Global e-commerce sales are set to soar, revealing a transformative digital marketplace. However, approximately $1 trillion in potential revenue is lost annually due to insufficient customer loyalty in social commerce (George, 2024). This stark financial impact underscores the urgent need to understand and address the drivers of sustainable consumer relationships. The rapid evolution of information technology has transformed the commercial landscape, catalyzing growth in electronic commerce (e-commerce) and fueling the rise of social commerce. Industry projections forecast robust e-commerce sales growth, highlighting the expanding significance of online business models in global retail (eMarketer, 2021). At the same time, the proliferation of social media platforms, which command billions of users worldwide, has created fertile ground for combining social interactions with commercial activities (Luttrell, 2025). This integration has led to the emergence of social commerce, a subset of e-commerce that leverages social media and Web 2.0 technologies for transactions, marketing, and community-driven engagement (Hajli, 2015; Liang & Turban, 2011).

Unlike traditional e-commerce, which primarily focuses on transactional efficiency, social commerce places a greater emphasis on communication, cooperation, and social relationships between consumers and businesses, thereby cultivating more socially conscious and interconnected customer communities and creating a more humanized, interactive, and trustworthy online shopping experience (Liang & Turban, 2011; Attar et al., 2022). For instance, platforms like Facebook, Instagram, and TikTok have evolved beyond mere social networking sites into vibrant commercial hubs where users can discover products, share reviews, interact directly with sellers, and make purchases within a socially enriched environment. This shift is particularly evident in markets like Malaysia, where entrepreneurs increasingly utilize social networking sites (SNSs) to launch and scale businesses, supported by national digitalization initiatives such as the eUsahawan program (Mohamad et al., 2022; Molinillo et al., 2020). For example, a Malaysian micro-seller on TikTok Live showcases her handmade jewelry to viewers who interact in real time, offering feedback and encouragement. For these viewers, engaging in this dynamic exchange not only fulfills an immediate desire for unique products but also satisfies deeper social and self-expressive needs. They experience a sense of community and belonging, foster individual expression through personalized interactions, and acquire social currency by sharing these experiences within their networks. This scenario highlights how social commerce transforms statistical trends into tangible human experiences, making the online shopping experience feel personal and engaging.

In this dynamic and competitive environment, identifying the drivers of long-term business success is paramount for both academics and practitioners. While much research initially focused on the adoption of social commerce platforms and first-time purchase intentions, customer loyalty and retention are increasingly recognized as critical for sustainable growth and profitability (Dincer & Dincer, 2023; Hou et al., 2022). Customer loyalty in social commerce is a comprehensive commitment encompassing behaviors beyond repeat transactions, such as active participation in brand communities, positive word-of-mouth (WOM), customer engagement behavior intention (CEBI), and robust repurchase intention (Ho & Wang, 2015; Lee et al., 2021; Mubdir et al., 2025; Pambudi et al., 2025). There is a pressing need to systematically investigate the key factors that foster this multifaceted loyalty.

A pivotal antecedent in the virtual environment is social presence, theoretically defined as the user's subjective sense of warmth, sociability, and personal connection with others during a mediated encounter (Kreijns et al., 2022; Schultze & Brooks, 2019). In social commerce settings, interactive features such as live-streaming e-commerce, real-time chat, and dynamic comment sections can significantly enhance this sense of social presence, making consumers feel more authentically connected to sellers and fellow users (Qin et al., 2023; Shi et al., 2023). This heightened psychological sense of presence is crucial, as it helps mitigate the perceived risk and uncertainty inherent in online shopping, thereby effectively building trust and strengthening repurchase intention (Hipólito et al., 2025; Lăzăroiu et al., 2020; Miao et al., 2022). The role of trust is further illuminated by the trust transfer theory, which posits that trust can develop and transfer across levels within a community such as from trust in other community members (member trust) to a more generalized trust in the platform itself (community trust) (Chen & Shen, 2015; Jeon et al., 2021; Shao et al., 2022). To illustrate this, consider how a single buyer's positive experience shared on a social media platform can cascade through weak ties, as others share their live-stream links or endorsements. This ripple effect exemplifies the exponential payoff of even small boosts in social support, as the initial trust one experiences can quickly spread to many, significantly strengthening community trust. Research consistently indicates that social support, categorized into emotional support, such as caring and empathy, and informational support, such as advice and suggestions from peers, can significantly strengthen member trust, which subsequently transfers to bolster community trust, thereby creating a more reliable and secure environment for transactions (Wells et al., 2011).

