Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7, 1390-1400 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 14 May 2025; Revised: 13 June 2025; Accepted: 17 June 2025; Published: 17 July 2025 * Correspondence: citrakusumadewi@telkomuniversity.ac.id The influence of low self-control, fear of missing out online reviews, hedonic motivations, materialism, and price value on impulsive buying through impulsiveness of social networks and positive attitude toward targeted advertising among young Shopee consumers in Indonesia Cut Tamara Falajunah1, Citra Kusuma Dewi2* 1,2Master of Management Study Program, School of Economics and Business, Telkom University, Bandung, Indonesia; cuttamarafalajunah@student.telkomuniversity.ac.id (C.T.F) citrakusumadewi@telkomuniversity.ac.id (C.K.D). Abstract: This study explores the phenomenon of impulsive buying among Generation Z Shopee users in Indonesia, focusing on the influence of psychological and social factors. A quantitative, causal research design was employed, with data collected from 300 respondents through an online survey. The analysis utilized Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4 to evaluate both the measurement and structural models, ensuring the validity and reliability of the instruments. The findings reveal that low self-control, fear of missing out (FOMO), and materialism significantly influence impulsive buying behavior. Social network impulsiveness and positive attitudes toward targeted advertising served as important mediators. Hedonic motivation, online reviews, and perceived price value also had substantial effects, although FOMO and perceived price value were not directly significant. Digital media plays a crucial role in shaping impulsive buying behavior, with internal psychological factors amplifying these effects through social media platforms and personalized advertisements. This research offers valuable insights for marketers targeting Generation Z consumers, emphasizing the need for responsible advertising that accounts for psychological triggers. It also underscores the importance of digital literacy and emotional regulation in consumer decision-making. Keywords: FOMO, Impulsive buying, Low self-control, Social media, Targeted advertising. 1. Introduction 1.1. Overview of the Research Object 1.1.1. Background As explained by Cindy and Ardini [1] the rapid advancement of digital technology has transformed consumer behavior, with a growing preference for online shopping. This shift accelerated during the COVID-19 pandemic, as consumers adapted to digital platforms due to physical restrictions and the need for convenience [2]. While consumers often compare prices to secure the best deals, price value alone does not significantly influence impulsive buying [3]. In Indonesia, higher-priced items are often associated with better quality, which may shape consumer perceptions differently. Online reviews, especially positive ones, enhance consumer confidence and trust. Although reading reviews can delay purchases [2], Indonesian consumers rely on them to avoid low-quality products, making reviews a key factor in shaping buying decisions [4]. Shopee, one of Indonesia’s leading e-commerce platforms, offers a streamlined shopping experience with features such as seller ratings, discounts, and pre-orders [5]. Its popularity stems from its convenience, allowing users to shop from home, compare products easily, and take advantage of promotional deals. https://orcid.org/0000-0001-5096-1385 1391 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate The rise of e-commerce has amplified impulsive buying is behavior driven by emotions and psychological factors. Limited-time offers, flash sales, and simplified purchasing processes stimulate spontaneous purchases [6]. Feelings of dissatisfaction, anxiety, or FOMO (fear of missing out) may also result from unmet expectations Ramadhian [7]. Nyrhinen, et al. [8] highlights the “impulsiveness of social networks,” describing how peer influence and social norms on social media platforms shape impulsive buying. According to We Are Social (2024), 35.4% of Indonesian users search for products via social media, while 47.9% seek shopping inspiration, indicating social media’s crucial role in purchase decisions. Targeted advertising, particularly on platforms like Shopee, is another strong influence. These ads use user data to present relevant products, increasing the likelihood of purchases. Consumers who perceive such ads as meaningful are more receptive to social media recommendations and more likely to buy impulsively [8]. This effect is particularly strong among Gen Z, who respond positively to non- repetitive and personalized ads [9]. Materialism prioritizing material possessions for happiness is