Mobile advergaming has emerged as a powerful tool in digital marketing, offering brands a unique way to connect with consumers through immersive, game-based experiences. As mobile devices become increasingly integral to daily life, advergames provide interactive, on-the-go engagement that surpasses the limitations of traditional media (Mittal & Kumar 2020; Mittal, Kumar & Seppi 2022). These games encourage repeated use, creating multiple touchpoints for brand exposure while maintaining user interest through entertaining gameplay mechanics. Unlike static advertisements, advergames integrate brand content directly into the gaming experience, fostering deeper engagement and brand familiarity. This form of gamified advertising uses game elements, such as rewards, challenges and progress tracking, to make interactions more enjoyable and emotionally resonant (Van Berlo & Chen 2024; Van Berlo, Van Reijmersdal & Eisend 2021). Advergames positively influence consumer perceptions and attitudes by increasing the hedonic value of brand messages (Singh & Milan 2025; Van Berlo et al. 2021).

The effectiveness of advergames is reflected in market trends: global mobile in-app advertising spend is projected to grow from $1bn to $1.5bn per day by 2029, with mobile gaming leading this growth (Statista Market Insights 2024). Recent studies affirm that advergaming enhances consumer engagement across cognitive, emotional, and behavioural domains, with satisfaction acting as a key mediator (Van Berlo & Chen 2024). Furthermore, advergames strengthen brand recall, attitude and purchase intention, especially when brand identity aligns with game content (Adis 2020). Elements such as music can further enrich the user experience and increase brand resonance, particularly among younger audiences (Farzinnejad et al. 2024).

Advergames offer a powerful marketing tool by merging gameplay with brand messaging, capitalising on players’ immersive flow experiences to enhance consumer engagement. The intense and voluntary involvement in gaming can positively shape brand perceptions and influence purchasing behaviour (Ghosh et al. 2021; Hsiao et al. 2022). The notion of ‘flow experience’, a state of deep concentration and enjoyment, emerges as a central mechanism linking gameplay to positive brand outcomes (Csikszentmihalyi 1975; Hooker et al. 2019).

Numerous studies highlight how flow experience enhances brand attitudes and purchase intentions in advergaming environments (Anandya, Prabowo & Darsono 2023; Catalán et al. 2019). Flow experience is often induced by gameplay factors, such as interactivity, challenge and immersion (Catalán et al. 2019). Positive emotions triggered by enjoyment fuel deeper flow states, which are, in turn, associated with stronger engagement and brand affinity (Biró & Kato 2024; Wang, Wang & Zuo 2023). Brand interactivity and familiar gameplay further increase user satisfaction and brand awareness (Farzinnejad & Baghaei 2022; Khezrian, Farzinnejad & Baghaei 2022). However, findings on the mediating role of flow experience are mixed. Some studies indicate that flow experience indirectly enhances satisfaction and continuance intention through enjoyment (Masao & Salehudin 2023), while others question flow experience’s direct impact on satisfaction (Catalán et al. 2019).

In emerging markets, such as India, Brazil, China and South Africa, advergames are increasingly used to build brand familiarity and drive behavioural responses (Komulainen, Lappeman & Islam 2019; Wanick et al. 2019). These culturally relevant games leverage the intrinsic motivation of users to share, invite others and interact with branded content, further amplifying engagement (Heidari 2024). Catalán et al. (2019) explore how brand familiarity enhances flow experience in mobile advergames, boosting their effectiveness. These authors found that familiarity and game repetition positively affect brand attitude and purchase intentions, though they did not examine the link between flow experience and satisfaction, focusing instead on brand-related outcomes. Similarly, Hsiao et al. (2022) showed that brand familiarity strengthens the connection between advergame attitudes and brand attitudes, with game beliefs driving purchase intentions. However, both studies overlooked the role of flow experience in shaping user satisfaction. Catalán et al. (2019) focused primarily on how brand familiarity and repeated gameplay influenced brand attitudes and purchase intentions, but did not assess satisfaction as an outcome of flow experience. Likewise, Hsiao et al. (2022) examined the moderating role of brand familiarity on the relationship between advergame and brand attitudes, omitting satisfaction from their framework. While both confirm the importance of flow experience and brand familiarity in building brand perceptions, neither empirically tested whether immersive gameplay translates into satisfaction. This leaves a conceptual gap concerning the emotional outcomes of flow experiences, which this study seeks to address by positioning satisfaction as a key mediating mechanism in advergaming.

