ORIGINAL RESEARCH

 

Unveiling the power of social influencers in brand trust and brand identification

 

 

Ji-Young Kim^I; Sung-Hoon Ko^II; Yongjun Choi^III

^ICollege of Business Administration, Hankuk University of Foreign Studies, Seoul, Republic of Korea
^IIGraduate School of Education, Kyonggi University, Suwon, Republic of Korea
^IIICollege of Business Administration, Hongik University, Seoul, Republic of Korea

Correspondence

 

 

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ABSTRACT

PURPOSE: This study investigates the effects of social influencer characteristics (i.e., opinion leadership and parasocial interaction) on forming follower brand trust and identification
DESIGN/METHODOLOGY/APPROACH: This study included 286 Korean consumers (144 males and 142 females) with social media experience. We tested the hypotheses using structural equation modelling, multiple regression, bootstrapping and multigroup model analysis within the fast moving consumer goods (FMCG) sector, with a particular focus on an orange juice brand.
FINDINGS/RESULTS: Opinion leadership and parasocial interaction (i.e., the one-sided, quasi-social relationship between individuals and social influencers through media consumption) were positively related to follower brand trust and brand identification, and brand trust had a positive relationship with brand identification. The mediating effect of brand trust in the positive relationships between social influencer characteristics and brand identification was significant. We also found that opinion leadership was positively related to brand identification in the male group, while parasocial interaction had a positive relationship to brand identification in the female group.
PRACTICAL IMPLICATIONS: Organisations need to be aware that opinion leadership and parasocial interaction are vital for understanding the effectiveness of social influencer marketing. In addition, they need to take a close look at social influencer characteristics as they affect brand performance by target group.
ORIGINALITY/VALUE: Our results suggest that brand trust is essential in explaining how social influencer characteristics relate to brand identification. This study is the first to analyse gender-based variations in brand identification formed by opinion leadership and parasocial interaction highlighting the roles of social influencer characteristics in marketing.

Keywords: social influencer; social influencer marketing; S-O-R; opinion leadership; parasocial interaction; brand trust; brand identification; gender.

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Introduction

The rapid growth of social media has led to a wide range of content users creating, disseminating and consuming. Such a social phenomenon paved the way for the emergence of social influencers with many followers, and social influencers started to play a role as new marketing communicators (Turcotte et al., 2015). Accordingly, as the importance of social influencer marketing as a marketing strategy is more significant than ever (Adegbola et al., 2018), companies need to understand the roles of social influencers for effective marketing communication.

Social influencer marketing uses social influencers to influence potential or non-potential consumers in the digital world. The ubiquitous connection enabled by the spread of social media usage has fundamentally changed the position of consumers in the existing traditional power-centred structure (Evans, 2019). Social influencer marketing aims to create positive emotions or perceptions about the brand through interactive communication with followers or potential followers on social media, ultimately leading to positive consumer behaviours. As maintaining long-term relationships with consumers based on their preference for a specific brand is vital for companies (Morgan-Thomas & Veloutsou, 2013), most companies use social influencers to promote their brands in various ways to better communicate with consumers.

The effectiveness of social influencer marketing has drawn much attention, especially since the emergence of the coronavirus disease 2019 (COVID-19) pandemic. According to a study conducted by the American Association of Advertisers (ANA) in 2018 (before the COVID-19 pandemic), 75% of consumers were engaged in social influencer marketing; however, only 36% of them believe that social influencer marketing worked (Taylor, 2020). However, the United Kingdom market research on the firm global web index (GWI) revealed that 47% of all social platform users increased the time spent on social platforms after the COVID-19 pandemic. It indicates that digital-based, intact cultural consumption, which has become dominant because of the COVID-19 pandemic, has strengthened the social influencer's role. Accordingly, 94% of marketers consider social influencer marketing effective; notably, social influencer marketing effectiveness is 11 times greater than traditional advertising (Lou & Yuan, 2019).

