“Are They Really Influencing You?” How Beauty Influencers Drive Positive Consumer Behavior Toward Brand Social Commerce Through Parasocial Interaction

ABSTRACT

Drawing on theory from the Social Credibility Model (SCM), this paper evaluates the impact of Influencer Marketing (IM) in Brand Social Commerce (BSC). We analyze how Parasocial Interaction (PSI) with influencers leads to positive attitudes related to Affective Engagement (AFF) to BSC, Co-creation (CCO), and Perceived Confidence (CONF), as well as the indirect effects on the intention to follow others' shopping advice (FOL). As a moderator effect, we elaborate that channel preference moderates the relationship between PSI with AFF, CCO, and CONF. This study is based on a survey of 533 Brazilian consumers and the data validated using structural equation modeling. The results confirm that PSI drives positive consumer attitudes in BSC. Moreover, PSI increases the direct effect of CCO and CONF and the indirect effect of FOL among less risk-averse online shoppers. This finding has implications for online sellers who invest in IM campaigns. We provide novel insights into the effectiveness of IM and contribute to digital advertising theory.

Keywords:
Influencer Marketing; Social Commerce; Affective Engagement; Co-creation; Perceived Confidence

RESUMO

Com base na teoria do Modelo de Credibilidade da Fonte (Source Credibility Model - SCM), este artigo avalia o impacto do Marketing de Influenciadores (Influencer Marketing - IM) em um Comércio Social da Marca (Brand Social Commerce - BSC). Analisamos como a Interação Parasocial (Parasocial Interaction - PSI) com influenciadores conduz a atitudes positivas relacionadas ao Engajamento Afetivo (Affective Engagement - AFF) com o BSC, Cocriação (CCO) e Confiança Percebida (CONF), bem como os efeitos indiretos sobre a intenção de seguir recomendações de compra de outros (Intention to Follow Recommendation - FOL). Considerando um efeito moderador, demonstramos que a preferência de canal modera a relação entre PSI e AFF, CCO e CONF. Este estudo é baseado em uma pesquisa com 533 consumidores brasileiros, e os dados foram validados por meio de modelagem de equações estruturais. Os resultados confirmam que a PSI impulsiona atitudes positivas dos consumidores no BSC. Além disso, a PSI aumenta o efeito direto de CCO e CONF e o efeito indireto de FOL entre os consumidores menos avessos ao risco em compras online. Esses achados têm implicações para online retailers que investem em campanhas de IM, oferecendo novos insights sobre a eficácia do IM e contribuindo para a teoria de publicidade digital.

Keywords:
Marketing de Influência; Comércio Social; Engajamento Afetivo; Cocriação; Confiança Percebida

1. INTRODUCTION

Influencer marketing (IM) is centered on Social Media Influencers (SMIs), who are now regarded as internet celebrities (Sánchez-Fernández & Jiménez-Castillo, 2021). Influencers have become important for digital advertising and assumed multiple roles on social media. They strengthen customer-brand engagement, make product recommendations and persuade followers to shop online (Farivar & Wang, 2022).

Marketing professionals have faced the challenge of selecting influencers whose profiles fit the target audience of the brand and guarantee the financial results of the campaigns (Commentator, 2020). Previous models have examined the relationship between the personal characteristics of influencers and the construction of their sphere of influence, offering insights in this direction. Liu, Li, and Lee (2021) underscored the traits of trustworthiness, reliability, and transparency in making influencers appear honest, which encourages consumers to heed their recommendations and make purchases. Cheung et al. (2022) cited that influencers' creative, interactive and visually appealing content encourages followers' attitudes. Similarly, Casaló, Flavián, and Ibáñez-Sánchez (2020) emphasized the creativity and uniqueness of influencers in their Social Network (SNS) accounts, which makes them attractive opinion leaders. Sokolova and Kefi (2020) demonstrated how physical and social attractiveness, as well as a homophilic attitude, can lead to credibility.

Previous models have been able to prove, based on cognitive and behavioral dimensions, the informative value and attractiveness of influencers' narratives on their SNS accounts. However, they are limiting models in some respects for the current context. Firstly, influencer/consumer relationships embrace emotional dimensions. Psychological bonds drive more intimate relationships that explain the power of influencers (Berryman & Kavka, 2017) by making their product endorsements more effective (Berryman & Kavka, 2017). Secondly, there is increased collaboration between brands and influencers, and it is imperative to understand the implications of influential nodes in brand communities (Santos et al., 2022). Hence, to address this gap, the present study proposes novel directions in the field of IM studies.

Our methodological approach purposes to evaluate the influencers-followers interaction in the context of Social Media Brand Communities (SMBCs), which are brands' accounts marked by consumer co-creation, emotional bonds, and horizontal interaction (Santos et al., 2022). In doing so, this research utilizes the Source Credibility Models proposed by Hassan et al. (2021) to detail the foundation of the power of influencers. This theory states that credibility comes from an influencer's traits that can cause assimilation and emotional bonding behaviors. Following this, we address Parasocial Interaction (PSI), which refers to the proximity between followers and influencers that drives favorable consumer behavior (Jin, Muqaddam, & Ryu, 2019). We hope to introduce novel concepts that extend the findings of prior research on the credibility and persuasiveness of influencers. Our proposal is in line with the necessity of re-evaluating IM's persuasion models, as described by Lou (2022) when they coined the term "trans-parasocial relation" and introduced new dimensions, such as the sense of collaboration, co-creation and interactivity that exists between influencers and followers.

Moreover, we draw attention to the implementation of IM practices in the context of social commerce (SC). S-commerce (e.g., Instagram) is a hybrid of social media with e-commerce functionalities (Hairudin, Dahlan, & Selamat, 2019). Unlike conventional e-commerce models, SC promotes the organic knowledge of the brand's audience, and not just information originating from the brand (Hairudin, Dahlan, & Selamat, 2019; Hajli, 2020). Considering our emphasis on the pivotal role of social capital in the evolving landscape of e-commerce, the term Brand Social Commerce (BSC) will henceforth be employed to denote the dynamics of SCs in SMBCs.

In the BSC context, we emphasize how followers assess information from brands, consumers, or influencers based on authentic and shared experiences (Hajli, 2020). This alternative perspective aims to evaluate the way influencers fortify the social capital inherent to the social media facet of e-commerce, as well as the social support that underpins collaborative buying behaviors that transpire within the hybrid e-commerce channel (Kusuma et al., 2024). To the best of our knowledge, the extant literature on IM has primarily focused on measuring the unidirectional effects of influencers on consumer responses (Lou, 2022; Yuan & Lou, 2020; Sokolova & Kefi, 2020). However, we consider that current IM research must move toward assessing the joint effects of influencers in collaboration with brands and their communities, particularly when consumer experiences are shaped by the interplay among the influencer, the branded product, and its users (Santos et al., 2022).

Furthermore, we focus on how PSI can strengthen the emotional bond between the brand's followers and influencers, which can lead to more favorable consumer attitudes towards brand elements on the BSC. We emphasize PSI effects on consumers’ behaviors according to consumers' channel preference. Observing the effects of emotional connection on shopping channel preference is imperative when a considerable proportion of consumers still have apprehensions and skepticism about online shopping (Chen et al., 2015). There is a research opportunity to determine whether PSI can influence consumers who are more risk-averse to shop online. Hence, we examine how followers' channel preferences moderate the relationship between PSI and brand followers' behaviors on BSC.

