From Social Exclusion to Impulsive Buying: FOMO’s Role in Digital Consumption Regret

Abstract

Introduction

: Shoppertainment platforms such as TikTok Shop and Shopee Live combine live interaction, social proof, scarcity cues, and instant checkout, creating a shopping setting that can heighten emotional arousal among Generation Z consumers. This study examines how social exclusion, fear of missing out, online impulsive buying, and post-purchase regret operate together in Indonesian shoppertainment. Methods: A quantitative cross-sectional survey was conducted among Indonesian Generation Z users of TikTok Shop and Shopee Live. Validated reflective measures were adapted from prior studies and translated through forward and back translation. The data were analysed using partial least squares structural equation modelling with bootstrapping. Results: The findings show that social exclusion is strongly associated with FOMO, but its direct association with online impulsive buying is not significant. FOMO is positively associated with online impulsive buying and post-purchase regret, while online impulsive buying is positively associated with post-purchase regret. Mediation testing indicates that FOMO fully mediates the relationship between social exclusion and online impulsive buying, and online impulsive buying partially mediates the relationship between FOMO and post-purchase regret. Conclusion: FOMO is the central psychological pathway through which social exclusion is translated into impulsive purchases in shoppertainment. The study highlights the ethical need for platforms and brands to reduce manipulative urgency cues and protect consumer agency.

KEYWORDS social exclusion; fomo; online impulsive buying; post-purchase regret; generation z; shoppertainment. Introduction Online shopping has become a key area for studying consumer behaviour, especially among Generation Z who grew up in digitally immersive environments (Deloitte, 2025). The emergence of shoppertainment, which blends live streaming, social interaction, and instant commerce on platforms like TikTok Shop and Shopee Live, creates a buying context that is qualitatively different from conventional e-commerce (Lo et al., 2022; Nuraisah et al., 2024; Qu et al., 2023). In these settings real-time social cues such as live viewer counts, countdown timers, and hosts’ calls to action raise emotional arousal and tend to speed up purchasing decisions (Qu et al., 2023). At the same time mood states and a compulsion to consume are intensified by feelings of social disregard or rejection, and mechanisms like

Literature Review and Hypotheses Development

to Impulsive Buying: FOMO’s Role in Digital Consumption Regret Amdar1, Elia Ardyan2 12Sekolah Tinggi Ilmu Ekonomi Ciputra Makassar, South Sulawesi, Indonesia Correspondence: elia.ardyan@ciputra.ac.id1 Abstract Introduction: Shoppertainment platforms such as TikTok Shop and Shopee Live combine live interaction, social proof, scarcity cues, and instant checkout, creating a shopping setting that can heighten emotional arousal among Generation Z consumers. This study examines how social exclusion, fear of missing out, online impulsive buying, and post-purchase regret operate together in Indonesian shoppertainment.

Methods

: A quantitative cross-sectional survey was conducted among Indonesian Generation Z users of TikTok Shop and Shopee Live. Validated reflective measures were adapted from prior studies and translated through forward and back translation. The data were analysed using partial least squares structural equation modelling with bootstrapping. Results: The findings show that social exclusion is strongly associated with FOMO, but its direct association with online impulsive buying is not significant. FOMO is positively associated with online impulsive buying and post-purchase regret, while online impulsive buying is positively associated with post-purchase regret. Mediation testing indicates that FOMO fully mediates the relationship between social exclusion and online impulsive buying, and online impulsive buying partially mediates the relationship between FOMO and post-purchase regret. Conclusion: FOMO is the central psychological pathway through which social exclusion is translated into impulsive purchases in shoppertainment. The study highlights the ethical need for platforms and brands to reduce manipulative urgency cues and protect consumer agency.

KEYWORDS social exclusion; fomo; online impulsive buying; post-purchase regret; generation z; shoppertainment. Introduction Online shopping has become a key area for studying consumer behaviour, especially among Generation Z who grew up in digitally immersive environments (Deloitte, 2025). The emergence of shoppertainment, which blends live streaming, social interaction, and instant commerce on platforms like TikTok Shop and Shopee Live, creates a buying context that is qualitatively different from conventional e-commerce (Lo et al., 2022; Nuraisah et al., 2024; Qu et al., 2023). In these settings real-time social cues such as live viewer counts, countdown timers, and hosts’ calls to action raise emotional arousal and tend to speed up purchasing decisions (Qu et al., 2023). At the same time mood states and a compulsion to consume are intensified by feelings of social disregard or rejection, and mechanisms like Social Exclusion and fear of missing out (FOMO) appear to be strong drivers of impulsive buying and later regret among Generation Z consumers (Mudjiyanto et al., 2025; Wijaya et al., 2025; Zhang et al., 2024). Understanding how Social Exclusion and FOMO operate as psychological precursors in shoppertainment settings matters for both theory and practice. It helps refine consumer behaviour models and informs ethical marketing and digital well-wellbeing policies (Gezgin, 2025; Lee & Shrum, 2012). Although research on FOMO and impulsive buying is growing, important gaps remain. Most studies have focused on general social media or traditional e-commerce contexts (Hussain et al., 2023; Tandon et al., 2021), leaving live-commerce dynamics largely underexamined. Table 1. Comparison of Closely Related Studies Study Context Key Constructs Method Key Finding Luo et al. (2021) General online, China SE → Self-Esteem → OIB SEM Selfesteem mediates SE → OIB Zhang et al. (2024) Online platforms, China SE → OIB PLS-SEM SE directly increases OIB Febrianty et al. (2025) Shopee, Indonesia Scarcity → FOMO → OIB PLS-SEM FOMO mediates scarcity → OIB Mudjiyanto et al. (2025) Social media, Indonesia FOMO → OIB Descriptive FOMO drives Gen Z impulsive buying Çelik et al. (2019) Retail stores, Turkey FOMO → OIB → PPR Regression FOMO increases OIB and PPR Tandon et al. (2021) Social media (SLR) FOMO antecedents/outcomes SLR FOMO linked to compulsive behaviour Moreover, the mediating role of FOMO in translating Social Exclusion into impulsive buying and the downstream consequence of post-purchase regret, has not been systematically examined within the shoppertainment context among Generation Z in Indonesia. A comparison of closely related studies is presented in Table 1, this study addresses that gap by tracing the full psychological chain from Social Exclusion to FOMO, from FOMO to impulsive online buying, and from impulsive buying to post-purchase regret, all within a shoppertainment setting. It extends prior research in three ways. First, it tests the entire sequence in a context that blends live streaming, social cues, and instant commerce. Second, it examines whether FOMO fully mediates the link between Social Exclusion and impulsive buying, rather than treating FOMO merely as an antecedent. Third, it focuses on Generation Z users in Indonesia, a fast-growing shoppertainment market whose psychological responses remain underexamined. Social Exclusion Social Exclusion refers to the experience of being ignored, rejected, or ostracised from one's social group (Williams & Nida, 2022). In the digital world, Social Exclusion can happen, for instance, when an individual is ignored on social media (Luo et al., 2021). This kind of psychological pain can trigger a self-defensive mechanism of compensatory consumption, whereby an individual engages in the purchase of a good in an attempt to "repair" a negative psychological state and a damaged self (Mandel et al., 2016). FOMO (Fear of Missing Out) FOMO is defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent, characterised by the desire to stay continually connected with what others are doing (Ardyan & Sanapang, 2023; Przybylski et al., 2013). There are numerous factors that significantly impact FOMO, including: anxiety (Rahmania et al., 2023; Wijaya et al., 2025), scarcity effect (Febrianty et al., 2025), neuroticism (Saritepeci & Kurnaz, 2024), hedonism motivation (Deliana et al., 2024), time cost (Jabeen et al., 2023), and vulnerable narcissism (Brailovskaia et al., 2023).

Online Impulsive Buying Automated negative reinforcement impulsive buying behaviour occurs when individuals attempt to dissociate negative affective states regardless of the irrational (unplanned) psychological costs (Gezgin, 2025). It is more pronounced among the Gen-Z population, socialized on the net and thus providing online shops easy access points for shopping to fill the emotional gap when Exclusion is felt (Lee & Shrum, 2012). As consumers, people make unplanned purchases driven by strong emotions. This is referred to as online impulsive buying, consisting of unplanned purchases made through the Internet (Verhagen & van Dolen, 2011). This type of behaviour occurs due to an interplay of internal states, such as hedonism (Aziz et al., 2025), Social Exclusion (Zhang et al., 2024), mood management, anxiety, FOMO (Mudjiyanto et al., 2025), and external stimuli, such as platform flash discounts and seamless checkout. Among all generations, members of Generation Z, which has greater exposure and thus greater vulnerability to psychological and digital stimuli, are more likely than other generations to buy for instant gratification and social validation impulsively (Lina et al., 2022). Decisions are frequently made in a hasty and emotional manner by individuals. The majority of individuals can easily recall or envision instances in which a poor decision resulted in painful regret; indeed, impulse purchases are widely recognized as a key source of post-decision remorse precisely because they bypass deliberate evaluation (Grigsby et al., 2021; Morozova & Vlaev, 2024).

Post-Purchase Regret Regret, which occurs after counterfactual thinking such as "if only I had…", is a negative emotion felt when a different purchasing choice might have led to a more favourable outcome (Rychalski & Hudson, 2017). The stronger emotional impulse and lower reasoning in impulsive buying decisions, the more likely the emotionally charged 'wrong' decisions will feel after the excitement is gone (Badgaiyan & Verma, 2015). For Generation Z, such relentless, digitally driven impulsive behaviour may lead to dissatisfaction, as well as other negative brand actions such as returning items and leaving bad reviews (Lisjak et al., 2015). According to prior research, there are numerous factors that contribute to post-purchase regret, including: consumer ethnocentrism (Dankwah et al., 2024), impulsive buying (Barta et al., 2023; Beikverdi et al., 2024; Sönmezay, 2023), brand betrayal (Sameeni et al., 2022), and Attractiveness of alternatives (Sarwar et al., 2020). Hypotheses Development Social Exclusion occurs when people perceive themselves as outsiders to their social circle (Williams & Nida, 2022). Social Exclusion can significantly impact individuals, resulting in emotional discomfort and cognitive disarray that may culminate in self-destructive conduct (Han, 2020). Several studies explain that Social Exclusion can increase online impulsive buying (Luo et al., 2021; Zhang et al., 2024). Young individuals may purchase items impulsively to conform to group norms, obtain social acceptance, or regain a sense of self-worth that has been diminished by Social Exclusion when organizations or social norms validate specific behaviors, such as consumerism (Mukti et al., 2024). However, this relationship is not universal. Zhang et al. (2024) show that self-control moderates the link between Social Exclusion and impulsive buying, so people with stronger self-control are less likely to respond impulsively to feelings of exclusion. Luo et al. (2021) report a similar moderation by risk preference, where risk- averse individuals display a weaker direct reaction to exclusion. Together, these findings imply that the direct path from Social Exclusion to impulsive buying depends on individual differences. In shoppertainment settings, where emotional arousal is constant and self-control may be depleted, the

