Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7, 383-393 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 5 May 2025; Revised: 10 June 2025; Accepted: 13 June 2025; Published: 4 July 2025 * Correspondence: agam.hatta@binus.ac.id The influence of TikTok daily reward gamification and social presence on impulsive buying behavior: The mediating role of emotional arousal on social commerce platforms Agam Rahman Hatta1*, Aby Miesvontoko1, Desman Hidayat2 1Management Department, BINUS Business School Undergraduate Program, Bina Nusantara University Jakarta, Indonesia 11480; agam.hatta@binus.ac.id (A.R.H.) aby.miesvontoko@binus.ac.id (A.M.) 2BINUS Entrepreneurship Center, Management Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta, Indonesia 11480; d4906@binus.ac.id (D.H.). Abstract: This study explores the influence of TikTok’s Daily Reward gamification, user experience, and social presence on impulsive buying behavior within social commerce, with emotional arousal as a mediating variable. The research addresses the growing prevalence of impulsive consumer behavior driven by interactive and emotionally engaging platform features such as gamification and live streaming. Using a quantitative approach, data were collected from 127 TikTok Shop users through an online survey and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that both Daily Reward gamification and social presence significantly affect emotional arousal, which in turn moderately influences impulsive buying behavior. However, emotional arousal was only found to significantly mediate the relationship between gamification and impulsive buying behavior, while its mediating role between social presence and impulsive buying was not statistically supported. These findings underscore the importance of emotionally engaging platform features in stimulating unplanned consumer purchases and provide strategic insights for businesses aiming to enhance user interaction and conversion rates on social commerce platforms. Keywords: Emotional arousal, Gamification, Impulsive buying, Social commerce, Social presence, TikTok shop. 1. Introduction The digital era has brought about a significant transformation in the landscape of commerce, with social commerce emerging as a phenomenon that fundamentally changes modern consumer shopping behavior. The integration between social media platforms and e-commerce has created a more interactive and engaging commercial ecosystem, in which TikTok has emerged as a dominant player in this revolution [1]. According to recent data, TikTok surpassed 1.5 billion active global users in 2023, with transactions on TikTok Shop growing by 600% year-over-year in the first quarter of 2023 [2]. This phenomenon marks a new era in digital commerce, presenting both challenges and opportunities for businesses and researchers to understand the dynamics of consumer behavior on social commerce platforms. In an effort to increase engagement and drive transactions, TikTok has implemented various gamification elements, with the daily reward system being one of the most prominent features. This system is designed to create a habit loop and enhance user retention by providing daily incentives to users [3]. The implementation of gamification in the context of social commerce not only serves as a tool to boost engagement but also plays a role in shaping emotional arousal that can influence consumers’ purchasing decisions. Recent studies show that gamification elements can increase users’ dopamine levels, creating a sense of excitement and urgency that has the potential to trigger impulsive buying behavior [4]. mailto:agam.hatta@binus.ac.id 384 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate Social presence is another important dimension that influences user behavior on social commerce platforms like TikTok Shop. Social presence refers to the extent to which users feel the social presence of others when interacting on a digital platform. This social presence can be manifested through features such as user reviews, live streaming, or real-time comments, which allow users to experience interpersonal connections even in a virtual environment. Studies show that social presence plays a significant role in building consumer trust and increasing purchase intentions by mediating trust and positive attitudes toward the platform [5, 6]. In the context of TikTok Shop, these features not only create a more personalized shopping experience but also strengthen the users' emotional engagement with the platform, thereby encouraging impulsive buying behavior [7]. Although some previous studies have explored the impact of gamification on consumer behavior in the context of conventional e-commerce, there is still a significant gap in understanding the interaction between the daily reward system, social presence, and emotional arousal in the