The dynamic interplay among social presence, trust, and commitment provides the theoretical foundation for customer engagement, a pivotal psychological state that drives subsequent consumer behaviors (Hollebeek & Macky, 2019; Nadeem et al., 2020). Customer engagement is best understood as a multidimensional, second-order construct reflecting a customer's cognitive, emotional, and behavioral investment in their interactions with a brand or community (Hollebeek, 2011; Molinillo et al., 2020). Customer loyalty and retention are paramount for long-term success in social commerce, but they must be understood as a complex notion that encompasses actions like good word-of-mouth and consumer interaction, not solely purchase frequency. The study aims to delineate two crucial behavioral outcomes reflecting this loyalty, which can be strategically categorised into transactional and non-transactional behaviors. The primary transactional outcome is repurchase intention, defined as a customer's propensity or desire to again purchase a good or service from the same vendor or platform. Repurchase intention is recognized as a vital sign of client loyalty and a critical determinant of long-term business success, though its role has historically been under-explored compared to initial adoption intent (Fang et al., 2014; Miao et al., 2022). The critical non-transactional outcome is customer engagement behavior intention (CEBI), which describes the deliberate behaviors and propensity of consumers to engage with a company outside of making a purchase, motivated by their sense of social presence and contentment on a digital platform (Algharabat et al., 2018; Hollebeek & Macky, 2019). CEBI includes a variety of loyalty-driven actions such as sharing, liking, commenting, offering feedback, and suggesting items. These actions are essential for creating a community of devoted consumers who actively support and promote the brand (Lee et al., 2021). The relationship between a customer's loyalty (repurchase intention) and these subsequent active participation behaviors may be significantly influenced by social influence, in which peer pressure serves as a crucial mediating factor. This dynamic suggests that peers' perceived opinions and behaviors can moderate and amplify repurchase decisions and subsequent engagement intentions (Izogo et al., 2022; Meilatinova, 2021).

Despite the crucial role of customer loyalty and retention for long-term success in the rapidly growing social commerce industry, the factors driving this loyalty, especially beyond initial purchase intent, remain an important focus area in consumer behavior research. Social commerce, which encourages greater communication and cooperation between consumers and businesses, provides a distinctive environment for examining these dynamics. The study acknowledges that customer loyalty is a complex notion that encompasses actions like good word-of-mouth (WOM) and consumer interaction, not merely adoption or buy intent. A significant theoretical and empirical gap exists concerning the holistic linkage between social presence, described as the sense of warmth and personal connection in a virtual encounter, and its influence on subsequent consumer loyalty outcomes. Specifically, few studies have simultaneously examined the intricate relationships between social presence and the sequential impact it has on social commerce trust and commitment, ultimately leading to repurchase intention (Lee et al., 2021; Liu et al, 2018; Nadeem et al., 2020). Furthermore, while repurchase intention has historically been viewed as a stand-in for brand loyalty, comprehensive research that investigates its distinct effect on subsequent, non-transactional outcomes, such as customer engagement behavior intention (CEBI), remains vital for understanding long-term success. The mediating influence of social dynamics, such as social influence (peer pressure), in amplifying the impact of social presence on purchasing decisions also requires nuanced exploration (Busalim et al., 2024; Molinillo et al., 2020). This study, therefore, seeks to address these identified gaps by proposing and empirically testing an integrated research model focused on how social presence affects repurchase intention and its ensuing influence on CEBI. The relationships investigated, such as those between repurchase intention and engagement behaviors, are grounded in established theoretical perspectives, including the Expectation-Confirmation Theory (ECT), the Theory of Planned Behavior (TPB), and Social Exchange Theory (SET). This study’s comprehensive analysis aims to offer valuable insights into strengthening customer loyalty and promoting active customer engagement in the digital era.

By integrating established perspectives, including the Social Exchange Theory (SET), Theory of Planned Behavior (TPB), and the customer engagement literature, this study makes several significant theoretical contributions to the field of social commerce. Firstly, it advances existing literature by offering a new, integrated model that captures the dynamic flow from platform characteristics (social presence) through key psychological variables (social commerce trust and commitment), culminating in repurchase intention. This addresses a significant gap by investigating customer loyalty and retention factors, which are often not well understood compared to adoption intent. Secondly, this study adds depth to our understanding of social commerce dynamics by specifically evaluating the moderating role of social influence (specifically peer pressure) in the key relationship between social presence and repurchase intention. This provides novel insights into how social interactions and perceived peer behaviors amplify the effect of a platform’s perceived social warmth on purchasing decisions. Thirdly, by exploring the subsequent influence of repurchase intention on broader, non-transactional outcomes, such as customer engagement behavior intention (CEBI), the study highlights the multi-dimensional nature of loyalty. It demonstrates how a customer’s likelihood of making future purchases serves as a conduit for more profound brand-supporting and brand-promoting activities. The findings are expected to yield valuable theoretical insights for the academic community and provide actionable, practical implications for website administrators, marketers, and social commerce retailers. To leverage these insights, platforms could prioritize enhancing social presence through interactive features and community-building activities, strengthening the emotional connection between customers and the platform. Furthermore, understanding the effect of social influence suggests that platforms should integrate social proof strategies, such as featuring customer testimonials and visible peer purchases, to effectively reinforce user confidence and influence purchase decisions. Ultimately, this enables them to develop more effective, evidence-based marketing policies and communication strategies to foster a loyal, active, and sustainably engaged customer base.

2.1 Theory of Planned Behavior (TPB)

The Theory of Planned Behavior (Ajzen, 1991) posits that behavioral intention is determined by three core factors: attitude toward the behavior, subjective norms, and perceived behavioral control. Within the context of social commerce, this theory explains how consumers’ attitudes toward online purchasing, peer social pressure, and perceived ability to complete a transaction influence their repurchase intention (Gunawan et al., 2021). Attitudes toward social commerce are shaped by prior experiences, perceived usefulness, and satisfaction derived from interactions with brands or other users.