In light of the growing impact of social influencers (Saima & Khan, 2020), previous studies have examined the role of opinion leadership as a defining characteristic of social influencers (Bobkowski, 2015; Casaló et al., 2020; De Veirman et al., 2017; Fakhreddin & Foroudi, 2022; Farivar et al., 2021; Weeks et al., 2017). Notably, parasocial interactions on social media have emerged because of the interplay between social influencers and consumers (Lou & Kim, 2019). Furthermore, the establishment of parasocial interactions targeting specific audiences can prompt the target to assume a role akin to that of a friend to consumers (Tsai & Men, 2017). Thus, highlighting the importance of these parasocial interactions becomes crucial as consumer engagement on social media platforms increases. In line with this, recent research delves into the relational dynamics of influencer advertising, emphasising parasocial interactions and their impact on consumers (Agnihotri et al., 2023; Areni, 2022; Jin et al., 2021; Kim, 2022), demonstrating that social influencers shape consumers' positive attitudes and purchase intentions. This indicates that engagement in parasocial interactions aligns consumer attitudes with influencer perspectives. Therefore, a comprehensive investigation of parasocial interactions in shaping brand evaluations is essential, complementing the exploration of opinion leadership.

Focusing on the social influencer's two characteristics, opinion leadership (Akdevelioglu & Kara, 2020) and parasocial interaction (Sokolova & Kefi, 2020), previous studies revealed that social influencers could elicit others' brand-related behaviours by providing various information based on experience and knowledge in a specific field. In other words, the social influencer's opinion leadership and parasocial interaction coexist as factors that can persuade consumers by forming brand relationships. Overheated competition among social influencers for sponsorships and paid advertisements sometimes leads to unethical and untruthful brands. An untruthful brand can result in negative perceptions and reactions from consumers and thus pose risks to brand performance; trust in the brand can be a significant factor in maintaining long-term brand relationships with consumers (Reichheld et al., 2000).

Drawing on the S-O-R (stimulus, organism, response) theory, this study explores the relationships among social influencer characteristics (i.e., opinion leadership and parasocial interaction), brand trust and brand identification. We specifically aim to explore the roles of social influencer characteristics in shaping consumers' brand trust and brand identification. Furthermore, this study investigates the differences between male and female consumers in the relationship between social influencer characteristics and brand identification. Gender plays a crucial role in market segmentation and shaping consumer attitudes (Dommeyer & Gross, 2003). For example, men value goal-oriented cues in purchasing situations, but women prefer relationship-oriented cues such as affection and intimacy (Meyers-Levy, 1989). Past studies also showed that men tend to prioritise personal achievements and assert opinions strongly in group settings, while women lean towards conformity and alignment with group opinions (Moorman & Blakely, 1995). Consequently, acknowledging these differences is essential in social influencer marketing. Thus, this study fills this gap by applying the S-O-R theory to enhance our understanding of how opinion leadership and parasocial interaction (stimulus) build brand trust (organism) that leads to brand identification (response), providing significant insights into consumer-brand relationships and social influencer marketing strategies. Specifically, in consumer behaviour studies, easily accessible food items, commonly encountered in daily life, are often used as stimuli (e.g., Chitturi et al., 2019; Kim & Kim, 2021; Tassiello et al., 2021). Distinguishing between low and high involvement, low-involvement products, like juice, tend to prompt quicker purchasing decisions (Erdem et al., 2006; Kuenzel & Musters, 2007; Rossiter & Percy, 1991; Tassiello et al., 2021). Therefore, in this study, we introduce orange juice as a stimulus representing a low-involvement product, with the aim of providing insights for companies selling such products in the Korean market.

Our research questions are as follows:

• RQ1. How do social influencer characteristics (opinion leadership and parasocial interaction) affect brand identification?

• RQ2. Which social influencer characteristics (opinion leadership vs. parasocial interaction) have a greater influence on brand trust and brand identification?

• RQ3. How does brand trust affect brand identification?

