The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences

Available online at www.rajournals.in International Journal of Management and Economics Invention ISSN: 2395-7220 DOI: 10.47191/ijmei/v11i11.02 Volume: 11 Issue: 11 November 2025 International Open Access Impact Factor: 8.518 (SJIF) Page no. 4796-4804 4796 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences Nhu Anh Le1, Dinh An Vu2, Thi Nhi Phan3, Thi Phuong Oanh Nguyen4, Huyen Trang Phan5 1,2,5 Department of Business Administration, College of Economics - Vinh University 3,4Department of Accounting, College of Economics - Vinh University ARTICLE INFO ABSTRACT Published Online: 10 November 2025 Corresponding Author: Huyen Trang Phan Gamification has rapidly become a core strategy in marketing, but what happens when it fails is still not well understood. This study addresses this gap by examining how a Failed Gamification Experience (FGE), defined as a violation of consumers’ hedonic expectations, influences Brand Boycott Intentions (BBI). Drawing on Expectancy Violation Theory (EVT), data were collected from 457 Vietnamese consumers who had engaged with gamified marketing activities. Using hierarchical multiple regression, the study found that even after accounting for gender differences, FGE remained a positive and highly significant predictor of BBI, explaining an additional 13.1% of the variance in boycott intention. The results suggest that flawed gamification is not simply a technical or aesthetic failure but a significant trigger for punitive consumer behavior. Conceptually, this research introduces and validates FGE as a new construct, extending service-failure theory into the context of interactive digital marketing. Practically, it highlights that brands must approach gamification with rigorous design, fairness, and recovery mechanisms to avoid serious reputational consequences. KEYWORDS: Gamification, Service Failure, Brand Boycott, Expectancy Violation Theory, Digital Marketing, Gender. 1. INTRODUCTION The growing prominence of the experience economy has fundamentally changed how consumers relate to brands. Generation Z consumers no longer settle for products that simply work; they look for experiences that are enjoyable, emotionally engaging, and participatory (Lemon & Verhoef, 2016; Hollebeek et al., 2021). In this context, gamification, defined as the use of game-design principles in non-game settings, has moved beyond a marketing experiment to become a central strategic approach (Deterding et al., 2011; Seaborn & Fels, 2015). In emerging digital economies such as Vietnam, this shift is especially visible. Businesses are no longer competing only to attract new customers but also to retain and engage existing ones. Gamification provides an effective means to do so, combining entertainment with measurable engagement outcomes (Google, Temasek, & Bain & Company, 2022). Evidence of this trend can be seen across sectors—from e-commerce platforms offering daily reward challenges to financial apps encouraging saving habits through interactive progress systems. These gamified experiences are reshaping how Vietnamese consumers interact with brands, especially among younger users who tend to associate “fun” with authenticity and product quality (Koivisto & Hamari, 2019; Halim & Purwanegara, 2024). Yet, implementing gamification is rarely a neutral act. Once introduced, it implicitly sets expectations that the experience will be enjoyable, fair, and rewarding. In reality, this means users are not only participants but also evaluators, continually assessing whether the system delivers on its promises. This dynamic creates what may be described as a “highengagement, high-risk” paradox. Gamification builds emotional and behavioral commitment, but that same engagement can amplify vulnerability when something goes wrong. In this study, 66.7% of respondents reported interacting with gamified features weekly or daily—suggesting that brands have largely succeeded in cultivating committed users. However, higher involvement also elevates expectations. According to Expectancy Violation Theory (EVT), when expectations are violated by a valued source, the resulting negative reactions can be especially strong. Consequently, when a gamified system fails—through technical glitches, unbalanced rewards, or unclear rules—users may not perceive it as a minor inconvenience but rather as a broken “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4797 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 promise. What begins as a design flaw may gradually evolve into a sense of betrayal, prompting emotional withdrawal or even retaliatory behaviors toward the brand. While the benefits of gamification have been widely celebrated, its potential downsides remain far less understood. In recent years, a growing body of research has started to draw attention to what scholars now describe as the “dark side” of gamification (Bhutani & Behl, 2023). When poorly designed, gamified systems may do more harm than good—fueling anxiety, frustration, or even a sense of being manipulated. In some cases, users may disengage altogether (Bhutani & Behl, 2023; Shu et al., 2025). In this light, a Failed Gamification Experience (FGE) should not be seen merely as a technical glitch. Rather, it represents a deeper breakdown—a violation of users’ hedonic expectations. It occurs when the enjoyment, fairness, or sense of reward that users anticipate from gamified interactions fails to materialize. Despite a growing recognition of such negative experiences, most discussions to date have remained largely conceptual. Very few studies have sought to measure FGE in a systematic way or to test whether it might lead to serious consumer responses, such as brand boycotts. This absence of empirical evidence highlights an important gap in the current literature. This study aims to address that gap by asking a central question: Does a Failed Gamification Experience (FGE) significantly increase Brand Boycott Intentions (BBI), even after accounting for gender differences? To explore this question, the research sets out three specific objectives: • To conceptualize and validate FGE as a form of hedonic expectancy violation. • To examine how FGE influences BBI through the theoretical lens of Expectancy Violation Theory (EVT). • To test this relationship while controlling for gender, which is known to moderate consumer complaint and response behavior. The study contributes to the literature in three interrelated ways. Theoretically, it extends Expectancy Violation Theory (EVT) to a new context—hedonic digital-service failure— thereby bridging research on gamification and service recovery. Methodologically, it introduces and validates a Failed Gamification Experience (FGE) scale, offering a concrete means of quantifying a specific form of digitalexperience failure that has previously been described only in conceptual terms. Practically, the study provides empirical evidence that failed gamified experiences can directly provoke punitive consumer responses, including brand boycotts. Taken together, these contributions shift the discussion from the conventional question of how gamification enhances engagement to the more critical issue of what happens when gamification fails. In a digital economy where engagement and vulnerability increasingly go hand in hand, this reframing appears both timely and necessary. 2. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 2.1. Theoretical Foundation: Expectancy Violation Theory (EVT) The theoretical foundation of this study is Expectancy Violation Theory (EVT). Originally developed by Burgoon (1978) to explain people’s reactions to personal space violations in interpersonal communication, EVT suggests that individuals form expectations about others’ behavior in social interactions. When actual behavior deviates from those expectations, it triggers both physiological arousal and cognitive appraisal processes. This violation captures attention and prompts the individual to evaluate two key aspects—the nature of the violation (positive or negative) and the reward valence of the violator. The outcomes of these evaluations, in turn, shape subsequent communicative and behavioral responses (Burgoon & Hale, 1988). Negative violations committed by low-reward sources tend to produce the most unfavorable reactions. Although EVT was initially grounded in nonverbal communication, it has since been widely applied in marketing and consumer research to explain reactions to unexpected events, particularly service failures (Saeed et al., 2024). A service failure can be seen as a negative violation of customer expectations about service performance (Koc, 2019). Scholars have applied Expectancy Violation Theory (EVT) to understand how consumers react when brands fail to meet their expectations across different contexts. These include corporate ethical lapses, digital service disruptions such as data breaches, and other unexpected breakdowns in online interactions. Research has shown that when consumers experience such violations, they reassess the brand’s reliability and moral standing, which can lead to emotional and behavioral consequences such as distrust, anger, and punitive intentions. For instance, Saeed et al. (2024) demonstrated that expectation violations in digital brand interactions significantly heighten negative consumer evaluations and increase the likelihood of retaliatory responses. In digital environments, where nonverbal cues are absent and communication occurs through technological systems, expectations regarding reliability, responsiveness, and fairness may play an even more critical role in shaping user reactions (Ashraf & Bardhan, 2024). 