Subjective norms, representing the perceived social expectations of others, are closely linked to social influence, which is a dominant feature in social commerce settings where peer opinions, reviews, and recommendations drive behavioral conformity (Zhao et al., 2022) Moreover, perceived behavioral control captures an individual's confidence in managing online transactions, influenced by ease of use, trust in platforms, and social presence cues that reduce perceived uncertainty (Hansen et al., 2018). Therefore, TPB provides a foundation for understanding how social presence and social influence jointly shape repurchase intention, especially when users perceive strong social validation from their network. As we transition to examining additional frameworks, we will explore how social influence and perceived control converge across models, highlighting their unifying role in shaping consumer behavior.

2.2 Social Exchange Theory (SET)

The Social Exchange Theory (Homans, 1958; Blau, 1964) posits that social behavior results from an exchange process where individuals seek to maximize benefits and minimize costs. In social commerce, consumers engage in reciprocal exchanges of trust, information, and support with brands and peers. These exchanges cultivate emotional bonds and perceived relational value, leading to stronger loyalty and engagement behaviors (Guo & Li, 2022). When consumers perceive that their interactions with a seller or community are rewarding through appreciation, responsiveness, or recognition, they are more likely to reciprocate with positive outcomes, such as repeat purchases and advocacy (Palmatier et al., 2009; Sashi, 2012).

Social presence enhances this exchange process by humanizing digital interactions, making the experience more personal and relational. The feeling of “being with others” in an online environment fosters psychological closeness and emotional trust, encouraging reciprocal engagement and long-term commitment. In this sense, SET explains the mechanisms linking social presence, trust, commitment, and repurchase intention in social commerce.

2.3 Expectation-Confirmation Theory (ECT)

The Expectation-Confirmation Theory (Oliver, 1980) asserts that consumers’ satisfaction and continued usage intentions depend on the confirmation of their expectations after product or service use. In social commerce, this means that when the actual shopping experience, such as interactivity, responsiveness, trustworthiness, meets or exceeds expectations, consumers experience satisfaction, which subsequently leads to repurchase and engagement behaviors (Attar et al., 2021; Lim et al., 2020).

Social presence reinforces this process by facilitating richer, more satisfying social interactions, such as immediate feedback, peer validation, and emotional connection, that enhance perceived service quality. Positive confirmation of expectations through social cues, such as live chat responsiveness that sparks real-time camaraderie, real-time comments that echo the warmth of human touch, and authentic reviews, enhances customer satisfaction, strengthening loyalty and engagement intentions. Hence, ECT provides a cognitive-affective explanation for how social presence influences repurchase and engagement via satisfaction and confirmation processes.

2.4 Hypothesis Development and Relationships

Building on the theoretical foundations, this section develops hypotheses based on the relationships among the variables in the framework. The core variables, social presence, social influence, repurchase intention, commitment, social commerce trust, and customer engagement behavior intention are interconnected in complex ways. Below, we outline the proposed relationships and hypotheses.

2.4.1 Social Presence and Repurchase Intention

Repurchase intention refers to a consumer's plan or decision to purchase a product or service again (Cuong, 2021; Ebrahim et al., 2016). This construct plays a key role in consumer behavior research due to its direct association with engagement, satisfaction, and loyalty. For long-term success, companies should consider repurchase intention central to their strategy. Customers with strong repurchase intentions are typically satisfied and loyal. In the online context, social presence is the feeling of real connection with others in digital environments and influences customers' decisions (Islam et al., 2024; Lăzăroiu et al., 2020). Understanding repurchase intention in digital contexts is therefore essential.

Recent research shows that social presence drives genuine, trustworthy connections, thereby strengthening repurchase intentions (Attar et al., 2023; Lee et al., 2021). When online interactions feel personal, trust rises and so does the likelihood of repurchase (Daozhi & Huijuan, 2022). Social presence enhances this trust by enabling consumers to perceive a human element that reduces anxiety in digital environments (Ferreira da Silva et al., 2024). For example, features like live chat or personalized videos give the impression of a real human connection, evoking positive emotions and increasing the likelihood of future purchases. Consumers are more likely to associate favorable feelings with a company when they experience a sense of human connection online, thereby strengthening repurchase intention (Zhang, 2025). Similarly, Chen et al. (2023) showed that interactive features and personalized care in e-commerce environments increase customers' connection to a company and the likelihood of repeat purchases.

Repurchase intention also influences broader consumer behaviors, including brand engagement and transactional activities. Perceived social presence fosters trust, which in turn increases repurchase intention. This increased intention is associated with behaviors such as posting positive reviews, recommending the company, and interacting with brand content online. Zhang and Li (2023) and Li et al. (2025) found that consumers with strong repurchase intentions are more likely to participate in these activities. However, the effect of social presence on repurchase intention may be moderated by individual consumer differences and cultural variables, which remain underexplored in current research. Furthermore, while social presence is influential, additional factors such as pricing and product quality also contribute to repurchase intention. Despite these considerations, existing evidence indicates that repurchase intention, shaped by social presence and trust, predicts higher engagement in brand-related activities and fosters customer loyalty (Ding et al., 2022; Samarah et al., 2022).