specific context of social commerce like TikTok Shop. For example, [8] highlight that while gamification can enhance consumer-brand engagement, the moderating effects of environmental gamification in social media marketing remain underexplored, especially regarding impulse buying in social commerce contexts. Additionally, research by Khoi, et al. [9] demonstrates that emotional arousal plays a mediating role in the relationship between social presence and impulsive buying behavior during live- streaming social commerce, supporting the need for further investigation into these dynamics in platforms such as TikTok Shop. Furthermore, Xiang, et al. [10] emphasize the influence of social relationship factors, such as parasocial interaction, on impulse buying in social commerce. This study aims to comprehensively analyze how the daily reward gamification and social presence influence impulsive buying behavior through the mediation of emotional arousal. A deeper understanding of this relationship will not only contribute theoretically to the development of digital consumer behavior models but also provide practical insights for the development of more effective social commerce strategies. 2. Literature Review 2.1. Gamification in Social Commerce Gamification has become a strategic instrument in the evolution of social commerce, defined as the use of game design elements in a non-game context to enhance user engagement and motivation. In the context of TikTok Shop, the daily reward system serves as a concrete manifestation of gamification implementation, aiming to create a behavioral loop and increase user retention Huseynov [11]. This system adopts the principles of operant conditioning, where users are given positive reinforcement through rewards that can be redeemed for discounts or shopping vouchers. Recent studies show that the implementation of the daily reward system can increase the frequency of visits by up to 45% and purchase intention by 32% on social commerce platforms [12]. Furthermore, gamification elements like daily rewards not only enhance user engagement but also influence impulsive buying behavior through the mediation of emotional responses, with perceived enjoyment and social interaction as key factors that strengthen this relationship [13]. H1: TikTok's daily reward gamification has a positive effect on users' emotional arousal. 2.2. Social Presence in Social Commerce Social presence refers to the user's perception that they are interacting with real people on a digital platform, not just with systems or algorithms. In the context of social commerce, social presence can be enhanced through features such as comment sections, live streaming, user reviews, and direct interactions with sellers or influencers. This social presence creates a sense of community and trust, which in turn strengthens the emotional connection between users and the platform [14]. Research shows that high social presence can increase perceived trust and engagement, thereby influencing impulsive buying decisions [15]. In addition, social presence can also trigger more intense emotional 385 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate responses, such as a sense of urgency or social involvement, which ultimately encourages consumers to make impulsive purchases without deep rational consideration [16]. H2: Social presence has a positive effect on users' emotional arousal. 2.3. Emotional Arousal in the Digital Context Emotional arousal is a psychological condition characterized by increased emotional activation and physiological readiness. In the context of digital commerce, emotional arousal can be triggered by various stimuli such as visual merchandising, time-limited offers, and social proof [9, 17]. Neuropsychological research shows that high levels of arousal can affect decision-making processes by increasing impulsivity and reducing critical thinking [9]. Recent studies indicate that emotional arousal triggered by elements of social commerce platforms can increase the likelihood of impulsive buying behavior. In fact, in the context of platforms like TikTok, gamification design (such as daily rewards) and dynamic social interactions can strengthen emotional arousal, creating a cycle of emotional stimulation that shortens the cognitive evaluation process and encourages spontaneous buying actions [18]. H3: Emotional arousal has a positive effect on impulsive buying behavior. H4: Emotional arousal mediates the effect of daily reward gamification on impulsive buying behavior. H5: Emotional arousal mediates the effect of social presence on impulsive buying behavior. H6: TikTok's daily reward gamification influences impulsive buying behavior through the mediating role of emotional arousal. H7: Social presence influences impulsive buying behavior through the mediating role of emotional arousal. 