2.2. From Functional to Hedonic Violations in Digital Services The unique contribution of this study lies in extending EVT to a relatively unexplored context: hedonic digital-service failure. Previous research has largely focused on utilitarian or security-related violations, such as delayed deliveries, website malfunctions, or breaches of personal data (Goode et al., 2015). Gamified services, however, operate on a different “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4798 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 premise. They promise not only functional efficiency but also an enjoyable, fair, and rewarding experience (Koivisto & Hamari, 2019). A Failed Gamification Experience (FGE), therefore, represents a dual violation. It encompasses both a functional failure, such as a glitch, lag, or unresponsive interface, and a hedonic failure in which users feel unfairly treated or disappointed by unrewarding gameplay mechanics. This combination of unmet expectations may amplify emotional and cognitive responses, producing stronger negative reactions than functional failures alone (Nazifi et al., 2021; Husairi et al., 2021). Because gamification inherently appeals to emotion, an FGE may be perceived less as a technical shortcoming and more as a breach of psychological trust—a subtle form of deception that can evoke a sense of betrayal.. 2.3. Consequences of Violated Expectations: Brand Boycott Intentions When expectations are seriously and negatively violated, EVT predicts that individuals will reappraise the violator and may engage in compensatory or punitive actions. In the consumer domain, these reactions can range from spreading negative word-of-mouth to switching brands—and, in more severe cases, initiating or joining brand boycotts (Liu et al., 2021). A boycott represents one of the strongest forms of consumer retaliation, reflecting a deliberate choice not only to avoid the brand but also to persuade others to do the same (Sameeni et al., 2024).Applying EVT to this context suggests a logical sequence of effects: a Failed Gamification Experience (FGE) constitutes a negative expectancy violation, which triggers adverse cognitions and emotions such as disappointment, anger, or a sense of betrayal. These negative appraisals then shape unfavorable brand evaluations and strengthen consumers’ motivations to punish the brand— manifesting ultimately as Brand Boycott Intentions (BBI).. Based on the synthesis of EVT and the nature of FGE as a dual violation of consumer expectations, the main research hypothesis is developed as follows: Hypothesis 1: A failed gamification experience (FGE) has a positive and statistically significant impact on brand boycott intentions (BBI). 2.4. The Role of Gender as a Control Variable Gender is not merely a demographic descriptor but also a theoretically meaningful control variable. Prior research consistently highlights gender-based differences in consumer decision-making and behavioral responses, particularly in the context of service failures (Koc, 2019). For instance, men have been found to display more assertive complaint behavior, whereas women may exhibit stronger emotional reactions or employ different coping strategies (Snipes et al., 2006). In gaming environments, these distinctions appear even more pronounced. Men, who often adopt a more competitive or goal-oriented approach, may experience greater frustration when their objectives are blocked by technical issues or perceived unfairness, leading to more intense punitive responses (Veltri et al., 2014). Preliminary analysis of this study’s dataset also indicates a statistically significant difference in boycott intentions between male and female participants. Without controlling for this effect, the estimated relationship between Failed Gamification Experience (FGE) and Brand Boycott Intentions (BBI) could be distorted by omitted-variable bias. Including gender as a control variable in the regression model therefore ensures that the observed influence of FGE on BBI reflects its unique contribution rather than gender-based variance. In doing so, the study provides a more rigorous and reliable test of Hypothesis H1, addressing the question: Does a failed gamification experience increase boycott intentions beyond the baseline differences between men and women? 3. RESEARCH METHODOLOGY 3.1. Research Design and Data Collection This study employs a quantitative, cross-sectional research design. Data were collected through an online survey disseminated across major social media platforms in Vietnam. The target population comprised Vietnamese consumers aged 18 and above who had previously engaged in gamified marketing activities. Following a thorough datacleaning process to eliminate incomplete or inconsistent responses, a total of 457 valid questionnaires were retained for analysis. This sample size exceeds the recommended threshold for regression-based studies, providing sufficient statistical power to support reliable interpretation of the findings (Hair et al., 2019). 