The Relationship Between Shopping Environment Factors Via Livestreams and Customers' Impulsive Buying Behavior Invietnam: TheModerating of Impulsive Buying Trendency

The Relationship Between Shopping Environment Factors Via Livestreams and Customers' Impulsive Buying Behavior Invietnam: TheModerating of Impulsive Buying Trendency | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Relationship Between Shopping Environment Factors Via Livestreams and Customers' Impulsive Buying Behavior Invietnam: TheModerating of Impulsive Buying Trendency Van Dat Tran, Cong Truong Huynh Le This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6877937/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Objectives Based on the synthesis of background theory, research concepts and related research articles, the research has built a research model on the relationship between shopping environment factors via livestreams and customers' impulsive buying behavior in Vietnam. Methods The research was conducted with data collected from 522 customers shopping for goods via livestreams on the platforms TikTok, Facebook, and Shopee. Results The results showed that the theoretical research model was consistent with the market data, and the results of testing 14 hypotheses were all accepted. The results of the SEM linear structural model testing showed that the environmental factors of shopping through livestreams, including scarcity and vicarious experience, had a positive impact on cognitive reactions; scarcity, vicarious experience, social interaction, social contagion, social presence of livestreams, social presence of viewers, and social presence of products had a positive impact on affective reactions. Cognitive reactions had a positive impact on affective reactions, affective reactions had a positive impact on impulsive buying urge, impulsive buying urge had a positive impact on impulsive buying behavior. Finally, the results of the moderator variable test showed that there is an impact of the moderator variable impulsive buying tendency on the impact of affective reactions to impulsive buying urge and an impact of the moderator variable impulsive buying tendency on the impact of impulsive buying urge on impulsive buying urge behavior. Conclusions Based on the research results, the author gives managerial implications to enhance customers' impulsive shopping behavior through livestreams. Shopping environment factors through livestreams cognitive reactions affective reactions impulsive buying urge impulsive buying behavior impulsive buying tendency Figures Figure 1 1. Introduction Livestreaming is becoming an effective business tool on social media and e-commerce platforms, enhancing the shopping experience thanks to its real-time interaction capabilities. This format is superior to traditional social commerce by allowing online sellers to showcase products in live videos and answer customer questions immediately (Ang et al., 2018 ; Forrester et al., 2021). Two-way simultaneous interaction is created between sellers and customers through live chat (Kang et al., 2021 ). From there, livestreaming has the ability to stimulate emotional consumer behavior, motivating customers to make purchasing decisions not based on actual needs, but because they are attracted, fascinated, or following the majority trend. This is an important premise leading to the increase in impulse buying behavior in the live broadcast commercial environment. Impulsive buying is defined as unplanned purchase behavior triggered by immediate stimuli (Xu et al., 2020 ). According to Hausman ( 2000 ), up to 30–50% of retail sales come from impulsive buying behavior, of which nearly 90% of people make impulse purchases. About 40% of online shopping also originates from this behavior. Recent studies also confirm that livestreaming has a strong impact on impulsive buying through factors such as social presence, personalization, and entertainment (Deng et al., 2022; Cui et al., 2022 ). These factors stimulate positive emotions, creating a state of excitement that makes customers make purchase decisions even though the product is not in the plan (Lo et al., 2022 ; Zhang et al., 2022 ). The S-O-R (Stimulus – Organism – Response) model of Sherman et al. ( 1997 ), applied by many researchers (Lee and Chen, 2021 ; Li et al., 2022 ; Lo et al., 2022 ), has proven effective in explaining the impact of external stimuli (stimulus) on internal states (organism) and behavioral responses (response), thereby clarifying the process of forming impulsive shopping behavior in the context of livestreaming. In addition to marketing stimuli such as products, prices, promotions, etc., consumer behavior is also influenced by internal cognitive and emotional factors such as trust, perceived value (Ming et al., 2021 ; Zhang et al., 2022 ), flow experience (Cui et al., 2022 ; Dong et al., 2022), or happy mood (Khoi and Le, 2022). However, existing literature still presents several gaps. First, although aspects of the livestream environment such as scarcity, vicarious experience, social interaction, and social contagion are believed to shape customer reactions, their individual and combined effects remain underexplored (Lo et al., 2022 ). Second, many previous studies have predominantly emphasized emotional responses, while cognitive responses—which play an equally critical role in triggering impulsive buying—have been largely overlooked. Third, few studies have investigated the moderating role of impulsive buying tendency, despite evidence suggesting that individuals with higher impulsivity are more prone to being swayed by emotional stimuli (Goel et al., 2022 ). To address these gaps, this study proposes an integrated research model that comprehensively examines the influence of livestreaming environment factors on both cognitive and emotional responses, and how these responses in turn drive impulsive buying behavior. Furthermore, the study investigates the moderating effect of individual impulsive buying tendency on the relationship between emotional responses and behavioral outcomes. By doing so, this research contributes to a deeper and more nuanced understanding of the psychological mechanisms that underlie impulsive consumer behavior in the rapidly evolving livestream shopping context, particularly in the Vietnamese market. 2. Literature review and hypotheses 1.1 Live broadcast media channels Livestream commerce integrates live video and online shopping, enabling consumers to access product information, interact in real time, and make purchases directly through the broadcast platform (Lee, 2018; Xu et al., 2020 ). It surpasses traditional e-commerce and social media-based sales by leveraging advanced technologies from the Industry 4.0 era (Ma et al., 2022). Sellers present products via social media, while consumers engage through text-based interactions, forming a virtual environment that facilitates real-time transactions (Nguyen Thu Ha, 2020). This model reduces time and costs while enhancing shopping efficiency. In Vietnam and globally, livestream commerce is expanding rapidly. It strengthens customer engagement, improves product visualization, and conveys professionalism and relatability through seller presentations (Wongkitrungrueng and Assarut, 2020). Moreover, it supports timely and informed decision-making by offering updated and comprehensive product information during and after the session (Gao et al., 2021). This dynamic format is redefining online retail experiences. 2.2. Social presence of live streamers The live shopping environment is an evolving e-commerce ecosystem that integrates real-time product presentation with customer interaction, encouraging immediate purchasing behavior (Busalim et al., 2021). In this context, consumers shift from passive recipients to active participants capable of influencing others during the session. Several environmental factors shape consumer behavior in live commerce. Scarcity, driven by limited time or product availability, creates urgency (Eisend, 2008 ; Akram et al., 2018 ). Vicarious experience allows consumers to imagine using products through visuals rather than direct contact (Chen et al., 2019 ). Social interaction enables behavioral adjustments based on engagement with sellers and other viewers (Horton and Wohl, 1956). Emotional contagion involves absorbing the emotions of others in the broadcast space (Hatfield et al., 1992). Social presence enhances authenticity and trust through visible engagement (Lu et al., 2016; Poletti and Michieli, 2018). Lastly, product presence refers to the perceived tangibility of items through detailed visual representation (Vonkeman et al., 2017; Kang, 2020). 2.3. Impulse buying behavior Impulse buying is a complex and multidimensional behavior often driven by emotional or hedonic motives (Babin et al., 1994). It refers to spontaneous purchases made without prior planning, usually triggered by a strong and sudden urge (Block and Morwitz, 1999; Kacen and Lee, 2002). Such behavior is typically difficult to control and distinct from rational or planned decision-making (Chan et al., 2017). In online contexts, impulse buying is more frequent due to reduced consideration of alternatives or budget constraints (Wu et al., 2020). Stimuli such as advertising, appealing visuals, and live broadcasts enhance curiosity and emotional responses, increasing impulsive purchases. This study views impulse buying as a spontaneous act influenced primarily by online stimuli. According to Kim (2003), the consumer decision process includes five stages: need recognition, information search, evaluation of alternatives, purchase decision, and post-purchase evaluation. Positive post-purchase experiences foster brand loyalty and reinforce repeated buying behavior (Churchill and Peter, 1998). 2.4. Theorical background 2.4.1. The S–O–R (Stimulus–Organism–Response) model The S–O–R (Stimulus–Organism–Response) model is commonly used to explain consumer behavior in situations influenced by the shopping environment. According to Tai and Fung (1997), this model emphasizes the role of external stimuli (S), influencing the consumer's internal emotional state (O), which in turn leads to behavioral responses (R), including purchase behavior. Sherman et al. ( 1997 ) divided the stimuli in the shopping environment into three main groups: social factors (salesperson, other buyers), design factors (layout, color, images), and ambient factors (lighting, scent). These factors have the ability to strongly influence emotions, arouse interest, and stimulate unplanned purchase behavior. In the context of modern e-commerce, especially online shopping through live broadcast channels, the S–O–R model still retains its explanatory value. The broadcast environment is designed to be lively and fun with continuous interaction between sellers and customers, creating a positive emotional state, thereby promoting impulsive buying behavior. However, this model still has limitations due to simplifying the consumer decision-making process, ignoring complex factors such as culture, society and long-term influence of behavior. 2.4.2. Flow experiences Flow is a positive psychological state in which individuals are fully immersed and focused on an activity, often accompanied by excitement and satisfaction (Csikszentmihalyi, 2000). This state enhances positive experiences and satisfaction by minimizing distractions and increasing behavioral control (Gao and Bai, 2014; Dong et al., 2023). In live broadcasting contexts, flow is marked by deep engagement with the content, a sense of absorption, and loss of time awareness (Chen et al., 2022). It is further associated with temporary enjoyment and a sense of control during interaction with online sales content (Cui et al., 2022 ; Hyun et al., 2022). Wu et al. (2021) link flow to perceived challenge, usefulness, and spontaneity in content engagement. As a subjective state, flow depends on the participant’s skills, the challenge level, and commitment. This study defines flow as intense customer concentration during live broadcasts, where interactive and engaging presentations stimulate interest and may trigger impulsive buying. 2.4.3. Behavioral psychology theory Behavioral psychology, also known as behaviorism, focuses on explaining human behavior through responses to stimuli from the living environment (Watson, 1994). According to this approach, behavior is formed through the process of learning, conditioning, and can be observed intuitively without delving into the inner life. Freud (1994) added that behavior is influenced by environmental stimuli, but is also governed by internal emotions and desires. Behaviorism refers to two main types of conditioning: classical and operant. Classical conditioning forms behavior based on associations between stimuli and natural responses; meanwhile, operant conditioning is maintained through the reinforcement of behavior observed from others. In the context of this study, behaviorism is applied to explain how consumers respond to environmental factors in live broadcasts. Factors such as social media, relatives or celebrities can influence emotions, stimulating shopping behavior to satisfy psychological needs. Positive emotional states such as happiness are more likely to lead to impulsive shopping behavior. However, the limitation of behavioral theory is that it does not fully consider factors such as free will, internal emotions and personal judgment processes, which also play an important role in consumer behavior. 2.5. Hypothesis Cognitive reactions refers to the mental processing that occurs when individuals encounter external stimuli, such as information on a shopping website (Parboteeah et al., 2009 ). This process involves both interpretation and emotional evaluation. Emotional reactions, on the other hand, reflects individuals’ affective reactions, including feelings of joy, excitement, and satisfaction (Kamboj, 2020). In the context of live-stream shopping, environmental stimuli can activate both cognitive and emotional reactions. According to the S-O-R model by Mehrabian and Russell ( 1974 ), external stimuli influence internal states—namely cognition and emotion—which in turn shape consumer behavior. Parboteeah et al. ( 2009 ) applied this model to show how website environments can trigger emotional states and lead to impulse buying. Scarcity persuasion, a key factor in live-stream shopping, intensifies emotional responses by creating urgency and competition (Malhotra, 2010). Wu et al. (2021) confirmed that scarcity, whether temporal or quantitative, enhances consumer excitement. Furthermore, scarcity persuasion increases perceived value (Eisend, 2008 ) and contributes to utilitarian shopping value (Chung et al., 2017), supporting its role in shaping consumer purchase decisions. Therefore, the authors propose the hypothesis: H1: Scarcity persuasion positively affects cognitive reactions H2: Scarcity persuasion positively affects emotional reaction Rook ( 1987 ) argued that visual buying behavior is initiated by the visual contact between the customer and the product. Beatty and Ferrell ( 1998 ) also explained that visual purchasing is formed through the pleasure of experiencing the product (MacInnis and Price, 1987). The impact of vicarious experience on customers' cognitive and emotional reactions is also based on the theory of the S-O-R model proposed by Mehrabian and Russell ( 1974 ), environmental factors affect human cognition and emotion. According to Sowinska and Sokol (2019), it is the vicarious experience that creates an information channel for customers to learn and evaluate and causes a strong stimulating reaction to customers, or that is the impact on customers' product perception. On the other hand, Chen et al. ( 2019 ) also suggested that this vicarious experience will also positively affect customers' emotional reactions, such as excitement, enjoyment, and perceived future enjoyment (Vazquez et al., 2020). In addition, Roberts (2010) also suggested that through listening and reflective thinking, customers will collect experiences from the broadcast channel combined with their own experiences to make clearer purchasing behavior. Therefore, the author proposes the hypothesis: H3: Vicarious experience positively affects cognitive reactions H4: Vicarious experience positively affects emotional reactions Previous studies have identified that social interaction positively contributes to the creation of one-way emotional attachment to social actors (Aw and Labrecque, 2020 ; Chen et al., 2019 ). The impact of social interaction on customers' cognitive and emotional responses is also based on the theory of the S-O-R model proposed by Mehrabian and Russell ( 1974 ), environmental factors influence human cognition and emotion. The communication literature has demonstrated that social interaction reflects relevant media use because it can influence users' emotional reactions to media characters and media (i.e., websites) (Labrecque, 2014; Rubin et al., 1985). For example, social interaction has been found to foster affective trust (Chen et al., 2019 ). Gong and Li (2017) determined that social interaction can shape viewers’ attitudes toward products and services (Sokolova and Kefi, 2020) and even contribute to the enjoyment of the shopping experience (Xiang et al., 2016 ). Therefore, the author proposes the hypothesis: H5: Social interaction positively affects emotional reactions The impact of social contagion on customers' cognitive and emotional reactions is also based on the theory of S-O-R model proposed by Mehrabian and Russell ( 1974 ), environmental factors affect human cognition and emotion. In the study of commerce through live broadcast, social contagion has been applied to allow viewers to influence each other at multiple levels (Hu et al., 2017; Xue et al., 2020). Furthermore, Wang et al. ( 2018 ) found that social contagion can influence the impulsive buying process through emotional reactions. Social contagion is proposed to have a significant impact on emotional reactions through impulsive buying on live broadcasts. Therefore, the author proposes the hypothesis: H6: Social contagion has a positive impact on