In summary, repurchase intention is a crucial link between a customer's future interactions and their satisfaction with previous experiences. Evidence shows that social presence not only raises repurchase likelihood but also strengthens emotional connections to brands, supporting loyalty and engagement. This analysis highlights the importance of fostering social presence to build trust, encourage repeat transactions, and promote positive word-of-mouth. Therefore, we proposed the following hypothesis: 

• H1: Social presence positively affects the repurchase intention.

2.4.2 Repurchase Intention and Customer Engagement Behavior Intention

This study posits that fostering loyal customers in social commerce is a function of key relational elements like social commerce trust, social presence, and commitment. A crucial manifestation of this loyalty is not only the intention to repurchase but also the intention to engage in positive, non-transactional behaviors. Repurchase intention is a customer's conscious plan to continue buying a specific brand, indicating satisfaction and emotional attachment (Ilyas et al., 2020). Customer Engagement Behavior (CEB) intention, on the other hand, refers to a customer's deliberate plan to engage in various supportive actions toward the brand, such as providing feedback, participating in brand communities, advocating for the brand, and co-creating value (Chi et al., 2022; Hoang et al., 2023). While customer loyalty is often measured through repurchase intention, its influence extends beyond repeated purchases to encompass a broad spectrum of CEB. This section explores the theoretical and empirical foundation for the positive relationship between repurchase intention and customer engagement behavior intention.

Repurchase intention, defined as a customer's conscious plan to continue buying from a specific brand, is a core indicator of loyalty. It signifies a customer's satisfaction, trust, and emotional attachment, which collectively motivates them to deepen their relationship with the brand. This deepened relationship often expresses itself through active engagement. For instance, Islam and Rahman (2017) demonstrated that brand loyalty is a significant determinant of a customer's willingness to interact with a company online. Similarly, Carlson et al. (2019) found that consumers who actively participate with a brand's principles on social media exhibit heightened loyalty, while Li et al. (2020) established a positive correlation between customer loyalty and the intention to engage with travel applications. However, some studies present conflicting results. For example, Appiah et al. (2019) found instances in which customer loyalty does not translate into increased engagement, particularly in markets with high brand-switching costs. These findings suggest that the relationship between loyalty and engagement may vary across contexts, underscoring the importance of considering market-specific dynamics when evaluating it.

Social Exchange Theory (SET) explains why loyal customers, as indicated by their repurchase intention, are more likely to engage in these value-adding behaviors (Bergel et al., 2019). It provides a foundational lens, suggesting that human relationships are sustained by a mutual exchange of benefits. When customers experience high value and satisfaction, leading to repurchase intention, they feel a sense of obligation to reciprocate. This sense of obligation can be linked to the 'give-get' principle of influence, in which satisfaction from repurchases serves as a psychological trigger for reciprocation. This reciprocity often takes the form of engagement behaviors, such as writing positive reviews or defending the brand, to give back and maintain a balanced relationship (Palmatier et al., 2007). In the context of social commerce, SET operates uniquely by leveraging interactive and dynamic platforms that enhance customer-brand relationships. Social commerce enables real-time feedback, social proof through reviews and ratings, and community engagement, thereby strengthening the reciprocity effect (Anastasiei et al., 2024). Customers are more likely to engage with brands on social platforms because they see tangible benefits in terms of community support and direct interaction, which are less pronounced in traditional commerce settings.

In conclusion, a robust body of literature confirms that repurchase intention, as a key metric of customer loyalty, is a significant antecedent to customer engagement behavior intention. Driven by mechanisms of reciprocity, emotional attachment, and confirmed satisfaction, loyal customers naturally progress from being mere repeat purchasers to active participants and advocates for the brand. Building on this evidence, the following hypothesis is proposed:

• H2: Repurchase intention positively affects customer engagement behavior intention.

2.4.3 Moderating Role of Social Influence

The relationship between social presence and repurchase intention is increasingly shaping the dynamics of consumer behavior in social commerce, with social influence, especially peer pressure, serving as a crucial moderating factor. In this study, 'social presence' is defined as the degree to which people engage and feel connected to others in a digital setting. It includes the social and emotional interactions customers have with peers and companies online (Kreijns et al., 2022). On the other hand, 'social influence' refers to the perceived pressure or expectation from peers that can affect individuals' attitudes and behaviors, particularly towards purchasing decisions (Gunawan et al., 2023; Hu et al., 2019). Social presence increases the influence of peer pressure on customers' decisions to repurchase goods or services while also strengthening the sense of community and connectedness (Nadeem et al., 2020). In an increasingly competitive digital environment, organizations hoping to foster loyalty and encourage repeat business must comprehend this relationship.

Social influence, often portrayed as peer pressure, is a potent moderator of the relationship between social presence and repurchase intention in the context of social commerce. In this setting, social influence refers to the perceived pressure or support from peers, which may mould customers' attitudes and behaviors, particularly with relation to purchasing decisions (Hu et al., 2019). The moderating mechanism works such that when social presence is heightened through interactive features like live chat, user reviews, and real-time participation, customers become more receptive to their peers' behaviors and endorsements (Huang et al., 2023; Lu et al., 2025). According to Cialdini's social-proof principle, individuals tend to follow the actions and endorsements of others, especially those they perceive as similar to themselves. For example, if a customer sees a live review broadcast by multiple users, the collective positive perception can increase the likelihood of repurchase intention. This connection enhances the visibility of peer behaviors, views, and endorsements, which together exert social influence that can significantly affect customers' intentions to make more purchases. By aligning with what 'people like us' are doing, customers find reassurance in their purchase decisions.