The research model proposed in this article is empirically evaluated using Structural Equation Modeling (SEM) through a survey conducted in Brazil with 533 followers of a beauty startup, Just for You. The decision to conduct the study on IM in Brazil is motivated by two factors. Firstly, this country has great regional relevance, accounting for more than 30% of IM investments in Latin America (Influencity, 2023). Secondly, more than 75% of Brazilian brands allocate funds to IM, underscoring the significance of this digital strategy (Navarro, 2024)

The following sections will describe each construct for the proposed model to assess the drivers and effects of PSI.

2. LITERATURE REVIEW

2.1. The role of Parasocial Interaction (PSI) in the relationship between Influencers and Followers and its effects on Brand Social Commerce (BSC)

PSI arises from the perception of "friendship" when followers believe they have an intimate and genuine relationship with influencers (Sokolova & Perez, 2021). Maintaining a daily routine of monitoring the influencer's activity leads to closeness and intimacy (Liu, Li, & Lee, 2021). PSI promotes deep emotions and connections (Jin, Muqaddam, & Ryu, 2019) and strengthens the psychological bond between the consumer and the brand (Berryman & Kavka, 2017).

In the work of Ballester et al. (2025), they highlighted the effects of PSI on brand engagement behavior activation and influencer content consumption. Likewise, this study proposes a similar structure but extends the model to adapt it to the BSC environment. That said, it assesses the impact of PSI on followers' interaction with the brand, the brand community, and the brand's products, as SMIs can lead to (i) greater hedonic pleasure due to the feeling of fun and happiness (Silaban et al., 2022); and (ii) higher levels of co-creation based on emotional bonds (Cheung et al., 2022); iii.) greater trust in advertised products due to immersive practices (Sander et al., 2021). Specifically, this study analyzes the positive effects of PSI on brand in terms of (i) affective engagement, and (ii) co-creation, and iii.) perceived confidence of products in the BSC.

2.2. Building PSI with followers through Influencers' traits

This study uses the SCM (Hassan et al., 2021) to select three influencer characteristics - helpfulness, relatability, and articulation - and investigate how they affect the formation of intimacy between influencers and consumers (Haobin Ye, Fong, & Luo, 2021).

The helpfulness trait helps consumers cope with online information overload (Choeh, Lee, & Park, 2015). Influencers' posts or video tutorials are highly visual, with simple, understandable messages based on real experiences that guide consumers in considering and selecting products in e-commerce (Stubb & Colliander, 2019). Another result of this characteristic is achieving an emotional connection when influencers reveal their weaknesses, thereby reinforcing honest dialogue and supporting their followers (Dekavalla, 2022). Referring to a range of problems, such as depression and other disorders (Parrott et al., 2020), they provide emotional support to their audience. In the makeup tutorials, although videos are aesthetically refined to show the results of the products, influencers can make themselves extremely vulnerable during the prep phase by showing their (real) acne-prone skin (Berryman & Kavka, 2017). Influencers create an honest narrative while offering advice and promoting the feeling that consumers are not alone. This attitude helps increase parasocial interaction (Dekavalla, 2022).

Another fundamental characteristic of developing a more effective influencer's narrative discourse is the relatability trait. Being relatable means that influencers post openly about their experiences and emotional aspects, reinforcing the idea of "real friends" (Biswas, Sengupta, & Ganguly, 2022). SMIs showcase their lifestyle and create a self-presentation that followers can trust and relate to (Dhanesh & Duthler, 2019; Berryman & Kavka, 2017). Elements such as unbiased or jargon-free content (Atiq et al., 2022) create a perception of access to the personal opinions of influencers, generating a genuine connection. Perceived similarities between communicators and audiences create feelings of convergence and intimacy, leading to PSI (Harbin Ye, Fong, & Luo, 2021). Even having similar characteristics to influencers (such as gender, age, behavioral aspects, and lifestyle) produces the feeling of "family intimacy" - or the "Big Sister" effect (Berryman & Kavka, 2017). Wishful identification, the ideal model represented by influencers, in which followers strive to imitate them, positively drives parasocial relationships (Hu et al., 2020).

The third influencer characteristic discussed in this study is the articulation trait. Influencer content production is not haphazard and requires minimal structural planning, such as selecting a location or evaluating audio and video technical requirements. Thus, articulation refers to the quality of the influencers' message, including whether it is understandable, attractive, creative, or interactive. SMIs produce content that is useful, unique, fun, and high in appeal, leading to a positive attitude and intimacy with the audience, thereby reinforcing the parasocial relationship (Cheung et al., 2022). Aw and Chuah (2021) noted that visually appealing and aesthetically pleasing content ensures a greater closeness between followers and influencers, strengthening parasocial connections.

As a result of the above discussion, the first hypotheses of this study assume that the influencers' traits can positively drive Parasocial Interaction:

H1 (a-c): The Influencer's interaction perceived traits of a) Helpfulness, b) Relatability, and c) Articulation can directly and positively impact PSI with followers of the BSC.

2.3. Effects of PSI on consumers' behaviors in the BSC

The relation between PSI and Affective Engagement with the BSC

In social media research, affective engagement refers to the positive feelings, pleasure, or emotions experienced when interacting with an object, such as a brand, website, or social media account (Hollebeek, Glynn, & Brodie, 2014). Consumers experience excitement, joy, and fun during online shopping, which leads to a better user experience and ultimately drives purchase and repurchase intentions (Izogo & Jayawardhena, 2018).

Prior literature has shown that PSI has a positive impact on affective engagement. Chen, Wen, and Silalahi (2021) found that when YouTubers share their experiences, they increase consumers' affective trust, creating an emotional bond. PSI increases affective reactions and emotions toward media personalities, creating positive feelings for brands, products, and shopping experiences (Lo et al., 2022). Garcia, Björk, and Kazemitabar (2022) concluded that parasocial relationships lead to increased emotional responses and commitment to the social media figure. Based on these assumptions, the following hypothesis is proposed:

H2.a: PSI with the Brand's Influencer can directly and positively impact the Affective Engagement with the BSC.

The relation between PSI and Co-creation in the BSC

SMIs play a crucial role in fostering a sense of belonging within the group by sharing their personal experiences and connecting with their audience on a relatable level (Kim & Park, 2013; Doha, Elnahla, & McShane, 2019). They support more active consumer collaboration and increase group dynamics (De Veirman, Cauberghe, & Hudders, 2017) in the shopping process (Ahmad & Laroche, 2017).

Just as PSI induces sentiments of friendship and closeness with content producers, it then activates followers' co-creation behaviors when they like, share, and comment on endorsed brand publications (Tolbert & Drogos, 2019). As parasocial relationships create an illusion of two-way communication between followers and influencers, people believe that their comments and content published will be read and considered. This illusionary interaction fosters democratization between media personalities and audiences, creating a sense of continuous collaboration (Lou, 2022). Based on the above, the following hypothesis is assumed:

H2.b: PSI with the Brand's Influencer can directly and positively impact the Co-creation behavior of the BSC's followers.

