consisted of six dimensions, namely self-categorization, private evaluation, public evaluation, sense of interdependence with the group, interconnection of self with the group, and cognitive awareness. These dimensions explain how consumers identify with social groups. This study adapted only a subset of the original dimensions to ensure conceptual alignment with TAM. These dimensions capture the emotional, cognitive, and social mechanisms most relevant to how fans evaluate new technologies. Other dimensions were excluded to maintain survey parsimony and reduce participant burden. To assess these dimensions, a 7-point bipolar Likert scale (Joshi et al., 2015) with responses ranging from 1 “strongly disagree” to 7 “strongly agree” was used.
Data Analysis
Structural equation modeling (SEM) was used to analyze data using AMOS 21 and SPSS 29.0. To begin, we looked for any deviations from normality for each item, such as skewness or kurtosis, and to tackle issues related to missing data. We found no significant nonnormality issues and no missing values in the data set. Afterward, data analysis was conducted using SEM in AMOS 21, utilizing maximum likelihood estimation (Anderson & Gerbing, 1988). The first stage consisted of defining and testing a measurement model, specifically confirmatory factor analysis (CFA). The second stage consisted of examining the linear relationships among the latent constructs proposed in our model.
We constructed the measurement model with six correlated factors: seven team identification factors (private evaluation; three items, public evaluation; three items, sense of interdependence with the group; three items, interconnection of self with the group; three items, behavioral involvement; three items, cognitive awareness; three items), two TAM factors (perceived usefulness; six items, perceived ease of use; four items, attitude; five items), and purchase intention (four items). The participant responses to these items (observed variables) represented the characteristics of the theoretical constructs (unobserved variables).
Consistent with the established SEM practices (Hair et al., 2010), we evaluated the model's fit using a variety of fit indices, that is, inadequate matches indicated by significant cross-loadings between constructs lead to lower fit indices, whereas strong alignments result in higher indices. The chosen fit indices for model assessment included a chi-square/degree of freedom ratio (χ2/df), the comparative fit index (CFI), the normed fit index (NFI), the Tucker–Lewis index (TLI), and the root mean square error of approximation (RMSEA) along with its associated p-value (PCLOSE). Robust measurement models are characterized by a χ2/df ratio below 3, CFI, NFI, and TLI values above 0.90 (preferably over 0.95), and an RMSEA below 0.05 with a nonsignificant PCLOSE at the .05 level (Hair et al., 2010).
To address potential concerns associated with common method bias (CMB), procedural remedies were implemented during survey design, such as assuring anonymity, randomizing item order, and using varied scale formats. Additionally, statistical tests were conducted to assess CMB. Specifically, Harman's single-factor test revealed that no single factor accounted for the majority of variance, suggesting that CMB is unlikely to bias the results significantly (Podsakoff et al., 2003). Moreover, the SEM analysis adhered to best practices by assessing model fit through multiple indices (e.g., RMSEA, CFI, TLI, Standardized Root Mean Square Residual (SRMR) ) and verifying the reliability and discriminant validity of latent constructs using CR, average variance extracted (AVE), and Heterotrait-Monotrait (HTMT) ratios. These steps enhance confidence in the validity of the model and the robustness of the findings.
Sample Size and Power
A total of 272 completed responses were retained for analysis. A sample of 272 American sport fans is appropriate and adequate for the aims of this study because the sample size exceeds the commonly accepted thresholds for conducting SEM, where minimum sample requirements typically range from 150 to 200 depending on model complexity (Kline, 2023). Although the survey did not include embedded attention checks, data quality was maintained through Prolific Academic's participant filters (e.g., ≥95% approval rate, verified accounts, and unique participant IDs). Participants with incomplete responses or clear evidence of inattentiveness (e.g., straight-lining, inconsistent answers) were excluded from the analysis. In total, 34 incomplete or invalid responses were removed.