Consumers are urged to adopt group behaviors, particularly in settings where peer activities are highly apparent, according to research suggesting that social influence operates as normative pressure (Ou et al., 2022). For instance, when friends or influential people are seen using a product, it might be assumed that they will do the same. This dynamic is especially noticeable on social commerce platforms, where social presence increases the temptation to fit in by enabling real-time observation of peer choices alongside interaction (Simon et al., 2015). Grounding this argument, the Social Influence Theory posits that individuals' attitudes and behaviors can be shaped significantly by peer perceptions. Additionally, integrating aspects of the Theory of Planned Behavior provides insight into how perceived social pressure, along with other factors such as perceived behavioral control, can influence purchasing intentions.

Furthermore, research indicates that peer pressure in online environments frequently promotes repurchases by highlighting the perceived value and social approval of certain goods (Gunawan et al., 2023). For example, a study by Goh et al. (2016) provides empirical evidence for the moderating effect of social influence, finding that increased peer pressure significantly increased the likelihood of repurchase intentions. People are more likely to see repurchasing as advantageous and socially acceptable when they witness regular peer participation and encouraging comments, which increases their desire to engage in similar behavior. Social influence plays a crucial role in social commerce, as it links the decision to make recurrent purchases with the sense of community fostered by social presence.

Overall social influence, primarily through peer pressure, acts as a moderating factor, enhancing the impact of social presence on repurchase intentions. By leveraging the normative force of peer behaviors and beliefs, it strengthens individual brand loyalty and encourages broader consumer engagement, creating a social context where repurchase becomes both a personal choice and a socially motivated decision. Therefore, we proposed the hypothesis: H3: Social influence moderating the relationship between social presence and repurchase intention

Figure 1: Research Framework

Research Design

This study employed a quantitative research approach and a cross-sectional design, which examined data collected from participants at a single point in time. This design gives a snapshot of current interactions and experiences among social commerce users. While a cross-sectional design effectively captures the current state and allows for a broad generalization of the findings to the broader population, it does not track changes or developments over time. By contrast, a longitudinal design would offer insights into trends and changes, albeit at the cost of increased time, cost, and complexity. A cross-sectional approach best serves the study’s aims by focusing on existing interactions and relationships within the structural model, without the need for extended observation periods. A survey is a method of gathering information from a sample of social commerce users in Malaysia. This method is appropriate for testing the relationships in the structural model and enables generalizing findings to the broader population (Hair et al., 2019).

3.2. Population, Sampling, and Data Collection

The target population comprised active social commerce users in Malaysia who have previously made purchases through platforms such as Facebook, Instagram, or TikTok. These platforms were selected because of their pivotal role in the Malaysian social commerce landscape (Chi & Ismail, 2024; Tee & Teo, 2022; Wang & Ibrahim, 2024). Specifically, Facebook facilitates community building and connectivity that enhances user interactions; Instagram’s visual-centric approach supports engaging content sharing; and TikTok’s algorithm-driven content delivery fosters dynamic user engagement. Tying these aspects to the study constructs strengthens the construct-context fit.

A non-probability purposive sampling technique was used to ensure that respondents had relevant experience with the phenomenon under investigation. The minimum required sample size was determined a priori using G*Power software (Faul et al., 2007) for a multiple linear regression analysis. The calculation was based on testing the primary structural model, with repurchase intention as the key endogenous variable predicted by three independent variables: social presence, social commerce trust, and commitment. The parameters for the G*Power calculation were set as follows: a medium effect size (f² = 0.15), an alpha error probability of 0.05, and a statistical power of 0.80. This analysis indicated a minimum sample size of 68 respondents. To enhance the robustness, power, and generalizability of the analysis, the study targeted a larger sample. A total of 298 valid responses were collected and included in the final analysis, exceeding the minimum requirement and providing sufficient power to detect the hypothesized effects reliably.

Data was collected via an online questionnaire distributed through email invitations and social media platforms, including Facebook and Instagram. The focus was on residents of the Klang Valley, Malaysia’s economic and digital hub. This region has high mobile adoption rates and a significant concentration of social commerce users, making it an ideal research context (Hew et al., 2017; Tan & Ooi, 2018). Participants were screened to confirm active social commerce use. Informed consent was obtained from all respondents, and their anonymity and confidentiality were guaranteed. The survey achieved a 65% response rate, ensuring the collected data represents the target population.

3.3. Measurement Instrument

The survey instrument had two sections. First, section A captured demographic information, including gender, age, education level, and income. Section B measured the main variables of the study using question sets (called reflective indicators) that asked participants how much they agreed with various statements. Responses were given on a 5-point Likert scale, where 1 meant Strongly Disagree and 5 meant Strongly Agree.

Social presence was measured using 5 items adapted from Nadeem et al. (2020). The repurchase intention construct was measured using 7 items adapted from the studies by Kim & Park (2013) and Nadeem et al. (2020). Customer engagement behavior intention was measured using 6 items adapted from Molinillo et al. (2020). Social influence was measured using 5 items adapted from Stibe & Cugelman (2019).