From a flow experience theory perspective, immersive experiences can trigger positive affective and cognitive responses towards associated stimuli, in this case, the embedded brand. The more immersive the gameplay, the more favourable the user’s perception of the brand becomes, as flow experience fosters openness and receptivity (Biró & Kato 2024). Thus, flow experience is expected to shape brand attitude directly. The literature supports that advergames enhance brand engagement through flow experience. While the exact mechanisms may differ across studies, converging motivational states, immersive gameplay and brand interactivity remain critical to favourable brand outcomes. Flow experience theory also posits that the flow state itself is intrinsically rewarding and pleasurable (Csikszentmihalyi 1975). Applied to advergaming, this suggests that users who experience flow during gameplay derive greater satisfaction from the interaction, independent of their brand-related perceptions. This forms the basis for a direct relationship between flow experience and satisfaction. Finally, brand familiarity is introduced as a boundary condition that may influence how flow experience affects satisfaction. Prior literature suggests that familiarity strengthens or weakens the impact of experiential stimuli, depending on the context (Catalán et al. 2019). Testing this moderation contributes to boundary-setting in flow experience theory by examining whether the effect of flow experience is uniform across consumer segments with varying brand knowledge. Consequently, the study hypothesises that:

Satisfaction plays an important role in advergaming, functioning as a mediating factor between immersive gameplay and consumer responses such as engagement, loyalty and behavioural intentions (Van Berlo & Chen 2024). Their quantitative study confirms that experiential satisfaction links advergame interaction to cognitive, emotional and behavioural engagement, positioning satisfaction as both a key outcome and a psychological mechanism within the consumer journey. A key driver of satisfaction is immersion, a state in which players become deeply engaged with the game environment, enhancing enjoyment and sustained playtime (Demidiuk & Plechawska 2022). Recent studies in gamification contexts further support the view that immersion precedes satisfaction. For instance, Li and Aumeboonsuke (2025) found that immersion, achievement and social interaction significantly enhance the overall consumer experience, which in turn strengthens brand engagement and loyalty in co-branded gamification campaigns. Similarly, in the domain of augmented reality gaming, immersive experiences have been shown to significantly predict satisfaction and continued engagement intentions (Utomo & Oktavia 2024). Research shows that experiential satisfaction plays a central mediating role in gamified advertising. Van Berlo and Chen (2024) found that advergaming enhances cognitive, emotional and behavioural responses, with satisfaction linking these effects to brand engagement. Similarly, Arifah, Suryani and Samopa (2022) highlight that integrating marketing messages within engaging advergames fosters emotional connection and brand recall in e-commerce settings. Beyond advertising, gamification in contexts like savings promotion also shows strong links to satisfaction. Kusumo et al. (2024) found that rewards and challenges increase user satisfaction, driving positive behavioural outcomes among millennials. User satisfaction reflects how well a product meets user expectations, influencing continued use and brand loyalty (Lukita et al. 2023). Using the KANO model², Zhang and Tang (2023) further demonstrate that different gamification elements have varying effects on satisfaction, with some generating excitement and others fulfilling basic expectations.

In summary, satisfaction is both an outcome and a mechanism in advergaming, connecting gameplay experiences with meaningful consumer responses across different domains. While existing studies have investigated gamification and advergaming’s impact on consumer engagement and brand recall (Arifah et al. 2022; Van Berlo & Chen 2024), the psychological mechanisms driving satisfaction in advergame experiences remain underexamined. Research highlights immersion, cognitive involvement and gamified features as key influencers of user behaviour (Demidiuk & Plechawska 2022; Kusumo et al. 2024), yet few studies integrate flow experience, brand familiarity, brand satisfaction and brand attitude into a cohesive model, especially for mobile advergames. Catalán et al. (2019) demonstrate that brand familiarity enhances flow experience, boosting brand attitude and purchase intentions, but they do not connect flow experience to satisfaction. Similarly, Hsiao et al. (2022) show that brand familiarity strengthens the advergame attitudes’ effect on brand perceptions, yet these authors also overlook the link between satisfaction and flow experience. Although satisfaction is recognised as a vital outcome (Zhang & Tang 2023), its mediating role, alongside the sequential or parallel mediation of flow experience and brand attitude between gameplay and satisfaction, remains largely unexplored. Building on cognitive appraisal models, a favourable brand attitude is theorised to enhance overall evaluation of the brand-related experience. When gameplay evokes a positive brand impression, this cognitive evaluation may transfer to emotional satisfaction with the advergame, reinforcing post-consumption responses. While flow experience is inherently enjoyable, its effect on satisfaction may also operate indirectly by enhancing brand attitude. This aligns with flow experience theory’s assertion that immersive experiences can alter attitudes, which subsequently shape outcome evaluations. This hypothesis clarifies the mechanism through which flow experience impacts satisfaction by testing brand attitude as a mediator, thereby contributing to theory development. It is thus proposed that:

This study addresses these gaps by testing a structural model within M&M’s Adventure mobile game context, examining how flow experience shapes brand attitude and satisfaction, and assessing flow experience and brand attitude as mediators among young South African consumers. In summary, the proposed model leverages flow experience theory to explain how psychological immersion during gameplay translates into favourable brand and experience outcomes. By testing mediation and moderation mechanisms, the study not only applies but also extends and qualifies flow experience theory within a mobile advergame setting in an emerging market.

The proposed hypotheses are collectively illustrated in the conceptual model presented in Figure 1.

This study employed a quantitative research design and utilised PLS-SEM to examine consumer satisfaction and engagement in advergaming. The branded game, M&M’s Adventure, served as the focal advergame. Before completing the questionnaire, respondents were required to download and play the advergame on their mobile devices (iOS or Android), enabling a more immersive and reflective engagement with the brand-embedded experience.

Data were collected through an online questionnaire administered after gameplay. The questionnaire comprised four main sections: (1) screening and consent, (2) technology and gaming background, (3) demographic profile and (4) psychometric measures of the focal constructs. Measurement items were adapted from validated scales in the literature to ensure construct reliability and contextual relevance (see Table 1). These included items for flow experience (Catalán et al. 2019; Novak, Hoffman & Yung 2000), satisfaction (Park & Lee 2011), brand attitude (Catalán et al. 2019; Wise et al. 2008) and brand familiarity (Catalán et al. 2019; Ping, Goh & Teo 2010).

A pilot test involving 30 respondents was conducted to assess the clarity, sequence and relevance of the questionnaire. Feedback from the pilot informed final refinements to ensure a clear and user-friendly instrument. The pilot group reflected similar demographic characteristics to the main sample, increasing contextual relevance.

A total of 311 online questionnaires were received between 25 June and 23 July 2023. Following a data quality review, five responses were removed because of incompleteness or response bias, resulting in a final valid sample of 306 respondents and a response rate of 98.5%. Respondents were recruited using a combination of convenience and snowball sampling (Etikan & Bala 2017). Respondents were South African consumers aged between 18 and 35 years, corresponding to digitally engaged Generation Z and Millennial cohorts – demographics known to be most responsive to mobile advergames.

To participate, respondents had to meet the following inclusion criteria: (1) be at least 18 years old, (2) agree to participate voluntarily, (3) consent to downloading and playing the M&M’s Adventure mobile game (the game was free) and (4) complete the online questionnaire in full. Individuals who did not fulfil these requirements were excluded from the study. Respondents were asked to first play the advergame and then complete the survey, which took approximately 10 min to complete.

A summary of the demographic characteristics of the sample is provided in Table 2. The majority of respondents identified as black (81%), female (50.2%) and aged between 18 and 24 years (51.4%). Online gaming frequency and preferences varied, with a substantial proportion engaging in virtual reality (25.7%) and augmented reality games (19%). Respondents reported various motivations for gaming, including escapism, social connection and fantasy.

Table 1 presents the constructs, sources, item wording and scale anchors. All items were measured using seven-point or five-point Likert-type scales, depending on construct-specific best practices.

Data were analysed using SmartPLS 4 (Ringle, Wende & Becker 2024), a widely recognised tool for estimating both the measurement model and structural paths in PLS-SEM. The model’s adequacy was verified using several criteria. Standardised Root Mean Square Residual (SRMR) was used to assess global model fit (Henseler, Ringle & Sarstedt 2016). Variance Inflation Factors (VIF) were used to detect multicollinearity among indicators (Diamantopoulos & Siguaw 2006). To assess common method bias (CMB), the full collinearity approach was applied, whereby VIF values for each latent construct were examined (Kock 2015). In addition, Harman’s single-factor test was conducted, along with a one-factor model using maximum likelihood (ML) estimation with Promax rotation, to determine whether a single factor accounted for the majority of the variance, and further ensure that CMB is not a significant threat to validity.