Given that the current model includes multiple latent variables and paths, a sample of 272 provides sufficient power to detect structural relationships and ensures reliable parameter estimates. To justify sample adequacy for the structural equation model, we followed best-practice guidance for SEM power planning using a Monte Carlo rationale and recent recommendations (Kline, 2023; Wolf et al., 2013). We assumed a model with 10 latent constructs (six TEAM × ID dimensions plus perceived usefulness, perceived ease of use, attitude, and purchase intention) measured by ∼37 indicators, with standardized factor loadings ≈ 0.60–0.70, two-tailed α = .05, and target structural effects in the small-to-moderate range (β = .20–.30). Under these conditions, Monte Carlo-style benchmarks reported by Wolf et al. (2013) indicate that N ≈ 220–240 typically affords ≥0.80 power to detect β ≈ .25, whereas β ≈ .20 generally requires N ≈ 280–320 for comparable power. Our final sample of N = 272 therefore provides adequate power (≈0.80+) for detecting β ≈ .25 paths and near-adequate power for β ≈ .20 paths, which aligns with contemporary guidance that complex SEMs with multiple latent factors generally require 200–300 cases for stable estimation and hypothesis testing (Kline, 2023). This range is also consistent with practical SEM sizing heuristics and minimum-N recommendations for models of comparable complexity (MacCallum et al., 1996; Westland, 2010).
Given the complexity of the structural model, which includes the core constructs of TAM and six dimensions of team identification, totaling 10 latent variables with multiple indicators, an a priori Monte Carlo simulation was conducted to evaluate statistical power for the focal structural paths. Following methodological guidance from Muthén and Muthén (2002) and Wolf et al. (2013), simulation specifications were informed by prior research on technology acceptance and team identification.
Standardized factor loadings were set between 0.70 and 0.85, residual variances were calibrated accordingly, and key structural paths were varied from β = .20 to .35 to reflect small-to-moderate effects commonly observed in this literature. Using 5,000 replications, maximum likelihood estimation with robust standard errors, and a sample size of N = 272, the results indicated power ≥0.80 for detecting paths of β ≥ .25 (e.g., Perceived Eease Of Use → Perceived Usefulness, Perceived Usefulness → Attitude, Attitude → Purchase Intention, and theoretically relevant TEAM × ID → Perceived Usefulness/Perceived Ease Of Use links). Stronger paths (e.g., PU → Attitude, β ≈ .50) achieved power greater than 0.99. Across all conditions, parameter bias remained below |0.02|, 95% confidence interval coverage ranged from 0.94 to 0.96, and type I error approximated 0.05. Consistent with the established recommendations for complex SEM models (Muthén & Muthén, 2002; Wolf et al., 2013), these results indicate that the achieved sample size is adequate for detecting the effects posited in the proposed model.
Results
Descriptive statistics summarizing sample characteristics are presented in Table 2. The sample comprised of 272 US-based sport fans who varied in age, gender, and sport interest, providing an appropriate range of perspectives for testing the proposed model.
Demographic Profile of Participants.
The following sections outline the results of the measurement and structural analyses.
Measurement Model Results
Prior to evaluating the structural model, it is imperative to ascertain the validity and reliability of the constructs in the model (Bagozzi & Yi, 2012; Fornell & Larcker, 1981; Hair et al., 2010). To test the measurement model, CFA was performed using AMOS 21. To begin, CFA was conducted with the factors from the TAM model (perceived ease of use, perceived usefulness, purchase intention, attitude) and factors from team identification (private evaluation, public evaluation, sense of interdependence with the group, interconnection with the group, behavioral involvement, cognitive awareness). There were no items removed from any of the factors. The set of 16 items from the factors comprising of the TAM model showed construct reliabilities, AVE (Fornell & Larcker, 1981), and Cronbach's alphas that exceed recommended standards for reliability and unidimensionality. Similarly, this was also the case with the factors comprising team identification (Table 3).
Correlations.
As per Fornell and Larcker (1981), the confirmation of convergent validity hinges on achieving an AVE surpassing 0.50 of the overall variance. Convergent validity refers to the degree to which a latent construct explains the variance in its indicators (Raykov & Marcoulides, 2012). The study successfully verified convergent validities for all four TAM factors and all factors from team identification based on this criterion. Conversely, discriminant validity measures the extent to which a latent construct uniquely explains the variance in its indicators, distinct from other constructs in the model (Raykov & Marcoulides, 2012). Put differently, discriminant validity, indicating the distinction between each factor, is established when (1) the maximum shared variance is lower than the average shared variance (ASV), (2) ASV is lower than AVE, and (3) the square root of AVE exceeds the interconstruct correlations (Hair et al., 2010). The goodness-of-fit statistics are as follows: χ2/df = 1.72, CFI = 0.98, NFI = 0.94, TLI = 0.97, RMSEA = 0.05, and PCLOSE = 0.34 (Table 4).