emotional reaction The impact of the presence of live broadcasters on customers' cognitive and emotional reactions is also based on the theory of the S-O-R model proposed by Mehrabian and Russell ( 1974 ), environmental factors affect human cognition and emotion. According to Park and Lin (2020), customers are more likely to form positive stereotypes about an attractive live broadcaster, which leads customers to form positive attitudes toward the products they advertise. The social media presence of live broadcasters narrows the psychological distance between viewers and live broadcasters and can help viewers better understand the products they desire, thereby increasing viewers' sense of trust (Jiang et al., 2019 ). The social presence of live broadcasters enhances viewers’ focus on live-streaming commerce, as live broadcasters can provide better personalized services according to viewers’ needs (Yim et al., 2017). In addition, customers’ shopping enjoyment can be increased by more human elements in live-streaming commerce, where viewers can see live broadcasters and contact them in real time as if they were communicating face-to-face (Liu et al., 2020). Previous research by Shen (2012) confirmed that the social presence of live broadcasters can increase customers’ emotional reactions. Therefore, the author proposes the hypothesis: H7: Social presence of livestreamers positively affects emotional reactions The impact of viewer presence on customers' cognitive and emotional reactions is also based on the theory of S-O-R model proposed by Mehrabian and Russell ( 1974 ), environmental factors affect human cognition and emotion. The interactivity between viewers in the chat box gives viewers a better sense of social presence, thus encouraging them to participate in the information exchange process (Li et al., 2018). Shopping is considered a social activity performed with companions, such as friends or family members (Lu et al., 2016). Shoppers create a pleasurable experience when interacting with their shopping companions (Wolfinbarger and Gilly, 2001). Live broadcast commerce can satisfy customers' social needs. A high level of perceived presence is beneficial to enhance more friendly communication, and therefore, customers are more likely to enjoy and have a positive shopping experience (Zhu et al., 2006). In general, customers have little knowledge about the actual quality of the product. Live broadcasts allow customers to read, post, and review comments (Fang et al., 2018 ). In this way, customers can exchange product information with each other, which may increase customers' emotional reactions and thus make purchase decisions. Therefore, the author proposes the hypothesis: H8: Social presence of viewer has a positive impact on emotional reactions Product testing during live broadcasts makes customers feel excited. However, on online platforms, customers cannot physically interact with the product due to spatial separation (Vonkeman et al., 2017). High product presence can be a solution to this concern by narrowing the psychological distance between customers and the product (Kang, 2020). The impact of product presence on customers' cognitive and emotional reations is also based on the S-O-R model theory proposed by Mehrabian and Russell ( 1974 ), environmental factors affect human cognition and emotion. Live broadcast commerce has the potential to provide customers with a shopping experience similar to that of a real product experience. Live broadcasters often try out the product themselves, often accompanied by a vivid demonstration of the product experience. This can make customers imagine what will happen when using the product and then create an emotional reactions (Chen et al., 2019 ). Therefore, the author proposes the hypothesis: H9: Social presence of products positively affects emotional reactions Previous studies have shown that positive cognitive reactions are closely related to positive emotional reactions. Verhagen and Dolen (2011) applied the cognitive-emotion theory and showed that trust precedes emotion, and thus perceived attractiveness of goods and communication style on the website are important factors that generate positive emotions. Chih et al. (2012) suggested that customers' evaluations of the appropriateness of impulsive buying behavior had a positive impact on the stimulation of online impulsive buying behavior. According to Chen et al. ( 2019 ), cognitive reactions serve as the foundation for emotional reactions, whereby information must be perceived as credible before an emotional attachment to an individual, brand, or product can be established. Similarly, the usefulness of information must be cognitively examined before an attitude can be formed (Hsu et al., 2013). Parboteeah et al. ( 2009 ) and Xiang et al. ( 2016 ) proposed that cognitive response to usefulness is positively related to emotional reactions. Hsiao’s (2020) study complements previous studies in which cognitive evaluation of values ​​is found to positively contribute to emotional reactions to satisfaction and thus can stimulate purchase intention. Therefore, the authors propose the hypothesis: H10: Cognitive reations positively affects emotional reactions Impulse buying is defined as a spontaneous and emotionally driven desire to make a purchase without prior planning (Rook, 1987 ). This behavior is often triggered by emotional reactions and immediate gratification, sometimes leading to negative consequences due to limited consideration of long-term outcomes (Eysenck et al., 1985; Puri, 1996). Rook and Fisher ( 1995 ) identify emotions as a key cognitive component in impulsive buying behavior, while Parboteeah et al. ( 2009 ) and Xiang et al. ( 2016 ) emphasize the significant influence of emotional responses on impulsive buying urge. According to Eroglu et al. (2001), positive emotions experienced during shopping, such as enjoyment, can stimulate unplanned buying. Interpersonal elements such as intimacy and personal connection in online shopping environments further enhance this motivation (Chen et al., 2019 ; Xiang et al., 2016 ). Positive emotional states, including joy and excitement, have been shown to contribute directly to impulsive buying urge (Shen and Khalifa, 2012). Thus, the following hypothesis is proposed: H11: Emotional reactions have a positive impact on impulse buying urge Impulsive buying urge refers to the urge to acquire goods or services driven by immediate emotional or situational triggers (Rook, 1987 ; Loewenstein and Lerner, 2003). While situational constraints such as budget and time may limit actual behavior, numerous studies confirm that the motivation to buy impulsively is a strong predictor of subsequent action (Beatty and Ferrell, 1998 ). Therefore, the next hypothesis is proposed: H12: Impulse buying urge positively affects impulse buying behavior The moderating role of impulse buying Impulsive buying tendency refers to the personality trait of individuals in terms of their tendency to act impulsively in purchase situations (Verplanken and Herabadi, 2001). Previous research has identified impulse buying tendency as an important moderator in the relationship between emotional reactions and impulse buying as well as between impulse buying and impulsive buying behavior (Zafar et al., 2021). Individuals with a high impulse buying tendency generally tend to have other characteristics, such as high action orientation, so such individuals may tend to develop a stronger impulse to act impulsively in purchase situations (Baumeister, 2002; Goel et al., 2022 ). According to Lo et al. ( 2022 ), individuals with a high impulse buying tendency are more susceptible to emotional influences and more likely to develop impulse buying urge. In contrast, individuals with low impulse buying tendencies may still be affected by emotions but will have better self-control, reducing the likelihood of impulsive buying urge. Individuals with high impulse buying tendencies are more likely to convert impulse buying urge into actual impulse buying behavior, even without prior purchase planning. Individuals with low impulse buying tendencies may feel the urge to buy but will still consider, analyze, and restrain themselves before making a decision about engaging in impulse buying behavior. Therefore, the authors propose the following hypothesis: H13a: Impulse buying tendencies moderate the relationship between emotional reactions and impulsive buying urge. H13b: Impulse buying tendencies moderate the relationship between impulse buying urge and impulsive buying behavior 2.5.8. Research framework Based on the general theoretical framework and a review of related studies and research gaps, the author plans to develop a research model from the original model of Lo et al. ( 2022 ) because this model focuses on studying environmental factors of livestream sales through the issues of sellers and customers. However, to complete the model and Lo et al. ( 2022 ), the author will inherit additional variables of social media presence of live streamers, social media presence of viewers, and social media presence of products by Lee and Chen ( 2021 ); Li et al. ( 2022 ); Zhang et al. ( 2022 ) to fully cover all factors related to the livestream sales environment. Therefore, the proposed research model is as follows (Fig. 1 ): 3. Methodology 3.1. Methodology used The preliminary quantitative study was conducted to evaluate the reliability and validity of the measurement scales as a preparatory step for the main study, which would employ Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). Initially, the internal consistency of the scales was assessed using Cronbach’s Alpha. Subsequently, Exploratory Factor Analysis (EFA) was performed to explore the underlying factor structure and refine the scales where necessary, ensuring that they are suitable for validation through CFA in the main study. According to Hair et al. (2006), a minimum of 50 observations is required for EFA, with 100 being preferable to ensure the robustness of the results. In line with this recommendation, the researcher administered a pilot survey using an online format. The target respondents were individuals from the researcher's personal and professional networks, including family members, friends, and colleagues residing in major urban centers such as Hanoi, Da Nang, Hue, Ho Chi Minh City, and Can Tho. 3.2. Questionnaire design These participants were selected based on their active use of social media and engagement in online shopping—criteria relevant to the study’s context. After one month of data collection, 127 valid responses were obtained, exceeding the recommended threshold for preliminary quantitative studies. The data were then coded, processed, and analyzed using SPSS version 25. The results of this pilot study provided a basis for refining the measurement model prior to conducting CFA and SEM on a larger sample in the main study. The scales measuring variables in the current research were adopted from existing literature. Specifically, we used the scale from Chen et al. (2022) with three items to measure Scarcity Persuasion, and a three-item scale from Chen and Lin (2017) was utilized to measure Vicarious Experience. Social Interaction was measured using four items from Chen and Lin (2017), and Social Contagion was assessed using three items adapted from Lim et al. (2012). Additionally, we adopted a four-item scale to measure Social Presence of Livestreamers and and Social Presence Viewer with three items from Ming et al. ( 2021 ). Social Presence of Product was measured using four items from from Chen et al. ( 2019 ). Cognitive Reactions and Emotional Reactions form Li et al. ( 2022 ). Impulsive Buying Urge with four items from Lee và Chen (2021). Impulsive Buying Behavior with three items and Impulsive Buying Tendency with three items form Chen et al. (2022) in Table 1 . Table 1 Constructs and measurement items. Contrust Items Measures Supporting Refences Scarcity Persuasion SP1 When watching promotions through live broadcast, I think many people will compete with me to buy promotional items Chen et al. (2022) SP2 When watching promotions through live broadcast, I think promotional products will sell out quickly SP3 I think product scarcity is strategically created by pulling customers to stay in the live broadcast shopping scene Vicarious Experience VE1 By watching the live broadcast of the product introduction, I can feel what the author wants to say about the introduced products as well as their experience of using them Chen and Lin (2017) VE2 By watching the live broadcast of the product introduction, I can imagine what the author wants to say about the introduced products as well as their experience of using them VE3 By watching the live broadcast of the product introduction, I can imagine what the author wants to say about the recommended products and their experience of using them Social Interaction SI1 When watching a live broadcast, I can easily exchange and share opinions with the livestreamers or other viewers Chen and Lin (2017) SI2 When I am watching a live broadcast, the broadcaster knows that I am interested in them SI3 When I am watching a live broadcast, I feel closer to the broadcaster SI4 When I am watching a live broadcast, the broadcaster will provide enough opportunities to respond and ask questions Social Contagion SC1 My behavior is influenced by other team members Lim et al. (2012) SC2 My behavior influences other team members SC3 Our team agrees on similar opinions Social Presence Livestreamers SPL1 I can understand the attitudes of live broadcasters by interacting with them through live broadcast Ming et al. ( 2021 ) SPL2 It feels human to communicate with live broadcasters through live broadcast SPL3 Communicating with sellers through streamers through live broadcast is very warm SPL4 I can know what sellers look like when interacting with them through live broadcast Social Presence Viewer SPV1 I know other viewers in the live stream are also interested in the product Ming et al. ( 2021 ) SPV2 I know other viewers in the live stream are also sharing information about the product SPV3 I know other viewers in the live stream have purchased the product Social Presence of Product SPP1 I feel enthusiastic about the recommended product Chen et al. ( 2019 ) PSP2 I feel inspired by the recommended products SPP3 I feel excited about the recommended products SPP4 I feel interested in the recommended products Cognitive Reactions CR1 I feel excited when shopping through watching live broadcast Li et al. ( 2022 ) CR2 I feel excited when shopping through watching live broadcast CR3 I feel surprised when shopping through watching live broadcast CR4 I feel confident when shopping through watching live broadcast Emotional Reactions ER1 I feel happy when shopping through watching live broadcasts Li et al. ( 2022 ) ER2 I feel happy when shopping through watching live broadcasts ER3 I feel satisfied when shopping through watching live broadcasts ER4 I feel comfortable when shopping through watching live broadcasts Impulsive Buying Urge IBU1 When watching live broadcasts, I want to buy items that are not related to my original shopping goals Lee và Chen (2021) IBU2 I suddenly feel like buying things when shopping on a live broadcast commerce platform IBU3 While watching a live broadcast commerce program, I tend to buy items that are not related to my original shopping goals IBU4 When I shop on a live broadcast commerce platform, I suddenly feel like buying something Impulsive Buying Behavior IBB1 When I watch live shopping, I often buy items other than or outside of my specific shopping goals Chen et al. (2022) IBB2 There are many things I have bought from live shopping, but I rarely use them IBB3 Sometimes I buy things from live shopping because I like to buy them rather than because I need them Impulsive Buying Tendency IBT1 When I watch product recommendations through live, I want to buy items other than my specific shopping goals Chen et al. ( 2019 ) IBT2 When I watch product recommendations through live, I want to buy items that are not related to my specific shopping goals IBT3 When I watch product recommendations through live, I tend to buy items outside of my specific shopping goals 4. Results and findings 4.1. Demographic statistics The author collected 553 responses, of which 31 responses did not meet the requirements, and finally the author had 522 valid responses left, and this number satisfied the sample size requirement. The characteristics of the official research sample with a sample size of n = 522 observations were classified by gender, age, place of residence, occupation, education level, monthly income, and frequency of use per day, details are presented in Table 2 . Table 2 Response rate of groups. Character Frequency Percentage Gender Male 171 32,8 Female 351 67,2 Age From 16 to 22 years old 170 32,6 From 23 to 30 years old 246 47,1 From 31 to 40 years old 92 17,6 More than 40 years old 14 2,1 Location Ho Chi Minh 160 30,7 Ha Noi 117 22,4 Hue 53 10,2 Da Nang 88 16,9 Can Tho 74 14,2 Others 30 5,7 Occupation Student 84 16,1 Officer 174 33,3 Technical 74 14,2 Business 119 22,8 Others 71 13,6 Education Highschool 120 23,0 College 115 22,0 Undergraduate 226 43,3 Postgraduate 61 11,7 Income per month Below 7 million 73 14,0 From 7 to unde r15 million 188 36,0 From 15 to under 25 million 167 32,0 More than 25 million 94 18,0 Frequency of use Below 2 hours 110 21,1 From 2 to 4 hours 314 60,2 More than 4 hours 98 18,8 Based on the results of Table 2 , among the 522 official customers, the female gender accounts for a higher proportion of 67.2%. In terms of age, the age group from 16 to 30 years old accounts for the majority, with 79.7%, these are young customers who are convenient in using smart technology devices to access social networks. In terms of place of residence, Ho Chi Minh City accounts for the highest proportion of 30.7%, followed by Hanoi with 22.4%, these are the two largest cities in Vietnam. In terms of occupation, office workers account for the highest proportion, with 33.3%. The educational level is university, with the highest proportion of 43.3%. In terms of monthly income, income from 7 to under 15 million and from 15 to under 25 million accounts for the majority; this is considered the average income level and convenient for customers to shop online. The frequency of use of customers from 2 to 4 hours accounts for the highest rate at 60.2%. 