• RQ4. Does brand trust play a mediating role in the relationship between social influencer characteristics and brand identification?

• RQ5. Is there a significant difference between male and female consumers?

 

Theoretical background

Social influencer and social influencer marketing

The recent transition to a digital-based society has resulted in a new type of celebrity producing and sharing various contents on social media and retaining many followers. Accordingly, consumers become interested in content generated by online personalities (i.e., social influencers) and make purchase decisions based on their recommendations (Mohsin, 2020). Social influencers lead public opinions by interacting with their followers. Because two-way communications are essential in marketing, social influencers strengthen their presence through active communication with users of social media platforms, such as Instagram and YouTube. Accordingly, followers recognise them as important sources of information, creating cognitive, emotional and conative changes in consumers.

As the use of social media increases exponentially, many companies focus on social influencer marketing to effectively achieve marketing communication (Boerman, 2020). In particular, social influencer marketing provides an effective alternative to communicating by integrating commercial content into social content that younger consumers crave (Childers et al., 2019). Furthermore, social influencers interconnect with others more actively and make recommendations based on their high social status with more information (Araujo et al., 2017). Therefore, opinion leadership and parasocial interaction are crucial to persuasion in the relationship between social influencers and followers; these two characteristics are complementary (Farivar et al., 2021).

The S-O-R paradigm

In this study, we applied the S-O-R theory (Mehrabian & Russell, 1974) to explore our research questions for the following reasons. It has established itself as a robust framework for scrutinising consumer perceptions, attitudes and behaviours (Casaló et al., 2020; Gamage & Ashill, 2023). Simultaneously, it has been employed to explore the influence of social media in the marketing context (Casaló et al., 2020; Djafarova & Bowes, 2021; Gamage & Ashill, 2023). Additionally, the S-O-R theory proves valuable in discerning distinctions between male and female consumer groups. Supporting this, past studies grounded on the S-O-R theory have demonstrated that males and females tend to respond differently to external stimuli, such as emotional advertising (Fisher & Dubé, 2005) and shared beliefs (Yang et al., 2022). Hence, we found that the S-O-R theory provides a solid foundation for our research model.

Firstly, a stimulus is an environment that influences consumer decisions at a specific moment (Jacoby, 2002). For example, in marketing, advertisement, brand, price, interior, word of mouth and store location can act as stimuli as they influence consumer behaviours. Therefore, the stimulus from social influencer characteristics can be a motivation and a stimulus for the brand trust, which refers to 'the willingness of the average consumer to rely on the ability of the brand to perform its stated function' (Chaudhuri & Holbrook, 2001:82) that affects consumers' inner state towards the brand. Secondly, the organism refers to consumers' cognitive and emotional states, mediating between stimulus and response (Kamboj et al., 2018). A response (i.e., brand identification in this study) through brand trust appears when two social influencer stimuli (i.e., opinion leadership and parasocial interaction) are present. That is, the establishment of brand trust signifies a high valuation of the brand by consumers, potentially increasing the extent to which consumers identify with the brand. Past studies also support the pivotal role of brand trust in facilitating the formation of brand identification (Becerra & Badrinarayanan, 2013; Bergami & Bagozzi, 2000; Kuenzel & Halliday, 2008). Thus, trust is an organism (Harris & Goode, 2010). A response represents an action or outcome (Manthiou et al., 2017). Brand identification refers to 'a consumer's perceived state of oneness with a brand' (Stokburger-Sauer et al., 2012:407). Consumers are likely to prefer brands characterised by high brand identification because brand identification entails the symbolic or self-expressive consumption of a brand, serving as a means for consumers to express their social identity (Aaker, 1997). Thus, brand identification formed through brand trust indicates a response.

Drawing upon the S-O-R theory, we aim to enhance our understanding of the mechanisms of how opinion leadership and parasocial interaction (stimulus) build brand trust (organism) that leads to brand identification (response). Brand trust, representing a consumer-brand relationship, constitutes an organism and can positively affect brand performance, mediating the relationship between social influencer characteristics and brand identification, ultimately eliciting brand identification as a response.