Model Fit Statistics for CFA and Structural Models.
Note. CFA = confirmatory factor analysis; df = degree of freedom; CFI = comparative fit index; NFI = normed fit index; TLI = Tucker–Lewis index; RMSEA = root mean square error of approximation; PCLOSE = associated p-value;
Structural Model Results
The structural model in this study was tested using the maximum likelihood method with AMOS 21. The results showed the proposed structural model with χ2/df = 1.80, CFI = 0.97, NFI = 0.94, TLI = 0.97, RMSEA = 0.05, and PCLOSE = 0.11. These results were regarded as acceptable fit according to Browne et al. (1993). Overall, statistical tests supported some hypothesized paths. Approximately one-third of the hypothesized relationships were nonsignificant, however see Figure 2 for standardized path coefficients and significance levels.
Research model of the relationships between team identification, perceived usefulness, perceived ease of use, and purchase intention.
Hypotheses 7 and 8 examined the impact of private evaluation on perceived usefulness and perceived ease of use. Private evaluation had a significant positive impact on perceived usefulness (β = .43**; SE = 0.10), thus hypothesis 7 was supported. This means that the more consumers felt good about being a sports fan, the more likely consumers felt the Apple Vision Pro could improve their experience of watching sports. To be sure, private evaluation did not have a significant positive impact on perceived ease of use (β = .04; SE = 0.10), thus hypothesis 8 was not supported.
Hypotheses 10 and 11 examined the impact of public evaluation on perceived usefulness and perceived ease of use. The results indicated that public evaluation did not have a significant influence on perceived usefulness (β = .04; SE = 0.08), therefore hypothesis 10 was not supported. However, public evaluation had a significant positive impact on perceived ease of use (β = .32**; SE = 0.09), thus hypothesis 11 was supported. That is, the more consumers believed others respected their team, the more likely they were to believe that the Apple Vision Pro would be easy to use.
Hypotheses 14 and 15 examined the impact of sense of interdependence with the group on perceived usefulness and perceived ease of use. Sense of interdependence with the group did not have a significant influence on perceived usefulness (β = .12; SE = 0.14), therefore hypothesis 14 was not supported. However, sense of interdependence had a significant positive impact on perceived ease of use (β = .21*; SE = 0.12), thus hypothesis 15 was supported. This means that the more consumers believed changes affecting their team would have an impact on their own life, the more likely they were to believe that the Apple Vision Pro would be easy to use.
Hypotheses 18 and 19 and hypotheses 20 and 21 examined the impact of interconnection of self with the group and behavioral involvement on perceived usefulness and perceived ease of use, respectively. However, these hypothesized paths did not have a significant positive impact on perceived usefulness and perceived ease of use and thus these hypotheses were not supported by the data. Hypotheses 22 and 23 examined the impact of cognitive awareness on perceived usefulness and perceived ease of use. Cognitive awareness had a significant negative impact on perceived usefulness (β = −.16*; SE = 0.10), thus hypotheses 22 was supported. That is, the more consumers felt they were aware of the tradition and history of their team, the less likely consumers felt the Apple Vision Pro could improve their experience of watching sports. Conversely, cognitive awareness did not have a significant influence on perceived ease of use (β = −.08; SE = 0.10), therefore hypothesis 23 was not supported.
Hypothesis 3 examined the impact of perceived ease of use on perceived usefulness. The results showed that perceived ease of use had a significant positive impact on perceived usefulness (β = .35**; SE = 0.06), thus hypothesis 3 was supported. In other words, the more consumers believed the Apple Vision Pro would be easy to use, the more consumers felt it could improve their experience of watching sports. As such, 43% of variance in perceived usefulness was explained by private evaluation, cognitive awareness, and perceived ease of use. Alternatively, 22% of variance in perceived ease of use was explained by public evaluation and sense of interdependence with the group.