also linked to impulsive buying. Social comparison and imitation further drive this behavior, especially on social media, where curated lifestyles influence consumer choices [3]. Generation Z, the first digital-native generation, is deeply embedded in online culture. Their consumption is shaped by individual values, identity expression, and a desire for instant gratification [4]. Their heavy use of technology and social media, combined with low self-control, increases susceptibility to impulsive buying [8]. Approximately 41% of Gen Z identify as impulsive buyers, a higher rate than Generation X or millennials [9]. FOMO plays a key role in impulsive purchases, often overriding hesitation and encouraging instant action [10, 11]. Excessive social media use contributes to distraction, anxiety, and increased FOMO among Gen Z [4]. Hedonic motivations—seeking pleasure or stress relief further drive impulsive buying. For many, browsing and shopping online is an enjoyable activity or escape, reinforcing emotional decision-making [11]. Based on the above phenomena, this research examines: "The Influence of Low Self-Control, Fear of Missing Out (FOMO), Online Reviews, Hedonic Motivations, Materialism, and Price Value on Impulsive Buying Through Impulsiveness of Social Networks and Positive Attitude Toward Targeted Advertising Among Young Shopee Consumers in Indonesia." 2. Research Methods 2.1. Study Design This study used a quantitative approach to examine a specific population, aiming to test predetermined hypotheses [12]. A literature review was conducted beforehand to explore previous research on the relationships between variables. The research design was causal, intended to identify factors influencing a particular issue [13]. An observational, non-experimental method was used to ensure objective data collection without manipulating variables [14]. The analysis focused on individuals at a single point in time, following a cross-sectional design [15]. Data were collected through structured questionnaires to assess respondents’ knowledge, attitudes, and behaviors [16]. As stated by Sekaran and Bougie [16] the change in independent variables potentially increases or decreases dependent variables. The independent variables assessed in this study included low self- control, positive attitude toward targeted advertising, impulsiveness of social networks, fear of missing out (FOMO), online reviews, hedonic motivations, materialism, and price value. The primary endpoint of interest was impulsive buying. 1392 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate 2.2. Study Subjects The population in this study encompassed consumers who regularly impulsively purchase through an online marketplace, namely Shopee. The study participants were required to be from the Gen Z population and showing impulsive buying behavior. Sampling method utilized in this study was the non-probability technique of purposive sampling, in which the participant was selected from a specific target group with certain knowledge and criteria. Therefore, the inclusion criteria constitute: 1) respondents from the Gen Z population; 2) respondents using e-commerce Shopee; and 3) respondents with impulsive buying experience. Sample size was determined using the formula by Digdowiseiso [17]. With this formula, the adequate sample size was at least 270.60 sample, rounded to 271 samples. 2.3. Data Collection Data collection was performed through online questionnaires by employing Google Form, which were then distributed through various social media platforms, including Facebook, Telegram, WhatsApp, Line, Twitter, and Instagram. The questionnaires were sent with target respondents of Gen Z population who used the e-commerce Shopee. The secondary data for this study was Shopee company profile and impulsive buying trend. Likert scale was incorporated to assess one’s opinion and behavior. This scale evaluates respondents’ attitude in 5 different levels: 1 (strongly disagree); 2 (disagree); 3 (neutral); 4 (agree); and 5 (strongly agree). 2.4. Definition Low self-control refers to an individual's limited capacity to regulate cognitive processes, emotions, and motivational impulses. It is characterized by challenges in exercising self-discipline and a tendency to act impulsively without sufficient deliberation. Social network-induced impulsiveness pertains to the influence exerted by social networks, which can shape subjective norms and ultimately affect young consumers' purchasing decisions. This construct includes factors such as purchasing inspiration, visual product appeal through social media platforms, and peer pressure to conform to online trends. A positive attitude toward targeted advertising involves consumer receptiveness to marketing strategies directed