The relation between PSI and Perceived Confidence in the products of BSC

Trust can be understood as an internal belief that one party will not harm the interests of another or exploit their vulnerability in an exchange (Al-Debei, Akroush & Ashouri, 2015). Within the context of influencers, trust emerges through interactions that are reciprocal, (a)synchronously interactive, and co-created. These dynamics shape trans-parasocial relationships between influencers and followers, generating a sense of intimacy that enables new forms of persuasion. Such persuasion operates not only at the individual (one-to-one) level but also collectively (one-to-many), which enhances behavioral intentions while reducing resistance to advertising (Lou, 2022). In this way, influencers affect consumer behavior by fostering emotionally resonant relationships and by inspiring their audiences (Dhanesh and Duthler, 2019; Lou, 2022).

Building on this, the alignment between an influencer’s social image and a consumer’s self-ideal-known as self-influencer congruence-plays a crucial role in strengthening this intimacy. When followers perceive such congruence, they experience stronger parasocial identification, which in turn fosters more favorable evaluations of the brands and products the influencer endorses (Shan, Chen, & Lin, 2020). This process helps explain why consumers are often motivated to purchase products recommended by influencers: through the mechanism of idealization, followers associate endorsed products with the possibility of moving closer to their self-ideal. The principle of imitation, a fundamental aspect of human behavior, further reinforces this tendency, as individuals come to believe that adopting products used by influencers will help them embody the desired traits or lifestyle. Ultimately, influencer endorsements enhance consumers’ perceived confidence by linking consumption with aspirational identity.

Xu, Cui and Lyu (2022) highlighted that, through parasocial relationships, followers believe influencers are honest reviews which leads to more confidence in the brand and its claims. According to Leite and Baptista (2022), parasocial relationships explain the transfer of credibility from influencers to the products they promote. Moreover, the feeling of friendship leads to trust in the streamers and their recommended products, which enhances the quality of information about endorsed products, a vital factor in reducing information asymmetry in e-commerce. Regarding maintaining parasocial relationships with SMIs, consumers perceive them as altruistic. They note that influencers do not act in their self-interest, and consumers do not doubt the claims and promises of the endorsed products (Chung & Cho, 2017)

Given the above, we developed the following hypothesis:

H2.c: PSI with the Brand’s Influencer can directly and positively impact followers’ Perceived Confidence in the products advertised on the BSC.

2.4. Effects of consumers’ behaviors in the BSC on Intention to Follow Shopping Advice

Affective Engagement and Intention to Follow Shopping Advice

Hu and Chaudhry (2020) emphasized an integrative recommendation effect in e-commerce, fueled by emotional attachment, in which users want to recommend the site to others and follow the recommendations of other users. In line with this, Casaló, Flavián, and Ibáñez-Sánchez (2017) found that the greater the perceived enjoyment, the greater the interest in following the recommendations on Instagram. Herrando, Martín‐De Hoyos (2022) highlighted that users are more willing to buy products recommended by others when they are involved on an emotional basis. Applied to YouTube’s context, Silaban et al. (2022) demonstrated that viewers’ and YouTubers’ interactions based on joy and happiness lead to a greater intention to follow and give recommendations. As a result, it is stated the following hypothesis:

H3.a: Affective Engagement with BSC can have a direct and positive impact on the Intention to follow others’ shopping advice for BSC products.

Co-creation and Intention to Follow Shopping Advice

When consumers influence one another, they generate knowledge that helps others make more informed purchasing decisions in the future (Wang, Lin, & Spencer, 2019). As there is more feedback, recommendations, and ratings, they are likely to follow the recommendations of others (Handarkho, 2020). Furthermore, the social component of s-commerce fosters bonds and mutual trust among consumers. Hence, their comments or ratings influence one another to make similar choices (Doha, Elnahla, & McShane, 2019).

By applying the concept of flow to the relationship between influencers and followers, it becomes clear that continuous interaction with the content of influencers and the audience leads to a cognitive state characterized by curiosity, attention, interest, and a sense of control. This topic has been studied in detail by Hoffman and Novak (2009), who address how flow drives behavioral attitudes toward the brand. In social commerce, there is a "collective wisdom" (Hoffman and Novak, 2009) that confers reliability and credibility on recommendations suggested by other users, shaping not only purchase intentions based on these suggestions but also personal interest in offering suggestions and recommendations (Zhang et al., 2014). Assuming this, we elaborated the following hypothesis:

H3.b: Co-creation in BSC can have a direct and positive impact on the Intention to follow others’ shopping advice for BSC products.

Perceived Confidence and Intention to Follow Shopping Advice

In their study, Xu, Cui, and Lyu (2022) investigated the role of trust in product quality within the context of live-streaming e-commerce. Their findings suggest that a streamer's high reputation serves as an indicator of public endorsement, particularly when previous purchasers report that the products met their expectations. This positive community feedback not only enhances trust in the streamer but also in the quality of the promoted products, thereby significantly influencing consumers' purchase intentions.

Reinikainen et al. (2020) highlighted a virtuous circle between audience participation in brand communities with influencers and levels of trust. Their research demonstrates that more active communities- characterized by frequent audience comments and engagement-strengthen PSI and enhance the perceived credibility of influencers. In turn, it encourages further interaction and reinforces collective trust in the products endorsed within the community, ultimately increasing members' willingness to follow influencer recommendations. Lee and Lee (2022) found that stronger PSI with influencers and higher perceived credibility translate into greater confidence in recommended products, thereby increasing followers' intention to purchose those endorsed items.

Based on these premises, the following hypothesis was formulated:

H3.c: Perceived confidence in the brand's products advertised on BSC can directly and positively affect the Intention to follow others' shopping advice for BSC products.

2.5. The moderator effect of shopping channel preference between PSI and consumer behaviors in the BSC.

In the contemporary business landscape, marketers are allocating financial resources to invest in IM due to influencers' capacity to persuade their followers to adopt their recommendations, thereby positively driving brand sales (Influencer Marketing - Social Sensei, 2023). However, IM campaigns may produce limited conversion results if they do not consider followers' preferences regarding shopping channels. A consumer can be persuaded by an influencer's post on the BSC and prefer to buy the product in a physical store (Curalate, 2020). For small brands (e.g., startups) whose product sales are 100% online, as in this study, channel preference is a relevant issue to investigate.

Influencers play a crucial role in enhancing the brand's trust system (Leite and Baptista, 2022). Han et al. (2022) noted that affective trust in influencers generates positive feelings in consumers and influences trust in a broader sense, extending to the brand, other community members, and the information transmitted on social networks, based on emotional support. More importantly, influencers create more favorable and positive attitudes toward the brand among those who perceive more significant risks in online shopping (Chen et al., 2015). They influence to change their state of mind. Based on these assumptions, the following hypothesis is developed:

H4 (a-c): The positive effect of PSI on a) Affective engagement of followers to BSC, b) Co-creation behavior of followers of the BSC, and c) Perceived Confidence in the products advertised on the BSC will be more significant among consumers who prefer shopping in traditional commerce than among consumers who prefer shopping in online commerce.

In sum, we developed a conceptual model (Figure 1) to evaluate the direct impact of influencers´ traits (e.g., helpfulness, relatability, and articulation) on the psychological connection between influencers and BSC followers. Furthermore, we examine the role of PSI in generating positive attitudes - affective engagement, co-creation, and perceived confidence - which can impact intentions to follow others' shopping advice. Finally, this study explores how influencers can improve the favorability of online channels, particularly among consumers who are hesitant to make online purchases.