4.2. Reliability Test After synthesizing the method and the meanings of the test coefficients, for this study, the author decided to use a large sample size to suit the testing of the new scale with an expanded context. Therefore, the Cronbach's Alpha coefficient to measure the reliability of the scale will be based on the results of Nunally (1978) with the result being greater than 0.6. In addition, the total correlation coefficient of the observed variables must be greater than 0.3 to ensure reliability. The test results are summarized in the following table: It shows that the factors scarcity, vicarious experience, Social interaction, Social contagion, Livestreamers' Social Presence, Viewers' Social Presence, Products' social presence, Cognitive response; Emotional response; Impulsive Buying Urge, Impulsive Buying Behavior, Impulsive Buying Tendency all have Cronbach's Alpha coefficients greater than 0.6 with values ​​of 0.845; 0.937; 0.909; 0.812; 0.849; 0.880; 0.938; 0.847; 0.896; 0.855; 0.809; 0.845; At the same time, the total item correlation coefficients of the measurement observations for these factors are all greater than 0.3 and the Cronbach's Alpha value if the variable is removed is all less than the overall Cronbach's Alpha value of the group. Therefore, we can see that these factors and their observations all achieve reliability, meeting the conditions for EFA analysis. 4.3. Confirmatory factor analysis (CFA) To assess the reliability of the measurement scales, composite reliability values above 0.6 are considered acceptable. Based on the results presented in Table 4 , the composite reliability scores for the variables Scarcity Persuasion (SP), Vicarious Experience (VE), Social Interaction (SI), Emotional Contagion (EC), Social Presence of Livestreamer (SPL), Social Presence of Viewers (SPV), Social Presence of Products (SPP), Cognitive Responses (CR), Emotional Responses (ER), Impulse Buying Urge (IBU), and Impulse Buying Behavior (IBB) are 0.845, 0.937, 0.909, 0.813, 0.849, 0.881, 0.938, 0.847, 0.896, 0.858, and 0.810, respectively. Since all values exceed the minimum threshold, it can be concluded that the scales demonstrate high internal consistency and are reliable for use in the study. Regarding convergent validity, the average variance extracted (AVE) should exceed 0.5 for each construct. According to Table 4 , the AVE values for Scarcity Persuasion, Vicarious Experience, Social Interaction, Emotional Contagion, Presence of Streamers, Presence of Viewers, Product Presence, Cognitive Reaction, Emotional Reaction, Impulsive Buying Urge, and Impulsive Buying Behavior are 0.645, 0.833, 0.714, 0.594, 0.585, 0.712, 0.792, 0.581, 0.684, 0.668, and 0.588, respectively. Since all AVE values are greater than 0.5, the constructs meet the criteria for convergent validity. Table 4 Confirmatory factor analysis (CFA) fitting indices. Estimate Cronbach CR AVE Scarcity Persuasion 0,845 0,845 0,645 SP1 6,97 2,358 0,717 0,778 SP2 7,03 2,387 0,712 0,783 SP3 7,00 2,305 0,705 0,791 Vicarious Experience 0,937 0,937 0,833 VE1 7,12 4,342 0,869 0,910 VE2 7,14 4,522 0,865 0,912 VE3 7,11 4,593 0,876 0,904 Social Interaction 0,909 0,909 0,714 SI1 10,46 5,757 0,789 0,883 SI2 10,40 5,980 0,779 0,887 SI3 10,41 5,667 0,797 0,881 SI4 10,41 5,754 0,809 0,876 Social Contagion 0,813 0,812 0,594 SC1 6,84 3,036 0,618 0,785 SC2 6,85 2,863 0,668 0,735 SC3 6,90 2,719 0,700 0,701 Social Presence of Livestreamer 0,849 0,849 0,585 SPL1 11,25 5,753 0,696 0,805 SPL2 10,98 5,984 0,668 0,817 SPL3 11,02 5,957 0,694 0,806 SPL4 11,15 5,888 0,694 0,806 Social Presence of Viewers 0,881 0,880 0,712 SPV1 7,52 2,849 0,756 0,840 SPV2 7,61 2,698 0,799 0,802 SPV3 7,49 2,738 0,749 0,848 Social Presence of Products 0,938 0,938 0,792 SPP1 10,58 9,023 0,803 0,934 SPP2 10,68 8,287 0,861 0,915 SPP3 10,70 8,277 0,880 0,909 SPP4 10,76 8,002 0,868 0,914 Cognitive Response 0,847 0,847 0,581 CR1 10,26 6,583 0,705 0,796 CR2 10,24 6,727 0,699 0,799 CR3 10,21 6,832 0,680 0,807 CR4 10,31 7,001 0,650 0,820 Emotional Response 0,896 0,896 0,684 ER1 10,81 6,757 0,787 0,859 ER2 10,82 6,527 0,791 0,857 ER3 10,78 6,853 0,756 0,870 ER4 10,91 6,687 0,742 0,876 Impulsive Buying Urge 0,858 0,855 0,668 IBU1 7,60 2,006 0,744 0,783 IBU2 7,45 2,007 0,733 0,794 IBU3 7,65 2,380 0,718 0,813 Impulsive Buying Behavior 0,810 0,809 0,588 IBB1 6,94 3,676 0,636 0,761 IBB2 6,92 3,498 0,680 0,716 IBB3 6,99 3,338 0,659 0,738 Impulsive Buying Tendency 0,845 IBT1 6,9713 2,358 0,717 0,778 IBT2 7,0307 2,387 0,712 0,783 IBT3 7,0019 2,305 0,705 0,791 Note. n = 407; ***p < 0.001; Environmental concern is the control variable. CR: composite reliability; AVE: average variance extracted. Source: Created by authors. Cronbach’s Alpha (CA) and Composite Reliability (CR) were used to assess the internal consistency reliability of all constructs. As shown in Table 4 , all constructs reported high reliability, with CA values ranging from 0.762 to 0.913, exceeding the threshold of 0.70 (Hair et al., 2010 ). This indicates that the measurement items for each construct are internally consistent and reliable. Next, convergent validity was assessed using two criteria: (1) Average Variance Extracted (AVE) and (2) standardized factor loadings. The diagonal values in Table 5 represent the square root of the AVE for each construct, and all are greater than 0.70—specifically, the values range from 0.762 to 0.913—surpassing the recommended threshold of 0.50 (Fornell & Larcker, 1981 ). Furthermore, the standardized factor loadings for all items were statistically significant and above 0.60, confirming that the constructs demonstrate adequate convergent validity (Hair et al., 2010 ). Moreover, discriminant validity was assessed using the Fornell-Larcker criterion. The square root of the AVE for each construct (displayed on the diagonal in Table 5 ) is higher than any of its correlations with other constructs (off-diagonal values), indicating that each construct shares more variance with its own measures than with others. In addition, none of the confidence intervals for correlation coefficients includes the value of 1, providing further support for discriminant validity (Fornell & Larcker, 1981 ) in Table 5 . Table 5 Discriminant validity. SP VE SI SC SPl SPV SPP CR ER IBU IBB SP 0.890 VE 0.381 *** 0.845 SI 0.652 *** 0.384 *** 0.827 SC 0.331 *** 0.279 *** 0.441 *** 0.762 SPL -0.116 * -0.181 *** -0.022 0.026 0.913 SVP 0.518 *** 0.432 *** 0.465 *** 0.223 *** 0.013 0.765 SPP 0.131 ** 0.019 0.170 *** 0.089† 0.06 0.093† 0.844 CR 0.455 *** 0.360*** 0.559 *** 0.396 *** 0.094† 0.411 *** 0.079 0.817 ER 0.301 *** 0.516 *** 0.369 *** 0.417 *** -0.179 *** 0.253 *** 0.025 0.318 *** 0.803 IBU -0.013 0.066 0.094† 0.101† -0.189 *** -0.025 0.015 0.097 0.118* 0.77 IBB 0.592 *** 0.355 *** 0.618 *** 0.405 *** -0.007 0.418 *** 0.187 *** 0.490 *** 0.246 *** -0.148 ** 0.767 Note. Square roots of AVE are in bold; Correlations between variables are in off-diagonal elements; Heterotrait-Monotrait ratios are in italic. Source: Created by authors. 4.4. Structural Equation Modeling (SEM) The data analysis reveals significant positive relationships among all proposed variables. Scarcity Persuasion shows a strong positive effect on cognitive reaction (β = 0.429, p < 0.001), supporting H1. Vicarious experience (β = 0.101, p < 0.001) and social interaction (β = 0.090, p < 0.001) also exhibit positive influences on cognitive reaction, thereby supporting H2 and H3. Emotional contagion demonstrates a significant effect on emotional reactions (β = 0.078, p < 0.001), confirming H4. Likewise, the presence of streamers (β = 0.094, p < 0.001) and the presence of viewers (β = 0.094, p < 0.001) positively influence emotional reactions, supporting H5 and H6. Product presence significantly enhances both cognitive and emotional reactions (β = 0.159, p < 0.001), supporting H7. Furthermore, cognitive reactions positively affect impulse buying urge (β = 0.083, p < 0.001), and emotional responses show an even stronger effect (β = 0.543, p < 0.001), confirming H8 and H9. Flow experience also has a positive impact on impulse buying urge (β = 0.226, p < 0.001), thus supporting H10. Notably, emotional reactions strongly predict impulse buying urge (β = 0.578, p < 0.001), supporting H11. Finally, impulsive buying urge significantly influences impulse buying behavior (β = 0.524, p < 0.001), thereby confirming H12. Collectively, the results provide empirical support for all hypothesized relationships, as summarized in Table 6 . Table 6 Results of hypothesis test. Hypothesis Standardized path coefficient Result H1 0.429*** Support H3 0.090*** Support H2 0.101*** Support H4 0.078*** Support H5 0.094*** Support H6 0.094*** Support H7 0.159*** Support H8 0.083*** Support H9 0.543*** Support H10 0.226*** Support H11 0.578*** Support H12 0.524*** Support Note. N = 319, *p < .05; **p < .01; ***p < .001. Moderating effect of impulsive buying tendency To examine the moderating role of impulsive buying tendency (IBT), we used Model 1 of the PROCESS macro (Hayes, 2013 ). First, the direct effect of impulsive buying tendency on impulsive buying behavior (HV) was significant (p < 0.001). Next, we examined whether the interaction term (emotional response × impulsive buying tendency) had a significant effect on impulsive buying urge (IBU). The result shows a significant interaction effect (β = 0.1985, p < 0.001), indicating that impulsive buying tendency positively moderates the relationship between emotional response and impulsive buying urge. Thus, H13a is supported. In addition, the effect of the interaction term (impulsive buyng ugre × impulsive buying tendency) on impulsive buying behavior was also significant (β = 0.2468, p < 0.001). This result suggests that impulsive buying tendency also moderates the relationship between impulsive buying urge and actual impulsive buying behavior, and this moderating effect is positive. Therefore, H13b is also supported in Table 7 . Table 7 Path coefficients and significances Hypothesis Path Standardized path coefficient Result H13a ER➝ IBU(moderated by XH) 0.1985*** Support H13b IBU ➝ IBB (moderated by IBT) 0.2468*** Support ER = Emotional response, IBU = impulsive buying Ugre, IBB = Impulse buying behavior, IBT = Impulsive buying tendency, ***p < 0.001 5. Discussion The findings from the quantitative analysis confirm that the proposed theoretical model fits well with the empirical data. All 14 hypothesized relationships, which explore the influence of livestream-based shopping environments on consumers' impulse buying behavior in Vietnam, are statistically supported. The structural equation modeling results reveal that various elements of the livestream shopping environment significantly impact both cognitive and emotional reactions. Specifically, scarcity persuasion exerts a strong positive influence on cognitive reactions (standardized coefficient = 0.429), while vicarious experience also contributes positively (β = 0.090). In terms of emotional reactions, multiple environmental factors show significant effects. Scarcity (β = 0.101), vicarious experience (β = 0.078), social interaction (β = 0.094), and social contagion (β = 0.094) all positively influence emotional reactions. Additionally, the social presence of streamers (β = 0.159), social presence of viewers (β = 0.083), and social presence of product (β = 0.543) are found to be key emotional triggers within the livestream setting. Beside, cognitive reactions further enhance emotional reaction (β = 0.226), highlighting the interaction between rational evaluation and affective reactions. Emotional reactions are shown to significantly drive impulsive buying urge (β = 0.578), which in turn positively influences actual impulse buying behavior (β = 0.524). Moreover, the moderating role of individual impulsive buying tendency is confirmed. This variable strengthens the relationship between emotional reactions and impulsive buying urge, as well as between buying urge and actual behavior. These results emphasize the psychological complexity of impulse purchases in the context of livestream commerce. Based on these empirical findings, the study provides a foundation for strategic recommendations aimed at enhancing consumer engagement and stimulating impulse buying through livestream platforms. Managerial implications derived from these results are discussed in the following section. 6. Conclusion and managerial implications 6.1. Conclusion Based on the hypothesis testing results regarding the relationship between livestream shopping environment factors and impulsive buying behavior in Vietnam, several managerial implications can be drawn. First, scarcity persuasion significantly influences both cognitive and emotional reactions, thereby encouraging impulsive purchases. Marketers should strategically create a sense of scarcity by limiting product quantities, displaying countdown timers, or showing the number of items sold and remaining. However, excessive use of this tactic can lead to consumer distrust or psychological discomfort, so it must be applied with caution. Second, vicarious experience positively affects consumer responses. Livestreamers should share authentic user experiences, respond promptly to comments, and demonstrate product use clearly. This builds a sense of realism and trust. Avoiding overly scripted or exaggerated content is crucial to prevent consumer skepticism. Third, social interaction enhances emotional reactions, which in turn stimulate impulsive buying. E-commerce platforms should encourage product reviews and viewer interactions during livestreams. Designing livestreams as engaging, dialogue-based events rather than scripted presentations can increase emotional connection and brand attachment. Fourth, social contagion plays a significant role. When viewers observe others enthusiastically purchasing or engaging, they are more likely to join. Strategies such as flash sales, surprise giveaways, and group-buying campaigns can amplify this effect. Incentivizing users to refer friends or post reviews on social media also fosters wider engagement. Fifth, the presence of livestream hosts influences emotional reactions. Hosts should maintain an energetic and engaging atmosphere, provide clear and honest responses to questions, and incorporate entertaining elements to retain viewer attention. Well-trained hosts or collaborations with influencers can further enhance trust and purchase intention. Sixth, the presence of other viewers can also trigger emotional responses and impulsive actions. Sellers should promote viewer interaction through comments, questions, and minigames. Personalized engagement, such as addressing viewers by name or recommending tailored products, enhances the perceived value of the session. Seventh, product presence strongly influences emotions. High-quality visual presentations, accurate information, and advanced display technologies can improve the perceived appeal of products. Personalized product suggestions based on user preferences can further drive cross-selling and impulse purchases. Finally, impulsive buying tendency moderates the relationship between emotional responses and buying behavior. Marketing strategies should emphasize emotional stimulation, such as through exclusive deals, limited-time offers, and interactive promotions, to capitalize on consumers’ impulsive inclinations during livestream shopping. 6.2. Theory and managerial implications 6.2.1. Theory implications This study was conducted to synthesize the theoretical framework related to the factors of shopping environment through live broadcast media, cognitive response, emotional response and impulsive shopping behavior of customers. The S-O-R model (Sherman et al., 1997 ) was deployed to study the impact of stimuli on the object and response because the theory has been proven to be applicable in understanding the process of forming impulsive shopping behavior (Lee and Chen, 2021 ; Li et al., 2022 ; Lo et al., 2022 ). The flow experience theory (Csikszentmihalyi, 2000) is also related to the topic because the flow experience theory refers to the creativity, comfort or freedom of customers in accessing information to make a certain decision. This explains why customers can be caught up in the shopping process and easily make unplanned purchasing decisions. When customers reach the flow state, they are easily influenced by environmental and emotional factors, thereby performing impulsive shopping behavior. At the same time, the study reviewed related studies to identify research gaps up to now. Most previous studies focused on factors affecting normal shopping behavior and then inferred to impulsive buying behavior. Therefore, this study focuses on aspects related to customer psychology, such as customers' cognitive reactions and emotional reactions, shopping environments through live broadcast media belonging to both sellers and buyers affecting customers' impulsive buying behavior. On the other hand, measuring the moderation level of impulse buying tendency on the relationship between emotional reactions to impulse buying urge and the relationship between impulse buying urge and impulse buying behavior. 6.2.2. Practice implications This study offers practical insights for online retailers leveraging livestreaming to stimulate impulse purchases. The findings highlight the importance of creating a compelling shopping environment that triggers both cognitive and emotional reactions. Retailers should use scarcity persuasion strategically to create urgency, while ensuring authenticity through real-time interactions, honest demonstrations, and relatable content. Encouraging active viewer engagement, facilitating social interactions, and enhancing the presence of hosts and products can significantly influence buyer behavior. Furthermore, personalizing the shopping experience and incorporating emotional triggers—such as limited-time offers or interactive promotions—can effectively target consumers with a higher tendency for impulsive buying. These strategies, when thoughtfully applied, can enhance viewer immersion and drive spontaneous purchases during livestream shopping sessions. 