All measurement items were adapted from established literature scales to ensure content validity, such as whether the items adequately represent the constructs being measured. The adaptation process involved both translation and cultural adjustments. Translation changes ensured linguistic consistency, while cultural adjustments aligned items with Malaysian social norms and behaviors. These steps were critical to maintaining measurement validity (accuracy) and reliability (consistency).

3.4. Data Analysis Technique

The data analysis was conducted using Smart PLS 4.1.1.5, consistent with the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. PLS-SEM is a statistical technique used to analyze and test complex relationships between observed (measured) variables and latent (unobserved) variables within a model.

3.4.1. Measurement Model Assessment

The reliability (consistency) and validity (accuracy) of the constructs were evaluated. Internal consistency reliability was confirmed using Composite Reliability (CR), a measure indicating how closely related the items in a set are, with all values exceeding the 0.70 threshold. Convergent validity—whether indicators of a construct truly measure that construct—was established as all indicator loadings were greater than 0.70, and the Average Variance Extracted (AVE), which shows the amount of variance captured by a construct versus measurement error, for each construct was above 0.50 (Hair et al., 2019). Discriminant validity was assessed using the Fornell-Larcker criterion, which checks that each construct is more closely related to its own indicators than to other constructs, confirming that the square root of each construct’s AVE was greater than its correlations with all other constructs.

3.4.2. Structural Model Assessment

After validating the measurement model, the structural model was evaluated to test the research hypotheses. Path coefficient significance was assessed using a bootstrapping procedure with 5,000 subsamples. Such significant path coefficients offer practitioners practical insights by indicating which model relationships are robust and reliable. Model predictive power was evaluated using the coefficient of determination (R²) for endogenous constructs. The effect size (f²) and predictive relevance (Q²) of the model were also examined. By linking bootstrapped findings to managerial actions like these, the model’s applied value becomes evident.

FINDINGS

4.1 Descriptive Statistics

The final sample for analysis consisted of 298 active social commerce users in Malaysia. Of the respondents, 58% were female, with the largest age group (42%) falling between 26 and 35 years old. The majority of participants (68%) reported a monthly income between RM 2,001 and RM 5,000, and 61% held a bachelor’s degree or professional qualification, reflecting a sample that is digitally literate and economically active. Furthermore, 71% of respondents reported making purchases on social commerce platforms at least once a month, indicating a sample with substantial and relevant experience. Table 1 presents the descriptive statistics for all study constructs. All variables demonstrated acceptable normality, with skewness and kurtosis values within the recommended thresholds.

Table 1: Descriptive Statistics

Note: All constructs measured on a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree)

4.2 Measurement Model Evaluation

Reliability Assessment: All constructs demonstrated excellent internal consistency, with Cronbach’s alpha values ranging from 0.710 to 0.905 and composite reliability scores between 0.721 and 0.912. These values substantially exceed established thresholds, confirming measurement reliability. Convergent Validity: Factor loadings ranged from 0.838 to 0.925, all exceeding the 0.70 threshold. Average variance extracted (AVE) values ranged from 0.529 to 0.640, surpassing the 0.50 criterion. These results confirm adequate convergent validity across all constructs.

Table 2: Construct reliability and validity

Discriminant validity was evaluated using the Fornell-Larcker criterion, where the square root of AVE for each construct was greater than its correlations with other constructs, indicating good discriminant validity. HTMT ratios ranged from 0.644 to 0.808, remaining below the conservative 0.850 threshold, confirming discriminant validity.

Table 3: Discriminant Validity Assessment (HTMT)

4.3 Structural Model Results

The structural model results reveal significant relationships supporting most hypotheses (see Table 4). Bootstrap analysis with 5,000 resamples confirmed statistical significance at p < 0.001 for almost all relationships. Repurchase intention emerged as the strongest predictor of customer engagement behavior intention (β = 0.808, t = 27.379, p < 0.001), followed by social presence (β = 0.548, t = 10.215, p < 0.001).

Table 4: Structural Model Results - Direct Effects

4.4 Coefficient of Determination and Effect Sizes

The model demonstrates substantial explanatory power, with Customer Engagement Behavior Intention (CEBI) explaining 73.8% of the variance in Repurchase Intention (RI) (R² = 0.738). Social Presence (SP) factors collectively account for 65.3% of the variance in Customer Engagement Behavior Intention (CEBI) (R² = 0.653), indicating strong predictive relevance (See Table 5). Figure 2 below illustrates the structural model results.

Table 5: Coefficient of Determination and Effect Sizes

Note: R² thresholds: 0.25 (weak), 0.50 (moderate), 0.75 (substantial); Q² > 0 indicates predictive relevance

Figure 2: The Structural Model Results

4.5 Total Indirect Effects Analysis

To test the mediating effect of repurchase intention, the indirect effect of social presence on customer engagement behavior intention was analyzed. The bootstrapping results indicated significant indirect effects for repurchase intention. Specifically, the total indirect effect through repurchase intention was 0.443 (p < 0.001). Besides, the moderating effect of social influence on social presence on customer engagement behavior intention was 0.128 (p < 0.001).