3.2. Measurement and Data Analysis All constructs were measured using multi-item scales on a seven-point Likert scale (1 = “Strongly disagree” to 7 = “Strongly agree”). The Failed Gamification Experience (FGE) construct was measured using a five-item authordeveloped scale, while Brand Boycott Intention (BBI) was adapted from established measures in prior studies. Gender was included as a binary control variable (0 = Female, 1 = Male). Data were analyzed using SPSS version 29.0. Reliability and validity of the measures were confirmed before hypothesis testing. Hierarchical multiple regression analysis was then conducted to examine the effect of FGE on BBI while controlling for gender. Hierarchical Multiple Regression was used to test the proposed relationships: Step 1 (Model 1): The control variable (Gender) was entered first to establish a baseline model predicting BBI. Step 2 (Model 2): The independent variable (FGE) was added to the model. The significance of FGE’s regression coefficient and the change in the coefficient of determination (∆R²) between the two models were examined to assess the incremental explanatory power of FGE beyond gender effects. “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4799 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 4. RESULTS 4.1. Sample Profile Table 1 summarizes the demographic characteristics and interaction patterns of the 457 valid respondents. The sample composition reflects a relatively young and digitally active population, consistent with the focus of this study on Generation Z consumers. Females accounted for 58.6% of participants, while males represented 41.4%, indicating a moderate gender imbalance but still sufficient diversity for analysis. In terms of age, the 19–22 group dominated the sample (73.1%), followed by smaller proportions of respondents aged 23–25 and above 25. This distribution aligns closely with the age range most engaged in gamified marketing and mobile-based brand interactions in Vietnam. Regarding experience and engagement, the data reveal a notably high level of exposure to gamification. Approximately 66.8% of participants reported interacting with gamified content weekly (46.2%) or daily (20.6%). Such frequency suggests that gamification has become an integral part of their digital consumption habits rather than an occasional experience. This also supports the assumption that Gen Z consumers are not only familiar with gamified systems but actively integrate them into their everyday online behaviors. These descriptive findings provide a strong foundation for subsequent hypothesis testing. Table 1: Demographic Profile of Survey Respondents (N=457) Characteristic Category Frequency (n) Percentage (%) Gender Male 189 41.4 Female 268 58.6 Age Group 19 - 22 334 73.1 23 - 25 82 17.9 26 - 28 41 9 Interaction Frequency Daily 94 20.6 Several times a week 211 46.2 Several times a month 56 12.3 Rarely 96 21.0 Source: the authors 4.2. Measurement Model Assessment The reliability and validity of the measurement instruments were rigorously examined to ensure the robustness of subsequent analyses. Both constructs demonstrated excellent internal consistency, with Cronbach’s Alpha values of 0.887 for Failed Gamification Experience (FGE) and 0.861 for Brand Boycott Intention (BBI)—well above the conventional benchmark of 0.70, indicating strong reliability. An Exploratory Factor Analysis (EFA) was then conducted to assess the underlying structure of the data. The KaiserMeyer-Olkin (KMO) measure of sampling adequacy was 0.887, and Bartlett’s Test of Sphericity was highly significant (p < 0.001), confirming that the dataset was suitable for factor analysis. The EFA extracted two distinct factors, jointly explaining 69.7% of the total variance, thereby supporting both convergent and discriminant validity of the measurement model. Overall, these results confirm that the measurement scales used in this study are both statistically reliable and theoretically sound, providing a solid foundation for hypothesis testing in the next stage of analysis. “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4800 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 Table 2: Measurement Scale Assessment Results Construct No. of Items Cronbach's Alpha KMO Bartlett's Test (Sig.) Total Variance Explained (%) Failed Gamification Experience (FGE) 5 0.887 0.887 < 0.001 69.7 Brand Boycott Intention (BBI) 4 0.861 Source: the authors 4.3. Preliminary Analysis: Gender Differences in Boycott Intention An Independent Samples t-test was conducted to examine potential gender-based differences in Brand Boycott Intention (BBI). As shown in Table 3, the results reveal a statistically significant difference between male and female respondents. Males reported a higher mean score (M = 5.68, SD = 0.99) compared to females (M = 5.34, SD = 1.13). Since Levene’s Test for equality