7. Limitation and future research Despite its contributions, this study has several limitations that suggest avenues for future research. First, the research model focuses solely on specific environmental factors in the livestream shopping context—namely scarcity persuasion, vicarious experience, social interaction, social contagion, and the presence of livestream hosts, viewers, and products—while other potentially influential variables remain unexplored. Future studies should consider expanding the model to include additional psychological, technological, or contextual factors that may also drive impulsive buying behavior. Second, the sample was limited to a few major cities in Vietnam, which may not fully represent consumer behavior in other regions. Future research should broaden the geographic scope to include more diverse localities and examine how regional or cultural differences influence impulse buying. Additionally, analyzing variations across different demographic groups (e.g., age, income, online shopping habits) could uncover nuanced insights into how customer characteristics moderate the impact of environmental factors, thereby providing more targeted managerial strategies. Abbreviations S–O–R Stimulus–Organism–Response SP Scarcity Persuasion VE Vicarious Experience SI Social Interaction (SI), EC Emotional Contagion, SPL Social Presence of Livestreamers SPV Social Presence Viewers SPP Social Presence of Products CR Cognitive Responses (CR), ER Emotional Reactions IBM Impulse Buying Urge IBB Impulse Buying Behavior Declarations Acknowledgements Many thanks to all the participants, the main investigators and the research team. Funding This research did not receive any specifc grant from funding agencies in the public, commercial, or not-for-proft sectors. Availability of data and materials Data is available from the corresponding author upon reasonable request. Declaration interests statement The authors declare no conflict of interest. Ethical approval Ethics approval for the research was granted by Ho Chi Minh Banking University and Publication Ethics Committee on 1.05.2023, under decision number H10REA15. All procedures involving human participants followed the ethical standards of the institutional and national research committees and aligned with the 1964 Helsinki Declaration and its amendments. C onsent to participate We provided detailed information to the participants about the purpose, scope and expectations of the study before they participated in the study. We explained the aims of the study, the information requested from the participants, the data collection process and the method of using the data in a clear and understandable language. Before the research survey questionnaire, the participants received a consent form between May 1, 2023 and May 1, 2025, having read and understood the research’s purpose. We informed the participants that participation in the study was completely voluntary and that they had the right to withdraw from the study at any stage. We obtained written informed consent forms from the participants. These forms indicate that the participants accepted the terms of the study and approved the use of their data for the purposes of the study. Consent for publication Informed written consent for publication was obtained from all participants. Authors’ contributions All authors made substantial contributions to the conceptualization of the work and developed the interview guides Van Dat Tran: Data collection; analysis; methodology; writing original draft; Van Dat Tran: Review and editing: Van Dat Tran: Data collection; analysis: Huynh Le Cong Truong; Data collection; analysis. Huynh Le Cong Truong: Date collection; translation. Huynh Le Cong Truong: Data collection; translation Huynh Le Cong Truong: Data collection. Van Dat Tran: Supervision and review Van Dat Tran: Review and editing Van Dat Tran: Data collection; methodology; supervision; review and editing. References Akram, U., Hui, P., Khan, M. K., Tanveer, Y., Mehmood, K., & Ahmad, W. (2018). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6877937","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489646622,"identity":"67b3d8d8-56db-49ab-b420-0eddc60c3662","order_by":0,"name":"Van Dat Tran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYDCCAyCi4gCDAZCSIFILM2MDwxmStTC2kaKF7/j54495591J3M7AfPA2D8PhPIJaJM8kMzbzbnuWuLOBLdkaqKWYoBaDA8mMjTO3HU7ccIDHTJqHIS2xgaCW84+BWuaAtPB/I1LLjWTGho8NYFvYgFpsCGuRvPHYcMaHY8+MNxxmM7acY0CEFr7ziQ8+JNTckd1wvPnhjTcVEoS1IAAz2J3Eqx8Fo2AUjIJRgAcAALFAQ5kPDB4SAAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Van","middleName":"Dat","lastName":"Tran","suffix":""},{"id":489646623,"identity":"4f753a70-2c6e-4a2d-a433-5ebcaf9427d4","order_by":1,"name":"Cong Truong Huynh Le","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"Truong Huynh","lastName":"Le","suffix":""}],"badges":[],"createdAt":"2025-06-12 08:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6877937/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6877937/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87563648,"identity":"d66d4f73-592a-485a-b32a-d6b6666a79ee","added_by":"auto","created_at":"2025-07-25 09:05:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27232,"visible":true,"origin":"","legend":"\u003cp\u003eProposed model.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6877937/v1/3fc56c2303c16e1249bb2191.png"},{"id":87564955,"identity":"1264e3c9-153b-4dfc-a284-a03f2d1905a9","added_by":"auto","created_at":"2025-07-25 09:21:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1832542,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6877937/v1/2930c2f0-9b9d-4c14-bfee-eff42a6718b0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Relationship Between Shopping Environment Factors Via Livestreams and Customers' Impulsive Buying Behavior Invietnam: TheModerating of Impulsive Buying Trendency\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLivestreaming is becoming an effective business tool on social media and e-commerce platforms, enhancing the shopping experience thanks to its real-time interaction capabilities. This format is superior to traditional social commerce by allowing online sellers to showcase products in live videos and answer customer questions immediately (Ang et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Forrester et al., 2021). Two-way simultaneous interaction is created between sellers and customers through live chat (Kang et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). From there, livestreaming has the ability to stimulate emotional consumer behavior, motivating customers to make purchasing decisions not based on actual needs, but because they are attracted, fascinated, or following the majority trend. This is an important premise leading to the increase in impulse buying behavior in the live broadcast commercial environment.\u003c/p\u003e\u003cp\u003eImpulsive buying is defined as unplanned purchase behavior triggered by immediate stimuli (Xu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to Hausman (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), up to 30\u0026ndash;50% of retail sales come from impulsive buying behavior, of which nearly 90% of people make impulse purchases. About 40% of online shopping also originates from this behavior. Recent studies also confirm that livestreaming has a strong impact on impulsive buying through factors such as social presence, personalization, and entertainment (Deng et al., 2022; Cui et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These factors stimulate positive emotions, creating a state of excitement that makes customers make purchase decisions even though the product is not in the plan (Lo et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The S-O-R (Stimulus \u0026ndash; Organism \u0026ndash; Response) model of Sherman et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), applied by many researchers (Lee and Chen, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lo et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), has proven effective in explaining the impact of external stimuli (stimulus) on internal states (organism) and behavioral responses (response), thereby clarifying the process of forming impulsive shopping behavior in the context of livestreaming.\u003c/p\u003e\u003cp\u003eIn addition to marketing stimuli such as products, prices, promotions, etc., consumer behavior is also influenced by internal cognitive and emotional factors such as trust, perceived value (Ming et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), flow experience (Cui et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dong et al., 2022), or happy mood (Khoi and Le, 2022). However, existing literature still presents several gaps. First, although aspects of the livestream environment such as scarcity, vicarious experience, social interaction, and social contagion are believed to shape customer reactions, their individual and combined effects remain underexplored (Lo et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Second, many previous studies have predominantly emphasized emotional responses, while cognitive responses\u0026mdash;which play an equally critical role in triggering impulsive buying\u0026mdash;have been largely overlooked. Third, few studies have investigated the moderating role of impulsive buying tendency, despite evidence suggesting that individuals with higher impulsivity are more prone to being swayed by emotional stimuli (Goel et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address these gaps, this study proposes an integrated research model that comprehensively examines the influence of livestreaming environment factors on both cognitive and emotional responses, and how these responses in turn drive impulsive buying behavior. Furthermore, the study investigates the moderating effect of individual impulsive buying tendency on the relationship between emotional responses and behavioral outcomes. By doing so, this research contributes to a deeper and more nuanced understanding of the psychological mechanisms that underlie impulsive consumer behavior in the rapidly evolving livestream shopping context, particularly in the Vietnamese market.\u003c/p\u003e"},{"header":"2. Literature review and hypotheses","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.1 Live broadcast media channels\u003c/h2\u003e\u003cp\u003eLivestream commerce integrates live video and online shopping, enabling consumers to access product information, interact in real time, and make purchases directly through the broadcast platform (Lee, 2018; Xu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It surpasses traditional e-commerce and social media-based sales by leveraging advanced technologies from the Industry 4.0 era (Ma et al., 2022). Sellers present products via social media, while consumers engage through text-based interactions, forming a virtual environment that facilitates real-time transactions (Nguyen Thu Ha, 2020). This model reduces time and costs while enhancing shopping efficiency. In Vietnam and globally, livestream commerce is expanding rapidly. It strengthens customer engagement, improves product visualization, and conveys professionalism and relatability through seller presentations (Wongkitrungrueng and Assarut, 2020). Moreover, it supports timely and informed decision-making by offering updated and comprehensive product information during and after the session (Gao et al., 2021). This dynamic format is redefining online retail experiences.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Social presence of live streamers\u003c/h2\u003e\u003cp\u003eThe live shopping environment is an evolving e-commerce ecosystem that integrates real-time product presentation with customer interaction, encouraging immediate purchasing behavior (Busalim et al., 2021). In this context, consumers shift from passive recipients to active participants capable of influencing others during the session. Several environmental factors shape consumer behavior in live commerce. Scarcity, driven by limited time or product availability, creates urgency (Eisend, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Akram et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Vicarious experience allows consumers to imagine using products through visuals rather than direct contact (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Social interaction enables behavioral adjustments based on engagement with sellers and other viewers (Horton and Wohl, 1956). Emotional contagion involves absorbing the emotions of others in the broadcast space (Hatfield et al., 1992). Social presence enhances authenticity and trust through visible engagement (Lu et al., 2016; Poletti and Michieli, 2018). Lastly, product presence refers to the perceived tangibility of items through detailed visual representation (Vonkeman et al., 2017; Kang, 2020).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Impulse buying behavior\u003c/h2\u003e\u003cp\u003eImpulse buying is a complex and multidimensional behavior often driven by emotional or hedonic motives (Babin et al., 1994). It refers to spontaneous purchases made without prior planning, usually triggered by a strong and sudden urge (Block and Morwitz, 1999; Kacen and Lee, 2002). Such behavior is typically difficult to control and distinct from rational or planned decision-making (Chan et al., 2017). In online contexts, impulse buying is more frequent due to reduced consideration of alternatives or budget constraints (Wu et al., 2020). Stimuli such as advertising, appealing visuals, and live broadcasts enhance curiosity and emotional responses, increasing impulsive purchases. This study views impulse buying as a spontaneous act influenced primarily by online stimuli. According to Kim (2003), the consumer decision process includes five stages: need recognition, information search, evaluation of alternatives, purchase decision, and post-purchase evaluation. Positive post-purchase experiences foster brand loyalty and reinforce repeated buying behavior (Churchill and Peter, 1998).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Theorical background\u003c/h2\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1. The S\u0026ndash;O\u0026ndash;R (Stimulus\u0026ndash;Organism\u0026ndash;Response) model\u003c/h2\u003e\u003cp\u003eThe S\u0026ndash;O\u0026ndash;R (Stimulus\u0026ndash;Organism\u0026ndash;Response) model is commonly used to explain consumer behavior in situations influenced by the shopping environment. According to Tai and Fung (1997), this model emphasizes the role of external stimuli (S), influencing the consumer's internal emotional state (O), which in turn leads to behavioral responses (R), including purchase behavior. Sherman et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) divided the stimuli in the shopping environment into three main groups: social factors (salesperson, other buyers), design factors (layout, color, images), and ambient factors (lighting, scent). These factors have the ability to strongly influence emotions, arouse interest, and stimulate unplanned purchase behavior. In the context of modern e-commerce, especially online shopping through live broadcast channels, the S\u0026ndash;O\u0026ndash;R model still retains its explanatory value. The broadcast environment is designed to be lively and fun with continuous interaction between sellers and customers, creating a positive emotional state, thereby promoting impulsive buying behavior. However, this model still has limitations due to simplifying the consumer decision-making process, ignoring complex factors such as culture, society and long-term influence of behavior.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2. Flow experiences\u003c/h2\u003e\u003cp\u003eFlow is a positive psychological state in which individuals are fully immersed and focused on an activity, often accompanied by excitement and satisfaction (Csikszentmihalyi, 2000). This state enhances positive experiences and satisfaction by minimizing distractions and increasing behavioral control (Gao and Bai, 2014; Dong et al., 2023). In live broadcasting contexts, flow is marked by deep engagement with the content, a sense of absorption, and loss of time awareness (Chen et al., 2022). It is further associated with temporary enjoyment and a sense of control during interaction with online sales content (Cui et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hyun et al., 2022). Wu et al. (2021) link flow to perceived challenge, usefulness, and spontaneity in content engagement. As a subjective state, flow depends on the participant\u0026rsquo;s skills, the challenge level, and commitment. This study defines flow as intense customer concentration during live broadcasts, where interactive and engaging presentations stimulate interest and may trigger impulsive buying.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3. Behavioral psychology theory\u003c/h2\u003e\u003cp\u003eBehavioral psychology, also known as behaviorism, focuses on explaining human behavior through responses to stimuli from the living environment (Watson, 1994). According to this approach, behavior is formed through the process of learning, conditioning, and can be observed intuitively without delving into the inner life. Freud (1994) added that behavior is influenced by environmental stimuli, but is also governed by internal emotions and desires. Behaviorism refers to two main types of conditioning: classical and operant. Classical conditioning forms behavior based on associations between stimuli and natural responses; meanwhile, operant conditioning is maintained through the reinforcement of behavior observed from others. In the context of this study, behaviorism is applied to explain how consumers respond to environmental factors in live broadcasts. Factors such as social media, relatives or celebrities can influence emotions, stimulating shopping behavior to satisfy psychological needs. Positive emotional states such as happiness are more likely to lead to impulsive shopping behavior. However, the limitation of behavioral theory is that it does not fully consider factors such as free will, internal emotions and personal judgment processes, which also play an important role in consumer behavior.