The case study is based on the startup Just for You (JFY), Brazil's first online company specializing in personalized hair cosmetics. This firm was selected because: 1. developed a successful business case during its market launch, establishing partnerships with many Brazilian macro-influencers (Appendix 2), which allowed the startup to reach more than 300 thousand followers in its s-commerce (Instagram account); 2. operates 100% online in s-commerce (@justforbr) and e-commerce (www.justfor.com.br) and its marketing mix is wholly focused on digital advertising.

The following hypotheses are tested in this study based on the discussions in this section:

• H1 (a-c): The Influencer's perceived traits of a) Helpfulness, b) Relatability, and c) Articulation can directly and positively impact PSI with followers of the BSC.

• H2 (a-c): PSI with the Brand's Influencer can directly and positively impact a) Affective Engagement with the BSC; b) Co-creation behavior of followers of the BSC; c) followers' Perceived Confidence in the products advertised on the BSC.

• H3 (a-c): The a) Affective Engagement with the BSC; b) Co-creation in the BSC; c) Perceived confidence in the brand's products advertised on the BSC can have a direct and positive impact on the Intention to follow others' shopping advice for the products of BSC.

• H4 (a-c): The positive effect of PSI on a) Affective Engagement of followers to the brand's Instagram account, b) Co-creation behavior of followers of the BSC, and c) Perceived Confidence in the products advertised on the BSC will be greater among consumers who prefer shopping in traditional commerce than among consumers who prefer shopping in online commerce.

Figure 1:
Research Model

3. METHODOLOGY

3.1. Sampling and Data collection

Our case study is based on the startup Just for You (JFY), the first online company specializing in personalized hair cosmetics in Brazil. Although the assessment of one company may limit the generalization effect, it helps to deepen the analysis and access real consumers' opinions, in line with the current literature on SMI (Silaban et al., 2022).

The survey link was available on JFY's Instagram account (wall posts and Stories) for one month, and research participants agreed to share their information, which is required by law in the Brazilian market. The questionnaire was developed based on English literature and then translated into Portuguese. A pre-test survey was sent to 10 respondents to check for overall comprehension. This tool enabled the modification of question order, correction of grammatical errors, and assessment of attention level through the control question. The research design employed a cross-sectional approach to assess customer opinions over a specific period, and sampling was conducted using a non-probabilistic method. The mandatory condition for answering the questions was that participants followed JFY's Instagram account. After eliminating questionnaires from consumers who were not brand followers, those with incomplete forms, and those containing the incorrect option for the attention verification question, we obtained 533 valid questionnaires. To define the sample size, we followed the recommendation of using a minimum of 10 observations for each independent variable and the extensive sampling required for CB-SEM methodology (Hair et at, 2019).

The traits of influencers - helpfulness (HELP), relatability (REL), and articulation (ART) - were adapted from the study of (Hassan et al., 2021). The three items of PSI were altered from the work of (Xiang et al., 2016). About PSI effects: 1. co-creation (CCO) was adapted from (Wang, Lin, & Spencer, 2019); 2. affective engagement (AFF) extracted from Hollebeek et al. (2014); and 3. Perceived confidence in performance (CONF) from Wang, Lin, and Spencer (2019). The dependent variable of this model, the intention to follow other people's shopping advice (FOL), was adjusted from the work of Mazzarolo et al. (2021). Variables were measured (Schreiber et al., 2006) with a 7-item Likert scale from "strongly disagree" (1) to "strongly agree" (7).

We ran structural equation modeling and multigroup analysis through SPSS 28.0 and AMOS 28. We chose CB-SEM due to its robustness to test construct validity, explanatory power, and model fit adjustment. In addition, CB-SEM is a suitable method for analyzing causal inferences and for marketing research, particularly with multiple constructs, multiple regressions, and multigroup analysis (Hair, Babin, & Krey, 2017; Cheung et al., 2022).

3.2. Demographics

Table 1 shows the demographic characteristics of the 533 participants. Most (51%) were between 26 and 41 years old, female (87%), completed higher education (48%), followed by 26.5% who completed secondary education, and had a monthly household income between €474.01 and €2,371.00 (53%).

JFY's top 10 influencers had high awareness, as 76% of JFY's followers also followed them. Shopping channel preference was checked by asking respondents where they would most like to buy hair cosmetics, and 53% declared e-commerce, ahead of other traditional channels (supermarkets, fragrance shopping, pharmacies, sales consultants, and free shops), which is reasonable since the sample included buyers (48%) and non-buyers (52%) of JFY products.

Table 1.
Descriptive statistics (n=533).

Measure	Items	Frequency	Percentage
Age	14 a 18	32	6.0%
	19 a 25	143	26.8%
	26 a 41	270	50.7%
	42 a 57	79	14.8%
	> 57 anos	9	1.7%
Gender	Male	67	12.6%
	Female	466	87.4%
Education	No schooling	5	0.9%
	Incomplete basic education	6	1.1%
	Complete basic education	13	2.4%
	Incomplete middle school	23	4.3%
	Complete middle school	144	27.0%
	Incomplete higher school	86	16.1%
	Complete higher school	256	48.0%
Monthly household income	Up to €474,00	193	36.2%
	From €474,01 to €948,00	153	28.7%
	From €948,01 to €2.371,00	130	24.4%
	From €2,371,01 to €4,352,00	36	6.8%
	More than €4.352,01	21	3.9%
Profile of interviewees	Buyers for JFY	258	48%
	Non-buyers for JFY	275	52%
JFY Influencers	Follow them	406	76.2%
	Do not follow them	127	23.8%
Purchase Preference	E-commerce	280	52.5%
	Other Offline Channels	253	47.5%

4. DATA ANALYSIS AND RESULTS

4.1. Measurement model

According to the cut-off criteria used in the Schreiber et al. (2006), the proposed model fits well: X²/d.f.= 2.518 (≤ 3); CFI=0.966 (> .95); NFI=0.950 (≥ .95); TLI=0.959 (>. 95); GFI=0.904; RMSEA = 0.053 (<0.06); SRMR = 0.033 (<. 08).

The internal consistency (Table 2) of the data was examined according to cut-off references cited in the work of Cheung et al. (2023). Cronbach Alpha values were higher than 0.8. Composite reliability (CR) was superior at 0.8; in some variables, it was higher than 0.9 and denoted good reliability.

We used two different criteria for discriminant analysis, with values shown in Table 3. Applying Fornell and Larcker, as cited in the work of Henseler, Ringle, & Sarstedt (2015), we found AVE results greater than 0.6, considered acceptable, as the construct explains more than 50% of the variance of its items (Hair et al., 2019). As the square root of the average variance extracted (AVE) of each construct was greater than the pairwise correlations, we were able to prove the distinction between the constructs. To provide robust analysis, we also evaluated the HTMT values, considered more appropriate by Hair et al. (2019), in specific degrees of indicator loadings. As all the items showed values below the 0.90 threshold, we confirmed the level of distinction between the constructs.

The R² (R-squared) values of endogenous variables presented the following explanatory power: PSI (0.755), CCO (0.541), AFF (0.701), CONF (0.567), and FOL (0.758). Assuming values cited in Hair et al. (2019), PSI and FOL showed substantial explanatory power (R² ≥0.75) and AFF, CONF, and CCO moderate power (0.74≥ R²≥0.50).