Figure 1. Conceptual Model indirect route through FOMO (H6) likely becomes the dominant mechanism translating exclusion into impulsive purchases. H1: Social Exclusion has a positive and significant effect on online impulsive buying. Social Exclusion increases sensitivity to the social behaviours of people around them, especially on social media (Williams, 2007; Williams & Nida, 2022). The sense of being excluded from social situations is a driver of the fear of missing out (Przybylski et al., 2013). Social Exclusion amplifies the feeling of having inadequate information or experiences that ought to be shared within the individual's social circle (Bright & Logan, 2018). Thus, FOMO and Social Exclusion relate to emotional responses that indicate the loss of social connection (Elhai et al., 2016). H2: Social Exclusion has a positive and significant effect on FOMO. FOMO triggers a psychological urgency to engage in certain activities to attain and/or sustain social inclusion within a group, including purchase activities (Hussain et al., 2023). The incidence of FOMO has escalated due to the expansion of social media platforms and the incessant availability of information about individuals' activities and experiences (Alutaybi et al., 2020). These activities are performed without adequate justification, and rational alternatives are overlooked because the individual needs to alleviate the feeling of Social Exclusion emotionally. The pressure to purchase emotionally is more pronounced within the digital environment because promotional materials and information circulate rapidly (Bright & Logan, 2018). Hence, FOMO is a central motivator of online impulsive buying (Febrianty et al., 2025; Mudjiyanto et al., 2025; Verhagen & van Dolen, 2011). H3: FOMO has a positive and significant effect on Online Impulsive Buying. FOMO is the fear of missing out on the opportunity to acquire the products or services they desire (Kaddouhah, 2024). FOMO and emotional pressure purchase decisions are more likely to result in dissatisfaction and/or regret upon purchase (Çelik et al., 2019). Consumers feel societal pressure to make purchases even if they do not really need the product (Tandon et al., 2021). Regret can set in when buyers face reality after a purchase, realizing they made their decision with little thought (Zeelenberg & Pieters, 2007). Çelik et al. (2019) clarified that the post-purchasing regret of participants is influenced by their FOMO tendency. H4: FOMO has a positive and significant effect on PostPurchase Regret. Rook (1987) defines impulsive buying as a consumption decision made in a snap, without careful consideration. Most shoppers who make impulsive purchases regret them after the fact because they realize they did not meet their expectations (Rajagopal et al., 2019). Following an impulsive purchase, consumers may experience dissatisfaction, leading to emotions such as anger, guilt, and regret (Barta et al., 2023). Bakar et al. (2025) elucidated that when consumers

make online impulsive purchases, they experience feelings of regret regarding the quantity of money they have spent. H5: Online impulsive buying has a positive and significant effect on post-purchase regret. Indirectly, Social Exclusion might lead to impulsive online shopping. More recent works, however, recognize the importance of the fear of missing out (FOMO) in mediating the relationship between Social Exclusion and psychological variables (Febrianty et al., 2025). Socially excluded individuals often experience FOMO, and social FOMO motivates them to make impulsive online purchases (Przybylski et al., 2013). In this case, FOMO acts as a psychological conduit that drives social pressure to compulsive consumption (Hussain et al., 2023). Thus, the FOMO psychological effect, indirectly connected to Social Exclusion, highlights the mediating role of FOMO in the more online psychological consumptive behaviours. Because the direct link from Social Exclusion to impulsive online buying (H1) is theoretically complex, we propose the route through FOMO (H6) as the main mechanism explaining how feelings of exclusion lead to impulsive purchases in shoppertainment settings. In other words, Social Exclusion is expected to trigger FOMO, and that heightened FOMO then drives impulsive buying. H6: Social Exclusion has a positive and significant effect on Online Impulsive Buying through the mediation of FOMO. FOMO, as described in recent works, relates to impulsive buying and emotionally charged consumer behaviours that foster social attachment and lead to a loss of control over spending (Hussain et al., 2023). FOMO, when linked to impulsive purchases, tends to lead to negative consequences when purchase expectations are not met, thereby leading to regret (Zeelenberg & Pieters, 2007). Consequently, FOMO affects post-purchase regret indirectly through online impulsive buying (Tandon et al., 2021). People under FOMO do not take the time to assess their purchases rationally, and they experience an emotional realization—regret—when they buy dissatisfying products (Przybylski et al., 2013). This mediation indicates that impulsivity is the main pathway through which FOMO translates to post-purchase regret H7: FOMO has a positive and significant effect on PostPurchase Regret through the mediation of Online Impulsive Buying The following is the proposed research model in this study (see figure 1). This study aims to examine the associations among Social Exclusion, FOMO, online impulsive buying, and post-purchase regret among Generation Z users of shoppertainment platforms in Indonesia, with FOMO as a mediator between Social Exclusion and online impulsive buying, and online impulsive buying as a mediator between FOMO and post-purchase regret.

Methods Sample Sample characteristics based on data collected during the data collection period of July 1-14, 2025, covering 576 respondents, demonstrated a sharper and more representative demographic and behavioural profile (see Table 2). Age analysis showed that respondents aged 18 to 20 accounted for more than 90% of the sample. The 20-year-old age group represented the largest cohort of new respondents at 31.1%. The next largest age cohorts were 19 years at 23.1% and 22 years at 18.9%. There was one 29-year-old respondent, accounting for 0.2% of the survey and statistically insignificant. In the gender category, data consistently showed more female respondents (62.3%, 359) than male respondents (37.7%, 217), indicating a higher response rate from women. Almost half of the survey respondents (50.9%) reported a monthly income of 1 to 3 million Rupiah. Because 31.9% of respondents were in the lower income group of 0 to 1 million Table 2. Respondent Characteristics Characteristics Frequency % Age

18-22 519 90.10 23-25 54 9.38 26-29 3 0.50 Gender

Male 217 37.30 Female 359 62.30 Income

+3m 99 17.20 1-3m 293 50.90 0-1m 184 31.90 City

Makassar 342 59.40 Surabaya 55 9.50 Jakarta 38 6.70 Bandung 28 4.90 Medan 23 4.00 Manado 19 3.30 Samarinda 14 2.40 Bali 13 2.30 Semarang 5 0.90 Padang 2 0.30 Bulukumba 1 0.20 Solo 1 0.20 Sumbawa 1 0.20 Lampung 1 0.20 Bojonegoro 1 0.20 Bekasi 4 0.70 Malang 1 0.20 Yogyakarta 6 1.10 Palembang 1 0.20 Bandar Lampung 1 0.20 Cilacap 1 0.20 Bantul 2 0.30 Bogor 2 0.30 Denpasar 1 0.20 Jayapura 2 0.30 Kalimantan 2 0.30 Jawa Timur 1 0.20 Kendari 1 0.20 Tasikmalaya 1 0.20 Tangerang 1 0.20 Nabire 1 0.20 Sengkang 2 0.30 Pekanbaru 1 0.20 Palu 1 0.20 Platform

TikTok Shop 349 60.60 Tokopedia 5 0.90 Shopee Live 216 37.50 Others 6 1.20 Platform 576 Rupiah, it can be said that 82.8% of respondents have the spending power of university students and entry-level workers. Respondents were drawn from 35 cities across Indonesia, yet the sample is clearly skewed toward Makassar City, which accounts for 59.4% of cases. Other notable contributions came from Surabaya (9.5%) and Jakarta (6.7%). Although the dataset benefits from multi-city coverage, this geographic concentration warrants caution; extrapolating the

findings to other Indonesian cities should be done carefully and ideally validated with a more geographically balanced sample. The preference analysis showed a distinct inclination toward social commerce. TikTok Shop was by far the leading platform, favoured by 60.6% of respondents, and Shopee Live was chosen by 37.2%, with the two platforms together covering 97.8% of preferences. These results imply that the impulsive online shopping behaviours identified in this research occur almost entirely within the integrated spheres of entertainment, social interaction, and commerce. In this respect, traditional ecommerce platforms are virtually irrelevant. Overall, respondents could be characterized as young females (approximately 20 years old) from a major city, predominantly Makassar, with moderate to low purchasing power, and a strong preference for shoppertainment-style online shopping. Measurement This study uses four latent constructs, namely Social Exclusion (SE), Fear of Missing Out (FOMO), Online Impulsive Buying (OIB), and Post-Purchase Regret (PPR). Each variable is measured with multiple indicator items adapted from prior studies to maintain content validity. SE is captured using four items from Zhang et al. (2024). FOMO is measured with four items developed from the foundational work of Przybylski et al. (2013) and later validated in a consumption context by Mahena et al. (2025). OIB is assessed using four items adapted from Verhagen and van Dolen (2011) while PPR is measured with four items based on Zeelenberg and Pieters (2007). Because the respondents are Indonesian Gen Z users, all items were translated from English into Indonesian through a forward and back translation process to ensure conceptual equivalence. The initial translation was conducted by a bilingual researcher, then independently translated back by another bilingual researcher to confirm consistency with the original version. Minor adjustments in wording were applied to ensure clarity and natural expression in the Indonesian context without altering the meaning of each construct. All constructs in this study, SE, FOMO, OIB, and PPR, are specified as reflective measurement models, in line with their theoretical definition as latent variables whose indicators represent interchangeable manifestations of the same underlying concept (Hair et al., 2017). The measurement items used for each construct are summarized in Table 3. Each questionnaire item was measured using a 5-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). Analysis To analyze the quantitative data and test the complex hypothetical model in this study, we employed Structural Equation Modelling (SEM) using the Partial Least Squares (PLS) approach. The PLS-SEM approach was selected based on its suitability for prediction-oriented models, its capacity to handle complex structural paths without imposing normality assumptions, and its established application in consumer behaviour research (Hair et al., 2017). All data processing, statistical calculations, and hypothesis testing for this study were carried out via SmartPLS version 4. To reduce common method bias we assured respondent anonymity and interspersed items from different constructs throughout the questionnaire. As a statistical safeguard we followed Kock’s recommendation and checked full collinearity Variance Inflation Factor values for all indicators (Kock, 2015). Before analysis we screened the full set of 576 responses for missing data and outliers; none were excluded as all cases were complete and within acceptable ranges. Table 3. Variable and Indicators Variables Question Items References Social Exclusion I feel excluded from my friends' social media activities. (SE1) I often feel ignored by others on social media. (SE2) I feel unimportant to my community on social media. (SE3) I feel like my community on social media is avoiding me. (SE4) FOMO (Fear of Missing Out) I am afraid of missing out on popular social media trends. (F1) I feel anxious when I am not active on social media. (F2) I need to buy products because they are currently viral. (F3) I feel pressured when I see my friends buying new items I do not yet own. (F4) Online Impulsive Buying I often buy products spontaneously when I see them online. (OIB1) I buy items without much thought. (OIB2) I find it hard to resist the urge to shop online. (OIB3) I am tempted to buy products because they look attractive or are on sale. (OIB4) Post-Purchase Regret I regret buying a product impulsively. (PPR1) I should not have bought the product. (PPR2) I feel disappointed after buying the product. (PPR3) The money I spent on impulsive items should have been spent on something else. (PPR4)