at specific groups based on their interests, behaviors, and demographic characteristics. This dimension encompasses favorable perceptions of advertisements, associations between advertisements and successful purchases, and recognition of products through advertising. FOMO is defined as the anxiety stemming from the possibility of missing out on a superior product or failing to keep up with emerging trends, which influences consumer purchase decisions. It is manifested through impulsive purchasing behavior, urgency due to time-sensitive offers, discomfort from being excluded from online trends, and a sense of social exclusion when not participating in popular consumption behaviors. Online reviews serve as critical sources of information and recommendations that guide consumer evaluations of a product’s desirability. This construct includes actual user reviews, recommendations from online retailers, the perceived importance of seeking online feedback, and the habitual practice of consulting reviews prior to purchase. Hedonic motivation reflects the intrinsic drive to make purchases for the sake of enjoyment or pleasurable experiences. This is assessed based on the extent of satisfaction or pleasure derived during the shopping process. Materialism refers to a value orientation centered around the significance of material possessions. Indicators include the pursuit of social status through luxury goods, the aspiration to impress others via possessions, and a strong interest in acquiring high-end products. Price value denotes the relationship between the monetary cost of a product or service and the perceived benefit derived from it. This includes sensitivity to price fluctuations, the perception of value for money, and a balanced consideration of quality and price. Impulsive buying is defined as an unplanned and spontaneous purchase decision driven by an immediate emotional response. It is evaluated through behaviors such as emotionally driven purchases, sudden urges to buy, gratification from spontaneous shopping experiences, and decisions made without prior contemplation. 1393 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate 2.5. Statistical Analysis This study implemented non-test instrument assessment by collecting data through content validity. Validity ensures that all study indicators encompass all measured aspects [16]. This measurement involved expert judgement with the contribution of the lecturers of master of management specialized in marketing and supervisor. Expert judgement was paramount in evaluating the consistency of indicators. Reliability test was performed using Cronbach's Alpha or composite reliability approach. Statistical analysis consisted of descriptive analysis, partial least squares structural equation modelling (PLS-SEM), measurement model evaluation, and structural model evaluation. Descriptive analysis revealed data distribution characteristics, including mean, standard deviation (SD), variance, maximum and minimum value, and skewness [18]. Percentage measurement was conducted through several steps, as follows: 1) calculation on value from each respondent; 2) calculation of percentage by dividing item’s cumulative value to the frequency; 3) calculation of total value; 4) implementation of scoring scale with 5 grades; and 5) calculation of interval value. The score category was classified to: 20%-36% (very low); 36%-52% (low); 52%-68% (moderate); 68%-84% (high); and 84%- 100% (very high). PLS-SEM aims to optimize variance clarification on endogenous latent variable by estimating partial model series of smallest square regression [15]. PLS-SEM was conducted using SmartPLS software to explore inter-variables correlation. Outer model was evaluated through convergent validity, discriminant validity, and composite reliability. The criteria used to assess structural frame in PLS-SEM included determinant coefficient (R2), predictive relevance (Q2), and effect size (F2). Table 1. Participants Baseline Characteristics. Parameter Frequency (n) Percentage (%) Age 14-18 years 57 19 19-23 years 198 66 24-27 years 45 15 Educational Background Junior High School 12 4 Senior High School 98 32.7 Diploma 5 1.7 Bachelor Degree 183 61 Master Degree 2 0.7 Occupation Student/Scholar 167 55.7 Civil Servant 24 8.0 Private Company Employee 50 16.7 Entrepreneur 56 18.7 Other 3 1.0 3. Research Results 3.1. Baseline Characteristics of Study Participants This study involved 300 Generation Z participants who used Shopee and had experienced impulsive buying. Most participants (66%) were aged 19–23, followed by 19% aged 14–18, and 15% aged 24–27. Regarding education, 61% held a bachelor’s degree, 1.7% a diploma, and 0.7% a master’s degree. Additionally, 32.7% had completed senior high school, and 4% junior high school. In terms of occupation, the majority were students or scholars (55.7%), followed by entrepreneurs (18.7%), private employees (16.7%), civil servants (8%), and others (1%). Participants’ baseline characteristics are presented in Table 1. 