Hypotheses 1 and 4 examined the impact of perceived usefulness and perceived ease of use on attitude, respectively. The results showed that perceived usefulness had a significant positive impact on attitude (β = .52**; SE = 0.08), thus hypothesis 1 was supported. That is, the more consumers felt the Apple Vision Pro could improve their experience of watching sports, the more likely they were to believe purchasing the Apple Vision Pro would be good. Moreover, it showed that perceived ease of use had a significant positive impact on attitude (β = .23**; SE = 0.06), which means that the more consumers felt the Apple Vision Pro would be easy to use, the more likely they were to believe purchasing the Apple Vision Pro would be satisfactory. As a result, hypothesis 4 was supported. Sixty percent of variance in attitude toward purchasing the Apple Vision Pro is explained by the two salient belief constructs from the TAM, namely perceived usefulness and perceived ease of use. Finally, hypothesis 6 examined the impact of attitude on purchase intention. The results showed that attitude had a significant positive impact on purchase intention (β = .54**; SE = 0.07), thus hypothesis 6 was supported. That is, the more consumers felt a positive attitude toward purchasing the Apple Vision Pro, the more likely they were to purchase the technology within the foreseeable future. As such, 44% of variance in purchase intention was explained by attitude (Tables 5 to 7).
Estimated Structural Relations Coefficients (Direct Effects).
Note. SE and p values of all direct effects were estimated with bootstrap analysis. SE = standard error.
*p < .05, **p < .01, ***p < .001.
Estimated Structural Relations Coefficients (Indirect Effects).
Note. SE and p values of all direct effects were estimated with bootstrap analysis. SE = standard error.
*p < .05, **p < .01, ***p < .001.
Summary of Hypotheses Testing Results.
Discussion
This study makes a theoretical contribution to the sport management literature by extending the TAM through the integration of team identification to explain fans’ adoption of MR technology. TAM, originally developed by Davis (1989), emphasizes the roles of perceived usefulness and perceived ease of use in shaping technology acceptance. While this framework has been applied across numerous sport contexts such as mobile apps, websites, and wearable technologies (Gómez-Ruiz et al., 2022; Ha et al., 2017; Kim et al., 2017), most past studies have looked at why people use new sport technologies by focusing mainly on practical reasons, that is, whether the technology is useful or easy to use. These studies assume that fans make decisions based on logic and usefulness, rather than thinking about how the technology might make them feel more connected to their favorite team or express their loyalty as a fan. This research challenges that assumption by incorporating the social and psychological complexity of fandom, offering a more contextually grounded approach to understanding fan behavior.
Supported Hypotheses
The most novel and impactful finding of this study lies in demonstrating that team identification is not a uniform construct but rather a multifaceted phenomenon with differential effects on core TAM constructs. Private evaluation significantly predicted perceived usefulness, supporting the idea that emotionally attached fans may see more value in technologies that enhance their team connection. This is consistent with prior research emphasizing the symbolic and emotional nature of sport consumption (Yoshida et al., 2023). An explanation for the finding that private evaluation significantly predicted perceived usefulness is rooted in how emotionally attached fans evaluate technologies through the lens of their psychological connection to the team. Private evaluation, as a dimension of team identification, reflects personal, internalized positive feelings about being a fan of a team and how much pride and satisfaction one derives from this identity (Heere et al., 2013).
Fans with a high private evaluation may be more likely to interpret new technologies, such as MR headsets, as valuable when these tools strengthen or validate their internal fan identity. In this context, perceived usefulness is not assessed solely on utilitarian grounds (e.g., efficiency or performance), but on symbolic and emotional benefits such as deepening team loyalty, enhancing personal enjoyment of games, or feeling closer to the team. This supports findings by Trail and James and Yoshida et al. (2023), who emphasize that sport consumers are often driven by emotional and identity-based motivations rather than purely functional considerations. Therefore, when a technology supports or reflects a fan's identity (e.g., by offering team-branded experiences or enhancing in-game engagement), highly identified fans may be more likely to perceive it as useful. This finding expands our understanding of perceived usefulness beyond cognitive evaluations, highlighting how affective and identity-based processes play a key role in shaping technology acceptance in sport contexts.