Result and Discussion

Following the completion of data collection with 576 respondents, data analysis was conducted using the PLS approach. The analysis is performed in two stages: the measurement model evaluation and the structural model evaluation. In the first stage, the measurement model was evaluated to assess the validity and reliability of the constructs used in the study. The results of the validity and reliability tests are included in the table below (Table 4). As regards findings, the loading factor values for each research item ranged from 0.709 to 0.925. All of these values are above the threshold of 0.7, indicating strong indicator validity. In addition, the Average Variance Extracted (AVE) values for each variable ranged between 0.683 and 0.832, which means all values are above the acceptable minimum of 0.5. Therefore, the research instrument's convergent validity is established (Hair et al., 2017). As for the reliability test, the composite reliability (CR) values ranged from 0.895 to 0.952, which is excellent. The consistency of the high values of the Cronbach's Alpha, which ranged from 0.844 to 0.933, also helps in the reliability construct, which means that all of the CR and the Cronbach's Alpha values are above the 0.7 threshold and that the instruments used in the study are reliable (Hair et al., 2017). Discriminant validity was assessed using the HeterotraitMonotrait ratio (HTMT), as recommended by Henseler et al. (2015). As presented in Table 5, most HTMT values are below the threshold of 0.90. However, the HTMT value between FOMO and Online Impulsive Buying was 0.938, marginally exceeding the threshold. This overlap is theoretically anticipated given that FOMO is a direct and strong predictor of Online Impulsive Buying (β = 0.790, p < 0.001), and their conceptual proximity has been consistently documented in the literature (Febrianty et al., 2025; Mudjiyanto et al., 2025). The remaining HTMT values all fall below 0.90, confirming discriminant validity for the other construct pairs. To assess common method bias, full collinearity VIF values were examined for all indicators. As shown in Table 6, all VIF values ranged from 1.494 to 3.972, well below the accepted threshold of 5.0 (Hair et al., 2017), indicating that common method bias is unlikely to pose a serious concern in this dataset. The structural model refers to the process of testing the previously proposed hypotheses. This stage is used to

Adapted from Zhang et al. (2024) Adapted from Przybylski et al. (2013); Mahena et al. (2025) Adapted from Verhagen and van Dolen (2011) Adapted from Zeelenberg and Pieters (2007) examine the relationships between variables. Six of the seven proposed hypotheses were supported; H1 was not supported (see Table 7). The results of this study indicate that Social Exclusion does not have a significant effect on online impulsive buying, although the direction of the relationship is positive. Table 8 and Table 9 summarizes the structural model’s quality indicators. The R² values show the model explains 59.1% of the variance in FOMO, 67.8% in Online Impulsive Buying, and 38.0% in Post Purchase Regret, indicating moderate to substantial explanatory power (Hair et al., 2017). Blindfolding produced positive Q² values for all endogenous constructs: 0.442 for FOMO, 0.455 for Online Impulsive Buying, and 0.251 for Post Purchase Regret, confirming the model’s predictive relevance (Hair et al., 2017). Effect size estimates show a very large effect of Social Exclusion on FOMO with f² =1.446, and a large effect of FOMO on Online Impulsive Buying with f² = 0.792. In contrast, the effects of FOMO on Post Purchase Regret and of Online Impulsive Buying on Post Purchase Regret are small, with f² values of 0.062 and 0.047 respectively. The direct effect of Social Exclusion on Online Impulsive Buying is negligible, with f² = 0.002, which aligns with the non significant H1 (Hair et al., 2017). The non-significant direct link between Social Exclusion and Online Impulsive Buying (β = 0.042, p = 0.357, 95% CI [−0.045, 0.138]) is theoretically informative. It qualifies the simple compensatory consumption idea of Mandel et al. (2016), which assumes perceived social rejection automatically spurs purchases to mend the self. Two plausible mechanisms can account for this null finding. First, from a self regulatory perspective, social exclusion may raise vigilance and deliberation rather than impulsivity. When exclusion increases perceived risk, people may monitor their choices more closely and act with greater caution, especially for decisions with financial consequences (Luo et al., 2021; Zhang et al., 2024). In this sense, Social Exclusion works as a cognitive brake, not an accelerant, for impulse buying. Second, and consistent with the mediation results, exclusion may need to amplify emotion, specifically by heightening FOMO, before it leads to impulsive purchases. The indirect effect through FOMO is large and statistically significant (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]), which supports the idea that FOMO is the psychological conduit translating exclusion into impulsive behaviour. These two accounts are compatible rather than mutually exclusive. A strengthened self regulatory response can suppress any direct effect of exclusion, while the FOMOTable 4. Measurement Model Result Construct Item Code Item Loading CR CA AVE Fear of Missing Out F1 0.865 0.925 0.892 0.755

F2 0.838

F3 0.883

F4 0.883

Online Impulsive Buying OIB1 0.859 0.895 0.844 0.683

OIB2 0.855

OIB3 0.871

OIB4 0.709

Post Purchase Regret PPR1 0.850 0.896 0.847 0.684

PPR2 0.860

PPR3 0.852

PPR4 0.740

Social Exclusion SE1 0.894 0.952 0.933 0.832

SE2 0.925

SE3 0.915

SE4 0.915 Table 5. Heterotrait-Monotrait Ratio (HTMT) Construct FOMO OIB PPR SE FOMO —

OIB 0.938 —

PPR 0.664 0.678 —

SE 0.841 0.717 0.621 — Table 6. Collinearity Statistics (VIF) Indicator VIF F1 2.347 F2 2.106 F3 2.782 F4 2.704 OIB1 2.146 OIB2 2.185 OIB3 2.226 OIB4 1.494 PPR1 2.026 PPR2 2.187 PPR3 1.971 PPR4 1.628 SE1 2.954 SE2 3.972 SE3 3.606 SE4 3.503 mediated route remains operative. Finally, because these results come from cross sectional data, they should be read as statistical associations rather than causal claims. Longitudinal or experimental designs are needed to establish directionality. The analysis reveals a strong positive link between Social Exclusion and FOMO, β = 0.769, t = 38.685, p < 0.001, 95% CI [0.729, 0.807], f² = 1.446. This result echoes prior work showing that perceived ostracism amplifies sensitivity to social cues and the urge to stay connected (Elhai et al., 2016; Williams & Nida, 2022). When people feel left out of peers’ activities they pay closer attention to signals that others are enjoying experiences from which they are absent, and shoppertainment environments magnify that effect. Livestream services such as TikTok Shop and Shopee Live broadcast real-time viewer counts, social reactions, and host demonstrations that continuously signal communal consumption (Lo et al., 2022; Nuraisah et al., 2024). For socially excluded Gen Z users whose sense of self is tied to digital participation, these live cues deepen the feeling of being left out and so intensify FOMO. The finding also

sharpens theory: Przybylski (2013) framed FOMO as a relatively stable disposition, a chronic worry that others enjoy rewarding experiences (Przybylski et al., 2013). In shoppertainment settings that dispositional baseline becomes a situationally triggered emotional state that peaks during live events, driven by real-time scarcity signals, countdowns, and visible social proof of co-viewers purchasing (Qu et al., 2023). In short, Social Exclusion raises dispositional sensitivity and makes users particularly vulnerable to this situational FOMO, a mechanism that differs from conventional e-commerce where real-time social comparison cues are absent. FOMO shows a very strong positive link with Online Impulsive Buying in this sample, confirming it as the immediate driver of impulsive purchases (β = 0.790, p < 0.001, 95% CI[0.702, 0.867]; f² = 0.792, large). This finding matches a growing set of Indonesian studies (Febrianty et al., 2025; Mahena et al., 2025; Mudjiyanto et al., 2025) and extends that evidence into the live-stream commerce context. The process fits Hussain et al. (2023), who argue that FOMO generates a psychological urgency to obtain socially validated products, circumventing the careful cost–benefit thinking that underpins planned purchases. On shoppertainment platforms, that urgency is built into the environment: flash-sale timers, hosts announcing limited stock, and visible waves of co-viewer purchases create scarcity and social proof, which speed the conversion of FOMO into unplanned buying (Lo et al., 2022). The very large effect size here suggests shoppertainment is markedly more potent than conventional e-commerce or offline retail in turning FOMO into impulse purchases, and it calls for focused scholarly attention on live-stream affordances (Nuraisah et al., 2024). The positive link between FOMO and post-purchase regret (β = 0.344, p < 0.001, 95% CI [0.209, 0.470]) reveals a structural irony in shoppertainment. The same emotional urgency that pushes someone to buy so they do not miss out also creates the conditions for later regret. Purchases driven by FOMO are often motivated by a desire to join a fleeting social moment rather than by real need or clear value. After the live event ends and the social cues fade, buyers tend to re-evaluate what they bought against ordinary criteria, which invites counterfactual thinking such as “if only I had not bought this,” and that process fuels regret (Zeelenberg & Pieters, 2007). At the same time, the effect size is small though significant (f² = 0.062), which suggests that post-purchase regret is shaped by many factors. FOMO contributes directly, but other elements also matter, including product quality, social comparison after purchase, and financial strain. Prior research supports this broader view: Wegmann et al. (2017)

Table 7. Hypothesis Testing Results H Relationships β t-stat p 95% CI Remarks H1 Social Exclusion -> Online Impulsive Buying 0.042 0.921 0.357 [-0.045, 0.138] Rejected H2 Social Exclusion -> FOMO 0.769 38.685 <0.001 [0.729, 0.807] Accepted H3 FOMO -> Online Impulsive Buying 0.790 18.777 <0.001 [0.702, 0.867] Accepted H4 FOMO -> Post-Purchase Regret 0.344 5.151 <0.001 [0.209, 0.470] Accepted H5 Online Impulsive Buying -> Post-Purchase Regret 0.301 4.162 <0.001 [0.160, 0.441] Accepted H6 Social Exclusion -> FOMO -> Online Impulsive Buying 0.608 17.534 <0.001 [0.538, 0.674] Accepted H7 FOMO -> Online Impulsive Buying -> PostPurchase Regret 0.238 4.203 <0.001 [0.127, 0.348] Accepted Table 8. R², R²adj, and Q² Construct R² R²adj Q² Interpretation FOMO 0.591 0.590 0.442 Moderate Online Impulsive Buying 0.678 0.677 0.455 Moderate PostPurchase Regret 0.380 0.378 0.251 Moderate Table 9. Effect Size (f²) Construct R² R²adj SE → FOMO 1.446 Large FOMO → OIB 0.792 Large FOMO → PPR 0.062 Small OIB → PPR 0.047 Small SE → OIB 0.002 Negligible show that FOMO-driven online engagement can produce negative affective outcomes, such as dissatisfaction and regret, when the anticipated social reward does not persist. In short, FOMO is an important piece of the regret puzzle in shoppertainment, but it operates within a wider affective and evaluative process. The positive link between Online Impulsive Buying and Post-Purchase Regret (β = 0.301, p < 0.001, 95% CI [0.160, 0.441]) fits with prior evidence showing that rapid, emotiondriven purchase decisions weaken the buyer’s ability to justify the choice afterward, and thereby raise the chance of regret (Barta et al., 2023; Beikverdi et al., 2024; Sönmezay, 2023). Grigsby et al. (2021) argue that impulsive shoppers feel more regret because they lack the deliberative time and resources needed to form forward-looking rationalizations. In shoppertainment, the contrast between the excitement of a live event and the calmer post-stream state makes that mismatch especially stark, so Generation Z users may discover after the fact that the purchase does not meet a real need (Bakar et al., 2025; Qu et al., 2023). The small effect size (f² = 0.047) suggests impulsive buying is only one of several contributors to regret, and that individual factors like financial literacy, self-control, and product involvement likely moderate the link. The very large and significant indirect path from Social Exclusion to Online Impulsive Buying via FOMO (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]) alongside a negligible direct path (β = 0.042, f² = 0.002) implies a mediation pattern in which FOMO is the key psychological channel. In other words, social exclusion seems to fuel situational FOMO, and that heightened FOMO, not exclusion itself, drives impulsive purchases. Shoppertainment platforms are especially fertile for this mechanism because real-time social proof and urgency cues translate abstract feelings of exclusion into an immediate opportunity to rejoin a social moment through buying (Lo et al., 2022; Nuraisah et al., 2024). Finally, the indirect route from FOMO to Post-Purchase Regret through Online Impulsive Buying (β = 0.238, p < 0.001, 95% CI [0.127, 0.348]) shows that impulsivity is a

consequential intermediate step. When FOMO shortens deliberation time as shoppertainment mechanics are designed to do, consumers skip the prospective checks that might prevent regret later (Grigsby et al., 2021). Because FOMO also has a direct effect on regret, the pattern creates a potential feedback loop: FOMO prompts impulsive buying, impulsive buying fuels regret, and regret may in turn alter future vulnerability to FOMO as consumers try to repair perceived poor choices (Tandon et al., 2021).