of variances was significant (p = 0.027), the results for “Equal variances not assumed” were applied. Under this condition, the difference remained highly significant (t(434.44) = 3.467, p = 0.001). This finding provides empirical justification for including gender as a control variable in the subsequent regression analysis. It confirms that gender differences meaningfully influence boycott intentions, and controlling for this variable helps isolate the unique effect of Failed Gamification Experience (FGE) on Brand Boycott Intention (BBI). Table 3: Independent Samples T-test for Brand Boycott Intention by Gender Gender N Mean Std. Deviation t df Sig. (2tailed) Male 189 5.68 0.988 3.467 434.438 0.001 Female 268 5.34 1.130 Source: the authors 4.4. Hypothesis Testing A hierarchical multiple regression analysis was conducted to test Hypothesis H1, which proposed that a Failed Gamification Experience (FGE) would positively influence Brand Boycott Intention (BBI), even after controlling for gender. The results are summarized in Table 4. In Model 1, only the control variable—Gender—was entered into the regression equation. The model was statistically significant (F(1, 455) = 11.48, p = 0.001) and accounted for 2.5% of the variance in BBI (Adjusted R² = 0.023). Gender emerged as a significant predictor (β = 0.157, p = 0.001), confirming that male respondents reported higher levels of boycott intention than females. In Model 2, the independent variable FGE was added. The model remained highly significant (F(2, 454) = 42.68, p < 0.001) and demonstrated a substantial improvement in explanatory power, with an R² change (∆R²) of 0.131 (p < 0.001). The final model explained 15.8% of the total variance in BBI (Adjusted R² = 0.154). Crucially, after controlling for gender, FGE remained a positive and highly significant predictor of BBI (β = 0.395, p < 0.001). This indicates that consumers who experienced failed gamification interactions were significantly more likely to express boycott intentions toward the associated brand. Therefore, Hypothesis H1 is strongly supported. Table 4: Hierarchical Multiple Regression Results Predicting Brand Boycott Intention Model 1 Model 2 Predictor β β (Constant) Gender (1=Male) 0.157*** 0.102* “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4801 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 FGE 0.395*** Model Summary R2 0.025 0.158 Adjusted R2 0.023 0.154 ∆R2 0.025 0.131 F 11.48*** 42.68*** ∆F 11.48*** 84.03*** Note: * p < 0.05, ** p < 0.01, *** p < 0.001. Dependent Variable: BBI. Source: the authors 5. DISCUSSION AND MANAGERIAL IMPLICATIONS 5.1. Summary of Findings This study produced two key findings. First, male participants, on average, demonstrated stronger brand boycott intentions than female participants following a Failed Gamification Experience (FGE). This gender-based difference aligns with prior evidence suggesting that men tend to display more assertive or punitive responses to perceived service failures. Second, and more importantly, even after controlling for gender, a poor-quality gamification experience remained a powerful and statistically significant predictor of consumers’ boycott intentions. The inclusion of FGE in the regression model explained an additional 13.1% of the variance in boycott intention, underscoring its substantial explanatory contribution. This result holds both theoretical and managerial importance. It empirically substantiates the idea that a failed gamified experience is not just a trivial user inconvenience but a meaningful predictor of punitive consumer behavior. In other words, it converts the often abstract notion of “poor user experience” into a quantifiable risk factor—demonstrating that a considerable share of potential consumer backlash can be directly attributed to the perceived fairness, enjoyment, and quality of gamified features. 5.2. Theoretical Implications: Extending Expectancy Violation Theory The results of this study reinforce and extend Expectancy Violation Theory (EVT) in two important ways. First, the findings provide strong empirical support for the idea that the violation of hedonic expectations, such as enjoyment, fairness, and reward, can provoke negative consequences just as severe as violations of utilitarian expectations related to functionality or efficiency. This challenges the conventional assumption that entertainment features are peripheral to brand performance. Instead, the evidence suggests that these hedonic dimensions now form an essential part of the brand promise in interactive and gamified environments. Second, the strength of the Failed Gamification Experience (FGE) effect may lie in its dual nature. An FGE represents both a performance-based failure (e.g., technical glitches or system lag) and a value-based failure (e.g., unfair rules or unbalanced rewards), thereby violating users’ expectations of fairness and transparency (Baghi & Gabrielli, 2021). Prior research indicates that violations of moral or ethical expectations tend to elicit far harsher reactions than purely technical or performance-related failures (Pullig et al., 2006). Therefore, an FGE may evoke a combination of emotional responses: functional frustration and moral outrage. This dual violation helps explain why FGE has such a strong influence on brand boycott intentions, extending EVT beyond its traditional utilitarian focus into a hedonic and moral context relevant to digital interaction environments. 