2.4. Impulsive Buying Behavior in Social Commerce Impulsive buying behavior is defined as an unplanned, spontaneous purchase driven by external stimuli and strong emotional responses. In the context of social commerce, this phenomenon is reinforced by a combination of social influence, personalized content, and psychological triggers [19]. Platforms like TikTok Shop optimize these elements to create an environment conducive to impulsive buying. Research shows that purchases on social commerce platforms tend to be more impulsive compared to planned purchases [20]. "Furthermore, the immersive interface design on platforms like TikTok Shop—with a combination of autoplay videos, personalized recommendation algorithms, and integrated 'Shop Now' features—creates a 'flow state' experience that reduces users' ability to control shopping impulses, thereby reinforcing the tendency for impulsive buying behavior [21]. Figure 1. Research Model. 386 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate 3. Research Methodology 3.1. Research Design and Approaches This study focuses on analyzing and proving how Gamification Feature, Social Presence, and User Experience has a positive relationship to Emotional Arousal and could positively affecting impulsive buying behavior. The study uses a non-probability sampling method, specifically employing purposive sampling with judgmental sampling, where potential respondents are filtered based on pre-established criteria and characteristics. An online survey questionnaire will be distributed to respondents through Google Forms. All respondent data will be processed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS Version 4 software. 3.2. Research Instrument The variables in this study are based on several instruments designed as the foundation for the questions in the questionnaire. These instruments are derived from previous relevant studies and have been selected based on their relevance to this research. The measurements for Gamification of Daily Reward adapted from Meng and Leung [22]. Social Presence from Wang, et al. [23]. Emotional Arousal from Qu, et al. [17]; Zhang, et al. [18]; Wang, et al. [23] and Gu, et al. [24] and Impulsive Buying Behavior from Pranata, et al. [25] and Nilam and Amelindha [26]. The study will use a five- point Likert scale in the questionnaire, allowing respondents to select a scale from 1 to 5 to indicate how they relate to the items in each instrument. Table 1. Research Instrument. Construct Item Gamification of Daily Reward GR1 I feel motivated to use the TikTok app because of the daily reward feature. GR2 I want to use the TikTok app more frequently to receive bonuses from the daily reward. GR3 The rewards I receive on TikTok are an important factor in my decision to purchase an item. GR4 I feel happy when redeeming the rewards I earn. GR5 I feel challenged to keep collecting daily rewards on TikTok. Social Presence SP1 I feel like there's direct interaction with others when watching live streaming on TikTok. SP2 I am aware of other users who are interested in the products during live streaming. SP3 I feel that live streaming on TikTok provides a real social interaction experience. SP4 I feel comfortable communicating with the streamer during live streaming. SP5 I feel more connected with others when watching live streaming on TikTok. Emotional Arousal EA1 I feel excited to collect more rewards on TikTok so they can be used in transactions. EA2 I feel stimulated to make a purchase when I see attractive promotions on TikTok, especially after receiving daily rewards. EA3 I feel excitement when having an enjoyable shopping experience on TikTok Shop. EA4 I feel emotionally driven when receiving daily rewards from TikTok. EA5 I feel urged to use the rewards or discounts I receive before they expire. EA6 I feel more enthusiastic to buy products when I see many people interacting in the live streaming. Impulsive Buying IB1 When shopping on TikTok Shop, I tend to buy items that I had not planned to purchase. IB2 If I see something new and trending on TikTok Shop, I want to buy it. IB3 When I find something very interesting on TikTok Shop, I buy it without considering the consequences. IB4 Sometimes when shopping on TikTok Shop, I buy an item not out of necessity, but for enjoyment. IB5 I feel that making spontaneous purchases on TikTok Shop is an enjoyable experience. 