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Hypothesis\u003c/h2\u003e\u003cp\u003eCognitive reactions refers to the mental processing that occurs when individuals encounter external stimuli, such as information on a shopping website (Parboteeah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This process involves both interpretation and emotional evaluation. Emotional reactions, on the other hand, reflects individuals\u0026rsquo; affective reactions, including feelings of joy, excitement, and satisfaction (Kamboj, 2020). In the context of live-stream shopping, environmental stimuli can activate both cognitive and emotional reactions. According to the S-O-R model by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), external stimuli influence internal states\u0026mdash;namely cognition and emotion\u0026mdash;which in turn shape consumer behavior. Parboteeah et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) applied this model to show how website environments can trigger emotional states and lead to impulse buying. Scarcity persuasion, a key factor in live-stream shopping, intensifies emotional responses by creating urgency and competition (Malhotra, 2010). Wu et al. (2021) confirmed that scarcity, whether temporal or quantitative, enhances consumer excitement. Furthermore, scarcity persuasion increases perceived value (Eisend, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and contributes to utilitarian shopping value (Chung et al., 2017), supporting its role in shaping consumer purchase decisions. Therefore, the authors propose the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH1: Scarcity persuasion positively affects cognitive reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eH2: Scarcity persuasion positively affects emotional reaction\u003c/em\u003e\u003c/p\u003e\u003cp\u003eRook (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) argued that visual buying behavior is initiated by the visual contact between the customer and the product. Beatty and Ferrell (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) also explained that visual purchasing is formed through the pleasure of experiencing the product (MacInnis and Price, 1987). The impact of vicarious experience on customers' cognitive and emotional reactions is also based on the theory of the S-O-R model proposed by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), environmental factors affect human cognition and emotion. According to Sowinska and Sokol (2019), it is the vicarious experience that creates an information channel for customers to learn and evaluate and causes a strong stimulating reaction to customers, or that is the impact on customers' product perception. On the other hand, Chen et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) also suggested that this vicarious experience will also positively affect customers' emotional reactions, such as excitement, enjoyment, and perceived future enjoyment (Vazquez et al., 2020). In addition, Roberts (2010) also suggested that through listening and reflective thinking, customers will collect experiences from the broadcast channel combined with their own experiences to make clearer purchasing behavior. Therefore, the author proposes the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH3: Vicarious experience positively affects cognitive reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eH4: Vicarious experience positively affects emotional reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePrevious studies have identified that social interaction positively contributes to the creation of one-way emotional attachment to social actors (Aw and Labrecque, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The impact of social interaction on customers' cognitive and emotional responses is also based on the theory of the S-O-R model proposed by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), environmental factors influence human cognition and emotion. The communication literature has demonstrated that social interaction reflects relevant media use because it can influence users' emotional reactions to media characters and media (i.e., websites) (Labrecque, 2014; Rubin et al., 1985). For example, social interaction has been found to foster affective trust (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Gong and Li (2017) determined that social interaction can shape viewers\u0026rsquo; attitudes toward products and services (Sokolova and Kefi, 2020) and even contribute to the enjoyment of the shopping experience (Xiang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, the author proposes the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH5: Social interaction positively affects emotional reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe impact of social contagion on customers' cognitive and emotional reactions is also based on the theory of S-O-R model proposed by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), environmental factors affect human cognition and emotion. In the study of commerce through live broadcast, social contagion has been applied to allow viewers to influence each other at multiple levels (Hu et al., 2017; Xue et al., 2020). Furthermore, Wang et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that social contagion can influence the impulsive buying process through emotional reactions. Social contagion is proposed to have a significant impact on emotional reactions through impulsive buying on live broadcasts. Therefore, the author proposes the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH6: Social contagion has a positive impact on emotional reaction\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe impact of the presence of live broadcasters on customers' cognitive and emotional reactions is also based on the theory of the S-O-R model proposed by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), environmental factors affect human cognition and emotion. According to Park and Lin (2020), customers are more likely to form positive stereotypes about an attractive live broadcaster, which leads customers to form positive attitudes toward the products they advertise. The social media presence of live broadcasters narrows the psychological distance between viewers and live broadcasters and can help viewers better understand the products they desire, thereby increasing viewers' sense of trust (Jiang et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The social presence of live broadcasters enhances viewers\u0026rsquo; focus on live-streaming commerce, as live broadcasters can provide better personalized services according to viewers\u0026rsquo; needs (Yim et al., 2017). In addition, customers\u0026rsquo; shopping enjoyment can be increased by more human elements in live-streaming commerce, where viewers can see live broadcasters and contact them in real time as if they were communicating face-to-face (Liu et al., 2020). Previous research by Shen (2012) confirmed that the social presence of live broadcasters can increase customers\u0026rsquo; emotional reactions. Therefore, the author proposes the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH7: Social presence of livestreamers positively affects emotional reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe impact of viewer presence on customers' cognitive and emotional reactions is also based on the theory of S-O-R model proposed by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), environmental factors affect human cognition and emotion. The interactivity between viewers in the chat box gives viewers a better sense of social presence, thus encouraging them to participate in the information exchange process (Li et al., 2018). Shopping is considered a social activity performed with companions, such as friends or family members (Lu et al., 2016). Shoppers create a pleasurable experience when interacting with their shopping companions (Wolfinbarger and Gilly, 2001). Live broadcast commerce can satisfy customers' social needs. A high level of perceived presence is beneficial to enhance more friendly communication, and therefore, customers are more likely to enjoy and have a positive shopping experience (Zhu et al., 2006). In general, customers have little knowledge about the actual quality of the product. Live broadcasts allow customers to read, post, and review comments (Fang et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this way, customers can exchange product information with each other, which may increase customers' emotional reactions and thus make purchase decisions. Therefore, the author proposes the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH8: Social presence of viewer has a positive impact on emotional reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003eProduct testing during live broadcasts makes customers feel excited. However, on online platforms, customers cannot physically interact with the product due to spatial separation (Vonkeman et al., 2017). High product presence can be a solution to this concern by narrowing the psychological distance between customers and the product (Kang, 2020). The impact of product presence on customers' cognitive and emotional reations is also based on the S-O-R model theory proposed by Mehrabian and Russell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), environmental factors affect human cognition and emotion. Live broadcast commerce has the potential to provide customers with a shopping experience similar to that of a real product experience. Live broadcasters often try out the product themselves, often accompanied by a vivid demonstration of the product experience. This can make customers imagine what will happen when using the product and then create an emotional reactions (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, the author proposes the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH9: Social presence of products positively affects emotional reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePrevious studies have shown that positive cognitive reactions are closely related to positive emotional reactions. Verhagen and Dolen (2011) applied the cognitive-emotion theory and showed that trust precedes emotion, and thus perceived attractiveness of goods and communication style on the website are important factors that generate positive emotions. Chih et al. (2012) suggested that customers' evaluations of the appropriateness of impulsive buying behavior had a positive impact on the stimulation of online impulsive buying behavior. According to Chen et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), cognitive reactions serve as the foundation for emotional reactions, whereby information must be perceived as credible before an emotional attachment to an individual, brand, or product can be established. Similarly, the usefulness of information must be cognitively examined before an attitude can be formed (Hsu et al., 2013). Parboteeah et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and Xiang et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) proposed that cognitive response to usefulness is positively related to emotional reactions. Hsiao\u0026rsquo;s (2020) study complements previous studies in which cognitive evaluation of values ​​is found to positively contribute to emotional reactions to satisfaction and thus can stimulate purchase intention. Therefore, the authors propose the hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH10: Cognitive reations positively affects emotional reactions\u003c/em\u003e\u003c/p\u003e\u003cp\u003eImpulse buying is defined as a spontaneous and emotionally driven desire to make a purchase without prior planning (Rook, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). This behavior is often triggered by emotional reactions and immediate gratification, sometimes leading to negative consequences due to limited consideration of long-term outcomes (Eysenck et al., 1985; Puri, 1996). Rook and Fisher (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) identify emotions as a key cognitive component in impulsive buying behavior, while Parboteeah et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and Xiang et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) emphasize the significant influence of emotional responses on impulsive buying urge. According to Eroglu et al. (2001), positive emotions experienced during shopping, such as enjoyment, can stimulate unplanned buying. Interpersonal elements such as intimacy and personal connection in online shopping environments further enhance this motivation (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Xiang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Positive emotional states, including joy and excitement, have been shown to contribute directly to impulsive buying urge (Shen and Khalifa, 2012). Thus, the following hypothesis is proposed:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH11: Emotional reactions have a positive impact on impulse buying urge\u003c/em\u003e\u003c/p\u003e\u003cp\u003eImpulsive buying urge refers to the urge to acquire goods or services driven by immediate emotional or situational triggers (Rook, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Loewenstein and Lerner, 2003). While situational constraints such as budget and time may limit actual behavior, numerous studies confirm that the motivation to buy impulsively is a strong predictor of subsequent action (Beatty and Ferrell, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Therefore, the next hypothesis is proposed:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH12: Impulse buying urge positively affects impulse buying behavior\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe moderating role of impulse buying\u003c/b\u003e\u003c/p\u003e\u003cp\u003eImpulsive buying tendency refers to the personality trait of individuals in terms of their tendency to act impulsively in purchase situations (Verplanken and Herabadi, 2001). Previous research has identified impulse buying tendency as an important moderator in the relationship between emotional reactions and impulse buying as well as between impulse buying and impulsive buying behavior (Zafar et al., 2021). Individuals with a high impulse buying tendency generally tend to have other characteristics, such as high action orientation, so such individuals may tend to develop a stronger impulse to act impulsively in purchase situations (Baumeister, 2002; Goel et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). According to Lo et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), individuals with a high impulse buying tendency are more susceptible to emotional influences and more likely to develop impulse buying urge. In contrast, individuals with low impulse buying tendencies may still be affected by emotions but will have better self-control, reducing the likelihood of impulsive buying urge. Individuals with high impulse buying tendencies are more likely to convert impulse buying urge into actual impulse buying behavior, even without prior purchase planning. Individuals with low impulse buying tendencies may feel the urge to buy but will still consider, analyze, and restrain themselves before making a decision about engaging in impulse buying behavior. Therefore, the authors propose the following hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH13a: Impulse buying tendencies moderate the relationship between emotional reactions and impulsive buying urge.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eH13b: Impulse buying tendencies moderate the relationship between impulse buying urge and impulsive buying behavior\u003c/em\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.5.8. Research framework\u003c/h2\u003e\u003cp\u003eBased on the general theoretical framework and a review of related studies and research gaps, the author plans to develop a research model from the original model of Lo et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) because this model focuses on studying environmental factors of livestream sales through the issues of sellers and customers. However, to complete the model and Lo et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the author will inherit additional variables of social media presence of live streamers, social media presence of viewers, and social media presence of products by Lee and Chen (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Li et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); Zhang et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) to fully cover all factors related to the livestream sales environment. Therefore, the proposed research model is as follows (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Methodology used\u003c/h2\u003e\u003cp\u003eThe preliminary quantitative study was conducted to evaluate the reliability and validity of the measurement scales as a preparatory step for the main study, which would employ Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). Initially, the internal consistency of the scales was assessed using Cronbach\u0026rsquo;s Alpha. Subsequently, Exploratory Factor Analysis (EFA) was performed to explore the underlying factor structure and refine the scales where necessary, ensuring that they are suitable for validation through CFA in the main study. According to Hair et al. (2006), a minimum of 50 observations is required for EFA, with 100 being preferable to ensure the robustness of the results. In line with this recommendation, the researcher administered a pilot survey using an online format. The target respondents were individuals from the researcher's personal and professional networks, including family members, friends, and colleagues residing in major urban centers such as Hanoi, Da Nang, Hue, Ho Chi Minh City, and Can Tho.