5.3. The "Love-Becomes-Hate" Effect in the Interaction Economy For the highly engaged users in this study, 66.8 percent of whom reported interacting with gamified features weekly or daily, a failed gamification experience is likely interpreted not simply as a disappointment but as a betrayal. This dynamic aligns with what has been described as the “love becomes hate” effect, a psychological phenomenon where consumers who feel deeply attached to a brand exhibit strong negative emotions when their expectations are violated (Tolunay & Veloutsou, 2025). Previous studies have shown that customers with stronger relationships tend to hold higher expectations. When those expectations are broken, they experience the violation as more personal and emotionally intense, which can lead to a greater desire for revenge or punishment (Grégoire et al., 2009). The results of this study provide empirical support for this idea: the most engaged users, who interact frequently and invest emotionally in gamified brand experiences, are also the most likely to retaliate when those experiences fail. In the context of the interaction economy, where engagement is both the measure “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4802 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 and the currency of brand success, this finding highlights a critical paradox. The very consumers that brands aim hardest to engage, the loyal and emotionally invested users, also represent the greatest reputational risk when the promised experience fails to meet expectations. 5.4. Interpreting Gender Differences The finding that men display higher boycott intentions than women is an interesting secondary result that deserves further discussion. This pattern can be understood from several complementary perspectives. As noted earlier, research in consumer psychology and human-computer interaction suggests that men tend to be more competitive and goal oriented in gaming environments (Veltri et al., 2014). Consequently, a failure that prevents them from achieving a goal may evoke stronger feelings of frustration and anger. Social and cultural norms may also influence how dissatisfaction is expressed. Men may be more inclined to adopt direct and assertive punitive responses, such as brand boycotts, while women may express dissatisfaction through indirect or relational channels (Koc, 2019). Although additional research is needed to confirm these mechanisms, the current finding underscores the importance of considering demographic and psychological diversity when designing and managing digital customer experiences. 5.5 Managerial Implications The findings of this study have several important implications for managers. Gamification should be treated as a high-risk investment rather than a superficial marketing tactic. The quality of gamified features forms an integral part of the customer experience, and a poor implementation can significantly increase brand risk. The fact that Failed Gamification Experience (FGE) explains a substantial portion of boycott intention transforms what might seem like a minor design flaw into a quantifiable measure of consumer punishment risk. Equally important is the emphasis on user experience and quality assurance. Investing in careful testing and design is not only about preventing technical failures but also about ensuring that game rules and reward structures are perceived as fair and transparent. Addressing both functional and valuebased aspects of gamification can prevent feelings of manipulation or injustice and help preserve consumer trust. When failures do occur, organizations should implement well-defined recovery strategies. A timely and transparent response accompanied by meaningful compensation, such as bonus points or virtual rewards, can help reduce negative emotions and repair the sense of violated expectation (Liu et al., 2021). Such actions demonstrate accountability and can turn a potentially damaging situation into an opportunity to strengthen brand credibility. Finally, the gender difference observed in this study suggests that communication and recovery strategies may need to be customized for different user groups. Men, for example, may respond more positively to direct acknowledgment and corrective action, whereas women might appreciate empathetic communication and reassurance. Recognizing and adapting to these differences can improve the effectiveness of service recovery and contribute to stronger, more resilient customer relationships. 