Conclusion

: FOMO is the central psychological pathway through which social exclusion is translated into impulsive purchases in shoppertainment. The study highlights the ethical need for platforms and brands to reduce manipulative urgency cues and protect consumer agency.

KEYWORDS social exclusion; fomo; online impulsive buying; post-purchase regret; generation z; shoppertainment. Introduction Online shopping has become a key area for studying consumer behaviour, especially among Generation Z who grew up in digitally immersive environments (Deloitte, 2025). The emergence of shoppertainment, which blends live streaming, social interaction, and instant commerce on platforms like TikTok Shop and Shopee Live, creates a buying context that is qualitatively different from conventional e-commerce (Lo et al., 2022; Nuraisah et al., 2024; Qu et al., 2023). In these settings real-time social cues such as live viewer counts, countdown timers, and hosts’ calls to action raise emotional arousal and tend to speed up purchasing decisions (Qu et al., 2023). At the same time mood states and a compulsion to consume are intensified by feelings of social disregard or rejection, and mechanisms like Social Exclusion and fear of missing out (FOMO) appear to be strong drivers of impulsive buying and later regret among Generation Z consumers (Mudjiyanto et al., 2025; Wijaya et al., 2025; Zhang et al., 2024). Understanding how Social Exclusion and FOMO operate as psychological precursors in shoppertainment settings matters for both theory and practice. It helps refine consumer behaviour models and informs ethical marketing and digital well-wellbeing policies (Gezgin, 2025; Lee & Shrum, 2012). Although research on FOMO and impulsive buying is growing, important gaps remain. Most studies have focused on general social media or traditional e-commerce contexts (Hussain et al., 2023; Tandon et al., 2021), leaving live-commerce dynamics largely underexamined. Table 1. Comparison of Closely Related Studies Study Context Key Constructs Method Key Finding Luo et al. (2021) General online, China SE → Self-Esteem → OIB SEM Selfesteem mediates SE → OIB Zhang et al. (2024) Online platforms, China SE → OIB PLS-SEM SE directly increases OIB Febrianty et al. (2025) Shopee, Indonesia Scarcity → FOMO → OIB PLS-SEM FOMO mediates scarcity → OIB Mudjiyanto et al. (2025) Social media, Indonesia FOMO → OIB Descriptive FOMO drives Gen Z impulsive buying Çelik et al. (2019) Retail stores, Turkey FOMO → OIB → PPR Regression FOMO increases OIB and PPR Tandon et al. (2021) Social media (SLR) FOMO antecedents/outcomes SLR FOMO linked to compulsive behaviour Moreover, the mediating role of FOMO in translating Social Exclusion into impulsive buying and the downstream consequence of post-purchase regret, has not been systematically examined within the shoppertainment context among Generation Z in Indonesia. A comparison of closely related studies is presented in Table 1, this study addresses that gap by tracing the full psychological chain from Social Exclusion to FOMO, from FOMO to impulsive online buying, and from impulsive buying to post-purchase regret, all within a shoppertainment setting. It extends prior research in three ways. First, it tests the entire sequence in a context that blends live streaming, social cues, and instant commerce. Second, it examines whether FOMO fully mediates the link between Social Exclusion and impulsive buying, rather than treating FOMO merely as an antecedent. Third, it focuses on Generation Z users in Indonesia, a fast-growing shoppertainment market whose psychological responses remain underexamined. Social Exclusion Social Exclusion refers to the experience of being ignored, rejected, or ostracised from one's social group (Williams & Nida, 2022). In the digital world, Social Exclusion can happen, for instance, when an individual is ignored on social media (Luo et al., 2021). This kind of psychological pain can trigger a self-defensive mechanism of compensatory consumption, whereby an individual engages in the purchase of a good in an attempt to "repair" a negative psychological state and a damaged self (Mandel et al., 2016). FOMO (Fear of Missing Out) FOMO is defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent, characterised by the desire to stay continually connected with what others are doing (Ardyan & Sanapang, 2023; Przybylski et al., 2013). There are numerous factors that significantly impact FOMO, including: anxiety (Rahmania et al., 2023; Wijaya et al., 2025), scarcity effect (Febrianty et al., 2025), neuroticism (Saritepeci & Kurnaz, 2024), hedonism motivation (Deliana et al., 2024), time cost (Jabeen et al., 2023), and vulnerable narcissism (Brailovskaia et al., 2023).

Online Impulsive Buying Automated negative reinforcement impulsive buying behaviour occurs when individuals attempt to dissociate negative affective states regardless of the irrational (unplanned) psychological costs (Gezgin, 2025). It is more pronounced among the Gen-Z population, socialized on the net and thus providing online shops easy access points for shopping to fill the emotional gap when Exclusion is felt (Lee & Shrum, 2012). As consumers, people make unplanned purchases driven by strong emotions. This is referred to as online impulsive buying, consisting of unplanned purchases made through the Internet (Verhagen & van Dolen, 2011). This type of behaviour occurs due to an interplay of internal states, such as hedonism (Aziz et al., 2025), Social Exclusion (Zhang et al., 2024), mood management, anxiety, FOMO (Mudjiyanto et al., 2025), and external stimuli, such as platform flash discounts and seamless checkout. Among all generations, members of Generation Z, which has greater exposure and thus greater vulnerability to psychological and digital stimuli, are more likely than other generations to buy for instant gratification and social validation impulsively (Lina et al., 2022). Decisions are frequently made in a hasty and emotional manner by individuals. The majority of individuals can easily recall or envision instances in which a poor decision resulted in painful regret; indeed, impulse purchases are widely recognized as a key source of post-decision remorse precisely because they bypass deliberate evaluation (Grigsby et al., 2021; Morozova & Vlaev, 2024).

Post-Purchase Regret Regret, which occurs after counterfactual thinking such as "if only I had…", is a negative emotion felt when a different purchasing choice might have led to a more favourable outcome (Rychalski & Hudson, 2017). The stronger emotional impulse and lower reasoning in impulsive buying decisions, the more likely the emotionally charged 'wrong' decisions will feel after the excitement is gone (Badgaiyan & Verma, 2015). For Generation Z, such relentless, digitally driven impulsive behaviour may lead to dissatisfaction, as well as other negative brand actions such as returning items and leaving bad reviews (Lisjak et al., 2015). According to prior research, there are numerous factors that contribute to post-purchase regret, including: consumer ethnocentrism (Dankwah et al., 2024), impulsive buying (Barta et al., 2023; Beikverdi et al., 2024; Sönmezay, 2023), brand betrayal (Sameeni et al., 2022), and Attractiveness of alternatives (Sarwar et al., 2020). Hypotheses Development Social Exclusion occurs when people perceive themselves as outsiders to their social circle (Williams & Nida, 2022). Social Exclusion can significantly impact individuals, resulting in emotional discomfort and cognitive disarray that may culminate in self-destructive conduct (Han, 2020). Several studies explain that Social Exclusion can increase online impulsive buying (Luo et al., 2021; Zhang et al., 2024). Young individuals may purchase items impulsively to conform to group norms, obtain social acceptance, or regain a sense of self-worth that has been diminished by Social Exclusion when organizations or social norms validate specific behaviors, such as consumerism (Mukti et al., 2024). However, this relationship is not universal. Zhang et al. (2024) show that self-control moderates the link between Social Exclusion and impulsive buying, so people with stronger self-control are less likely to respond impulsively to feelings of exclusion. Luo et al. (2021) report a similar moderation by risk preference, where risk- averse individuals display a weaker direct reaction to exclusion. Together, these findings imply that the direct path from Social Exclusion to impulsive buying depends on individual differences. In shoppertainment settings, where emotional arousal is constant and self-control may be depleted, the

Figure 1. Conceptual Model indirect route through FOMO (H6) likely becomes the dominant mechanism translating exclusion into impulsive purchases. H1: Social Exclusion has a positive and significant effect on online impulsive buying. Social Exclusion increases sensitivity to the social behaviours of people around them, especially on social media (Williams, 2007; Williams & Nida, 2022). The sense of being excluded from social situations is a driver of the fear of missing out (Przybylski et al., 2013). Social Exclusion amplifies the feeling of having inadequate information or experiences that ought to be shared within the individual's social circle (Bright & Logan, 2018). Thus, FOMO and Social Exclusion relate to emotional responses that indicate the loss of social connection (Elhai et al., 2016). H2: Social Exclusion has a positive and significant effect on FOMO. FOMO triggers a psychological urgency to engage in certain activities to attain and/or sustain social inclusion within a group, including purchase activities (Hussain et al., 2023). The incidence of FOMO has escalated due to the expansion of social media platforms and the incessant availability of information about individuals' activities and experiences (Alutaybi et al., 2020). These activities are performed without adequate justification, and rational alternatives are overlooked because the individual needs to alleviate the feeling of Social Exclusion emotionally. The pressure to purchase emotionally is more pronounced within the digital environment because promotional materials and information circulate rapidly (Bright & Logan, 2018). Hence, FOMO is a central motivator of online impulsive buying (Febrianty et al., 2025; Mudjiyanto et al., 2025; Verhagen & van Dolen, 2011). H3: FOMO has a positive and significant effect on Online Impulsive Buying. FOMO is the fear of missing out on the opportunity to acquire the products or services they desire (Kaddouhah, 2024). FOMO and emotional pressure purchase decisions are more likely to result in dissatisfaction and/or regret upon purchase (Çelik et al., 2019). Consumers feel societal pressure to make purchases even if they do not really need the product (Tandon et al., 2021). Regret can set in when buyers face reality after a purchase, realizing they made their decision with little thought (Zeelenberg & Pieters, 2007). Çelik et al. (2019) clarified that the post-purchasing regret of participants is influenced by their FOMO tendency. H4: FOMO has a positive and significant effect on PostPurchase Regret. Rook (1987) defines impulsive buying as a consumption decision made in a snap, without careful consideration. Most shoppers who make impulsive purchases regret them after the fact because they realize they did not meet their expectations (Rajagopal et al., 2019). Following an impulsive purchase, consumers may experience dissatisfaction, leading to emotions such as anger, guilt, and regret (Barta et al., 2023). Bakar et al. (2025) elucidated that when consumers