Table 2.
Convergent Validity Results

Items	Factor Loadings	Cronbach Alpha	CR	AVE
Helpfulness (HELP)
Just for You Influencers:
Provided valuable tips on applying the JFY product.	0.91	0.94	0.94	0.83
They were helpful to evaluate the JFY product I bought.	0.92
They were helpful to familiarize with the JFY product bought.	0.90
Relatability (REL)
About Just for You Influencers:
I often look up to the influencer as a role model to shape my own behaviour.	0.88	0.85	0.85	0.66
I can easily identify myself with the influencer.	0.86
I want to copy the behaviour of the influencer.	0.70
Articulation (ART)
About JFY Video tutorials:
The choice of language that the influencer used is easy to understand	0.93	0.93	0.93	0.82
The video tutorial is well prepared.	0.90
The influencer video tutorial is engaging.	0.88
Parasocial Interaction (PSI)
Just for You Instagram Community:
The interaction with other members on JFY IG account makes me feel comfortable, especially with some influencers I hardly contact in real life, as if I were with friends.	1.01	0.89	0.97	0.91
I found myself comparing my opinion about products and brands with what other members said, especially with some influencers’ opinions.	0.91
I can trust the information I get from other members on JFY IG account , especially from influencers I’m interested in.	0.93
Affective Engagement (AFF)
When I use Just for You Instagram:
I am happy	0.88	0.91	0.91	0.78
I feel very positive	0.89
I am proud to use the account	0.89
Co-creation (CCO)
I am willing to engaging with the Just for You Instagram account to:
Rate and review	0.77	0.95	0.94	0.68
Respond to other reviews	0.74
Sharing product information	0.85
Recommend the brand`s products to my SNS contacts	0.88
Share my shopping experiences with my SNS contacts	0.83
Provide my experiences and suggestions when my SNS contacts are shopping	0.86
Recommend the brand`s products when my SNS contacts need advice	0.84
Perceived Confidence in performance (CONF):
About Just for You products:
I am sure that they willl perform as expected	0.80	0.88	0.88	0.70
Offer reliable quality	0.85
Offer consistent quality	0.86
Intention to follow other people´s shopping advice (FOL):
When I come accorss products endorsed by other users on Just for You Insgram, then:
I’ll buy products or services endorsed by the JFY IG I follow when I need	0.75	0.84	0.85	0.65
I will definitely try products or services endorsed by the JFY IG accounts I follow	0.83
I would recommend to a friend products or services endorsed by other people on the JFY IG I follow	0.85

• FL (Factor Loading), CA (Cronbach Alpha), Composite Reliability (CR), Average Variance Extracted (AVE)

Table 3.
Discriminant Validity.

Discriminant Validity	1	2	3	4	5	6	7	8
1. Helpfulness	0.911	0.738	0.800	0.801	0.608	0.545	0.599	0.665
2. Relatability	0.736	0.811	0.694	0.701	0.581	0.492	0.419	0.488
3. Articulation	0.862	0.692	0.904	0.789	0.620	0.538	0.569	0.569
4. Parasocial Interaction	0.718	0.626	0.706	0.953	0.726	0.639	0.638	0.674
5. Affective Engagement	0.608	0.579	0.620	0.650	0.883	0.702	0.747	0.800
6. Co-creation	0.554	0.499	0.547	0.567	0.713	0.827	0.645	0.733
7. Perceived Confidence	0.599	0.418	0.569	0.572	0.746	0.656	0.839	0.779
8. Intention to follow other people´s shopping advice	0.657	0.531	0.666	0.619	0.790	0.737	0.769	0.809

• Fornell-Larcker (below the main diagonal) and HTMT values (above the diagonal)

4.2. Structural Model Evaluation

All hypotheses proposed in the causal relationship model were validated (Table 4). The three influencers' interaction traits - Helpfulness (H1.a: supported, β= 0.367, p < 0.01), Relatability (H1.b: supported, β= 0.189, p < 0.01), and Articulation (H1.c: supported, β= 0.373, p < 0.01) - had a positive impact on the PSI. JFY's influencers are all mega-influencers, considered experts in the beauty industry, with over 1 million followers. Their storytelling emphasizes the importance of physical and emotional self-care, highlighting specific products that help them relax and meet their needs. The scenes shown are captured in detail by professional videos and are rich in resources to keep the audience close. The spontaneous and revealing communication of personal issues, combined with minimally planned production techniques, leads to the necessary emotional connection with followers (Berryman & Kavka, 2017; Scholz, 2021; Yuan and Lou, 2020).

Furthermore, we confirm that PSI drives affective engagement (H2.a: supported, β= 0.837, p < 0.01), co-creation (H2.b: supported, β= 0.736, p < 0.01), and perceived confidence in product performance (H2.c: supported, β= 0.753, p < 0.01) in the JFY's BSC. JFY's influencers' stories resonate with JFY's followers, evoking strong emotions and pleasant experiences when browsing JFY's BSC. The feeling of friendship with JFY's influencers shapes consumers' attitudes toward co-creating with their posts (Tolbert and Drogos, 2019). Validating the SCM (Hassan et al., 2021), this study demonstrates that JFY's influencers have a positive impact on the perceived confidence in JFY's products.

PSI's outcomes - affective engagement (H3.a, β= 0.341, p < 0.01), co-creation (H3.b, β= 0.327, p < 0.01), and perceived confidence (H3.c, β= 0.348, p < 0.01) - produce a direct effect on the intention to follow shopping advice. No significant difference was found between these coefficients. These results reinforce the social nature of BSC, where purchase consideration is influenced by active participation and endorsement of products by other users (Cheung et al., 2022). On the other hand, PSI also produced an indirect impact on Intention to follow shopping advice (through Affective Engagement: β indirect effect = 0.285, p < 0.01; Co-creation (β indirect effect = 0.241, p < 0.01) and Perceived Confidence (β indirect effect = 0.262, p < 0.01). The indirect effect of PSI demonstrates that influencers are also relevant within the context of exposure on a brand account, not just on their accounts, mediated by affective engagement, co-creation, and perceived confidence.

Table 4.
Hypothesis Test

Model Relationships	Hypothesis	Stad. Beta	Results
Helpfulness → Parasocial Interaction	H1.a	0,367***	Supported
Relatability → Parasocial Interaction	H1.b	0,189***	Supported
Articulation → Parasocial Interaction	H1.c	0,373***	Supported
Parasocial Interaction → Affective Engagement	H2.a	0,837***	Supported
Parasocial Interaction → Co-creation	H2.b	0,736***	Supported
Parasocial Interaction → Perceived Confidence	H2.c	0,753***	Supported
Affective Engagement → Intention to Follow others´ shopping advice	H3.a	0,341***	Supported
Co-creation → Intention to Follow others´ shopping advice	H3.b	0,327***	Supported
Perceived Confidence → Intention to Follow others´ shopping advice	H3.c	0,348***	Supported

• Notes: Significance level: ***p = <0.01; **p = <0.05; *p = <0.1; n.s.: non-significant.