6. CONCLUSION, LIMITATIONS AND FUTURE RESEARCH 6.1. Conclusion This study has successfully conceptualized, operationalized, and provided initial validation for the Failed Gamification Experience (FGE) as a new academic construct. By doing so, it has identified and quantified a significant risk associated with gamification, shifting the scholarly discussion from the question of “does it work?” to the more pressing issue of “what happens when it fails?” The findings empirically link Expectancy Violation Theory (EVT) with punitive consumer behaviors in digital marketing contexts. This connection extends EVT’s application to hedonic service failures and opens a new line of inquiry into negative consumer–brand dynamics in digital environments. The study thus contributes both theoretical depth and practical insight to the growing literature on consumer experience and brand engagement in the interaction economy. 6.2. Limitations Despite these contributions, the study has several limitations that should be acknowledged. First, its cross-sectional research design limits the ability to make definitive causal inferences about the observed relationships. Second, the reliance on self-reported data may introduce a degree of bias, as stated intentions do not always translate into actual behavior. Third, the convenience sampling approach, which focused on young and digitally experienced consumers in Vietnam, may restrict the generalizability of the findings to other markets or demographic segments. These limitations do not diminish the value of the findings but rather outline boundaries within which they should be interpreted. 6.3. Future Research Directions The limitations identified above point to several promising directions for future research. One avenue involves investigating potential mediating mechanisms. Future studies could empirically test the proposed causal chain linking Failed Gamification Experience to Perceived Betrayal, Brand Hate, and ultimately Brand Boycott Intention (Rasouli et al., 2025). Such research would deepen understanding of the emotional and psychological pathways through which negative gamification experiences influence consumer punishment behaviors. A second direction involves examining potential moderating factors. Future work may explore what conditions intensify or weaken the effect of FGE on boycott intentions. Variables such as the severity of the failure, the strength of the pre- “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4803 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 existing brand relationship, and individual personality traits could serve as important moderators (Alnawas et al., 2022). Identifying these factors would allow managers to anticipate and mitigate adverse consumer responses more effectively. Finally, future research should adopt more advanced methodological designs. Experimental approaches that manipulate the intensity or nature of an FGE could provide stronger causal evidence, while longitudinal studies could track changes in consumer attitudes and behaviors over time. These designs would contribute to a more dynamic understanding of how consumers process, recover from, or internalize negative digital experiences Conflict of Interest Statement: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. REFERENCES 1. Alnawas, I., Al Khateeb, A., Abu Farha, A., & Ndubisi, N. O. (2023). The effect of service failure severity on brand forgiveness: the moderating role of interpersonal attachment styles and thinking styles. International Journal of Contemporary Hospitality Management, 35(5), 1691-1712. https://doi.org/10.1108/IJCHM-03-2022-0290 2. Ashraf, A. R., & Bardhan, I. R. (2024). Navigating the digital frontier: The role of trust in consumer adoption of AI-powered financial services. Journal of Business Research, 173, 114441. https://doi.org/10.1016/j.jbusres.2023.114441 3. Bhutani, C., & Behl, A. (2023). The dark side of gamification in interactive marketing. In The Palgrave Handbook of Interactive Marketing (pp. 939-962). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-14961-0_40 4. Burgoon, J. K. (1978). A communication model of personal space violations: Explication and an initial test. Human Communication Research, 4(2), 129– 142. https://doi.org/10.1111/j.14682958.1978.tb00603.x 5. Burgoon, J. K., & Hale, J. L. (1988). Nonverbal expectancy violations: Model elaboration and application to immediacy behaviors. Communications Monographs, 55(1), 58–79. https://doi.org/10.1080/03637758809376158 6. Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: Defining "gamification". Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, 9–15. https://doi.org/10.1145/2181037.2181040 7. Goode, S., Lin, C., Tsai, J. C., & Jiang, J. J. (2015). Rethinking the role of security in client satisfaction with Software-as-a-Service (SaaS) providers. Decision Support Systems, 70, 73-85. https://doi.org/10.1016/j.dss.2014.12.005 8. Google, Temasek, & Bain & Company. (2022). eConomy SEA 2022: Through the waves, towards a sea of opportunity. https://www.bain.com/insights/economy-sea-2022/ 9. Grégoire, Y., Tripp, T. M., & Legoux, R. (2009). When customer love turns into lasting hate: The effects of relationship strength and time on customer revenge and avoidance. Journal of Marketing, 73(6), 18–32. https://doi.org/10.1509/jmkg.73.6.18 10. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage. 11. Halim, W. O., & Purwanegara, M. S. (2024). The Effect of Gamification toward Customer Engagement in Shopee E-Commerce. International Journal of Current Science Research and Review, 42(1), 1208-2024 12. Hollebeek, L. D., Kumar, V., & Srivastava, R. K. (2021). From customer-, to user-, to human-centric engagement: A research agenda. Journal of Service Research, 25(1), 165-171. https://doi.org/10.1177/1094670520977680 13. Husairi, M. A., Morgan, R. E., & De Luca, L. M. (2021). Market entry timing: The impact of complementary capabilities on strategic outcomes. Journal of Business Research, 132, 45-55. https://doi.org/10.1016/j.jbusres.2021.04.004 14. Koc, E. (2019). Service failures and recovery in hospitality and tourism: A review of literature and recommendations for future research. Journal of Hospitality Marketing & Management, 28(5), 513537. https://doi.org/10.1080/19368623.2019.1537139 15. Koivisto, J., & Hamari, J. (2019). The rise of motivational information systems: A review of gamification research. International Journal of Information Management, 45, 191–210. https://doi.org/10.1016/j.ijinfomgt.2018.10.013 16. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69– 96. https://doi.org/10.1509/jm.15.0420 17. Li, Y., Shang, X., & Wang, X. (2024). How corporate hypocrisy affects consumer boycott intention: A perspective of expectancy violation theory. Journal of Retailing and Consumer Services, 77, 103669. https://doi.org/10.1016/j.jretconser.2023.103669 18. Liu, Y., Lee, S. H., & Lee, Y. (2021). The effect of service recovery on brand loyalty in the hotel industry: The mediating role of brand image and the moderating role of attribution. Journal of Hospitality and Tourism Management, 46, 339-347. “The Impact of Failed Gamification Experiences on Brand Boycott Intentions, Controlling for Gender Differences” 4804 Nhu Anh Le1, IJMEI Volume 11 Issue 11 November 2025 https://doi.org/10.1016/j.jhtm.2021.01.009 19. Nazifi, A., Murdy, S., & Marder, B. (2021). A review of the dark side of gamification: A new research agenda. International Journal of Management Reviews, 23(3), 363-383. https://doi.org/10.1111/ijmr.12251 20. Pullig, C., Netemeyer, R. G., & Biswas, A. (2006). Attitude basis, certainty, and challenge alignment: A case of negative brand actions. Journal of the Academy of Marketing Science, 34(4), 528–542. https://doi.org/10.1177/0092070306287128 21. Rasouli, A., Kordnaeij, A., & Askarabad, M. K. (2025). The effect of perceived brand betrayal on brand hate, avoidance-like behaviors, and negative word-of-mouth. Journal of Promotion Management, 31(1), 1-24. https://doi.org/10.1080/10496491.2024.2389921 22. Saeed, N., Akhtar, N., Attri, R., & Yaqub, M. Z. (2024). How violation of consumers’ expectations causes perceived betrayal and related behaviors: Theoretical perspectives from expectancy violation theory. Journal of Retailing and Consumer Services, 81, 103961. https://doi.org/10.1016/j.jretconser.2024.103961 23. Sameeni, M. S., Qadeer, F., Ahmad, W., & Filieri, R. (2024). An empirical examination of brand hate influence on negative consumer behaviors through NeWOM intensity: Does consumer personality matter? Journal of Business Research, 173, 114469. https://doi.org/10.1016/j.jbusres.2023.114469 24. Seaborn, K., & Fels, D. I. (2015). Gamification in theory and action: A survey. International Journal of Human-Computer Studies, 74, 14–31. https://doi.org/10.1016/j.ijhcs.2014.09.006 25. Shu, L., Wu, Y., Wang, K., & Li, S. (2025). Consumer response to failure by service robots: the role of anticipatory guilt. Journal of Services Marketing. https://doi.org/10.1108/JSM-05-20240237 26. Snipes, R. L., Thomson, N. F., & Oswald, S. L. (2006). Gender bias in customer evaluations of service quality: an empirical investigation. Journal of Services Marketing, 20(4), 274-284. https://doi.org/10.1108/08876040610674616 27. Tolunay, A., & Veloutsou, C. (2025). Don’t make me hate you, my love! Perceived brand betrayal and the love-becomes-hate phenomenon. Journal of Business Research, 187, 115060. https://doi.org/10.1016/j.jbusres.2024.115060 28. Veltri, N. F., Krasnova, H., & Elgar, K. (2014). The role of gender and age in multichannel behaviour. Proceedings of the 22nd European Conference on Information Systems.