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Questionnaire design\u003c/h2\u003e\u003cp\u003eThese participants were selected based on their active use of social media and engagement in online shopping\u0026mdash;criteria relevant to the study\u0026rsquo;s context. After one month of data collection, 127 valid responses were obtained, exceeding the recommended threshold for preliminary quantitative studies. The data were then coded, processed, and analyzed using SPSS version 25. The results of this pilot study provided a basis for refining the measurement model prior to conducting CFA and SEM on a larger sample in the main study.\u003c/p\u003e\u003cp\u003eThe scales measuring variables in the current research were adopted from existing literature. Specifically, we used the scale from Chen et al. (2022) with three items to measure Scarcity Persuasion, and a three-item scale from Chen and Lin (2017) was utilized to measure Vicarious Experience. Social Interaction was measured using four items from Chen and Lin (2017), and Social Contagion was assessed using three items adapted from Lim et al. (2012). Additionally, we adopted a four-item scale to measure Social Presence of Livestreamers and and Social Presence Viewer with three items from Ming et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Social Presence of Product was measured using four items from from Chen et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Cognitive Reactions and Emotional Reactions form Li et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Impulsive Buying Urge with four items from Lee v\u0026agrave; Chen (2021). Impulsive Buying Behavior with three items and Impulsive Buying Tendency with three items form Chen et al. (2022) in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eConstructs and measurement items.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContrust\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMeasures\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSupporting Refences\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eScarcity\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePersuasion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen watching promotions through live broadcast, I think many people will compete with me to buy promotional items\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChen et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen watching promotions through live broadcast, I think promotional products will sell out quickly\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI think product scarcity is strategically created by pulling customers to stay in the live broadcast shopping scene\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eVicarious Experience\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVE1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBy watching the live broadcast of the product introduction, I can feel what the author wants to say about the introduced products as well as their experience of using them\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChen and Lin (2017)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBy watching the live broadcast of the product introduction, I can imagine what the author wants to say about the introduced products as well as their experience of using them\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVE3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBy watching the live broadcast of the product introduction, I can imagine what the author wants to say about the recommended products and their experience of using them\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eSocial Interaction\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSI1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen watching a live broadcast, I can easily exchange and share opinions with the livestreamers or other viewers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eChen and Lin (2017)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSI2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I am watching a live broadcast, the broadcaster knows that I am interested in them\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSI3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I am watching a live broadcast, I feel closer to the broadcaster\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSI4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I am watching a live broadcast, the broadcaster will provide enough opportunities to respond and ask questions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eSocial Contagion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMy behavior is influenced by other team members\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eLim et al. (2012)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMy behavior influences other team members\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOur team agrees on similar opinions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eSocial Presence Livestreamers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPL1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI can understand the attitudes of live broadcasters by interacting with them through live broadcast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eMing et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPL2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIt feels human to communicate with live broadcasters through live broadcast\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPL3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCommunicating with sellers through streamers through live broadcast is very warm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPL4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI can know what sellers look like when interacting with them through live broadcast\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eSocial Presence Viewer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI know other viewers in the live stream are also interested in the product\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eMing et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI know other viewers in the live stream are also sharing information about the product\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPV3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI know other viewers in the live stream have purchased the product\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eSocial Presence of Product\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel enthusiastic about the recommended product\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eChen et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel inspired by the recommended products\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel excited about the recommended products\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSPP4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel interested in the recommended products\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eCognitive Reactions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel excited when shopping through watching live broadcast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eLi et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel excited when shopping through watching live broadcast\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel surprised when shopping through watching live broadcast\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCR4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel confident when shopping through watching live broadcast\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEmotional Reactions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel happy when shopping through watching live broadcasts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eLi et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel happy when shopping through watching live broadcasts\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel satisfied when shopping through watching live broadcasts\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI feel comfortable when shopping through watching live broadcasts\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eImpulsive Buying Urge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBU1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen watching live broadcasts, I want to buy items that are not related to my original shopping goals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eLee v\u0026agrave; Chen (2021)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBU2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI suddenly feel like buying things when shopping on a live broadcast commerce platform\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBU3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhile watching a live broadcast commerce program, I tend to buy items that are not related to my original shopping goals\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBU4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I shop on a live broadcast commerce platform, I suddenly feel like buying something\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eImpulsive Buying Behavior\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I watch live shopping, I often buy items other than or outside of my specific shopping goals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChen et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThere are many things I have bought from live shopping, but I rarely use them\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSometimes I buy things from live shopping because I like to buy them rather than because I need them\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eImpulsive Buying Tendency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I watch product recommendations through live, I want to buy items other than my specific shopping goals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChen et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I watch product recommendations through live, I want to buy items that are not related to my specific shopping goals\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhen I watch product recommendations through live, I tend to buy items outside of my specific shopping goals\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Results and findings","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Demographic statistics\u003c/h2\u003e\u003cp\u003eThe author collected 553 responses, of which 31 responses did not meet the requirements, and finally the author had 522 valid responses left, and this number satisfied the sample size requirement. The characteristics of the official research sample with a sample size of n\u0026thinsp;=\u0026thinsp;522 observations were classified by gender, age, place of residence, occupation, education level, monthly income, and frequency of use per day, details are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResponse rate of groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCharacter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32,8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e351\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom 16 to 22 years old\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom 23 to 30 years old\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom 31 to 40 years old\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore than 40 years old\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHo Chi Minh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHa Noi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22,4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDa Nang\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16,9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCan Tho\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOfficer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTechnical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBusiness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22,8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHighschool\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e226\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eIncome per month\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow 7 million\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom 7 to unde r15 million\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom 15 to under 25 million\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore than 25 million\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eFrequency of use\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow 2 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom 2 to 4 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e60,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore than 4 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18,8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBased on the results of Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, among the 522 official customers, the female gender accounts for a higher proportion of 67.2%. In terms of age, the age group from 16 to 30 years old accounts for the majority, with 79.7%, these are young customers who are convenient in using smart technology devices to access social networks. In terms of place of residence, Ho Chi Minh City accounts for the highest proportion of 30.7%, followed by Hanoi with 22.4%, these are the two largest cities in Vietnam. In terms of occupation, office workers account for the highest proportion, with 33.3%. The educational level is university, with the highest proportion of 43.3%. In terms of monthly income, income from 7 to under 15\u0026nbsp;million and from 15 to under 25\u0026nbsp;million accounts for the majority; this is considered the average income level and convenient for customers to shop online. The frequency of use of customers from 2 to 4 hours accounts for the highest rate at 60.2%.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Reliability Test\u003c/h2\u003e\u003cp\u003eAfter synthesizing the method and the meanings of the test coefficients, for this study, the author decided to use a large sample size to suit the testing of the new scale with an expanded context. Therefore, the Cronbach's Alpha coefficient to measure the reliability of the scale will be based on the results of Nunally (1978) with the result being greater than 0.6. In addition, the total correlation coefficient of the observed variables must be greater than 0.3 to ensure reliability. The test results are summarized in the following table:\u003c/p\u003e\u003cp\u003eIt shows that the factors scarcity, vicarious experience, Social interaction, Social contagion, Livestreamers' Social Presence, Viewers' Social Presence, Products' social presence, Cognitive response; Emotional response; Impulsive Buying Urge, Impulsive Buying Behavior, Impulsive Buying Tendency all have Cronbach's Alpha coefficients greater than 0.6 with values ​​of 0.845; 0.937; 0.909; 0.812; 0.849; 0.880; 0.938; 0.847; 0.896; 0.855; 0.809; 0.845; At the same time, the total item correlation coefficients of the measurement observations for these factors are all greater than 0.3 and the Cronbach's Alpha value if the variable is removed is all less than the overall Cronbach's Alpha value of the group. Therefore, we can see that these factors and their observations all achieve reliability, meeting the conditions for EFA analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Confirmatory factor analysis (CFA)\u003c/h2\u003e\u003cp\u003eTo assess the reliability of the measurement scales, composite reliability values above 0.6 are considered acceptable. Based on the results presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the composite reliability scores for the variables Scarcity Persuasion (SP), Vicarious Experience (VE), Social Interaction (SI), Emotional Contagion (EC), Social Presence of Livestreamer (SPL), Social Presence of Viewers (SPV), Social Presence of Products (SPP), Cognitive Responses (CR), Emotional Responses (ER), Impulse Buying Urge (IBU), and Impulse Buying Behavior (IBB) are 0.845, 0.937, 0.909, 0.813, 0.849, 0.881, 0.938, 0.847, 0.896, 0.858, and 0.810, respectively. Since all values exceed the minimum threshold, it can be concluded that the scales demonstrate high internal consistency and are reliable for use in the study.\u003c/p\u003e\u003cp\u003eRegarding convergent validity, the average variance extracted (AVE) should exceed 0.5 for each construct. According to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the AVE values for Scarcity Persuasion, Vicarious Experience, Social Interaction, Emotional Contagion, Presence of Streamers, Presence of Viewers, Product Presence, Cognitive Reaction, Emotional Reaction, Impulsive Buying Urge, and Impulsive Buying Behavior are 0.645, 0.833, 0.714, 0.594, 0.585, 0.712, 0.792, 0.581, 0.684, 0.668, and 0.588, respectively. Since all AVE values are greater than 0.5, the constructs meet the criteria for convergent validity.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eConfirmatory factor analysis (CFA) fitting indices.