make online impulsive purchases, they experience feelings of regret regarding the quantity of money they have spent. H5: Online impulsive buying has a positive and significant effect on post-purchase regret. Indirectly, Social Exclusion might lead to impulsive online shopping. More recent works, however, recognize the importance of the fear of missing out (FOMO) in mediating the relationship between Social Exclusion and psychological variables (Febrianty et al., 2025). Socially excluded individuals often experience FOMO, and social FOMO motivates them to make impulsive online purchases (Przybylski et al., 2013). In this case, FOMO acts as a psychological conduit that drives social pressure to compulsive consumption (Hussain et al., 2023). Thus, the FOMO psychological effect, indirectly connected to Social Exclusion, highlights the mediating role of FOMO in the more online psychological consumptive behaviours. Because the direct link from Social Exclusion to impulsive online buying (H1) is theoretically complex, we propose the route through FOMO (H6) as the main mechanism explaining how feelings of exclusion lead to impulsive purchases in shoppertainment settings. In other words, Social Exclusion is expected to trigger FOMO, and that heightened FOMO then drives impulsive buying. H6: Social Exclusion has a positive and significant effect on Online Impulsive Buying through the mediation of FOMO. FOMO, as described in recent works, relates to impulsive buying and emotionally charged consumer behaviours that foster social attachment and lead to a loss of control over spending (Hussain et al., 2023). FOMO, when linked to impulsive purchases, tends to lead to negative consequences when purchase expectations are not met, thereby leading to regret (Zeelenberg & Pieters, 2007). Consequently, FOMO affects post-purchase regret indirectly through online impulsive buying (Tandon et al., 2021). People under FOMO do not take the time to assess their purchases rationally, and they experience an emotional realization—regret—when they buy dissatisfying products (Przybylski et al., 2013). This mediation indicates that impulsivity is the main pathway through which FOMO translates to post-purchase regret H7: FOMO has a positive and significant effect on PostPurchase Regret through the mediation of Online Impulsive Buying The following is the proposed research model in this study (see figure 1). This study aims to examine the associations among Social Exclusion, FOMO, online impulsive buying, and post-purchase regret among Generation Z users of shoppertainment platforms in Indonesia, with FOMO as a mediator between Social Exclusion and online impulsive buying, and online impulsive buying as a mediator between FOMO and post-purchase regret.

Methods Sample Sample characteristics based on data collected during the data collection period of July 1-14, 2025, covering 576 respondents, demonstrated a sharper and more representative demographic and behavioural profile (see Table 2). Age analysis showed that respondents aged 18 to 20 accounted for more than 90% of the sample. The 20-year-old age group represented the largest cohort of new respondents at 31.1%. The next largest age cohorts were 19 years at 23.1% and 22 years at 18.9%. There was one 29-year-old respondent, accounting for 0.2% of the survey and statistically insignificant. In the gender category, data consistently showed more female respondents (62.3%, 359) than male respondents (37.7%, 217), indicating a higher response rate from women. Almost half of the survey respondents (50.9%) reported a monthly income of 1 to 3 million Rupiah. Because 31.9% of respondents were in the lower income group of 0 to 1 million Table 2. Respondent Characteristics Characteristics Frequency % Age

18-22 519 90.10 23-25 54 9.38 26-29 3 0.50 Gender

Male 217 37.30 Female 359 62.30 Income

+3m 99 17.20 1-3m 293 50.90 0-1m 184 31.90 City

Makassar 342 59.40 Surabaya 55 9.50 Jakarta 38 6.70 Bandung 28 4.90 Medan 23 4.00 Manado 19 3.30 Samarinda 14 2.40 Bali 13 2.30 Semarang 5 0.90 Padang 2 0.30 Bulukumba 1 0.20 Solo 1 0.20 Sumbawa 1 0.20 Lampung 1 0.20 Bojonegoro 1 0.20 Bekasi 4 0.70 Malang 1 0.20 Yogyakarta 6 1.10 Palembang 1 0.20 Bandar Lampung 1 0.20 Cilacap 1 0.20 Bantul 2 0.30 Bogor 2 0.30 Denpasar 1 0.20 Jayapura 2 0.30 Kalimantan 2 0.30 Jawa Timur 1 0.20 Kendari 1 0.20 Tasikmalaya 1 0.20 Tangerang 1 0.20 Nabire 1 0.20 Sengkang 2 0.30 Pekanbaru 1 0.20 Palu 1 0.20 Platform

TikTok Shop 349 60.60 Tokopedia 5 0.90 Shopee Live 216 37.50 Others 6 1.20 Platform 576 Rupiah, it can be said that 82.8% of respondents have the spending power of university students and entry-level workers. Respondents were drawn from 35 cities across Indonesia, yet the sample is clearly skewed toward Makassar City, which accounts for 59.4% of cases. Other notable contributions came from Surabaya (9.5%) and Jakarta (6.7%). Although the dataset benefits from multi-city coverage, this geographic concentration warrants caution; extrapolating the

findings to other Indonesian cities should be done carefully and ideally validated with a more geographically balanced sample. The preference analysis showed a distinct inclination toward social commerce. TikTok Shop was by far the leading platform, favoured by 60.6% of respondents, and Shopee Live was chosen by 37.2%, with the two platforms together covering 97.8% of preferences. These results imply that the impulsive online shopping behaviours identified in this research occur almost entirely within the integrated spheres of entertainment, social interaction, and commerce. In this respect, traditional ecommerce platforms are virtually irrelevant. Overall, respondents could be characterized as young females (approximately 20 years old) from a major city, predominantly Makassar, with moderate to low purchasing power, and a strong preference for shoppertainment-style online shopping. Measurement This study uses four latent constructs, namely Social Exclusion (SE), Fear of Missing Out (FOMO), Online Impulsive Buying (OIB), and Post-Purchase Regret (PPR). Each variable is measured with multiple indicator items adapted from prior studies to maintain content validity. SE is captured using four items from Zhang et al. (2024). FOMO is measured with four items developed from the foundational work of Przybylski et al. (2013) and later validated in a consumption context by Mahena et al. (2025). OIB is assessed using four items adapted from Verhagen and van Dolen (2011) while PPR is measured with four items based on Zeelenberg and Pieters (2007). Because the respondents are Indonesian Gen Z users, all items were translated from English into Indonesian through a forward and back translation process to ensure conceptual equivalence. The initial translation was conducted by a bilingual researcher, then independently translated back by another bilingual researcher to confirm consistency with the original version. Minor adjustments in wording were applied to ensure clarity and natural expression in the Indonesian context without altering the meaning of each construct. All constructs in this study, SE, FOMO, OIB, and PPR, are specified as reflective measurement models, in line with their theoretical definition as latent variables whose indicators represent interchangeable manifestations of the same underlying concept (Hair et al., 2017). The measurement items used for each construct are summarized in Table 3. Each questionnaire item was measured using a 5-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). Analysis To analyze the quantitative data and test the complex hypothetical model in this study, we employed Structural Equation Modelling (SEM) using the Partial Least Squares (PLS) approach. The PLS-SEM approach was selected based on its suitability for prediction-oriented models, its capacity to handle complex structural paths without imposing normality assumptions, and its established application in consumer behaviour research (Hair et al., 2017). All data processing, statistical calculations, and hypothesis testing for this study were carried out via SmartPLS version 4. To reduce common method bias we assured respondent anonymity and interspersed items from different constructs throughout the questionnaire. As a statistical safeguard we followed Kock’s recommendation and checked full collinearity Variance Inflation Factor values for all indicators (Kock, 2015). Before analysis we screened the full set of 576 responses for missing data and outliers; none were excluded as all cases were complete and within acceptable ranges. Table 3. Variable and Indicators Variables Question Items References Social Exclusion I feel excluded from my friends' social media activities. (SE1) I often feel ignored by others on social media. (SE2) I feel unimportant to my community on social media. (SE3) I feel like my community on social media is avoiding me. (SE4) FOMO (Fear of Missing Out) I am afraid of missing out on popular social media trends. (F1) I feel anxious when I am not active on social media. (F2) I need to buy products because they are currently viral. (F3) I feel pressured when I see my friends buying new items I do not yet own. (F4) Online Impulsive Buying I often buy products spontaneously when I see them online. (OIB1) I buy items without much thought. (OIB2) I find it hard to resist the urge to shop online. (OIB3) I am tempted to buy products because they look attractive or are on sale. (OIB4) Post-Purchase Regret I regret buying a product impulsively. (PPR1) I should not have bought the product. (PPR2) I feel disappointed after buying the product. (PPR3) The money I spent on impulsive items should have been spent on something else. (PPR4) Result and Discussion Following the completion of data collection with 576 respondents, data analysis was conducted using the PLS approach. The analysis is performed in two stages: the measurement model evaluation and the structural model evaluation. In the first stage, the measurement model was evaluated to assess the validity and reliability of the constructs used in the study. The results of the validity and reliability tests are included in the table below (Table 4). As regards findings, the loading factor values for each research item ranged from 0.709 to 0.925. All of these values are above the threshold of 0.7, indicating strong indicator validity. In addition, the Average Variance Extracted (AVE) values for each variable ranged between 0.683 and 0.832, which means all values are above the acceptable minimum of 0.5. Therefore, the research instrument's convergent validity is established (Hair et al., 2017). As for the reliability test, the composite reliability (CR) values ranged from 0.895 to 0.952, which is excellent. The consistency of the high values of the Cronbach's Alpha, which ranged from 0.844 to 0.933, also helps in the reliability construct, which means that all of the CR and the Cronbach's Alpha values are above the 0.7 threshold and that the instruments used in the study are reliable (Hair et al., 2017). Discriminant validity was assessed using the HeterotraitMonotrait ratio (HTMT), as recommended by Henseler et al. (2015). As presented in Table 5, most HTMT values are below the threshold of 0.90. However, the HTMT value between FOMO and Online Impulsive Buying was 0.938, marginally exceeding the threshold. This overlap is theoretically anticipated given that FOMO is a direct and strong predictor of Online Impulsive Buying (β = 0.790, p < 0.001), and their conceptual proximity has been consistently documented in the literature (Febrianty et al., 2025; Mudjiyanto et al., 2025). The remaining HTMT values all fall below 0.90, confirming discriminant validity for the other construct pairs. To assess common method bias, full collinearity VIF values were examined for all indicators. As shown in Table 6, all VIF values ranged from 1.494 to 3.972, well below the accepted threshold of 5.0 (Hair et al., 2017), indicating that common method bias is unlikely to pose a serious concern in this dataset. The structural model refers to the process of testing the previously proposed hypotheses. This stage is used to