To detect non-response bias, early and late respondents were compared following Armstrong and Overton’s (1977) method. The potential for endogeneity was addressed through the Gaussian copula (GC) approach (Hult et al. 2018), which is suited for nonlinear estimation within PLS-SEM.

The moderating effect of brand familiarity on the relationship between flow experience and satisfaction was examined using a two-stage approach in SmartPLS. In the first stage, latent variable scores were extracted based on the measurement model. In the second stage, an interaction term was computed by multiplying standardised scores for flow experience and brand familiarity. This interaction term was added to the structural model to test whether the relationship between flow experience and satisfaction was contingent upon brand familiarity. Significance was assessed via bootstrapping with 5 000 subsamples as recommended by Hair et al. (2019), producing bias-corrected confidence intervals and p-values.

Throughout both the pilot and main data collection phases (June 2023–August 2023), strict ethical protocols were observed. Ethical clearance was granted by the researchers’ higher education institution under approval number 2022SCiiS019. The Faculty Research Ethics Committee reviewed and approved the questionnaire, cover letter and consent documentation to ensure compliance with institutional and national ethical standards. Informed consent was obtained electronically at the start of the online questionnaire. Respondents confirmed that they were 18 years or older and voluntarily agreed to download and play the M&M’s Adventure mobile game before completing the survey. Participation was entirely voluntary, with the right to withdraw at any time without penalty. No personally identifiable information was collected, ensuring anonymity and confidentiality. Respondents were informed about how their data would be accessed, securely stored, and used solely for academic purposes. In line with data protection regulations, they also retained the right to access, amend or object to the processing of their personal information. The study focused exclusively on human participants engaging with a mobile advergame.

The reliability and validity of the constructs, flow experience, brand attitude, satisfaction and brand familiarity were assessed before estimating the structural model. Table 3 presents the indicator loadings, Cronbach’s alpha values, composite reliability (CR) and average variance extracted (AVE) for all constructs. All item loadings ranged from 0.724 satisfaction/satisfaction item 1 (SAT/SAT1) to 0.959 (Flow2), exceeding the recommended threshold of 0.70 (Hair et al. 2019). Internal consistency reliability was confirmed as Cronbach’s alpha, and CR values for each construct exceeded 0.70, ranging between 0.778 and 0.926. Convergent validity was established as all AVE values were above the 0.50 threshold, ranging from 0.697 to 0.860 (see Figure 2).

Discriminant validity was assessed using the Fornell-Larcker criterion and Heterotrait–Monotrait ratio of correlations (HTMT) ratios (Table 4). The square root of each construct’s AVE (brand attitude: 0.882; flow experience: 0.927; satisfaction: 0.835) exceeded its inter-construct correlations (e.g. brand attitude–satisfaction: 0.582), satisfying the Fornell-Larcker criterion. HTMT ratios (e.g. brand attitude–satisfaction: 0.707; flow experience–satisfaction: 0.597) were below the 0.85 threshold, further confirming discriminant validity (Henseler et al. 2016).

Figure 3 and Table 5 present the structural model results. All direct paths were statistically significant and in the expected direction. Flow experience significantly influenced brand attitude (β = 0.423, p < 0.001, f² = 0.218), and both flow experience (β = 0.321, p < 0.001, f² = 0.147) and brand attitude (β = 0.446, p < 0.001, f² = 0.284) significantly influenced Satisfaction. The coefficient of determination (R²) indicated that 17.9% of the variance in brand attitude and 42.4% of the variance in Satisfaction were explained by the model. The R² values of brand attitude and satisfaction align with typical explanatory power in behavioural research, where complex psychological constructs often yield moderate R² values (Hair et al. 2019), as the study focuses on positive engagement drivers (flow experience, brand attitude, satisfaction). Predictive relevance (Q²) was confirmed with Q² values of 0.169 for brand attitude and 0.253 for Satisfaction, exceeding zero.

A mediation analysis was conducted to examine whether brand attitude mediates the relationship between flow experience and Satisfaction. As shown in Table 6, the indirect effect from flow experience to satisfaction through brand attitude was statistically significant (β = 0.189, p < 0.001). This indicates partial mediation, as the direct effect of flow experience on Satisfaction remained significant. Thus, flow experience contributes to Satisfaction both directly and indirectly by enhancing brand attitude.

A moderation analysis was then performed using a two-stage approach to test whether brand familiarity moderates the relationship between flow experience and satisfaction. The interaction term was non-significant (β = 0.040, p = 0.818), indicating that brand familiarity does not significantly alter the strength of the flow experience–satisfaction relationship (see Figure 3). This result suggests that the influence of flow experience on satisfaction remains stable regardless of whether respondents are highly or minimally familiar with the brand.