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCronbach\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAVE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScarcity Persuasion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,845\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,845\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,645\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,778\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,783\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,791\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVicarious Experience\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,937\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,937\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,833\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVE1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,910\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,912\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVE3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,904\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Interaction\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,909\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,909\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,714\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,883\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,779\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,887\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,797\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,881\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,876\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Contagion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,813\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,812\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,594\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,785\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,668\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,735\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,701\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Presence of Livestreamer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,849\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,849\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,585\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPL1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11,25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,805\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPL2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,668\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,817\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPL3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11,02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,957\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,806\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPL4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11,15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,806\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Presence of Viewers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,881\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,880\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,712\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,840\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,698\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,802\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPV3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,749\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,848\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Presence of Products\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,938\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,938\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,792\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9,023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,803\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,934\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8,287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,861\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,915\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8,277\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,909\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPP4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8,002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,868\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCognitive Response\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,847\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,847\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,581\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,583\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,796\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,699\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,799\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCR3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,807\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCR4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,650\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,820\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmotional Response\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,896\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,896\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,684\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,859\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,791\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,857\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,870\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,742\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,876\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImpulsive Buying Urge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,858\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,855\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,668\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBU1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,783\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBU2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,794\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBU3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,718\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,813\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImpulsive Buying Behavior\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0,810\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,809\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0,588\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,676\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,761\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,716\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,738\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImpulsive Buying Tendency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0,845\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,9713\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,778\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,0307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,783\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,0019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,791\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote. n\u0026thinsp;=\u0026thinsp;407; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Environmental concern is the control variable.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eCR: composite reliability; AVE: average variance extracted.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eSource: Created by authors.\u003c/em\u003e Cronbach\u0026rsquo;s Alpha (CA) and Composite Reliability (CR) were used to assess the internal consistency reliability of all constructs. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, all constructs reported high reliability, with CA values ranging from 0.762 to 0.913, exceeding the threshold of 0.70 (Hair et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This indicates that the measurement items for each construct are internally consistent and reliable. Next, convergent validity was assessed using two criteria: (1) Average Variance Extracted (AVE) and (2) standardized factor loadings. The diagonal values in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e represent the square root of the AVE for each construct, and all are greater than 0.70\u0026mdash;specifically, the values range from 0.762 to 0.913\u0026mdash;surpassing the recommended threshold of 0.50 (Fornell \u0026amp; Larcker, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Furthermore, the standardized factor loadings for all items were statistically significant and above 0.60, confirming that the constructs demonstrate adequate convergent validity (Hair et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Moreover, discriminant validity was assessed using the Fornell-Larcker criterion. The square root of the AVE for each construct (displayed on the diagonal in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e) is higher than any of its correlations with other constructs (off-diagonal values), indicating that each construct shares more variance with its own measures than with others. In addition, none of the confidence intervals for correlation coefficients includes the value of 1, providing further support for discriminant validity (Fornell \u0026amp; Larcker, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1981\u003c/span\u003e) in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDiscriminant validity.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSPl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSPV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSPP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eER\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eIBU\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eIBB\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.890\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.381 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.845\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.652 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.384 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.827\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.331 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.279 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.441 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.762\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSPL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.116 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.181 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.913\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSVP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.518 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.432 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.465 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.223 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.765\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSPP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.131 **\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.170 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.089\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.093\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.844\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.455 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.360***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.559 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.396 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.094\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.411 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.817\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eER\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.301 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.516 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.369 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.417 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.179 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.253 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.318 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.803\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIBU\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.094\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.101\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.189 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.118*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.77\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIBB\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.592 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.355 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.618 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.405 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.418 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.187 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.490 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.246 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e-0.148 **\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.767\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003cem\u003eNote. Square roots of AVE are in bold; Correlations between variables are in off-diagonal elements; Heterotrait-Monotrait ratios are in italic.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eSource: Created by authors.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Structural Equation Modeling (SEM)\u003c/h2\u003e\u003cp\u003eThe data analysis reveals significant positive relationships among all proposed variables. Scarcity Persuasion shows a strong positive effect on cognitive reaction (β\u0026thinsp;=\u0026thinsp;0.429, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H1. Vicarious experience (β\u0026thinsp;=\u0026thinsp;0.101, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and social interaction (β\u0026thinsp;=\u0026thinsp;0.090, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) also exhibit positive influences on cognitive reaction, thereby supporting H2 and H3. Emotional contagion demonstrates a significant effect on emotional reactions (β\u0026thinsp;=\u0026thinsp;0.078, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming H4. Likewise, the presence of streamers (β\u0026thinsp;=\u0026thinsp;0.094, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the presence of viewers (β\u0026thinsp;=\u0026thinsp;0.094, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) positively influence emotional reactions, supporting H5 and H6. Product presence significantly enhances both cognitive and emotional reactions (β\u0026thinsp;=\u0026thinsp;0.159, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H7.\u003c/p\u003e\u003cp\u003eFurthermore, cognitive reactions positively affect impulse buying urge (β\u0026thinsp;=\u0026thinsp;0.083, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and emotional responses show an even stronger effect (β\u0026thinsp;=\u0026thinsp;0.543, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming H8 and H9. Flow experience also has a positive impact on impulse buying urge (β\u0026thinsp;=\u0026thinsp;0.226, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), thus supporting H10. Notably, emotional reactions strongly predict impulse buying urge (β\u0026thinsp;=\u0026thinsp;0.578, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H11. Finally, impulsive buying urge significantly influences impulse buying behavior (β\u0026thinsp;=\u0026thinsp;0.524, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), thereby confirming H12. Collectively, the results provide empirical support for all hypothesized relationships, as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of hypothesis test.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStandardized path coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResult\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.429***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.090***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.101***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.078***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.094***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.094***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.159***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.083***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.543***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.226***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.578***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.524***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNote. N\u0026thinsp;=\u0026thinsp;319, *p\u0026thinsp;\u0026lt;\u0026thinsp;.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003ch2\u003eModerating effect of impulsive buying tendency\u003c/h2\u003e\u003cp\u003eTo examine the moderating role of impulsive buying tendency (IBT), we used Model 1 of the PROCESS macro (Hayes, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). First, the direct effect of impulsive buying tendency on impulsive buying behavior (HV) was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Next, we examined whether the interaction term (emotional response \u0026times; impulsive buying tendency) had a significant effect on impulsive buying urge (IBU). The result shows a significant interaction effect (β\u0026thinsp;=\u0026thinsp;0.1985, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that impulsive buying tendency positively moderates the relationship between emotional response and impulsive buying urge. Thus, H13a is supported.