4.3. Multigroup Analysis

For this research, we included two consumer profiles in the multigroup analysis: 1. followers who prefer to buy cosmetics products in e-commerce; 2. followers who prefer to shop in traditional channels (for example, supermarkets and perfumeries, among others), where there is physical assistance. The terminology used was e-commerce because it was easier for consumers to understand when referring to online shopping. Preliminary specific tests have been performed to analyze 1. the goodness of fit of the model and 2. confirmatory factor analysis to assess the reliability and validity (Tables 5 and 6). Our research model presented good results of goodness-of-fit: X²/d.f.= 2.442; CFI= 0.946; NFI=0.935; TLI=0.935; GFI=0.847; RMSEA = 0.049; SRMR = 0.0436). Results showed that the items in each dimension were related to the construct and effectively measured what they were intended to measure (Cheung et al., 2023). The metric invariance was tested as follows. The results in Table 7 show that when the constraint of equality of parameters is imposed on both samples, the model does not worsen significantly, which allows us to conclude that metric invariance is met. Therefore, any differences are observed between the relationship and not the measurement of constructs.

Table 5.
Convergent Validity Results of Multigroup Analysis

Items	E-commerce			Traditional
	Factor Loadings	CR	AVE	Factor Loadings	CR	AVE
Helpfulness (HELP)
Just for You Influencers:
The influencer provided valuable tips on applying the JFY product.	0.933	0.959	0.886	0.892	0.925	0.804
The influencer was helpful to evaluate the JFY product I bought.	0.946			0.918
The influencer was helpful to familiarize with the JFY product bought.	0.944			0.880
Relatability (REL)
Just for You Influencers:
I often look up to the influencer as a role model to shape my own behaviour.	0.924	0.886	0.725	0.844	0.833	0.626
I can easily identify myself with the influencer.	0.897			0.837
I want to copy the behaviour of the influencer.	0.718			0.683
Articulation (ART)
Just for You Influencers:
The choice of language that the influencer used is easy to understand	0.953	0.959	0.887	0.914	0.913	0.778
The video tutorial is well prepared.	0.934			0.871
The influencer video tutorial is engaging.	0.939			0.861
Parasocial Interaction (PSI)
Just for You Instagram Community:
The interaction with other members on JFY IG account makes me feel comfortable, especially with some influencers I hardly contact in real life, as if I were with friends.	0.815	0.930	0.816	0.857	0.907	0.765
I found myself comparing my opinion about products and brands with what other members said, especially with some influencers’ opinions.	0.965			0.893
I can trust the information I get from other members on JFY IG account , especially from influencers I’m interested in	0.924			0.874
Affective Engagement (AFF)
When I use Just for You Instagram:
I am happy	0.847	0.911	0.773	0.91	0.914	0.781
I feel very positive	0.895			0.868
I am proud to use the account	0.894			0.87
Co-creation (CCO)
I am willing to engaging with the Just for You Instagram account to:
Rate and review	0.791	0.947	0.718	0.841	0.944	0.707
Respond to other reviews	0.764			0.856
Sharing product information	0.856			0.906
Recommend the brand`s products to my SNS contacts	0.876			0.860
Share my shopping experiences with my SNS contacts	0.857			0.794
Provide my experiences and suggestions when my SNS contacts are shopping	0.915			0.788
Recommend the brand`s products when my SNS contacts need advice	0.863			0.836
Perceived Confidence in performance (CONF):
About Just for You products:
I am sure that they willl perform as expected	0.808	0.892	0.734	0.79	0.875	0.701
Offer reliable quality	0.878			0.854
Offer consistent quality	0.882			0.866
Intention to Follow others´ shopping advice (FOL):
When I come accorss products endorsed by other users on Just for You Insgram, then:
I’ll buy products or services endorsed by the JFY IG I follow when I need	0.726	0.845	0.646	0.733	0.859	0.672
I will definitely try products or services endorsed by the JFY IG accounts I follow	0.846			0.843
I would recommend to a friend products or services endorsed by other people on the JFY IG I follow	0.834			0.876

• FL (Factor Loading), Composite Reliability (CR), Average Variance Extracted (AVE)

Table 6.
Analysis of Discriminant Validity of Multigroup Analysis

What is your favorite place to buy products for your hair?		1	2	3	4	5	6	7	8
1. Helpfulness	E-commerce	0.94	0.80	0.87	0.77	0.60	0.50	0.52	0.65
	Only Traditional	0.90	0.67	0.89	0.82	0.66	0.64	0.66	0.69
2. Relatability	E-commerce	0.80	0.85	0.73	0.69	0.59	0.46	0.41	0.55
	Only Traditional	0.65	0.79	0.68	0.67	0.62	0.57	0.47	0.53
3. Articulation	E-commerce	0.85	0.72	0.94	0.78	0.61	0.46	0.52	0.62
	Only Traditional	0.80	0.65	0.94	0.78	0.70	0.67	0.52	0.62
4. Parasocial Interaction	E-commerce	0.78	0.74	0.77	0.90	0.63	0.48	0.53	0.59
	Only Traditional	0.82	0.66	0.81	0.87	0.73	0.71	0.67	0.73
5. Affective Engagement	E-commerce	0.59	0.57	0.59	0.71	0.88	0.69	0.75	0.81
	Only Traditional	0.63	0.59	0.66	0.74	0.88	0.75	0.77	0.80
6. Co-creation	E-commerce	0.50	0.48	0.44	0.56	0.67	0.85	0.61	0.75
	Only Traditional	0.59	0.53	0.63	0.70	0.73	0.84	0.66	0.76
7. Perceived Confidence	E-commerce	0.55	0.39	0.50	0.60	0.72	0.59	0.86	0.77
	Only Traditional	0.65	0.43	0.65	0.67	0.76	0.64	0.84	0.79
8. Intention to Follow other users´ shopping advice	E-commerce	0.67	0.57	0.64	0.67	0.80	0.72	0.75	0.80
	Only Traditional	0.64	0.50	0.72	0.71	0.79	0.71	0.79	0.82

• Note: The square root of the average variance extracted is in bold in the diagonal. The data above the diagonal are the correlations between constructs. Fornell-Larcker (above the main diagonal) and HTMT values (below the diagonal)

Table 7.
Measurement invariance test

Fit Indices	Unrestricted Model	Restricted Model
χ²	1543.473	1573.072
Degree of freedom (df)	632	658
P	< 0.001	< 0.001
CFI	0.946	0.946
TLI	0.935	0.938
NFI	0.912	0.911
RMSEA	0.049	0.048
χ² difference test	Δdf = 26; Δχ²= 29.599; and p = 0.390 > 0.05

According to the multigroup model results (Table 8), hypotheses were partially confirmed. Co-creation (Traditional: β = 0.821) and Perceived Confidence (Traditional: β = 0.801) increased effects among JFY's followers who prefer traditional channels, with significant differences detected. There were no significant differences in Affective Engagement (Traditional: β = 857; E-commerce: β = 804). These findings suggest new roles for influencers in increasing positive attitudes towards brands among users who are more risk-averse when shopping online. This is particularly salient in the context of companies with limited market presence, such as JFY, which engenders heightened risk perceptions among consumers regarding product and financial performance. (Forsythe et al., 2006).

Table 8.
Significant Differences

Relationships	Hypothesis	E-commerce vs Traditional
		Path coefficient difference	CR
Parasocial Interaction → Affective Engagement	H5.a	-0.053	1.186
Parasocial Interaction → Co-creation	H5.b	-0.197	3.086
Parasocial Interaction → Perceived Confidence	H5.c	-0.115	2.280

• CR: Critical Ratio for differences between parameters. * t = 1.65 for p < 0.1; ** t = 1.96 for p <0.05; and *** t = 2.58 for p < 0.01.