Adapted from Zhang et al. (2024) Adapted from Przybylski et al. (2013); Mahena et al. (2025) Adapted from Verhagen and van Dolen (2011) Adapted from Zeelenberg and Pieters (2007) examine the relationships between variables. Six of the seven proposed hypotheses were supported; H1 was not supported (see Table 7). The results of this study indicate that Social Exclusion does not have a significant effect on online impulsive buying, although the direction of the relationship is positive. Table 8 and Table 9 summarizes the structural model’s quality indicators. The R² values show the model explains 59.1% of the variance in FOMO, 67.8% in Online Impulsive Buying, and 38.0% in Post Purchase Regret, indicating moderate to substantial explanatory power (Hair et al., 2017). Blindfolding produced positive Q² values for all endogenous constructs: 0.442 for FOMO, 0.455 for Online Impulsive Buying, and 0.251 for Post Purchase Regret, confirming the model’s predictive relevance (Hair et al., 2017). Effect size estimates show a very large effect of Social Exclusion on FOMO with f² =1.446, and a large effect of FOMO on Online Impulsive Buying with f² = 0.792. In contrast, the effects of FOMO on Post Purchase Regret and of Online Impulsive Buying on Post Purchase Regret are small, with f² values of 0.062 and 0.047 respectively. The direct effect of Social Exclusion on Online Impulsive Buying is negligible, with f² = 0.002, which aligns with the non significant H1 (Hair et al., 2017). The non-significant direct link between Social Exclusion and Online Impulsive Buying (β = 0.042, p = 0.357, 95% CI [−0.045, 0.138]) is theoretically informative. It qualifies the simple compensatory consumption idea of Mandel et al. (2016), which assumes perceived social rejection automatically spurs purchases to mend the self. Two plausible mechanisms can account for this null finding. First, from a self regulatory perspective, social exclusion may raise vigilance and deliberation rather than impulsivity. When exclusion increases perceived risk, people may monitor their choices more closely and act with greater caution, especially for decisions with financial consequences (Luo et al., 2021; Zhang et al., 2024). In this sense, Social Exclusion works as a cognitive brake, not an accelerant, for impulse buying. Second, and consistent with the mediation results, exclusion may need to amplify emotion, specifically by heightening FOMO, before it leads to impulsive purchases. The indirect effect through FOMO is large and statistically significant (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]), which supports the idea that FOMO is the psychological conduit translating exclusion into impulsive behaviour. These two accounts are compatible rather than mutually exclusive. A strengthened self regulatory response can suppress any direct effect of exclusion, while the FOMOTable 4. Measurement Model Result Construct Item Code Item Loading CR CA AVE Fear of Missing Out F1 0.865 0.925 0.892 0.755

F2 0.838

F3 0.883

F4 0.883

Online Impulsive Buying OIB1 0.859 0.895 0.844 0.683

OIB2 0.855

OIB3 0.871

OIB4 0.709

Post Purchase Regret PPR1 0.850 0.896 0.847 0.684

PPR2 0.860

PPR3 0.852

PPR4 0.740

Social Exclusion SE1 0.894 0.952 0.933 0.832

SE2 0.925

SE3 0.915

SE4 0.915 Table 5. Heterotrait-Monotrait Ratio (HTMT) Construct FOMO OIB PPR SE FOMO —

OIB 0.938 —

PPR 0.664 0.678 —

SE 0.841 0.717 0.621 — Table 6. Collinearity Statistics (VIF) Indicator VIF F1 2.347 F2 2.106 F3 2.782 F4 2.704 OIB1 2.146 OIB2 2.185 OIB3 2.226 OIB4 1.494 PPR1 2.026 PPR2 2.187 PPR3 1.971 PPR4 1.628 SE1 2.954 SE2 3.972 SE3 3.606 SE4 3.503 mediated route remains operative. Finally, because these results come from cross sectional data, they should be read as statistical associations rather than causal claims. Longitudinal or experimental designs are needed to establish directionality. The analysis reveals a strong positive link between Social Exclusion and FOMO, β = 0.769, t = 38.685, p < 0.001, 95% CI [0.729, 0.807], f² = 1.446. This result echoes prior work showing that perceived ostracism amplifies sensitivity to social cues and the urge to stay connected (Elhai et al., 2016; Williams & Nida, 2022). When people feel left out of peers’ activities they pay closer attention to signals that others are enjoying experiences from which they are absent, and shoppertainment environments magnify that effect. Livestream services such as TikTok Shop and Shopee Live broadcast real-time viewer counts, social reactions, and host demonstrations that continuously signal communal consumption (Lo et al., 2022; Nuraisah et al., 2024). For socially excluded Gen Z users whose sense of self is tied to digital participation, these live cues deepen the feeling of being left out and so intensify FOMO. The finding also

sharpens theory: Przybylski (2013) framed FOMO as a relatively stable disposition, a chronic worry that others enjoy rewarding experiences (Przybylski et al., 2013). In shoppertainment settings that dispositional baseline becomes a situationally triggered emotional state that peaks during live events, driven by real-time scarcity signals, countdowns, and visible social proof of co-viewers purchasing (Qu et al., 2023). In short, Social Exclusion raises dispositional sensitivity and makes users particularly vulnerable to this situational FOMO, a mechanism that differs from conventional e-commerce where real-time social comparison cues are absent. FOMO shows a very strong positive link with Online Impulsive Buying in this sample, confirming it as the immediate driver of impulsive purchases (β = 0.790, p < 0.001, 95% CI[0.702, 0.867]; f² = 0.792, large). This finding matches a growing set of Indonesian studies (Febrianty et al., 2025; Mahena et al., 2025; Mudjiyanto et al., 2025) and extends that evidence into the live-stream commerce context. The process fits Hussain et al. (2023), who argue that FOMO generates a psychological urgency to obtain socially validated products, circumventing the careful cost–benefit thinking that underpins planned purchases. On shoppertainment platforms, that urgency is built into the environment: flash-sale timers, hosts announcing limited stock, and visible waves of co-viewer purchases create scarcity and social proof, which speed the conversion of FOMO into unplanned buying (Lo et al., 2022). The very large effect size here suggests shoppertainment is markedly more potent than conventional e-commerce or offline retail in turning FOMO into impulse purchases, and it calls for focused scholarly attention on live-stream affordances (Nuraisah et al., 2024). The positive link between FOMO and post-purchase regret (β = 0.344, p < 0.001, 95% CI [0.209, 0.470]) reveals a structural irony in shoppertainment. The same emotional urgency that pushes someone to buy so they do not miss out also creates the conditions for later regret. Purchases driven by FOMO are often motivated by a desire to join a fleeting social moment rather than by real need or clear value. After the live event ends and the social cues fade, buyers tend to re-evaluate what they bought against ordinary criteria, which invites counterfactual thinking such as “if only I had not bought this,” and that process fuels regret (Zeelenberg & Pieters, 2007). At the same time, the effect size is small though significant (f² = 0.062), which suggests that post-purchase regret is shaped by many factors. FOMO contributes directly, but other elements also matter, including product quality, social comparison after purchase, and financial strain. Prior research supports this broader view: Wegmann et al. (2017)

Table 7. Hypothesis Testing Results H Relationships β t-stat p 95% CI Remarks H1 Social Exclusion -> Online Impulsive Buying 0.042 0.921 0.357 [-0.045, 0.138] Rejected H2 Social Exclusion -> FOMO 0.769 38.685 <0.001 [0.729, 0.807] Accepted H3 FOMO -> Online Impulsive Buying 0.790 18.777 <0.001 [0.702, 0.867] Accepted H4 FOMO -> Post-Purchase Regret 0.344 5.151 <0.001 [0.209, 0.470] Accepted H5 Online Impulsive Buying -> Post-Purchase Regret 0.301 4.162 <0.001 [0.160, 0.441] Accepted H6 Social Exclusion -> FOMO -> Online Impulsive Buying 0.608 17.534 <0.001 [0.538, 0.674] Accepted H7 FOMO -> Online Impulsive Buying -> PostPurchase Regret 0.238 4.203 <0.001 [0.127, 0.348] Accepted Table 8. R², R²adj, and Q² Construct R² R²adj Q² Interpretation FOMO 0.591 0.590 0.442 Moderate Online Impulsive Buying 0.678 0.677 0.455 Moderate PostPurchase Regret 0.380 0.378 0.251 Moderate Table 9. Effect Size (f²) Construct R² R²adj SE → FOMO 1.446 Large FOMO → OIB 0.792 Large FOMO → PPR 0.062 Small OIB → PPR 0.047 Small SE → OIB 0.002 Negligible show that FOMO-driven online engagement can produce negative affective outcomes, such as dissatisfaction and regret, when the anticipated social reward does not persist. In short, FOMO is an important piece of the regret puzzle in shoppertainment, but it operates within a wider affective and evaluative process. The positive link between Online Impulsive Buying and Post-Purchase Regret (β = 0.301, p < 0.001, 95% CI [0.160, 0.441]) fits with prior evidence showing that rapid, emotiondriven purchase decisions weaken the buyer’s ability to justify the choice afterward, and thereby raise the chance of regret (Barta et al., 2023; Beikverdi et al., 2024; Sönmezay, 2023). Grigsby et al. (2021) argue that impulsive shoppers feel more regret because they lack the deliberative time and resources needed to form forward-looking rationalizations. In shoppertainment, the contrast between the excitement of a live event and the calmer post-stream state makes that mismatch especially stark, so Generation Z users may discover after the fact that the purchase does not meet a real need (Bakar et al., 2025; Qu et al., 2023). The small effect size (f² = 0.047) suggests impulsive buying is only one of several contributors to regret, and that individual factors like financial literacy, self-control, and product involvement likely moderate the link. The very large and significant indirect path from Social Exclusion to Online Impulsive Buying via FOMO (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]) alongside a negligible direct path (β = 0.042, f² = 0.002) implies a mediation pattern in which FOMO is the key psychological channel. In other words, social exclusion seems to fuel situational FOMO, and that heightened FOMO, not exclusion itself, drives impulsive purchases. Shoppertainment platforms are especially fertile for this mechanism because real-time social proof and urgency cues translate abstract feelings of exclusion into an immediate opportunity to rejoin a social moment through buying (Lo et al., 2022; Nuraisah et al., 2024). Finally, the indirect route from FOMO to Post-Purchase Regret through Online Impulsive Buying (β = 0.238, p < 0.001, 95% CI [0.127, 0.348]) shows that impulsivity is a

consequential intermediate step. When FOMO shortens deliberation time as shoppertainment mechanics are designed to do, consumers skip the prospective checks that might prevent regret later (Grigsby et al., 2021). Because FOMO also has a direct effect on regret, the pattern creates a potential feedback loop: FOMO prompts impulsive buying, impulsive buying fuels regret, and regret may in turn alter future vulnerability to FOMO as consumers try to repair perceived poor choices (Tandon et al., 2021).