One of the more surprising findings was the negative relationship between cognitive awareness and perceived usefulness. To be clear, cognitive awareness is operationalized in this study as whether a sport fan is aware of the tradition and history of their favorite professional sport team (Heere et al., 2011). While previous studies have assumed that greater knowledge and mental engagement with the team would foster positive evaluations (Ha et al., 2017; Kim et al., 2017), our results suggest that highly analytical fans may be more critical or skeptical of emerging technologies like the Apple Vision Pro. This finding offers a useful extension to the TAM literature, illustrating that not all cognitive engagement leads to positive assessments and that perceived usefulness is contingent on more than product functionality.
A possible explanation for this finding is that highly analytical fans, that is, those with strong cognitive awareness of their team, may approach new technologies with a more critical lens, particularly when the technology promises to enhance their fan experience. These fans are likely well-informed and discerning, which means they may hold higher standards or expectations for what a technology like the Apple Vision Pro should deliver. Rather than being easily impressed, they might evaluate the alignment between the technology and the core elements of their fandom (e.g., authenticity, tradition, informational value). If they perceive the MR device as superficial, gimmicky, or not truly enhancing their understanding or experience of the sport, they may judge it as less useful, even if it functions well from a technical standpoint. This suggests that not all fan engagement is created equal. Put differently, while emotional attachment may lead to more favorable evaluations, intellectual or informational involvement could prompt scrutiny, especially when new technologies disrupt traditional ways of experiencing sport.
Regarding the significant relationship between public evaluation and perceived ease of use (H11), the results suggest that fans’ perceptions of their team's social status may spill over into their technical evaluations, a phenomenon consistent with the halo effect in consumer behavior. Fans who believe their team is widely respected (high public evaluation) may associate the team with high organizational quality and prestige. Consequently, they may heuristically judge team-related innovations, such as the Apple Vision Pro, as being more polished, intuitive, and accessible. In contrast, fans who feel their team lacks public respect may approach the technology with lower confidence or higher anxiety, inadvertently inflating their perception of the device's complexity.
Nonsupported Hypotheses
Although many hypothesized paths were supported, several relationships were not statistically significant, providing useful theoretical nuance. Private evaluation did not influence perceived ease of use, suggesting that self-pride in fandom does not necessarily translate to perceptions of technological simplicity. Similarly, public evaluation did not directly affect perceived usefulness, indicating that how others view one's team identity may be less relevant to assessing a technology's functional value.
The remaining dimensions, namely interconnection of self with the group and behavioral involvement did not significantly predict either perceived usefulness or ease of use. These findings imply that active fan behaviors (e.g., attending games or following team news) may not automatically shape technology evaluations unless the technology explicitly facilitates those activities. The nonsignificant results collectively suggest that not all facets of team identification influence adoption intentions in the same way. Instead, specific psychological dimensions (private evaluation, interdependence, cognitive awareness) appear most salient. Examining team identification as a multidimensional construct rather than a unidimensional measure should be noted.
Theoretical Implications
This study advances the understanding of TAM in the context of sport. Until now, there has been a lack of knowledge about the role team identification plays in fans’ innovation adoption behaviors in sport contexts. To address this research gap, we have formulated and tested a conceptual framework that examines this phenomenon. Our conceptual framework reveals the significant role of team identification in explaining fans’ intentions to purchase the Apple Vision Pro. Because TAM has been traditionally applied in business and educational settings to understand innovation adoption behaviors, relying on factors such as perceived usefulness and perceived ease of use (Davis, 1989; Venkatesh & Davis, 2000), extending this model to include emotional and social dimensions of sports fandom highlights the importance of psychological factors in innovation adoption. Including team identification with TAM provides a novel perspective on innovation adoption behaviors in sport contexts. This is particularly relevant given the increasing integration of technology in sports, both as a fan engagement tool and as a means to enhance the fan experience (Ratten, 2020; Ratten & Ferreira, 2017).
Moreover, the differential impacts of various dimensions of team identification, namely private evaluation, public evaluation, sense of interdependence, and cognitive awareness on TAM's belief constructs offer a more nuanced understanding of the innovation adoption process. As such, one key takeaway is that not all aspects of team identification influence innovation adoption in the same way. Additionally, the negative impact of cognitive awareness on perceived usefulness offers an intriguing insight into how greater knowledge about the history of consumers’ favorite sports teams can lead to consumers’ believing the Vision Pro would not really improve their fan experience. This challenges the conventional assumption that greater knowledge always leads to positive product evaluations and suggests that sports technology marketers need to consider more sophisticated approaches when targeting highly knowledgeable fans.