Hypotheses development

Social influencer characteristics and brand identification

Social influencers are a source of information for consumers and, thus, persuasive. Two models can generally explain the effect of a social influencer: the source credibility model and the source attractiveness model. Source credibility pertains to the favourable qualities of a communicator that shape the audience's reception of a message, reflecting the perceived reliability of the information source (Ohanian, 1990). Source attractiveness, a combination of physical and social allure (Hakim, 2010), contributes to the development of parasocial interactions (Schiappa et al., 2007). Because of the human inclination to connect with attractive individuals, intensifying these interactions, source attractiveness strengthens parasocial interactions (Hartmann & Goldhorn, 2011). In essence, source credibility encapsulates the opinion leadership exhibited by social influencers, while source attractiveness reflects their engagement in parasocial interactions. More specifically, public trust is one of the main characteristics of professionalism and reliability and attractiveness includes intimacy, liking and similarity (McCracken, 1989). While public trust can increase consumer dependence on a social influencer and influence behavioural intentions with high persuasive power, intimacy means that followers feel a close emotional bond with a social influencer resulting from accumulated interactions (Simon & Tossan, 2018). For example, the physical attractiveness of YouTube bloggers can influence their parasocial relationships with followers, which, in turn, can affect followers' brand awareness and purchase intentions (Lee & Watkins, 2016). Thus, we can infer that social influencer characteristics can be a source of brand identification.

Opinion leadership is a characteristic of individuals who attempt to actively participate in accepting and disseminating information in the communication process between individuals or groups (Flynn et al., 1996). We expect social influencers' opinion leadership will increase their followers' brand identification. Those with high opinion leadership have the expertise and significantly influence consumers' purchasing decisions through active online activities and participation (Leal et al., 2014). Moreover, their innovativeness is positively related to their sensitivity, wherein the greater the novelty and uniqueness of a product, the heightened their responsiveness. Consumers align with the trends set by opinion leaders (Thakur et al., 2016), signifying that consumers are inclined to internalise and conform to the values of these leaders as if they were their own. Therefore, we predict that followers who perceive social influencers as opinion leaders are more likely to identify with those brands.

Parasocial interaction refers to forming a pseudo-intimacy with media personalities that one feels in genuine interpersonal relationships (Horton & Wohl, 1956). This form of interaction inherently differs from conventional social interaction, which entails mutual engagement and communication between individuals (Moschis & Churchill, 1978). Parasocial interaction embodies a concept that defines one-sided and virtual social relationships marked by a perceived illusion of intimacy. In further detail, it signifies a unilateral and virtual social connection wherein the interaction between a character and the audience creates the 'illusion of intimacy' (Cohen, 2003). Thus, followers can build relationships with brands by interacting with social influencers through social media. That is, social media enables a two-way parasocial interaction between a social influencer and a follower (Sokolova & Kefi, 2020). Followers' evaluations and attitudes towards products or brands can differ depending on the information provided by social influencers. Parasocial interaction can affect emotional response (Scott & Craig-Lees, 2010) and cognitive and behavioural levels (Knoll et al., 2015). Therefore, parasocial interactions facilitate consumer-brand relationships and even increase consumers' positive attitudes towards the brand and purchasing behaviours. In particular, increased intimacy with social influencers can increase consumers' familiarity, knowledge and understanding of the product (Munnukka et al., 2019). Accordingly, followers might feel that the social influencer is their friend, thus forming a psychological connection with them, which can act as a stimulus for liking and identification with the brand. Therefore, we hypothesise the following:

H₁: Social influencer opinion leadership positively affects the followers' brand identification.

H₂: Social influencer parasocial interaction positively affects the followers' brand identification.