4. Results and Discussion A total of 127 respondents were able and agreed to fill out the online survey questionnaire, selected based on standardized criteria and characteristics. These respondents were grouped according to gender, age, length of employment, and job level. The responses were 51% male and 49% female, with the majority in the age range of 21-30 years. Most of the respondents were undergraduate students, 387 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate with an average work experience of less than 10 years and an average salary of less than IDR 5 million, working in the Jakarta area. The job levels were as follows: 38% staff officer, 15% supervisor, 10% senior manager to general manager, 13% associate manager to manager, 7% associate director to director, and 13% director. Table 2. Convergent Validity. EA GDR PPI SP EA 1 0.844 EA 2 0.864 EA 3 0.631 EA 4 0.864 EA 5 0.855 EA 6 0.687 GDR 1 0.887 GDR 2 0.838 GDR 3 0.856 GDR 4 0.848 GDR 5 0.827 IBB 1 0.764 IBB 2 0.835 IBB 3 0.827 IBB 4 0.837 IBB 5 0.789 SP 1 0.703 SP 2 0.665 SP 3 0.733 SP 4 0.790 SP 5 0.813 The Structural Equation Modeling (SEM) model used several methods to assess the convergent validity of the indicators used in measuring the constructs. One of these methods is Outer Loading, which is a regression coefficient showing the relationship between an indicator and the latent construct in the SEM model. High outer loading, typically greater than 0.70, indicates a strong relationship. Indicators with outer loading values lower than 0.70 may need to be reconsidered for improvement or removal [27]. From the table, it can be concluded that all indicators have high outer loading (> 0.7), which means they have a strong relationship with the measured construct. Table 3. Discriminant Validity. EA GDR PPI SP EA 0.796 GDR 0.894 0.852 IBB 0.663 0.645 0.811 SP 0.592 0.544 0.595 0.743 Based on Fornell and Larcker [28] each construct must have an AVE > the square of the correlation with other constructs. Therefore, it can be concluded that all indicators are valid in terms of discriminant validity, where the AVE value for each model is greater than the square of the correlation with other constructs, specifically 0.796 > (0.663, 0.592)², 0.852 > (0.645, 0.544) ², 0.811 > 0.595², and 0.743. 388 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate Table 4. Construct Reliability. Cronbach's alpha Composite reliability (rho_a) Composite reliability (rho_c) Average variance extracted (AVE) SP 0.799 0.826 0.859 0.551 IBB 0.870 0.879 0.906 0.657 EA 0.881 0.895 0.911 0.634 GDR 0.905 0.906 0.930 0.725 In Savitri, et al. [29] the reliability assessment of the outer model in Partial Least Squares Structural Equation Modeling (PLS-SEM) can be done using two main indicators: Cronbach's Alpha and Composite Reliability. A Cronbach's Alpha value greater than 0.70 is considered good, while values below 0.60 indicate low internal consistency. A good Composite Reliability value is usually above 0.70. A higher CR value than 0.70 suggests that the construct has good reliability and the items used in the measurement mutually support the construct. Based on the table above, the values for both Cronbach’s Alpha and Composite Reliability (rho_c) exceed the standard, which means the variables have good reliability and mutually support each other. Table 5. R-Square. R-square R-square adjusted EA 0.815 0.811 IBB 0.514 0.501 The R-Square value in the inner model indicates the proportion of variance explained by independent constructs regarding the dependent constructs in the model [29]. R-square values are interpreted as follows: 0.19 (weak), 0.33 (moderate), and 0.67 (strong) [29]. Figure 2. R-Square Output: This figure shows the explained variance in Emotional Arousal and Impulsive Buying Behavior from the independent variables. From the R-Square table, Emotional Arousal has an R-square value of 0.815, meaning that 81% of the variance in emotional arousal is explained by the GDR and SP variable. Impulsive Buying Behavior has an R-square value of 0.514, meaning that 51% of the variance in work engagement is explained by 389 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate GDR and SP. The remaining 49% is explained by factors outside this study, indicating that GDR and SP has a moderate influence on Impulsive Buying Behavior. Table 6. Effect Size (f-square). EA GDR IBB SP EA 0.028 GDR 2.502 0.023 IBB SP 0.087 0.125 The effect size (f-square) in the inner model aims to measure the magnitude of the impact that the independent variable has on the dependent variable [29]. Effect size is an important measure to assess the strength of the relationship between variables in the model, which in turn helps evaluate how much an independent variable affects the change in the dependent variable [29]. The interpretation guidelines for f² are as follows: 0.02 is considered a small effect, 0.15 is considered a moderate effect, and 0.35 is considered a large effect [29]. Based on the effect size table, the following interpretations can be made: • Emotional Arousal has a small effect on Impulsive Buying Behavior with an f-square value of 0.028. • Gamification of Daily Reward has a large effect on Emotional Arousal with an f-square value of 2.502. • Gamification of Daily Reward has a small effect on Impulsive Buying Behavior with an f- square value of 