1394 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate 3.2. Characteristics Based on Participants Response The findings indicate that 69.3% of participants exhibited low self-control, categorized as high. Specifically, 68% admitted to buying unnecessary products, and 71% often purchased without proper consideration. A total of 68.4% showed a high level of impulsiveness of social networks. About 68% viewed social media as a source of purchase inspiration, 69% were motivated to buy products that appeared interesting on social media, and 68% were influenced by others showcasing appealing products online. Regarding positive attitudes toward targeted advertising, 70.3% of participants scored high. Seventy percent felt the ads were relevant, 71% said the ads increased their desire to buy, and 70% discovered products that matched their needs through such ads. FOMO was also high, with 68% of participants affected. Sixty-eight percent made quick purchases due to limited stock, 71% responded to countdown deals, 67% felt anxious when missing out on trending products (moderate), and 66% felt left out for not following trends (moderate). For online reviews, 70.75% of participants reported high engagement. Sixty-nine percent used reviews to decide on purchases, 70% followed shop recommendations, and 72% considered reviews essential for online shopping decisions. Hedonic motivations were high among 73% of participants, who stated that shopping brought them joy and excitement. Materialism was also high, reported by 70.25% of participants. Seventy-one percent saw collecting luxury items as a major achievement, 69% believed it reflected their life quality, and 72% felt satisfied when their items attracted attention. Regarding price value, 71.3% viewed it as an important factor. Seventy-one percent canceled purchases when prices rose, 71% believed online products were of good quality for their price, and 72% felt online markets offered fair value. Lastly, impulsive buying behavior was high among 71.75% of participants. Seventy-two percent bought products for pleasure, 70% made instant purchases without much thought, and 73% bought spontaneously, reflecting on the decision afterward. Table 2 summarizes the responses for each indicator of impulsive buying. Table 2. Participants Response for Indicators of Impulsive Buying. Parameter Mean Total Score Ideal Score Percentage (%) Category Low Self-Control 1040 1500 69.3 High Impulsiveness 1027.3 1500 68.4 High Positive Attitude Toward Targeted Advertising 1043 1500 70 High FOMO 1018 1500 68 High Online Reviews 1062 1500 70.75 High Hedonic Motivations 1097 1500 73 High Materialism 1054.5 1500 70.25 High Price Value 1069.3 1500 71.3 High Impulsive Buying 1074.5 1500 71.75 High 3.3. Statistical Analysis 3.3.1. Convergent Validity Convergent validity was performed using outer loadings and average variance extracted (AVE). The outer loading for each indicator was >0.7 and the AVE was >0.5. Therefore, every indicator in the variable assessed exhibited loading factor and AVE which fulfilled the standard determined in the relevant theoretical framework. The summary for convergent validity analyzed through SmartPLS was presented in Table 3. 1395 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate Table 3. Convergent Validity Value. Variable Item Loading Factor AVE Low Self Control LSC1 0.924 0.878 LSC2 0.950 Impulsiveness of Social Networks ISN1 0.916 0.828 ISN2 0.903 ISN3 0.911 Positive Attitude Toward Targeted Advertising PATTA1 0.923 0.842 PATTA2 0.905 PATTA3 0.923 FOMO (Fear of Missing Out) FM1 0.817 0.752 FM2 0.815 FM3 0.892 FM4 0.939 Online Reviews OR1 0.890 0.790 OR2 0.914 OR3 0.852 OR4 0.899 Hedonic Motivations HM1 1.000 1.000 Materialism MT1 0.751 0.537 MT2 0.750 MT3 0.722 MT4 0.709 Price Value PR1 0.793 0.747 PR2 0.885 PR3 0.911 Impulsive Buying IB1 0.884 0.729 IB2 0.815 IB3 0.892 IB4 0.939 3.3.2. Discriminant Validity Discriminant validity was assessed by comparing the square root of AVE with the correlation between variables. This comparison was depicted in the Fornell-Larcker criterion. Table 4 demonstrated that every square root of AVE for each variable was greater than the correlation between other variables. This indicated that every variable showed decent discriminant validity. Table 4. Forner-Larcker Criterion Value. FM HM IB ISN LSC MT OR PATTA PR FM 0.867 HM 0.027 1.000 IB 0.068 0.521 0.854 ISN 0.303 0.411 0.422 0.910 LSC 0.383 0.092 0.082 0.327 0.937 MT 0.060 0.279 0.327 -0.021 0.117 0.733 OR 0.304 0.411 0.422 0.736 0.339 -0.019 0.889 PATTA 0.336 0.498 0.390 0.731 0.320 -0.028 0.752 0.917 PR -0.143 0.137 0.144 -0.009 0.036 0.285 -0.029 -0.027 0.864 Discriminant validity might also be evaluated through cross-loading value. As shown below, the square root of AVE for each variable was greater than the correlation between variables, and cross- loading value for each variable was ≥0.7, indicating that every item incorporated in the study fulfilled the validity criteria. Table 5 presents the cross-loading value for each variable. 