5. DISCUSSION

5.1. About the friendship sense with influencers

Helpfulness and Articulation were the main drivers with similar effects on PSI (CR Intra = 0.267), followed by Relatability. Although these two first characteristics validate the value of information already highlighted by previous studies in the influencers/consumers relationship (Hajli, 2020; Scholz, 2021; Cheung et al., 2022), our results suggest a path that goes beyond the cognitive perspective. Helpfulness and articulation, as referred to in this work, are triggers for building genuine relationships (Sokolova and Perez, 2021).

On the other hand, the minor effect of relatability traits contrasts with the findings of other studies (Haobin Ye, Fong, & Luo 2021; Ballester et al. 2025). As we have analyzed the relationship created on a brand account, rather than on the influencers' accounts, the follower audience can be more diffuse and reduce the relatability with JFY´s influencers (Ballester et al. 2025).

Even if the effect is smaller than other characteristics, we found that JFY´s influencers establish a relatable sense of identity with JFY´s followers. Our results contrast with previous literature, which emphasized skills such as such as attractiveness, experience, originality, and uniqueness of SMIs to highlight influencers' superior qualities and ability to stand out from the crowd (Reinikainen et al., 2020; Casaló, Flavián, & Ibáñez-Sánchez, 2020). We contribute to previous literature by showing how influencers can establish a sense of relatable identity with the brand's followers, fortify the emotional bond, and facilitate the collaborative creation within the BSC framework

5.2. PSI and its effects on the BSC

This article reveals the direct effects of PSI on brand-consumer engagement, as well as the indirect effect on the intention to follow shopping advice. Several insights emerge from these results. First, influencers transfer their credibility (Hassan et al., 2021) and emotional attachment (Xiang et al., 2016) to the brand and its relationship with customers. Second, purchase intent occurs not only when influencers directly recommend products on their accounts (Masuda, Han, & Lee 2022), but also in the brand´s account, presupposing a high level of follower involvement (Chetioui, Benlafqih, & Lebdaoui, 2020). Third, influencers strengthen the bonds with the brand's community and enhance engagement, regardless of whether the brand's followers are more or less familiar with them. Consequently, we transition to a subsequent level of evaluation, proposing influencers' roles that extend beyond the scope of brand advocates or product endorsers, as previously discussed in extant literature (De Veirman, Cauberghe and Hudders, 2017; Leite and Baptista, 2022; Sánchez-Fernández & Jiménez-Castillo, 2021). From our perspective, influencers can enhance social support within the BSC (Ahmad & Laroche, 2017; Hassan et al., 2021) and increase the intimacy and credibility of their relationship with the public (Hassan et al., 2021). Influencers have been shown to induce positive consumer attitudes (Haobin Ye, Fong, & Luo, 2021); increase community influence (Farivar & Wang, 2022); and perceived trust in the products offered on the BSC (Sander et al., 2021). These effects indirectly impact the intention to follow shopping advice.

Building on these findings, this study highlights how, in s-commerce, socialization-through peer communication, emotional support, and parasocial interaction-significantly shapes behavioral intentions (Handarkho, 2020). Within this relational scope, SMIs’ interactions extend beyond traditional buyer-seller exchanges, fostering bonds within broader communities (Hu and Chaudhry, 2020). Influencers mediate relationships once held directly between brands and consumers, creating new forms of persuasion. This dynamic is particularly relevant in emerging markets such as Brazil, where SMIs play a central role in digital advertising. Nearly two-thirds of advertisers plan to invest in influencer partnerships, reflecting the steady growth of influencer-driven content (Navarro, 2024). For both established and emerging brands, collaborating with SMIs represents an opportunity to strengthen relationship quality and foster community-based social support (Handarkho, 2020).

5.3. Is PSI able to increase its favorability on online channels?

When evaluating the group most reluctant to buy online, the most significant effects produced by PSI were in co-creation behavior and perceived confidence. From PSI, we extend the "collective wisdom" effect, cited by Hoffman and Novak (2009), by addressing the feedback between collaboration and collective knowledge that guides behaviors in following the recommendations given. Feedback also reinforces the influencer's reputation (Xu, Cui, & Lyu 2022), which is transferred to brand credibility (Leite and Baptista (2022). This binomial of co-creation and perceived confidence becomes even stronger among consumers who have a greater aversion to online shopping due to emotional relationships with influencers. On the other hand, the level of affective engagement did not vary significantly according to the preferred channel, thereby aligning with the findings reported by Kusuma et al. (2024). These researchers cited a general effect of Instagram in providing pleasant experiences with other members and strengthening the brand community's social capital.

We demonstrated that mega-influencers elicit heightened levels of co-creation among brand's audience and augment levels of perceived confidence in brand products among consumers who favor traditional channels. Beauty mega-influencers craft powerful storytelling that combines popularity and authenticity, ensuring an intimacy pact (Berryman & Kavka, 2017) while maintaining the robustness of the information, which is valued even more by consumers who are wary of online channels.

The results of this research are promising, particularly among the few studies on BSC startups operating in emerging markets, such as Brazil. These companies struggle to compete in a beauty sector dominated by larger companies (Yuen, 2023). Hence, operating entirely online becomes a strategy to reduce the operational costs of mixed sales channels and increase competitiveness. On the other hand, startups are, by nature, companies with a less established track record, which increases user distrust and reduces purchase intent (Lowry et al., 2008). Developing a comprehensive online marketing strategy based on IM can simplify the marketing mix portfolio, guarantee greater conversion results and increase confidence in the brand and its products among consumers and, more specifically, among those who are more hesitant to make purchases online.

6. CONCLUSIONS AND MANAGERIAL IMPLICATIONS

The first part of this research showed that JFY's influencers drive intimacy pact with BSC's followers through their traits of helpfulness and articulation, to a greater extent, and then relatability. Influencers' ability to provide advice and allow followers to immerse themselves in the promoted products genuinely strengthens the social capital (Kusuma et al., 2024) and social support (Ahmad & Laroche, 2017) required in a hybrid channel such as s-commerce. These findings provide important insights for brands when co-promoting with SMIs. Brands must craft a genuine narrative in collaboration with influencers that aligns with the distinctive attributes or value propositions of their products. Hence, brands can optimize the efficacy of their communication to enlighten consumers and fortify their confidence in the performance of products that influencers on their BSC have endorsed. Furthermore, considering the relevance of helpfulness and articulation of influencers, brands should focus on live streams, tutorials, and unboxing videos, which are more useful for co-creation and educational purposes.

Our results also revealed that influencers play a role that extends beyond product promotion or fostering eWOM (De Veirman, Cauberghe, & Hudders, 2017). Through PSI, influencers strengthen positive emotions toward the BSC and increase consumers' intention to follow recommendations, driven by affective engagement, co-creation, and perceived confidence. To fully leverage these dynamics, brands must emphasize authenticity, transparency, and co-creation (Lou, 2022), allowing consumers to interact meaningfully with influencers and construct their own narratives. Importantly, consumers themselves are becoming active participants in BSCs, often taking on influencer-like roles within their own networks and shaping purchase intentions in their communities.

Given this expanded role of influencers, evaluating IM campaigns solely through ROI is limiting. A more comprehensive assessment should include metrics that capture co-creation with influencer posts (e.g., comments, shares) and content relevance (e.g., saved posts, length of views). In addition, brands need to assess influencers’ capacity to generate qualified leads, as immersive product experiences provided by influencers often attract e-commerce visitors with higher purchase intent compared to other digital campaigns. Finally, professionals should monitor campaign effects beyond the brand’s official account, since consumers frequently share content across different networks. Using tools such as sentiment analysis can help determine whether an influencer has become a trending topic and provide deeper insights into how the partnership shapes brand perception.