Social influencer characteristics and brand trust

Brand trust is the extent to which consumers believe a particular brand will satisfy their needs (Chinomona, 2016) and consumers' confident expectations of brands in risky situations (Delgado-Ballester, 2004). Brand trust differs from brand identification in that brand trust is grounded in reliability and confidence, whereas brand identification revolves more around the emotional and symbolic connection forged between the consumer and the brand. Brand trust is vital for organisations because it is pivotal in reducing consumer uncertainty (Zehir et al., 2011), affecting their purchasing decisions (Stewart, 2003). News presented online by opinion leaders rapidly spreads by showing consumers friendliness and credibility (Turcotte et al., 2015). Consumers consider product opinions and information from opinion leaders more reliable and persuasive than mass marketing (Stern & Gould, 1988). Thus, we expect that social influencers can form a high level of trust (Sokolova & Kefi, 2020) because they appear closer to specific audiences (Lou & Yuan, 2019). Moreover, trust in familiar objects transfers to new, unknown objects. For example, consumers can transfer trust in social influencers to the products, brands and services they offer.

The higher the consumer's perception of the opinion leadership of the social influencer, the lower the consumer's perception of risks towards a brand resulting from key clues like expertise and knowledge provided by social influencers. The professionalism of an informant has a very close relationship with public confidence (Hovland et al., 1953), and public confidence translates to credibility (Assael, 1998). Thus, social influencers' opinion leadership can enhance brand trust, representing a consumer-brand relationship. Social influencers' parasocial interactions can also positively affect brand trust. The main characteristic of parasocial interaction is the positive emotions one has continuously accumulated for a particular character (Dibble et al., 2016). Supporting this, parasocial interactions between celebrities and consumers tend to form trust in brands related to celebrities (Phua et al., 2018). More frequent interactions can lead to stronger quasi-social relationships, increasing the credibility of the information source. As such, followers build trust in a specific brand when they experience a parasocial interaction with a social influencer:

H₃: Social influencer opinion leadership positively affects the followers' brand trust.

H₄: Social influencer parasocial interaction positively affects the followers' brand trust.

Brand trust and brand identification

Based on social identity theory (Ashforth & Mael, 1989), brand identification refers to an individual's congruent feelings towards the brand; individuals with a high brand identification tend to consider the success or failure of the brand as their success or failure (Badrinarayanan & Laverie, 2011). In other words, brand identification is the perceived unity of the brand that reflects the consumer's self-image; it manifests the connection between the consumer's self-concept and the brand (Del Rio et al., 2001).

Brand identification is essential in consumer-brand relationships as it makes it easier to carry out brand-related activities. Thus, consumers with high brand trust highly value the consumer-brand relationship and maintain the relationship by creating an emotional commitment to the brand (Chaudhuri & Holbrook, 2002). Furthermore, trust in a specific brand reduces the psychological risk of consumers, thereby forming a more favourable brand unity. Supporting this, Batra et al. (2012) showed that a competitive brand includes consumers' trust and self-identity with the brand. Therefore, we hypothesise the following:

H₅: Followers' brand trust positively affects brand identification.

Mediating role of brand trust

Trust forms by evaluating an object's behaviour perceived through interaction with the object (Mayer et al., 1995). Cognitive trust reflects the consumer's perceived trust in a particular object or the consumer's desire to depend on the ability of a specific object. In contrast, affective trust reflects the consumer's perceived level of relationship, comfort or stability (Johnson & Grayson, 2005). For example, a customer may want to rely on credibility and express emotions (Rempel et al.,1985). As such, trust towards a specific object has a characteristic that can transfer to another object. Brand trust means a favourable evaluation of the brand; it impacts reinforcing brand identification because it provides greater confidence in how the brand will behave (Ling et al., 2021). Supporting this, consumers who trust a company's activities strengthen their identification with the company and evaluate it positively (Chudhari & Holbrook, 2001).