\u003c/p\u003e\u003cp\u003eIn addition, the effect of the interaction term (impulsive buyng ugre \u0026times; impulsive buying tendency) on impulsive buying behavior was also significant (β\u0026thinsp;=\u0026thinsp;0.2468, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This result suggests that impulsive buying tendency also moderates the relationship between impulsive buying urge and actual impulsive buying behavior, and this moderating effect is positive. Therefore, H13b is also supported in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003ePath coefficients and significances\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePath\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandardized path coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResult\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH13a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER➝ IBU(moderated by XH)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.1985***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH13b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIBU ➝ IBB (moderated by IBT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.2468***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eER\u0026thinsp;=\u0026thinsp;Emotional response, IBU\u0026thinsp;=\u0026thinsp;impulsive buying Ugre, IBB\u0026thinsp;=\u0026thinsp;Impulse buying behavior, IBT\u0026thinsp;=\u0026thinsp;Impulsive buying tendency, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe findings from the quantitative analysis confirm that the proposed theoretical model fits well with the empirical data. All 14 hypothesized relationships, which explore the influence of livestream-based shopping environments on consumers' impulse buying behavior in Vietnam, are statistically supported. The structural equation modeling results reveal that various elements of the livestream shopping environment significantly impact both cognitive and emotional reactions. Specifically, scarcity persuasion exerts a strong positive influence on cognitive reactions (standardized coefficient\u0026thinsp;=\u0026thinsp;0.429), while vicarious experience also contributes positively (β\u0026thinsp;=\u0026thinsp;0.090). In terms of emotional reactions, multiple environmental factors show significant effects. Scarcity (β\u0026thinsp;=\u0026thinsp;0.101), vicarious experience (β\u0026thinsp;=\u0026thinsp;0.078), social interaction (β\u0026thinsp;=\u0026thinsp;0.094), and social contagion (β\u0026thinsp;=\u0026thinsp;0.094) all positively influence emotional reactions. Additionally, the social presence of streamers (β\u0026thinsp;=\u0026thinsp;0.159), social presence of viewers (β\u0026thinsp;=\u0026thinsp;0.083), and social presence of product (β\u0026thinsp;=\u0026thinsp;0.543) are found to be key emotional triggers within the livestream setting. Beside, cognitive reactions further enhance emotional reaction (β\u0026thinsp;=\u0026thinsp;0.226), highlighting the interaction between rational evaluation and affective reactions. Emotional reactions are shown to significantly drive impulsive buying urge (β\u0026thinsp;=\u0026thinsp;0.578), which in turn positively influences actual impulse buying behavior (β\u0026thinsp;=\u0026thinsp;0.524).\u003c/p\u003e\u003cp\u003eMoreover, the moderating role of individual impulsive buying tendency is confirmed. This variable strengthens the relationship between emotional reactions and impulsive buying urge, as well as between buying urge and actual behavior. These results emphasize the psychological complexity of impulse purchases in the context of livestream commerce. Based on these empirical findings, the study provides a foundation for strategic recommendations aimed at enhancing consumer engagement and stimulating impulse buying through livestream platforms. Managerial implications derived from these results are discussed in the following section.\u003c/p\u003e"},{"header":"6. Conclusion and managerial implications","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e6.1. Conclusion\u003c/h2\u003e\u003cp\u003eBased on the hypothesis testing results regarding the relationship between livestream shopping environment factors and impulsive buying behavior in Vietnam, several managerial implications can be drawn. First, scarcity persuasion significantly influences both cognitive and emotional reactions, thereby encouraging impulsive purchases. Marketers should strategically create a sense of scarcity by limiting product quantities, displaying countdown timers, or showing the number of items sold and remaining. However, excessive use of this tactic can lead to consumer distrust or psychological discomfort, so it must be applied with caution. Second, vicarious experience positively affects consumer responses. Livestreamers should share authentic user experiences, respond promptly to comments, and demonstrate product use clearly. This builds a sense of realism and trust. Avoiding overly scripted or exaggerated content is crucial to prevent consumer skepticism.\u003c/p\u003e\u003cp\u003eThird, social interaction enhances emotional reactions, which in turn stimulate impulsive buying. E-commerce platforms should encourage product reviews and viewer interactions during livestreams. Designing livestreams as engaging, dialogue-based events rather than scripted presentations can increase emotional connection and brand attachment. Fourth, social contagion plays a significant role. When viewers observe others enthusiastically purchasing or engaging, they are more likely to join. Strategies such as flash sales, surprise giveaways, and group-buying campaigns can amplify this effect. Incentivizing users to refer friends or post reviews on social media also fosters wider engagement. Fifth, the presence of livestream hosts influences emotional reactions. Hosts should maintain an energetic and engaging atmosphere, provide clear and honest responses to questions, and incorporate entertaining elements to retain viewer attention. Well-trained hosts or collaborations with influencers can further enhance trust and purchase intention.\u003c/p\u003e\u003cp\u003eSixth, the presence of other viewers can also trigger emotional responses and impulsive actions. Sellers should promote viewer interaction through comments, questions, and minigames. Personalized engagement, such as addressing viewers by name or recommending tailored products, enhances the perceived value of the session. Seventh, product presence strongly influences emotions. High-quality visual presentations, accurate information, and advanced display technologies can improve the perceived appeal of products. Personalized product suggestions based on user preferences can further drive cross-selling and impulse purchases. Finally, impulsive buying tendency moderates the relationship between emotional responses and buying behavior. Marketing strategies should emphasize emotional stimulation, such as through exclusive deals, limited-time offers, and interactive promotions, to capitalize on consumers\u0026rsquo; impulsive inclinations during livestream shopping.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e6.2. Theory and managerial implications\u003c/h2\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e6.2.1. Theory implications\u003c/h2\u003e\u003cp\u003eThis study was conducted to synthesize the theoretical framework related to the factors of shopping environment through live broadcast media, cognitive response, emotional response and impulsive shopping behavior of customers. The S-O-R model (Sherman et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) was deployed to study the impact of stimuli on the object and response because the theory has been proven to be applicable in understanding the process of forming impulsive shopping behavior (Lee and Chen, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lo et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The flow experience theory (Csikszentmihalyi, 2000) is also related to the topic because the flow experience theory refers to the creativity, comfort or freedom of customers in accessing information to make a certain decision. This explains why customers can be caught up in the shopping process and easily make unplanned purchasing decisions. When customers reach the flow state, they are easily influenced by environmental and emotional factors, thereby performing impulsive shopping behavior. At the same time, the study reviewed related studies to identify research gaps up to now. Most previous studies focused on factors affecting normal shopping behavior and then inferred to impulsive buying behavior. Therefore, this study focuses on aspects related to customer psychology, such as customers' cognitive reactions and emotional reactions, shopping environments through live broadcast media belonging to both sellers and buyers affecting customers' impulsive buying behavior. On the other hand, measuring the moderation level of impulse buying tendency on the relationship between emotional reactions to impulse buying urge and the relationship between impulse buying urge and impulse buying behavior.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003e6.2.2. Practice implications\u003c/h2\u003e\u003cp\u003eThis study offers practical insights for online retailers leveraging livestreaming to stimulate impulse purchases. The findings highlight the importance of creating a compelling shopping environment that triggers both cognitive and emotional reactions. Retailers should use scarcity persuasion strategically to create urgency, while ensuring authenticity through real-time interactions, honest demonstrations, and relatable content. Encouraging active viewer engagement, facilitating social interactions, and enhancing the presence of hosts and products can significantly influence buyer behavior. Furthermore, personalizing the shopping experience and incorporating emotional triggers\u0026mdash;such as limited-time offers or interactive promotions\u0026mdash;can effectively target consumers with a higher tendency for impulsive buying. These strategies, when thoughtfully applied, can enhance viewer immersion and drive spontaneous purchases during livestream shopping sessions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"7. Limitation and future research","content":"\u003cp\u003eDespite its contributions, this study has several limitations that suggest avenues for future research. First, the research model focuses solely on specific environmental factors in the livestream shopping context\u0026mdash;namely scarcity persuasion, vicarious experience, social interaction, social contagion, and the presence of livestream hosts, viewers, and products\u0026mdash;while other potentially influential variables remain unexplored. Future studies should consider expanding the model to include additional psychological, technological, or contextual factors that may also drive impulsive buying behavior. Second, the sample was limited to a few major cities in Vietnam, which may not fully represent consumer behavior in other regions. Future research should broaden the geographic scope to include more diverse localities and examine how regional or cultural differences influence impulse buying. Additionally, analyzing variations across different demographic groups (e.g., age, income, online shopping habits) could uncover nuanced insights into how customer characteristics moderate the impact of environmental factors, thereby providing more targeted managerial strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eS\u0026ndash;O\u0026ndash;R \u0026nbsp;Stimulus\u0026ndash;Organism\u0026ndash;Response\u003c/p\u003e\n\u003cp\u003eSP \u0026nbsp;Scarcity Persuasion\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVE \u0026nbsp;Vicarious Experience\u003c/p\u003e\n\u003cp\u003eSI \u0026nbsp;Social Interaction (SI),\u003c/p\u003e\n\u003cp\u003eEC \u0026nbsp;Emotional Contagion,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSPL Social Presence of Livestreamers\u003c/p\u003e\n\u003cp\u003eSPV \u0026nbsp;Social Presence Viewers\u003c/p\u003e\n\u003cp\u003eSPP \u0026nbsp;Social Presence of Products\u003c/p\u003e\n\u003cp\u003eCR \u0026nbsp;Cognitive Responses (CR),\u003c/p\u003e\n\u003cp\u003eER \u0026nbsp;Emotional Reactions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIBM \u0026nbsp;Impulse Buying Urge\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIBB \u0026nbsp;Impulse Buying Behavior\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMany thanks to all the participants, the main investigators and the research team.\u003cstrong\u003e\u0026nbsp;Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specifc grant from funding agencies in the public, commercial, or not-for-proft sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration interests statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval for the research was granted by Ho Chi Minh Banking University and Publication Ethics Committee on 1.05.2023, under decision number H10REA15. All procedures involving human participants followed the ethical standards of the institutional and national research committees and aligned with the 1964 Helsinki Declaration and its amendments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eonsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe provided detailed information to the participants about the purpose, scope and expectations of the study before they participated in the study. We explained the aims of the study, the information requested from the participants, the data collection process and the method of using the data in a clear and understandable language. Before the research survey questionnaire, the participants received a consent form between May 1, 2023 and May 1, 2025, having read and understood the research\u0026rsquo;s purpose. \u0026nbsp;We informed the participants that participation in the study was completely voluntary and that they had the right to withdraw from the study at any stage. We obtained written informed consent forms from the participants. These forms indicate that the participants accepted the terms of the study and approved the use of their data for the purposes of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed written consent for publication was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors made substantial contributions to the conceptualization of the work and developed the interview guides Van Dat Tran: Data collection; analysis; methodology; writing original draft; Van Dat Tran: Review and editing: Van Dat Tran: Data collection; analysis: Huynh Le Cong Truong; Data collection; analysis. Huynh Le Cong Truong: Date collection; translation. Huynh Le Cong Truong: Data collection; translation Huynh Le Cong Truong: Data collection. Van Dat Tran: Supervision and review Van Dat Tran: Review and editing Van Dat Tran: Data collection; methodology; supervision; review and editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkram, U., Hui, P., Khan, M. K., Tanveer, Y., Mehmood, K., \u0026amp; Ahmad, W. (2018). How website quality affects online impulse buying: Moderating effects of sales promotion and credit card use. \u003cem\u003eAsia Pacific Journal of Marketing and Logistics\u003c/em\u003e, 30(1), 235\u0026ndash;256.\u003c/li\u003e\n\u003cli\u003eAng, T., Wei, S., \u0026amp; Anaza, N. A. (2018). Livestreaming vs pre-recorded: How social viewing strategies impact consumers\u0026rsquo; viewing experiences and behavioral intentions. \u003cem\u003eEuropean Journal of Marketing\u003c/em\u003e, 52(9/10), 2075\u0026ndash;2104.\u003c/li\u003e\n\u003cli\u003eAw, E. C. X., \u0026amp; Labrecque, L. I. (2020). 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The role of emotional and rational motivations. \u003cem\u003eInformation \u0026amp; Management\u003c/em\u003e, 59(4), 103588.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Shopping environment factors through livestreams, cognitive reactions, affective reactions, impulsive buying urge, impulsive buying behavior, impulsive buying tendency","lastPublishedDoi":"10.21203/rs.3.rs-6877937/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6877937/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eBased on the synthesis of background theory, research concepts and related research articles, the research has built a research model on the relationship between shopping environment factors via livestreams and customers' impulsive buying behavior in Vietnam.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe research was conducted with data collected from 522 customers shopping for goods via livestreams on the platforms TikTok, Facebook, and Shopee.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe results showed that the theoretical research model was consistent with the market data, and the results of testing 14 hypotheses were all accepted. The results of the SEM linear structural model testing showed that the environmental factors of shopping through livestreams, including scarcity and vicarious experience, had a positive impact on cognitive reactions; scarcity, vicarious experience, social interaction, social contagion, social presence of livestreams, social presence of viewers, and social presence of products had a positive impact on affective reactions. Cognitive reactions had a positive impact on affective reactions, affective reactions had a positive impact on impulsive buying urge, impulsive buying urge had a positive impact on impulsive buying behavior. Finally, the results of the moderator variable test showed that there is an impact of the moderator variable impulsive buying tendency on the impact of affective reactions to impulsive buying urge and an impact of the moderator variable impulsive buying tendency on the impact of impulsive buying urge on impulsive buying urge behavior.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eBased on the research results, the author gives managerial implications to enhance customers' impulsive shopping behavior through livestreams.\u003c/p\u003e","manuscriptTitle":"The Relationship Between Shopping Environment Factors Via Livestreams and Customers' Impulsive Buying Behavior Invietnam: TheModerating of Impulsive Buying Trendency","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-25 09:05:17","doi":"10.21203/rs.3.rs-6877937/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"64493497054944679793191248073609488644","date":"2025-08-04T14:41:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-23T05:11:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-16T15:19:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-25T07:30:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T03:40:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-06-23T03:37:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9468a9e3-9fe7-461c-adc2-222a52a40e9c","owner":[],"postedDate":"July 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-25T09:05:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-25 09:05:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6877937","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6877937","identity":"rs-6877937","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}