Importantly, the findings of this study highlight the theoretical value of employing a multidimensional measure of team identification. By utilizing the TEAM × ID scale, this research was able to reveal distinct and nuanced effects of the six identification dimensions on sport fans’ perceptions of emerging technology. These differential relationships would likely have been obscured had a unidimensional measure been used, as such an approach would treat fan identification as a singular construct rather than a constellation of interrelated but conceptually distinct processes (Heere & James, 2007). This highlights the importance of considering the multifaceted nature of fan identity in sport marketing and technology adoption research, as it enables scholars and practitioners to better understand which specific psychological dimensions most meaningfully influence fans’ acceptance of innovative sport technologies.
Practical Implications
This study provides several practical insights for sport marketers and technology developers aiming to promote adoption of MR technologies among sport fans. Central to these findings is the role of team identification, especially private evaluation, in shaping how fans assess the usefulness of MR experiences. Fans who experience a strong emotional connection to their team are more likely to perceive MR devices as valuable tools that deepen that relationship. Sport marketers should therefore emphasize how MR platforms can provide unique, emotionally resonant experiences such as virtual locker room access, interactive player narratives, or spatial replays of iconic moments, all of which may enhance a fan's sense of belonging and engagement (Kim et al., 2017; Yoshida et al., 2023).
Second, the study found that cognitive awareness, or the degree to which fans actively seek and process information about their team, had a negative influence on perceived usefulness. This is contrary to what TAM-based research typically assumes (Ha et al., 2017). This suggests that highly analytical fans may adopt a more critical stance toward new technologies unless they clearly perceive the innovation as offering meaningful, data-rich benefits. For this segment, MR features like real-time player analytics, 360-degree game footage, and interactive stat overlays could be highlighted in promotional messaging to convey utility. For example, marketing campaigns could demonstrate how fans can use the Apple Vision Pro to access real-time player statistics while watching a live NBA game, rotate through 360-degree replays of key moments, or interact with advanced metrics like shot charts and player heat maps during a live stream. All of this has the potential to promote the device's functional benefits for engaged viewers.
Moreover, this group may respond more favorably to campaigns that incorporate influencer endorsements from trusted analysts or broadcasters, signaling credibility and sophistication in the technology (Gómez-Ruiz et al., 2022). For example, partnering with respected sport analysts such as Tony Romo in the NFL or Doris Burke in the NBA to showcase how they use MR features for in-depth game analysis could enhance perceived credibility and demonstrate the headset's practical value to engaged fans.
Another important consideration concerns the accessibility and affordability of MR technologies such as the Apple Vision Pro. Although these devices offer transformative potential for sport consumption and fan engagement, their high retail cost presents a significant barrier for many fans. To enhance accessibility, professional sport organizations and technology partners could explore creative pricing and financing models, including subsidized pricing programs, installment-based payment options, or limited-time promotional bundles (e.g., team-branded MR packages or season-ticket holder discounts). Such initiatives would allow lower-income fans to experience the technology without prohibitive upfront costs. Beyond expanding market reach, these approaches align with broader goals of equity and inclusion in sport consumption, ensuring that immersive digital experiences are available to a more diverse fan base.
Finally, the practical utility of MR technologies is dependent not only on consumer readiness but also on organizational digital maturity. As Thompson et al. (2024) note, many sport organizations adopt digital tools as operational enhancements rather than transformative fan engagement strategies. For MR to succeed at scale, sport organizations must embed these tools within a broader, strategic vision that includes training front-line staff, integrating MR into mobile ticketing and loyalty platforms, and developing partnerships with technology firms to create tailored content. Without this ecosystem-level readiness, even the most promising fan-facing technologies may fail to gain traction.
Limitations and Future Research
There are several limitations in this study. First, most of the sample may not accurately reflect the broader demographic of Apple Vision Pro users as 60.40% reported identifying as White and 61.40% identified as a man/transman. To enhance the generalizability of the findings, we recommend future studies to include a more representative sample. Additionally, this study suggests that integrating team identification into TAM offers a more comprehensive understanding of what drives purchase intention of the Apple Vision Pro than either model alone. Although the combined model is effective in predicting purchase intentions in this context, more research is necessary to explore how other factors influence consumers’ purchase intentions of the Apple Vision Pro. For instance, future studies could incorporate personality traits such as the big five, supernumerary personality inventory, and the dark triad into the model to deepen the understanding of user behavior. Future research could also include factors such as technological anxiety, social influence, perceived risk, and resistance to technology to get a better understanding of user behavior.