Brand trust is also closely related to uncertain situations (Doney & Cannon, 1997). As social influencer marketing occurs in an environment of high uncertainty, brand trust can be an important factor along with social influencer characteristics perceived by consumers. In particular, brand trust refers to the belief that a brand will provide consistent and competent quality (Chudhari & Holbrook, 2001). Therefore, a brand trust formed through opinion leadership and parasocial interaction positively affects the formation of brand identification. We can consider brand trust as an unquestioning consumer expectation to receive the brand for which they paid. Thus, we hypothesise the following:

H₆: Followers' brand trust mediates the positive relationship between social influencers' opinion leadership and brand identification.

H₇: Followers' brand trust mediates the positive relationship between social influencers' parasocial interaction and brand identification.

 

Methodology

Study participants and procedure

This study employed a research company with seven million panels to collect data from Korean consumers who have used social media. A total of 323 people responded to the survey. After removing respondents who did not fall under the survey subject and who provided insincere responses, we entered 286 surveys for final data analysis. The respondents comprised 144 men (50.3%) and 142 women (49.7%). By age, 97 respondents were in their 20s (33.9%), 103 in their 30s (36.0%), 60 in their 40s (21.0%) and 26 in their 50s (9.1%). By the most memorable product posted by social media influencers, 74 respondents referred to food (25.9%), followed by cosmetics (n = 55, 19.2%), clothing (n = 51, 17.8%), electronics (n = 45, 15.7%), miscellaneous goods (bags, shoes, jewellery) (n = 40, 14.0%), exercise equipment (n = 10, 3.5%) and other (n = 11, 3.8%). Regarding the frequency of social media use for a week, 60 respondents marked 'less than or equal to three times' (21.0%), 62 responded, 'more than three times and less than or equal to five times' (21.7%), 43 indicated 'more than five times and less than or equal to seven times' (15.0%), 24 stated, 'more than seven times and less than or equal to nine times' (8.4%), and 97 reported, 'more than or equal to nine times' (33.9%).

Given consumers' extensive use of social media, we opted for Fast Moving Consumer Goods (FMCG) for several reasons. Fast Moving Consumer Goods comprises daily essentials designed for personal use, known for their affordability, frequent consumption and minimal purchase effort (Leahy, 2011). These products operate with low profit margins, facing substantial pressure for product availability and innovation and demanding significant investments in marketing (Diehl & Spinler, 2013). Establishing meaningful customer interactions in the FMCG sector presents notable challenges for organisations (Leahy, 2011). Therefore, our study seeks to explore the effect of social influencers, focusing on easily accessible stimuli consumed in daily life and shareable on platforms like Instagram. As a result, orange juice was chosen as a representative low-involvement product (Montandon et al., 2017). To minimise variations in attitudes because of factors like prior knowledge and awareness, we presented orange juice as a virtual brand product, omitting specific brand details.

In a similar vein, social influencers were depicted as virtual individuals in our study design. Moreover, in categorising social influencers, mega-influencers are those with more than a million followers, and micro-influencers have less than 10 000 followers (Schouten et al., 2020). Consequently, a social influencer in our study was portrayed as a virtual influencer with 200 000 followers, representing a well-known figure. This choice aimed to facilitate participant comprehension of the virtual persona by offering detailed characteristics associated with a renowned influencer. To enhance understanding, a dedicated virtual account was established, featuring images of daily life and products. The primary focus of the study aligned with the prevalent trend of showcasing beauty or food-related products on social media.

Measures

We used a seven-point Likert scale (1 = not at all agree, 7 = strongly agree) to measure opinion leadership, parasocial interaction, brand trust and brand identification.

Opinion leadership

Opinion leadership was measured using the items from King and Summers (1970), Weimann (1991), and Casaló et al. (2018). We used a total of four items (e.g., 'Fictitious character O provides important information to others', 'Fictitious character O advises others'). Cronbach's alpha (α) was 0.840.

Parasocial interaction

To measure parasocial interaction, we adapted the items used in Rubin and Perse (1987), Auter and Plamgreen (2000) and Lee and Watkins (2016) in this study, which included five items (e.g., 'I feel fictitious character O friendly like a friend', 'I feel fictitious character O natural and honest'). Cronbach's alpha was 0.948.