0.023. • Social Presence has a small to moderate effect on both, Emotional Arousal and Impulsive Buying Behavior with 0.087 and 0.125 respectively. Table 7. Path Coefficients. Original sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values Results GDR → EA 0.812 0.811 0.042 19.349 0.000 H1 Accepted SP → EA 0.151 0.150 0.057 2.626 0.009 H2 Accepted EA → IBB 0.271 0.276 0.159 1.706 0.088 H3 Accepted GDR → IBB 0.236 0.225 0.156 1.507 0.132 H4 Rejected SP → IBB 0.307 0.314 0.075 4.094 0.000 H5 Accepted Path coefficients measure the extent to which the independent variable can directly affect the dependent variable. The larger the path coefficient value, the stronger the influence of the independent variable on the dependent variable [29]. Path coefficients are divided into direct influence and indirect influence. . The significance of the path coefficient is interpreted if the p-value is smaller than 0.1 or the t-statistic value is greater than 1.645 with a significance level of 10%, indicating that the relationship between the variables is significant [29]. In this research, the p-value was used to assess the significance. The hypothesis results for the independent, dependent, and mediator variables are summarized in the table, as follows: • Gamification Daily Reward has a significant influence on Emotional Arousal (H1) with a p-value of 0.000 < 0.1, so H1 is Accepted. The original sample of H1 is 81.2% variance, meaning this influence is strong, with 18.8% of the variance explained by other factors. • Social Presence has a significant influence on Emotional Arousal (H2) with a p-value of 0.009 < 0.1, so H3 is Accepted. The original sample of H3 is 15.1% variance, meaning this influence is moderate, with 84,9% of the variance explained by other factors. 390 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate • Emotional Arousal has a significant influence on Impulsive Buying Behavior (H3) with a p- value of 0.088 < 0.1, so H3 is Accepted. The original sample of H3 is 27.1% variance, meaning this influence is moderate to strong, with 72,9% of the variance explained by other factors. • Gamification Daily Reward does not have a significant influence on Impulsive Buying Behavior (H4) with a pvalue of 0.132 > 0.1, so H4 is Rejected. The original sample of H4 is 23,6% variance, meaning this influence is moderate to strong, with 76,4% of the variance explained by other factors. • Social Presence has a significant influence on Impulsive Buying Behavior (H5) with a p-value of 0.000 < 0.1, so H5 is Accepted. The original sample of H5 is 30,7% variance, meaning this influence is moderate to strong, with 69,3% of the variance explained by other factors. Table 8. Path Coefficient. Original sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values Results GDR → EA → IBB 0.220 0.225 0.131 1.676 0.094 H6 Accepted SP → EA → IBB 0.041 0.042 0.031 1.320 0.187 H7 Rejected Path coefficients are used to measure the extent to which the independent variable indirectly affects the dependent variable through a mediating variable. According to Savitri, et al. [29] the significance of the path coefficient can be assessed using either the p-value (should be < 0.1) or the t-statistic (should be > 1.645) at a 10% significance level. If these criteria are met, the mediating effect is considered statistically significant. If not, the mediation is deemed insignificant, indicating that the mediating variable does not play a significant role in the relationship. In this study, Emotional Arousal (EA) was examined as a mediating variable between two independent variables—Gamification of Daily Reward (GDR) and Social Presence (SP)—and the dependent variable Impulsive Buying Behavior (IBB). The results are summarized as follows: ● GDR → EA → IBB, The original sample value for this path is 0.220, with a sample mean of 0.225 and a standard deviation of 0.131. The t-statistic is 1.676, and the p-value is 0.094. Since the p- value is less than 0.1 and the t-statistic is greater than 1.645, the mediating effect of Emotional Arousal between Gamification of Daily Reward and Impulsive Buying Behavior is statistically significant (H6). Meaning this influence is moderate to strong, the result does support the hypothesis that Emotional arousal significantly mediates this relationship . ● SP → EA → IBB, The original sample value for this path is 0.041, with a sample mean of 0.042 and a standard deviation of 0.031. The t-statistic is 1.320, and the p-value is 0.187. Since the p- value is greater than 0.1 and the t-statistic is less than 1.645, the mediating effect of Emotional Arousal between Social Presence and Impulsive Buying Behavior is not statistically significant (H7) . meaning this influence is weak, the result does not support the hypothesis that Emotional Arousal significantly mediates this relationship. In conclusion, based on the results of the mediation analysis, Emotional Arousal is not confirmed as a significant mediating variable in the relationship between Gamification of Daily Reward or Social Presence and Impulsive Buying Behavior. These findings suggest that while Emotional Arousal may be conceptually relevant, its mediating effect is not statistically supported in this study. 