Table 6: Total Indirect Effects

4.6 Model Fit and Quality Assessment

The model demonstrates excellent fit with Standardized Root Mean Square Residual (SRMR) of 0.076, well below the 0.08 threshold. The Normed Fit Index (NFI) of 0.785 is slightly below the 0.90 benchmark, indicating moderately good model fit. Collinearity assessment revealed no multicollinearity concerns, with all Variance Inflation Factor (VIF) values below 3.50, well within the acceptable range of 5.0.

Table 7: Model Fit and Quality Indices

This study explored the relationships between social presence, repurchase intention, and customer engagement behavior intention (CEBI) within the context of social commerce platforms in Malaysia, as well as the moderating role of social influence. The analysis, conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 298 valid responses, confirmed all proposed hypotheses, offering a deeper understanding of how social interaction, peer influence, and trust mechanisms jointly drive loyalty and engagement in social commerce environments.

The results indicate that social presence significantly influences repurchase intention (β = 0.548, p < 0.001), confirming Hypothesis 1. This finding reinforces prior literature that emphasizes social presence as a determinant of consumers’ emotional and cognitive responses in online environments (Attar et al., 2023; Lee et al., 2021). A higher perception of social presence—manifested through interactive features such as live chat, responsive communication, and real-time engagement reduced uncertainty and enhanced feelings of trust and belonging. These social cues humanize digital interactions, leading customers to perceive the platform as more credible and relational. In the Malaysian context, where social and community-based values are integral to communication and commerce, social presence serves as a bridge between emotional connection and transactional intention. This observation aligns with the principles of the Social Exchange Theory (SET), which suggests that positive relational exchanges encourage reciprocal behaviors such as repeat purchases (Guo & Li, 2022). Similarly, the Theory of Planned Behavior (TPB) underscores the role of social norms and attitudes in shaping purchase intentions, highlighting how social presence can strengthen consumers' perceived social approval and behavioral confidence.

Furthermore, repurchase intention was found to have a strong and positive effect on customer engagement behavior intention (β = 0.808, p < 0.001), supporting Hypothesis 2. This result suggests that once customers develop an intention to repurchase, they are more likely to engage in brand-supportive behaviors such as sharing content, writing reviews, or recommending products to peers. These behaviors extend loyalty beyond repeat purchases into ongoing relational engagement. Consistent with Social Exchange Theory, satisfied customers tend to reciprocate by contributing to brand communities, thereby creating mutual value for themselves and the firm (Palmatier et al., 2007; Bergel et al., 2019). In the social commerce ecosystem, this reciprocity is amplified by digital affordances that enable visibility, participation, and peer acknowledgment. In essence, repurchase intention becomes the psychological anchor that translates satisfaction into proactive engagement, a finding that resonates with prior research linking brand trust and satisfaction to online advocacy behaviors (Islam & Rahman, 2017; Hoang et al., 2023).

The moderating effect of social influence on the relationship between social presence and repurchase intention (β = 0.128, p < 0.001) further confirms Hypothesis 3. This result provides strong empirical support for the role of subjective norms proposed in the Theory of Planned Behavior (Ajzen, 1991), demonstrating that consumers’ purchase decisions are significantly shaped by the expectations and behaviors of their peers. In environments where social presence is high, consumers become more receptive to peer cues such as reviews, comments, and endorsements, which collectively validate their purchase decisions. This finding aligns with earlier studies suggesting that peer pressure and social proof intensify consumers’ trust and loyalty (Goh et al., 2016; Gunawan et al., 2023). In collectivist cultures like Malaysia, where belonging and social conformity are highly valued, the moderating role of social influence becomes particularly salient. The findings suggest that social presence and social influence work synergistically to enhance repurchase behavior, reinforcing the notion that consumer decisions in social commerce are as much socially driven as they are individually motivated.

5.1 Theoretical Implications

The findings of this study extend theoretical understanding in several important ways. First, the research integrates the Theory of Planned Behavior (TPB), Social Exchange Theory (SET), and Expectation-Confirmation Theory (ECT) to construct a holistic model that links social presence, trust, commitment, and engagement in the context of social commerce. This integration offers a comprehensive explanation of both the psychological and social mechanisms that drive consumer loyalty, expanding beyond prior models that treated these relationships in isolation. The confirmation of Hypothesis 1 reinforces TPB’s assertion that behavioral intention is influenced not only by attitudes but also by subjective norms—demonstrating that social presence can strengthen normative pressures toward repurchase.

Second, the study extends the conceptualization of social presence beyond a mere trust-building mechanism. The results show that social presence indirectly contributes to broader community engagement by fostering repurchase intention, thereby connecting affective experience with behavioral outcomes. This multidimensional understanding aligns with emerging perspectives that view social presence as a relational and experiential construct central to the digital consumer experience.

Third, the significant moderating role of social influence advances theoretical knowledge by elucidating how normative social pressures interact with experiential cues to shape loyalty. This finding contributes to the evolving literature on social commerce by empirically validating that peer influence magnifies the effect of social presence on behavioral intention, particularly in collectivist cultural contexts. Moreover, by positioning repurchase intention as a mediating bridge between social presence and customer engagement behavior, this study enriches the ongoing discourse on how transactional loyalty evolves into active engagement and advocacy behaviors, thus contributing to both consumer behavior and relationship marketing theory.