Conclusion This study examined the associations among Social Exclusion, Fear of Missing Out (FOMO), Online Impulsive Buying, and Post-Purchase Regret among 576 Generation Z users of shoppertainment platforms in Indonesia, analyzed using PLS-SEM with 5,000 bootstrap resamples. Six of the seven hypothesised associations were statistically supported. Social Exclusion was strongly and positively associated with FOMO (β = 0.769, p < 0.001), while its direct association with Online Impulsive Buying was non-significant (β = 0.042, p = 0.357). FOMO was positively associated with both Online Impulsive Buying (β = 0.790, p < 0.001) and Post-Purchase Regret (β = 0.344, p < 0.001). Online Impulsive Buying was positively associated with Post-Purchase Regret (β = 0.301, p < 0.001). FOMO fully mediated the association between Social Exclusion and Online Impulsive Buying (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]), and Online Impulsive Buying partially mediated the association between FOMO and Post-Purchase Regret (β = 0.238, p < 0.001, 95% CI [0.127, 0.348]). In addition, FOMO has a positive, direct impact on regretting a purchase and on impulsive buying. Social exclusion and the social pressure embedded in shoppertainment environments jointly intensify FOMO, which in turn increases unplanned buying and the likelihood of post-purchase regret. Digital impulse buying during Social Exclusion, particularly among Gen Z, is primarily driven by emotional impulses and socialrelational online networks. Thus, FOMO serves as the central emotional bridge through which social exclusion is converted into impulsive consumption, with post-purchase dissatisfaction as its downstream consequence. There are multiple theoretical advancements that can be explained in scholarly articles for consumer psychology and digital behavior. First, the fact that Social Exclusion directly and positively but non-significantly affects online impulsive buying, while significantly influencing it indirectly, especially through FOMO, helps explain the indirect emotional mechanisms in the consumer's decision. This result refines the compensatory consumption pathway proposed by Mandel et al. (2016), showing that the effect of social exclusion on impulsive buying hinges on FOMO as a necessary psychological mediator. The dependency is most pronounced in shoppertainment contexts, where platform features like real-time social cues, countdown timers, and scarcity signals repeatedly trigger situational FOMO (Lo et al., 2022; Nuraisah et al., 2024). Second, our demonstration of FOMO in the Social Exclusionimpulsive buying relationship expands the theoretical research on the psychology behind online impulsive consumption. Prior research treated FOMO as a basic emotion, but our study evidences that FOMO mediates translating Social Exclusion into an impulsive purchase. These findings are consistent with Wegmann et al. (2017), who found that FOMO-driven online engagement forecasts short-term consumption and brings negative emotions like regret. The added value of this study is that it ties together a specific platform context, shoppertainment, a defined cohort, Generation Z in Indonesia, and the full psychological chain from social exclusion via FOMO to impulsive buying and post-purchase regret. That particular combination has not been examined in the extant literature. These results offer concrete guidance for platform designers, brand managers, and policymakers. Because social exclusion drives impulsive buying mainly by increasing fear of missing out, interventions that reduce FOMO will likely work better than those that only target exclusion. Ethical concerns are crucial. Features that amplify FOMO, such as countdown timers, live viewer counts, and scarcity cues, may boost impulse sales but also increase post purchase regret, so designing to provoke FOMO imposes a real psychological cost on users. Responsible platforms should protect consumer agency by providing optional cooling off prompts before confirming live stream purchases, clearly distinguishing genuine scarcity from manufactured scarcity, simplifying refund and return procedures to reduce the sense of irreversibility, and sending post purchase reassurance messages to strengthen confidence in buyers’ decisions (Hussain et al., 2023). For brand managers, shoppertainment tactics that exploit exclusion sensitivity and FOMO can raise short term sales but risk eroding long term brand trust, especially given the regret cycle identified in H7. A more sustainable way to engage Generation Z is to build authentic communities that meet belonging needs directly, rather than exploiting the gap between belonging and exclusion. This study was not without its limitations. The first issue was geographical location. Makassar City accounted for over half (59.4%) of the participants, which constrains generalisation to other Indonesian urban markets with different consumption cultures, income profiles, and digital platform penetration patterns. The second issue stemmed from the data collection approach, which, in this case, was an online self-report questionnaire with possible value-laden responses. Although procedural safeguards were applied and full collinearity VIF values confirmed that common method bias is unlikely to be a serious concern in this dataset (Kock, 2015), temporally separating predictor and criterion measurement in future work would provide a stronger safeguard. Furthermore, the research did not incorporate selfcontrol, emotional regulation, and other personality factors, which, in the authors' view, are crucial and interrelated to the study of impulse buying. The cross-sectional design also References Alutaybi, A., Al-Thani, D., McAlaney, J., & Ali, R. (2020). Combating Fear of Missing Out (FoMO) on Social Media: The FoMO-R Method. International Journal of Environmental Research and Public Health, 17(17), 1–28. https://doi.org/10.3390/ijerph17176128 Ardyan, E., & Sanapang, G. M. (2023). Online Compulsive Buying and Brand Addiction in Indonesia: The Importance of Using Fear of Missing Out and Social Commerce Interactivity. 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precludes causal interpretation; the reported associations are statistical in nature, and longitudinal or experimental designs are required to establish temporal ordering. Lastly, the research was limited to only a handful of platforms, such as TikTok Shop and Shopee Live. Therefore, the findings should be generalized to other e-commerce platforms with caution. These limitations point to the need to incorporate a broader timeframe in future research to capture the emotional dynamics that are likely to change over time around the purchase. Longitudinal designs with multiple measurement waves, or experimental manipulations that activate social exclusion under controlled conditions, would allow causal claims to be tested more rigorously. Future research should also conduct multi-group analyses comparing structural paths between Makassar and metropolitan centres such as Jakarta and Surabaya to determine whether the mechanisms identified here operate uniformly across Indonesia's diverse urban landscape. Future research should also expand the geographical scope and include more psychological parameters to provide a fuller picture of consumers' digitally driven decision-making. This study provides an essential piece in understanding Generation Z consumption behaviour while also highlighting to industry stakeholders, policymakers, and academics the importance of developing a more balanced and sustainable digital ecosystem.

Author Contributions

Amdar Amdar conceptualized the study, developed the research framework, designed the research instrument, conducted data collection, performed data analysis using SmartPLS 4, and prepared the original manuscript draft. Elia Ardyan contributed to the refinement of the research methodology, validated the conceptual model, supervised the data analysis process, critically interpreted the findings, and reviewed and edited the manuscript for important intellectual content. All authors have read and approved the final version of the manuscript and agree to be accountable for all aspects of the work.