1396 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate Table 5. Cross-Loading Value. FM HM IB ISN LSC MT OR PATTA PR FM1 0.817 0.026 0.005 0.295 0.405 0.019 0.273 0.294 -0.088 FM2 0.815 0.040 0.038 0.259 0.329 -0.002 0.297 0.297 -0.150 FM3 0.892 -0.013 0.051 0.208 0.346 0.076 0.239 0.251 -0.088 FM4 0.939 0.040 0.081 0.315 0.345 0.069 0.281 0.335 -0.145 HM1 0.027 1.000 0.521 0.411 0.092 0.279 0.411 0.498 0.137 IB1 0.085 0.475 0.884 0.409 0.092 0.285 0.413 0.365 0.136 IB2 0.002 0.423 0.847 0.338 0.048 0.259 0.321 0.292 0.179 IB3 0.050 0.419 0.855 0.317 0.035 0.258 0.312 0.277 0.095 IB4 0.088 0.455 0.828 0.368 0.097 0.310 0.383 0.388 0.083 ISN1 0.273 0.396 0.374 0.916 0.299 -0.027 0.691 0.695 -0.010 ISN2 0.307 0.345 0.411 0.903 0.310 0.015 0.639 0.607 -0.031 ISN3 0.249 0.380 0.368 0.911 0.284 -0.042 0.679 0.690 0.015 LSC1 0.344 0.058 0.037 0.285 0.924 0.094 0.274 0.263 0.017 LSC2 0.373 0.109 0.109 0.325 0.950 0.123 0.354 0.332 0.048 MT1 0.002 0.194 0.207 -0.032 0.079 0.751 -0.044 -0.054 0.230 MT2 0.019 0.150 0.180 -0.024 0.127 0.750 -0.023 -0.043 0.231 MT3 0.041 0.092 0.171 -0.095 0.098 0.722 -0.098 -0.124 0.207 MT4 0.086 0.298 0.326 0.042 0.060 0.709 0.055 0.068 0.181 OR1 0.306 0.381 0.392 0.699 0.316 -0.046 0.890 0.669 -0.025 OR2 0.270 0.402 0.392 0.693 0.313 -0.026 0.914 0.743 -0.014 OR3 0.233 0.323 0.356 0.567 0.243 0.031 0.852 0.614 -0.029 OR4 0.269 0.350 0.356 0.652 0.330 -0.023 0.899 0.643 -0.036 PATTA1 0.338 0.488 0.379 0.689 0.329 0.009 0.722 0.923 -0.013 PATTA2 0.302 0.417 0.334 0.659 0.258 -0.043 0.674 0.905 0.010 PATTA3 0.283 0.461 0.359 0.663 0.291 -0.044 0.672 0.923 -0.069 PR1 -0.166 0.115 0.072 -0.084 0.042 0.302 -0.084 -0.075 0.793 PR2 -0.112 0.132 0.132 0.003 0.053 0.238 -0.032 -0.004 0.885 PR3 -0.117 0.113 0.148 0.020 0.007 0.235 0.008 -0.015 0.911 A more credible validity assessment was conducted using Heterotrait-Monotrait (HTMT) ratio. Table 6 revealed HTMT ratio value analysis for each variable. HTMT value obtained from the analysis was <0.9 which indicated that all constructed values within the model fulfilled the criteria of discriminant validity. Table 6. Heterotrait-Monotrait Ratio Value. FM HM IB ISN LSC MT OR PATTA PR FM HM 0.035 IB 0.066 0.555 ISN 0.340 0.433 0.474 LSC 0.456 0.096 0.088 0.370 MT 0.074 0.288 0.370 0.085 0.152 OR 0.339 0.429 0.468 0.812 0.376 0.095 PATTA 0.368 0.522 0.434 0.809 0.357 0.120 0.825 PR 0.166 0.151 0.158 0.055 0.055 0.381 0.059 0.055 3.4. Reliability Test Reliability assessment was conducted using composite reliability (CR) and Cronbach’s Alpha. Table 7 presents that each variable demonstrated CR or Cronbach’s Alpha of >0.7, which implied that variables studied had good and reliable internal consistency. 1397 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate Table 7. Summary of Reliability Test. Variable Composite Reliability Cronbach’s Alpha Low Self Control 0.935 0.863 Impulsiveness of Social Networks 0.915 0.896 Positive Attitude Toward Targeted Advertising 0.941 0.906 FOMO (Fear of Missing Out) 0.924 0.905 Online Reviews 0.938 0.911 Hedonic Motivations 1.000 1.000 Materialism 0.823 0.732 Price Value 0.898 0.837 Impulsive Buying 0.915 0.876 3.5. Structural Model Analysis This model, as shown in Figure 1, showed path coefficient, determination coefficient (R-Square), effect size (f-Square), as well as predictive relevance (Q-Square). Figure 1. Structural model. 3.6. R-Square Analysis Impulsive buying parameter showed R-square value of 0.400, which indicated that 40% of impulsive buying parameter could be explained by the indicators low self-control, positive attitude toward targeted advertising, impulsiveness of social networks, fear of missing out (FOMO), online reviews, hedonic motivations, materialism, dan price value. Positive attitude toward targeted advertising had an R-square value of 0.103, indicating that 10.3% of the variable positive attitude toward targeted advertising could be explained by low self-control. While impulsiveness of social networks had an R- 1398 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate square value of 0.544, which indicated that 54.4% of the variable impulsiveness of social networks could be explained by positive attitude toward targeted advertising and low self-control. Table 