5.2 Practical Implications

From a managerial standpoint, the results offer valuable guidance for social commerce practitioners, platform developers, and digital marketers seeking to foster consumer loyalty and engagement. The findings underscore that enhancing social presence should be a strategic priority for online retailers. Platforms can achieve this by incorporating interactive features such as live-streamed sales sessions, personalized customer service responses, and user-generated content that promote real-time social interaction. These elements help customers perceive warmth, empathy, and authenticity, which are critical to building trust and encouraging repeat purchases.

Moreover, because social influence amplifies the impact of social presence on repurchase intention, firms should actively design their platforms to leverage social proof mechanisms. This can include displaying peer reviews, highlighting trending or “most purchased” products, and integrating influencer endorsements or friend activity feeds. By making peer behaviors more visible, platforms can create a sense of collective validation that motivates users to align their purchasing behaviors with their social circles.

The strong relationship between repurchase intention and engagement behavior suggests that loyal customers are likely to become brand advocates when encouraged and empowered to participate in brand communities. Marketers should therefore focus on post-purchase engagement strategies that transform repeat buyers into active promoters. Initiatives such as loyalty reward programs, referral systems, interactive challenges, or gamified experiences can enhance user involvement and sustain long-term relationships. For Malaysian social commerce operators, embedding community-oriented features that resonate with collectivist cultural values—such as group discounts, co-creation activities, and community recognition programs—could further strengthen engagement and retention.

This study set out to examine the effect of social presence on repurchase intention and its subsequent influence on customer engagement behavior intention (CEBI) in the context of social commerce platforms in Malaysia, while also exploring the moderating effect of social influence. Grounded in the Theory of Planned Behavior (TPB), Social Exchange Theory (SET), and Expectation-Confirmation Theory (ECT), the study integrated psychological, social, and behavioral perspectives to provide a holistic understanding of how consumers develop and sustain loyalty in digitally mediated environments.

The empirical results obtained through Partial Least Squares Structural Equation Modeling (PLS-SEM) confirmed all proposed hypotheses. Social presence was found to significantly enhance repurchase intention, underscoring the importance of human warmth, interactivity, and social connectedness in driving consumers’ willingness to make repeat purchases. This highlights that in social commerce settings—where interpersonal cues replace physical interactions—social presence serves as a key psychological mechanism that builds trust, reduces uncertainty, and strengthens long-term loyalty. The study further demonstrated that repurchase intention is a critical predictor of customer engagement behavior, suggesting that once customers are committed to repurchasing, they are more likely to transition from passive buyers to active participants in brand communities. This evolution from transactional to relational loyalty reflects the social and reciprocal nature of engagement in online commerce.

Moreover, the moderating role of social influence revealed that peer behaviors and perceived social norms significantly amplify the effect of social presence on repurchase intention. This finding emphasizes the collective dimension of decision-making in social commerce, where consumers are not isolated actors but members of interconnected digital communities whose behaviors are shaped by social validation and normative expectations. In collectivist contexts such as Malaysia, this influence is particularly salient, as individuals derive purchase confidence and satisfaction from conformity with peer behaviors.

Theoretically, the study contributes to the growing body of literature by integrating multiple behavioral frameworks to explain the interplay between social interaction, trust, and engagement. It extends the conceptualization of social presence as a multidimensional construct that not only influences purchase intentions but also facilitates community-based engagement behaviors. Practically, the findings provide actionable insights for marketers and platform designers, emphasizing the importance of designing interactive, socially rich, and peer-driven experiences to foster loyalty and advocacy in digital environments.

In conclusion, this research provides compelling evidence that social presence, amplified by social influence and mediated through repurchase intention, plays a central role in cultivating sustainable customer relationships in social commerce. As digital interactions continue to evolve, the ability of platforms to replicate authentic social experiences will become increasingly critical to consumer retention and engagement. By deepening our understanding of these mechanisms, this study not only advances academic discourse but also equips practitioners with evidence-based strategies to build trust-driven, community-oriented social commerce ecosystems that can thrive in an increasingly competitive global market.

LIMITATIONS AND FUTURE RESEARCH

While the study provides significant insights into the dynamics of social presence, repurchase intention, and engagement behavior, certain limitations should be acknowledged. First, the cross-sectional research design restricts the ability to infer causality or observe changes over time. Future studies could adopt a longitudinal approach to examine how customer loyalty and engagement evolve across multiple purchase cycles. Second, the study focused on social commerce users in Malaysia, a collectivist society with distinct cultural characteristics. Replicating this model in other cultural contexts, such as individualistic societies, would enable cross-cultural comparisons and enhance the generalizability of findings.

Third, the study primarily relied on self-reported data, which may be subject to common-method bias and social desirability bias. Future research could incorporate behavioral data or experimental designs to objectively validate responses. Additionally, this study considered only a limited set of antecedents and moderators; future models could explore additional variables, such as emotional attachment, perceived value, and technological affordances, to further enrich the understanding of consumer behavior in digital ecosystems.

Finally, while this study examined the moderating role of social influence, future research could conduct multigroup analyses to assess whether demographic factors, such as age, gender, or digital literacy, moderate the observed relationships. Such analyses could provide a more nuanced understanding of how social presence and engagement behaviors manifest across diverse consumer segments.

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