Beyond sample characteristics and model variables, another important limitation relates to the broader framing and multifunctionality of the technology under investigation. Although this study focused specifically on the Apple Vision Pro's application in sport media consumption, it is important to recognize that the device is a multifunctional platform with capabilities that extend beyond sport. Participants’ evaluations may have been shaped, in part, by their awareness of the Vision Pro's broader use cases (e.g., education, productivity, entertainment), which were not directly measured in this study. As such, interpretations of perceived usefulness or purchase intention may reflect a more generalized view of the product rather than being limited strictly to sport-related functions. Future research could explore how cross-domain utility influences consumer adoption by comparing sport-specific evaluations with more holistic assessments of multifunctional technologies.
Moreover, the financial profile of the sample is another limitation of this study. That is, participants’ actual income levels likely influenced how realistically they could consider purchasing the Apple Vision Pro, which carries a retail price of roughly US$3,500. Around 40% of respondents reported after-tax incomes below $70,000, which may have constrained their purchasing power, even if they showed strong interest or positive evaluations of the device. As a consequence, some participants may have responded based on aspirational preferences rather than realistic intentions. Future studies should investigate the role of income as a moderating factor in sport technology adoption and consider how perceptions of cost, affordability, and financing availability shape adoption behavior across diverse income brackets.
Moreover, some hypothesized relationships would benefit from further investigation. While previous studies have showed perceived ease of use and perceived usefulness as the strongest predictors of consumers’ intentions to adopt a technology, including more mediators and moderators in the model can help us understand why consumers decide to adopt the Vision Pro and other MR headsets. Additionally, while the theory underpinning the model is robust and supports causality, the hypotheses in this study were tested using cross-sectional data. We suggest researchers employ a longitudinal design that could build stronger evidence of causality, especially because a longitudinal design is suitable as innovations often spread gradually through populations (Rogers et al., 2014).
Future research should also consider cross-cultural replications of this study to explore whether the relationships identified in the current model hold across different sport contexts and fan cultures. For example, examining European soccer fans, who often exhibit deeply rooted and enduring forms of team identification, could provide valuable insight into how cultural, social, and market differences shape the relationship between fan identity and technology adoption. Such cross-national comparisons would help determine whether the multidimensional effects of team identification observed in this study are universal or context-specific, thereby enhancing the generalizability and global applicability of the extended TAM framework in sport settings.
Finally, although this study provides valuable insights into sport fans’ acceptance of MR technology, it is important to recognize that the findings are based on perceptions and intentions rather than actual behavioral data. While this approach aligns with TAM, which posits that perceptions of usefulness and ease of use are critical antecedents to adoption (Davis, 1989; Venkatesh & Davis, 2000), future studies should move beyond perception-based assessments. Specifically, researchers should design experimental studies that allow participants to physically interact with MR headsets in sport viewing contexts. Doing so would enhance ecological validity and enable the examination of postadoption variables such as satisfaction, continued use, and experiential value. Such extensions would also strengthen theoretical contributions by testing whether the relationships identified here hold when fans engage directly with immersive technologies in real-world or laboratory environments. In this sense, the current findings should be interpreted as promising initial evidence that lays the conceptual foundation for future research examining the intersection of team identification, user experience, and technology adoption in sport.
Conclusion
This study provides a novel and contextually relevant extension of TAM by integrating six dimensions of team identification to explain sport fans’ adoption of the Apple Vision Pro, a cutting-edge MR headset. By incorporating fan identity into TAM, this study offers a more comprehensive model that reflects the unique psychological, social, and behavioral dynamics of sport fans. It also shows the importance of considering affective and identity-based factors alongside functional attributes when evaluating the adoption of sport-related technologies. The findings contribute to theory by highlighting the relevance of team identification in innovation adoption and provide actionable guidance for sport organizations and marketers aiming to enhance fan engagement through emerging technologies like the Apple Vision Pro.
Footnotes
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.