As this study reveals, PSI can alter consumers' state of mind and make brand followers more receptive to online shopping. PSI enhances community interaction, fosters confidence in the brand's products, and indirectly increases the intention to follow the shopping advice of other consumers (Farivar & Wang, 2022). In this case, one suggestion is for brands to leverage sales-oriented content (e.g., tutorials or live content) to promote immediacy in contact with the audience. Another recommendation is to provide a chatbot for customer service during live interactions so that consumers receive personalized assistance that helps reduce information asymmetry, especially among customers with a higher risk aversion to online purchases.

7. LIMITATIONS AND FUTURE RESEARCH DIRECTION

This study has some limitations that could provide opportunities for future work. Firstly, the sample data only included buyer/non-buyer profiles, which was adequate for data collection. However, including the profile of frequent buyers could add value to assessing the impact of PSI on the repurchase intention behavior of products recommended by others. In line with this proposal, future research would employ a longitudinal research method to capture the connections and psychological bonds established through more frequent exposure to published content (Hu et al., 2020).

Secondly, the results of the SCM (Hassan et al., 2021) were obtained from a single case analysis of a cosmetic startup. It would be interesting to apply the three selected influencer traits (helpfulness, articulation, and relatability) to other segments or sectors to see if there is a more generalized effect on these skills. Furthermore, as social media relationships evolve at the country level (Masuda, Han, and Lee, 2022), future studies could evaluate IM in other regions or on other s-commerce platforms (e.g., TikTok) to demonstrate how the effects of PSI vary across different contexts.

Thirdly, in terms of influencer profiles, some studies reinforce the differences between the types of influencer reach. Liu, Li, and Lee (2021) showed that micro-influencers boost PSI because they are more transparent and credible. A suggestion for future work would be to evaluate the impact of micro- and macro-influencers on consumer attitudes toward PSI and purchase behavior. This knowledge is essential for developing more effective IM strategies that enable brands to explore cost-effective alternatives, particularly for startups with limited marketing budgets.

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• DATA AVAILABILITY STATEMENT
  The dataset that supports the results of this study is not publicly available.

Appendix 1

Table S1
Measurement Item Used

Construct	Item
Helpfulness (Hassan,S.H.; Teo,S.Z.; Ramayah,T. and Al-Kumaim,N.H., 2021)	SEN1	The influencer provided valuable tips on applying the JFY product.
	SEN2	The influencer was helpful to evaluate the JFY product I bought.
	SEN3	The influencer was helpful to familiarize with the JFY product bought
Relatability (Hassan,S.H.; Teo,S.Z.; Ramayah,T. and Al-Kumaim,N.H., 2021)	REL1	I often look up to the influencer as a role model to shape my own behaviour.
	REL2	I can easily identify myself with the influencer.
	REL3	I want to copy the behaviour of the influencer.
Articulation (Hassan,S.H.; Teo,S.Z.; Ramayah,T. and Al-Kumaim,N.H., 2021)	ART2	The choice of language that the influencer used is easy to understand
	ART3	The video tutorial is well prepared.
	ART4	The influencer video tutorial is engaging.
Parasocial Interaction (Xiang,L.; Zheng,X.; Lee,M.K.O. and Zhao,D., 2016)	PAR2	The interaction with other members on JFY IG account makes me feel comfortable, especially with some influencers I hardly contact in real life, as if I were with friends.
	PAR3	I found myself comparing my opinion about products and brands with what other members said, especially with some influencers’ opinions.
	PAR4	I can trust the information I get from other members on JFY IG account , especially from influencers I’m interested in
Co-creation (Wang,X.; Lin,X. and Spencer,M.K., 2019)	COT1	Rate and review
	COT2	Respond to other reviews
	COT3	Sharing product information
	COT4	Recommend the brand`s products to my SNS contacts
	COT5	Share my shopping experiences with my SNS contacts
	COT6	Provide my experiences and suggestions when my SNS contacts are shopping
	COT7	Recommend the brand`s products when my SNS contacts need advice
Affective Engagement (Hollebeek,L.D.; Glynn,M.S. and Brodie,R.J., 2014)	ENG3	I am happy
	ENG4	I feel very positive
	ENG5	I am proud to use the account
Perceived Performance (Wang,X.; Lin,X. and Spencer,M.K., 2019)	RSK2	I am sure that they willl perform as expected
	RSK4	Offer reliable quality
	RSK6	Offer consistent quality
Purchase Intention (Mazzarolo,A.H.; Mainardes,E.W. and Innocencio,F.A., 2021)	END2	I’ll buy products or services endorsed by the JFY IG I follow when I need
	END3	I will definitely try products or services endorsed by the JFY IG accounts I follow
	END4	I would recommend to a friend products or services endorsed by other people on the JFY IG I follow

Appendix 2 - Top 10 JFY influencers in Influencer Marketing campaigns

1. Bárbara Evans Clark

(2.3 million followers on Instagram) https://www.instagram.com/barbaraevans22?igsh=Y2U0dGl2czdwZHBh

2. Biah Rodrigues Fakri

(2.2 million followers on Instagram) https://www.instagram.com/biahrodriguesz?igsh=MWF5amZnNWRtOWZ4YQ==

3. Camila Monteiro

(3.4 million followers on Instagram) https://www.instagram.com/camilamonteiro?igsh=MWl2eGs3YW4yZ2p0ZQ==

4. Fabiola Melo

(3.1 million followers on Instagram) https://www.instagram.com/fabiolamelooficial?igsh=ZW9oNWI1NzhhdmMx

5. Flavia Viana

(2.7 million followers on Instagram) https://www.instagram.com/flavia_viana?igsh=MXJzYjRmOXhpNXVzMQ==

6. Jade Seba

(2.4 million followers on Instagram) https://www.instagram.com/jadeseba?igsh=eWUybnF6eTRkc3Y0

7. Mari Maria

(21.4 million followers on Instagram) https://www.instagram.com/marimaria?igsh=MXIyOWxpejZzejU2cQ==

8. Mariana Sampaio

(2.0 million followers on Instagram) https://www.instagram.com/mariana?igsh=MTh4ampwZW5jemN6MQ==

9. Tata Estaniecki Cocielo

(12.4 million followers on Instagram) https://www.instagram.com/tata?igsh=MXVwY2Frb3BzNXM1cA==

10. Yá Burihan

(2.6 million followers on Instagram) https://www.instagram.com/yaburihan?igsh=c3doZmlsZGh2cHcw

ACKNOWLEDGMENTS

The authors would like to thank Grants PID2023-147414OB-I00 and TED2021-129513B-C22 funded by MCIN/AEI/10.13039/501100011033/FEDER, UE and European Union NextGenerationEU/PRTR

Edited by

• EDITOR-IN-CHIEF
  Marcia d’Angelo

• ASSOCIATE EDITOR
  Emerson Mainardes

Data availability

The dataset that supports the results of this study is not publicly available.

Publication Dates

• Publication in this collection
  29 June 2026
• Date of issue
  2026

History

• Received
  30 Oct 2024
• Reviewed
  09 Feb 2025
• Accepted
  19 Aug 2025