Acknowledgements

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References

Social Exclusion I feel excluded from my friends' social media activities. (SE1) I often feel ignored by others on social media. (SE2) I feel unimportant to my community on social media. (SE3) I feel like my community on social media is avoiding me. (SE4) FOMO (Fear of Missing Out) I am afraid of missing out on popular social media trends. (F1) I feel anxious when I am not active on social media. (F2) I need to buy products because they are currently viral. (F3) I feel pressured when I see my friends buying new items I do not yet own. (F4) Online Impulsive Buying I often buy products spontaneously when I see them online. (OIB1) I buy items without much thought. (OIB2) I find it hard to resist the urge to shop online. (OIB3) I am tempted to buy products because they look attractive or are on sale. (OIB4) Post-Purchase Regret I regret buying a product impulsively. (PPR1) I should not have bought the product. (PPR2) I feel disappointed after buying the product. (PPR3) The money I spent on impulsive items should have been spent on something else. (PPR4) Result and Discussion Following the completion of data collection with 576 respondents, data analysis was conducted using the PLS approach. The analysis is performed in two stages: the measurement model evaluation and the structural model evaluation. In the first stage, the measurement model was evaluated to assess the validity and reliability of the constructs used in the study. The results of the validity and reliability tests are included in the table below (Table 4). As regards findings, the loading factor values for each research item ranged from 0.709 to 0.925. All of these values are above the threshold of 0.7, indicating strong indicator validity. In addition, the Average Variance Extracted (AVE) values for each variable ranged between 0.683 and 0.832, which means all values are above the acceptable minimum of 0.5. Therefore, the research instrument's convergent validity is established (Hair et al., 2017). As for the reliability test, the composite reliability (CR) values ranged from 0.895 to 0.952, which is excellent. The consistency of the high values of the Cronbach's Alpha, which ranged from 0.844 to 0.933, also helps in the reliability construct, which means that all of the CR and the Cronbach's Alpha values are above the 0.7 threshold and that the instruments used in the study are reliable (Hair et al., 2017). Discriminant validity was assessed using the HeterotraitMonotrait ratio (HTMT), as recommended by Henseler et al. (2015). As presented in Table 5, most HTMT values are below the threshold of 0.90. However, the HTMT value between FOMO and Online Impulsive Buying was 0.938, marginally exceeding the threshold. This overlap is theoretically anticipated given that FOMO is a direct and strong predictor of Online Impulsive Buying (β = 0.790, p < 0.001), and their conceptual proximity has been consistently documented in the literature (Febrianty et al., 2025; Mudjiyanto et al., 2025). The remaining HTMT values all fall below 0.90, confirming discriminant validity for the other construct pairs. To assess common method bias, full collinearity VIF values were examined for all indicators. As shown in Table 6, all VIF values ranged from 1.494 to 3.972, well below the accepted threshold of 5.0 (Hair et al., 2017), indicating that common method bias is unlikely to pose a serious concern in this dataset. The structural model refers to the process of testing the previously proposed hypotheses. This stage is used to Adapted from Zhang et al. (2024) Adapted from Przybylski et al. (2013); Mahena et al. (2025) Adapted from Verhagen and van Dolen (2011) Adapted from Zeelenberg and Pieters (2007) examine the relationships between variables. Six of the seven proposed hypotheses were supported; H1 was not supported (see Table 7). The results of this study indicate that Social Exclusion does not have a significant effect on online impulsive buying, although the direction of the relationship is positive. Table 8 and Table 9 summarizes the structural model’s quality indicators. The R² values show the model explains 59.1% of the variance in FOMO, 67.8% in Online Impulsive Buying, and 38.0% in Post Purchase Regret, indicating moderate to substantial explanatory power (Hair et al., 2017). Blindfolding produced positive Q² values for all endogenous constructs: 0.442 for FOMO, 0.455 for Online Impulsive Buying, and 0.251 for Post Purchase Regret, confirming the model’s predictive relevance (Hair et al., 2017). Effect size estimates show a very large effect of Social Exclusion on FOMO with f² =1.446, and a large effect of FOMO on Online Impulsive Buying with f² = 0.792. In contrast, the effects of FOMO on Post Purchase Regret and of Online Impulsive Buying on Post Purchase Regret are small, with f² values of 0.062 and 0.047 respectively. The direct effect of Social Exclusion on Online Impulsive Buying is negligible, with f² = 0.002, which aligns with the non significant H1 (Hair et al., 2017). The non-significant direct link between Social Exclusion and Online Impulsive Buying (β = 0.042, p = 0.357, 95% CI [−0.045, 0.138]) is theoretically informative. It qualifies the simple compensatory consumption idea of Mandel et al. (2016), which assumes perceived social rejection automatically spurs purchases to mend the self. Two plausible mechanisms can account for this null finding. First, from a self regulatory perspective, social exclusion may raise vigilance and deliberation rather than impulsivity. When exclusion increases perceived risk, people may monitor their choices more closely and act with greater caution, especially for decisions with financial consequences (Luo et al., 2021; Zhang et al., 2024). In this sense, Social Exclusion works as a cognitive brake, not an accelerant, for impulse buying. Second, and consistent with the mediation results, exclusion may need to amplify emotion, specifically by heightening FOMO, before it leads to impulsive purchases. The indirect effect through FOMO is large and statistically significant (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]), which supports the idea that FOMO is the psychological conduit translating exclusion into impulsive behaviour. These two accounts are compatible rather than mutually exclusive. A strengthened self regulatory response can suppress any direct effect of exclusion, while the FOMOTable 4. Measurement Model Result Construct Item Code Item Loading CR CA AVE Fear of Missing Out F1 0.865 0.925 0.892 0.755 F2 0.838 F3 0.883 F4 0.883 Online Impulsive Buying OIB1 0.859 0.895 0.844 0.683 OIB2 0.855 OIB3 0.871 OIB4 0.709 Post Purchase Regret PPR1 0.850 0.896 0.847 0.684 PPR2 0.860 PPR3 0.852 PPR4 0.740 Social Exclusion SE1 0.894 0.952 0.933 0.832 SE2 0.925 SE3 0.915 SE4 0.915 Table 5. Heterotrait-Monotrait Ratio (HTMT) Construct FOMO OIB PPR SE FOMO — OIB 0.938 — PPR 0.664 0.678 — SE 0.841 0.717 0.621 — Table 6. Collinearity Statistics (VIF) Indicator VIF F1 2.347 F2 2.106 F3 2.782 F4 2.704 OIB1 2.146 OIB2 2.185 OIB3 2.226 OIB4 1.494 PPR1 2.026 PPR2 2.187 PPR3 1.971 PPR4 1.628 SE1 2.954 SE2 3.972 SE3 3.606 SE4 3.503 mediated route remains operative. Finally, because these results come from cross sectional data, they should be read as statistical associations rather than causal claims. Longitudinal or experimental designs are needed to establish directionality. The analysis reveals a strong positive link between Social Exclusion and FOMO, β = 0.769, t = 38.685, p < 0.001, 95% CI [0.729, 0.807], f² = 1.446. This result echoes prior work showing that perceived ostracism amplifies sensitivity to social cues and the urge to stay connected (Elhai et al., 2016; Williams & Nida, 2022). When people feel left out of peers’ activities they pay closer attention to signals that others are enjoying experiences from which they are absent, and shoppertainment environments magnify that effect. Livestream services such as TikTok Shop and Shopee Live broadcast real-time viewer counts, social reactions, and host demonstrations that continuously signal communal consumption (Lo et al., 2022; Nuraisah et al., 2024). For socially excluded Gen Z users whose sense of self is tied to digital participation, these live cues deepen the feeling of being left out and so intensify FOMO. The finding also sharpens theory: Przybylski (2013) framed FOMO as a relatively stable disposition, a chronic worry that others enjoy rewarding experiences (Przybylski et al., 2013). In shoppertainment settings that dispositional baseline becomes a situationally triggered emotional state that peaks during live events, driven by real-time scarcity signals, countdowns, and visible social proof of co-viewers purchasing (Qu et al., 2023). In short, Social Exclusion raises dispositional sensitivity and makes users particularly vulnerable to this situational FOMO, a mechanism that differs from conventional e-commerce where real-time social comparison cues are absent. FOMO shows a very strong positive link with Online Impulsive Buying in this sample, confirming it as the immediate driver of impulsive purchases (β = 0.790, p < 0.001, 95% CI[0.702, 0.867]; f² = 0.792, large). This finding matches a growing set of Indonesian studies (Febrianty et al., 2025; Mahena et al., 2025; Mudjiyanto et al., 2025) and extends that evidence into the live-stream commerce context. The process fits Hussain et al. (2023), who argue that FOMO generates a psychological urgency to obtain socially validated products, circumventing the careful cost–benefit thinking that underpins planned purchases. On shoppertainment platforms, that urgency is built into the environment: flash-sale timers, hosts announcing limited stock, and visible waves of co-viewer purchases create scarcity and social proof, which speed the conversion of FOMO into unplanned buying (Lo et al., 2022). The very large effect size here suggests shoppertainment is markedly more potent than conventional e-commerce or offline retail in turning FOMO into impulse purchases, and it calls for focused scholarly attention on live-stream affordances (Nuraisah et al., 2024). The positive link between FOMO and post-purchase regret (β = 0.344, p < 0.001, 95% CI [0.209, 0.470]) reveals a structural irony in shoppertainment. The same emotional urgency that pushes someone to buy so they do not miss out also creates the conditions for later regret. Purchases driven by FOMO are often motivated by a desire to join a fleeting social moment rather than by real need or clear value. After the live event ends and the social cues fade, buyers tend to re-evaluate what they bought against ordinary criteria, which invites counterfactual thinking such as “if only I had not bought this,” and that process fuels regret (Zeelenberg & Pieters, 2007). At the same time, the effect size is small though significant (f² = 0.062), which suggests that post-purchase regret is shaped by many factors. FOMO contributes directly, but other elements also matter, including product quality, social comparison after purchase, and financial strain. Prior research supports this broader view: Wegmann et al. (2017) Table 7. Hypothesis Testing Results H Relationships β t-stat p 95% CI Remarks H1 Social Exclusion -> Online Impulsive Buying 0.042 0.921 0.357 [-0.045, 0.138] Rejected H2 Social Exclusion -> FOMO 0.769 38.685 <0.001 [0.729, 0.807] Accepted H3 FOMO -> Online Impulsive Buying 0.790 18.777 <0.001 [0.702, 0.867] Accepted H4 FOMO -> Post-Purchase Regret 0.344 5.151 <0.001 [0.209, 0.470] Accepted H5 Online Impulsive Buying -> Post-Purchase Regret 0.301 4.162 <0.001 [0.160, 0.441] Accepted H6 Social Exclusion -> FOMO -> Online Impulsive Buying 0.608 17.534 <0.001 [0.538, 0.674] Accepted H7 FOMO -> Online Impulsive Buying -> PostPurchase Regret 0.238 4.203 <0.001 [0.127, 0.348] Accepted Table 8. R², R²adj, and Q² Construct R² R²adj Q² Interpretation FOMO 0.591 0.590 0.442 Moderate Online Impulsive Buying 0.678 0.677 0.455 Moderate PostPurchase Regret 0.380 0.378 0.251 Moderate Table 9. Effect Size (f²) Construct R² R²adj SE → FOMO 1.446 Large FOMO → OIB 0.792 Large FOMO → PPR 0.062 Small OIB → PPR 0.047 Small SE → OIB 0.002 Negligible show that FOMO-driven online engagement can produce negative affective outcomes, such as dissatisfaction and regret, when the anticipated social reward does not persist. In short, FOMO is an important piece of the regret puzzle in shoppertainment, but it operates within a wider affective and evaluative process. The positive link between Online Impulsive Buying and Post-Purchase Regret (β = 0.301, p < 0.001, 95% CI [0.160, 0.441]) fits with prior evidence showing that rapid, emotiondriven purchase decisions weaken the buyer’s ability to justify the choice afterward, and thereby raise the chance of regret (Barta et al., 2023; Beikverdi et al., 2024; Sönmezay, 2023). Grigsby et al. (2021) argue that impulsive shoppers feel more regret because they lack the deliberative time and resources needed to form forward-looking rationalizations. In shoppertainment, the contrast between the excitement of a live event and the calmer post-stream state makes that mismatch especially stark, so Generation Z users may discover after the fact that the purchase does not meet a real need (Bakar et al., 2025; Qu et al., 2023). The small effect size (f² = 0.047) suggests impulsive buying is only one of several contributors to regret, and that individual factors like financial literacy, self-control, and product involvement likely moderate the link. The very large and significant indirect path from Social Exclusion to Online Impulsive Buying via FOMO (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]) alongside a negligible direct path (β = 0.042, f² = 0.002) implies a mediation pattern in which FOMO is the key psychological channel. In other words, social exclusion seems to fuel situational FOMO, and that heightened FOMO, not exclusion itself, drives impulsive purchases. Shoppertainment platforms are especially fertile for this mechanism because real-time social proof and urgency cues translate abstract feelings of exclusion into an immediate opportunity to rejoin a social moment through buying (Lo et al., 2022; Nuraisah et al., 2024). Finally, the indirect route from FOMO to Post-Purchase Regret through Online Impulsive Buying (β = 0.238, p < 0.001, 95% CI [0.127, 0.348]) shows that impulsivity is a consequential intermediate step. When FOMO shortens deliberation time as shoppertainment mechanics are designed to do, consumers skip the prospective checks that might prevent regret later (Grigsby et al., 2021). Because FOMO also has a direct effect on regret, the pattern creates a potential feedback loop: FOMO prompts impulsive buying, impulsive buying fuels regret, and regret may in turn alter future vulnerability to FOMO as consumers try to repair perceived poor choices (Tandon et al., 2021). Conclusion This study examined the associations among Social Exclusion, Fear of Missing Out (FOMO), Online Impulsive Buying, and Post-Purchase Regret among 576 Generation Z users of shoppertainment platforms in Indonesia, analyzed using PLS-SEM with 5,000 bootstrap resamples. Six of the seven hypothesised associations were statistically supported. Social Exclusion was strongly and positively associated with FOMO (β = 0.769, p < 0.001), while its direct association with Online Impulsive Buying was non-significant (β = 0.042, p = 0.357). FOMO was positively associated with both Online Impulsive Buying (β = 0.790, p < 0.001) and Post-Purchase Regret (β = 0.344, p < 0.001). Online Impulsive Buying was positively associated with Post-Purchase Regret (β = 0.301, p < 0.001). FOMO fully mediated the association between Social Exclusion and Online Impulsive Buying (β = 0.608, p < 0.001, 95% CI [0.538, 0.674]), and Online Impulsive Buying partially mediated the association between FOMO and Post-Purchase Regret (β = 0.238, p < 0.001, 95% CI [0.127, 0.348]). In addition, FOMO has a positive, direct impact on regretting a purchase and on impulsive buying. Social exclusion and the social pressure embedded in shoppertainment environments jointly intensify FOMO, which in turn increases unplanned buying and the likelihood of post-purchase regret. Digital impulse buying during Social Exclusion, particularly among Gen Z, is primarily driven by emotional impulses and socialrelational online networks. Thus, FOMO serves as the central emotional bridge through which social exclusion is converted into impulsive consumption, with post-purchase dissatisfaction as its downstream consequence. There are multiple theoretical advancements that can be explained in scholarly articles for consumer psychology and digital behavior. First, the fact that Social Exclusion directly and positively but non-significantly affects online impulsive buying, while significantly influencing it indirectly, especially through FOMO, helps explain the indirect emotional mechanisms in the consumer's decision. This result refines the compensatory consumption pathway proposed by Mandel et al. (2016), showing that the effect of social exclusion on impulsive buying hinges on FOMO as a necessary psychological mediator. The dependency is most pronounced in shoppertainment contexts, where platform features like real-time social cues, countdown timers, and scarcity signals repeatedly trigger situational FOMO (Lo et al., 2022; Nuraisah et al., 2024). Second, our demonstration of FOMO in the Social Exclusionimpulsive buying relationship expands the theoretical research on the psychology behind online impulsive consumption. Prior research treated FOMO as a basic emotion, but our study evidences that FOMO mediates translating Social Exclusion into an impulsive purchase. These findings are consistent with Wegmann et al. (2017), who found that FOMO-driven online engagement forecasts short-term consumption and brings negative emotions like regret. The added value of this study is that it ties together a specific platform context, shoppertainment, a defined cohort, Generation Z in Indonesia, and the full psychological chain from social exclusion via FOMO to impulsive buying and post-purchase regret. That particular combination has not been examined in the extant literature. These results offer concrete guidance for platform designers, brand managers, and policymakers. Because social exclusion drives impulsive buying mainly by increasing fear of missing out, interventions that reduce FOMO will likely work better than those that only target exclusion. Ethical concerns are crucial. Features that amplify FOMO, such as countdown timers, live viewer counts, and scarcity cues, may boost impulse sales but also increase post purchase regret, so designing to provoke FOMO imposes a real psychological cost on users. Responsible platforms should protect consumer agency by providing optional cooling off prompts before confirming live stream purchases, clearly distinguishing genuine scarcity from manufactured scarcity, simplifying refund and return procedures to reduce the sense of irreversibility, and sending post purchase reassurance messages to strengthen confidence in buyers’ decisions (Hussain et al., 2023). For brand managers, shoppertainment tactics that exploit exclusion sensitivity and FOMO can raise short term sales but risk eroding long term brand trust, especially given the regret cycle identified in H7. A more sustainable way to engage Generation Z is to build authentic communities that meet belonging needs directly, rather than exploiting the gap between belonging and exclusion. This study was not without its limitations. The first issue was geographical location. Makassar City accounted for over half (59.4%) of the participants, which constrains generalisation to other Indonesian urban markets with different consumption cultures, income profiles, and digital platform penetration patterns. The second issue stemmed from the data collection approach, which, in this case, was an online self-report questionnaire with possible value-laden responses. 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