As illustrated in Figure 4, the slopes for both levels of brand familiarity (mean-centred at 0 and 1) are positive, indicating that higher levels of flow experience are associated with higher levels of satisfaction in both conditions. However, the lines are nearly parallel, and the slope difference is minimal, aligning with the non-significant interaction effect. Specifically, while satisfaction increases with flow experience, this increase occurs at a comparable rate regardless of respondents’ brand familiarity.

The structural model exhibited satisfactory fit. The SRMR for both the saturated and estimated models was 0.075, which is below the recommended cut-off of 0.08, indicating a good model–data fit (Henseler et al. 2016). The 95% and 99% confidence intervals for the SRMR further support the robustness of this fit (see Table 7).

Multicollinearity diagnostics were conducted by examining VIF values for all predictor constructs. As shown in Table 7, all VIF values were comfortably below the commonly accepted threshold of 2.0, suggesting no multicollinearity concerns among the predictors in the model.

To assess CMB, two diagnostic techniques were applied. Firstly, Harman’s single-factor test was conducted. The analysis revealed that the first unrotated factor accounted for 36.47% of the total variance, which is below the conservative threshold of 50%, indicating that CMB is unlikely to substantially distort the data. Secondly, a confirmatory comparison between a constrained one-factor model and the full measurement model was performed using ML estimation with Promax rotation. The one-factor model yielded a poor fit (χ² = 791.93, df = 27, p < 0.001), while the full model demonstrated a significantly better fit (χ² = 288.43, df = 19, p < 0.001). This provides further evidence that the data are not dominated by a single latent factor, thereby supporting the absence of severe CMB (see Table 7).

To examine potential non-response bias, a series of independent-samples median tests and Mann–Whitney U tests were conducted to compare early and late respondents. As reported in Appendix A, the findings indicate no statistically significant differences in satisfaction across response waves, both in terms of median and distribution. Similarly, while the median scores for flow experience did not differ significantly (p = 0.225), the distributional test revealed a statistically significant difference (p = 0.019), suggesting mild variation in how flow experience was experienced between early and late respondents.

Of particular note, brand attitude showed significant differences across both median (p < 0.001) and distribution (p = 0.000) tests, indicating a moderate degree of non-response bias on this construct. However, this bias is unlikely to affect the integrity of the structural model, as brand attitude acts as a mediator rather than an outcome, and all associated path relationships remain statistically significant and theoretically coherent.

To further ensure the validity of the model, endogeneity was tested using the GC method, which is well-suited for detecting endogenous bias in non-linear models estimated using PLS-SEM (Hult et al. 2018). As summarised in Appendix B, all copula-based coefficients across single-path, two-path and full model specifications were statistically non-significant (p > 0.05). These findings confirm that none of the latent path relationships are biased by omitted variable endogeneity, and thus the model’s inferences are statistically robust.

The findings of this study hold several valuable implications for brand managers, digital marketers and game developers aiming to integrate gamification strategies, particularly advergames, into their marketing communication mix. As the evidence from this study demonstrates, immersive gameplay (flow experience) plays a significant role in shaping consumers’ brand attitudes and overall satisfaction with the branded experience. These insights can be translated into actionable strategies to enhance brand-consumer engagement in competitive digital environments.

Firstly, adventure mobile games may limit the generalisability of findings to other advergames with different mechanics, narratives or brand integrations. Secondly, the sample is restricted to South African millennials and Generation Z, potentially overlooking cultural, socio-economic or generational variations that could influence consumer responses to advergaming. In addition, the cross-sectional design captures a snapshot of consumer behaviour, which may not account for long-term engagement or evolving brand perceptions. Lastly, the reliance on self-reported data introduces the possibility of response bias, which could affect the accuracy of the findings.

Future research should address these limitations by exploring a broader range of advergames to assess the consistency of flow experience, brand attitude and satisfaction across diverse gaming contexts. Comparative studies across different cultural or demographic groups could elucidate how contextual factors shape advergaming effectiveness. Longitudinal designs would offer insights into the sustained impact of advergames on brand loyalty and consumer behaviour over time. Furthermore, incorporating objective measures, such as gameplay analytics or physiological data, could mitigate self-report biases and provide a more nuanced understanding of user engagement. These avenues would enhance advergaming research’s theoretical and practical contributions, particularly in emerging markets.