8. R-Square Value. Variable R-Square Impulsiveness of Social Networks 0.544 Positive Attitude Toward Targeted Advertising 0.103 Impulsive Buying 0.400 Positive attitude toward targeted advertising against impulsiveness of social networks revealed the greatest value of 0.958, indicating strong influence. Meanwhile, other variables exhibited minor influence, including fear of missing out (FOMO) against impulsive buying, hedonic motivations against impulsive buying, impulsiveness of social networks against impulsive buying, low self-control against impulsive buying, materialism against impulsive buying, Online Reviews against impulsive buying, positive attitude toward targeted advertising against impulsive buying, Price Value against impulsive buying, low self-control against impulsiveness of social networks, dan low self-control against positive attitude toward targeted advertising. Table 9. Q-Square Value and F- Square Value. Variable Q-Square F-Square FM HM IB ISN LSC MT OR PATTA PR ISN 0.100 0.021 0.958 PATTA 0.094 0.114 IB 0.328 0.002 0.086 0.026 0.012 0.087 0.026 0.000 0.002 3.7. Predictive Relevance Analysis (Q-Square) Based on the Q-square evaluation conducted using the blindfolding feature in SmartPLS, all variables showed a value of >0, which indicated that the study model had predictive relevance. This implied that this study could predict dependent variables well. 3.8. Effect Size Analysis (F-Square) Based on the Table 9, positive attitude toward targeted advertising against impulsiveness of social networks revealed the greatest value of 0.958, indicating strong influence. Meanwhile, other variables exhibited minor influence, including fear of missing out (FOMO) against impulsive buying, hedonic motivations against impulsive buying, impulsiveness of social networks against impulsive buying, low self-control against impulsive buying, materialism against impulsive buying, Online Reviews against impulsive buying, positive attitude toward targeted advertising against impulsive buying, Price Value against impulsive buying, low self-control against impulsiveness of social networks, and low self-control against positive attitude toward targeted advertising. 4. Discussion This study reveals that low self-control does not have a direct and significant effect on impulsive buying, contrary to findings by Nyrhinen, et al. [8] who reported a strong positive relationship between low self-control and impulsive purchasing behavior in online shopping contexts. However, our results confirm that low self-control significantly influences both impulsiveness on social networks and a positive attitude toward targeted advertising, supporting the notion that individuals with poor self- regulation are more susceptible to external stimuli, especially in digital environments [8]. 1399 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 7: 1390-1400, 2025 DOI: 10.55214/25768484.v9i7.8923 © 2025 by the authors; licensee Learning Gate Importantly, we found that social network impulsiveness significantly and positively affects impulsive buying, aligning with Nyrhinen, et al. [8] who noted that individuals who exhibit impulsivity on social media platforms are more prone to make spontaneous purchases. In contrast, a positive attitude toward targeted advertising, while significantly related to social media impulsiveness, does not directly influence impulsive buying in this study. This diverges from previous findings by Nyrhinen [7] who reported a direct effect. Moreover, external factors such as hedonic motivation, online reviews, and materialism were shown to have positive and significant effects on impulsive buying, supporting the results of Chetioui and El Bouzidi [3]. These findings suggest that pleasure-seeking tendencies, reliance on peer-generated content, and materialistic values play vital roles in encouraging unplanned purchases. In contrast, FOMO and price value did not show significant direct effects, deviating from Chetioui and El Bouzidi [3] conclusions, especially regarding FOMO, which they identified as a major driver of impulsivity. Finally, mediation analysis reveals that low self-control does not significantly influence impulsive buying through either social media impulsiveness or attitudes toward targeted ads. Although a direct path from low self-control to these variables exists, the indirect effects are statistically insignificant, indicating the presence of other, more influential mediating factors. This suggests the complexity of consumer impulsivity and highlights the need for future research to explore alternative pathways, such as emotional regulation or peer influence mechanisms. 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] M. T. Cindy and L. 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