391 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate Table 9. (GOF). AVE R-square GDR 0.725 SP 0.551 EA 0.634 0.811 IBB 0.657 0.501 Average 0.64175 0.656 Note: GOF= 0.64884. Goodness of Fit (GoF) measures the extent to which the model can represent the relationships between the constructs in both the outer model (measurement) and inner model (structural) [30]. The formula is: GoF= √(AVE x R2). The GoF value can be categorized as follows: GoF ≥ 0.36: Model has a very good fit (large fit). 0.25 ≤ GoF < 0.36: Model has a moderate fit. GoF < 0.25: Model has a poor fit. Based on the table above, the GoF value is 0.424, which is greater than 0.36, indicating that the model has a large fit. Therefore, it can be concluded that the SEM model tested through both the outer and inner models is able to represent the relationships between the constructs well. 5. Conclusion This study aimed to analyze the influence of TikTok's Daily Reward Gamification, User Experience, and Social Presence on Impulsive Buying Behavior, with Emotional Arousal serving as a mediating variable. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results confirm several significant findings while also highlighting notable limitations. Firstly, the findings indicate that Gamification of Daily Reward (GDR) significantly influences Emotional Arousal, and Social Presence (SP) also has a significant but weaker direct effect on Emotional Arousal. Emotional Arousal, in turn, exhibits a weak to moderate but statistically significant direct influence on Impulsive Buying Behavior (IBB). Moreover, the mediating role of Emotional Arousal in the relationships between both GDR → IBB and SP → IBB was found to be statistically insignificant, as reflected by p-values above 0.1 and t- statistics below the threshold of 1.645. This indicates that Emotional Arousal, while influential in direct pathways, does not act as a significant mediator between these constructs in this model. The results point toward a more complex behavioral mechanism in which emotional arousal operates independently rather than as a bridge between marketing stimuli and consumer behavior. From a practical standpoint, these findings hold valuable implications for both the educational and professional/entrepreneurial sectors: • Educational Sector: This research provides a comprehensive example of applying digital consumer behavior theory using Structural Equation Modeling. It can be used as a teaching case for marketing, behavioral economics, or digital business courses to understand how psychological and technological constructs interact in a real-world social commerce setting. Students can learn how gamification, emotional triggers, and user interaction metrics are modeled and measured in practice. • Professional Sector / Entrepreneurs: For entrepreneurs and business practitioners, especially those operating in e-commerce or social commerce, this study highlights the strategic importance of gamification and social interaction features. TikTok’s Daily Reward system demonstrates strong potential to stimulate emotional engagement, which in turn can drive impulsive purchases. However, emotional pathways do not always mediate other marketing efforts, which suggests that designing user experiences should go beyond aesthetics and usability to integrate emotionally engaging content. Entrepreneurs are advised to consider interactive elements like live streaming, reward loops, and community engagement as mechanisms to enhance emotional arousal and consumer impulsivity. 392 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 383-393, 2025 DOI: 10.55214/25768484.v9i7.8587 © 2025 by the authors; licensee Learning Gate In conclusion, while not all hypotheses were supported, the study contributes to the growing understanding of how emotional mechanisms function in gamified social commerce platforms. Future research should consider exploring different mediators or moderating factors such as personality traits, time sensitivity, or peer influence to better map the dynamics of impulsive behavior in digital consumer contexts. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] Z. R. F. Nur, I. N. N. Rabbiana, T. Diba, and F. Fitroh, "TikTok shop: Unveiling the evolution from social media to social commerce and its computational impact on digital marketing," Journal of Computer Science and Engineering, vol. 4, no. 2, pp. 88-96, 2023. [2] N. M. Ariffin, A. Fikry, N. D. M. Shobri, and I. S. C. 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