Brand trust

Brand trust was measured using the five items from Chaudhuri and Holbrook (2001) and Erdem and Swait (2004) (e.g., 'Products posted by fictitious character O are reliable', 'Products posted by fictitious character O can be used with confidence'). Cronbach's alpha was 0.96.

Brand identification

To measure band identification, we adapted five items from Stokbuger-Sauer et al. (2012) and Belén del Río et al. (2001) (e.g., 'Products posted by fictitious character O seem to express my image well', 'Products posted by fictitious character O express my values well'). Cronbach's alpha was 0.959.

 

Results

Confirmatory factor analysis

Before testing our hypotheses, we performed confirmatory factor analysis to test the discriminant validity. The results showed acceptable fit indices, χ² (140) = 279.106, comparative fit index (CFI) = 0.977, Tucker Lewis index (TLI) = 0.972, goodness-of-fit statistic (GFI) = 0.908, normed-fit index (NFI) = 0.956, root mean square error of approximation (RMSEA) = 0.059, standardised root mean square residual (SRMR) = 0.036. In addition, the average variance extracted (AVE) exceeded 0.5, meaning it meets the traditional criteria.

Correlation analysis

Table 1 presents our study variables' means, standard deviations and correlations. The Pearson correlation coefficients ranged from 0.650 to 0.813. As expected, opinion leadership (r = 0.676, p < 0.01) and parasocial interaction (r = 0.650, p < 0.01) were positively related to brand trust. In addition, we found a positive relationship between brand trust and brand identification (r = 0.813, p < 0.01). Lastly, opinion leadership (r = 0.650, p < 0.01) and parasocial interaction (r = 0.736, p < 0.01) had a positive relationship with brand identification.

 

 

Hypotheses testing

We tested our hypotheses with structural equation modelling using AMOS 24.0. Our model fit indices were acceptable; χ² = 266.349 (df = 135, p = 0.000), CFI = 0.974, TLI = 0.973, GFI = 0.906, NFI = 0.958, RMSEA = 0.058, SRMR = 0.028. Our results indicate that opinion leadership positively relates to brand identification (path coefficient = 0.117, p < 0.05), supporting Hypothesis 1. In addition, we found support for Hypothesis 2 because parasocial interaction is positively related to brand identification (path coefficient = 0.218, p < 0.001). Both opinion leadership (path coefficient = 0.312, p < 0.001) and parasocial interaction (path coefficient = 0.487, p < 0.001) positively related to brand trust, supporting Hypotheses 3 and 4. Lastly, brand trust positively correlated with brand identification (path coefficient = 0.487, p < 0.001), thus supporting Hypothesis 5.

We also tested our RQ2, comparing the relative effect of opinion leadership and parasocial interaction on brand trust and brand identification. Table 2 presents the results. Firstly, the regression coefficients of opinion leadership and parasocial interaction on brand identification were 0.317 and 0.526, respectively, showing a relatively more substantial influence of parasocial interaction on brand identification. Secondly, the regression coefficients of opinion leadership and parasocial interaction on brand trust were 0.365 and 0.504, respectively, showing that parasocial interaction had a more significant influence on brand trust than opinion leadership.

Thirdly, the relationships between opinion leadership and parasocial interaction with brand identification were significant (p < 0.001, two-tailed). The indirect effects of opinion leadership and parasocial interaction on brand identification through brand trust were more significant than the direct effects of opinion leadership and parasocial interaction on brand identification (p < 0.05 and p < 0.001, respectively), confirming the significance of the brand trust's mediating effect and thus supporting Hypotheses 6 and 7. Table 3 and Figure 1 present the results.

 

 

 

 

Gender differences analysis

We conducted multiple group analyses to test the differences in path coefficients between males and females. The results are in Table 4 and Figure 2. Most path coefficients were higher in the female group, ∆ coefficient being 0.081 for the path from opinion leadership to brand identification, 0.072 for the path from parasocial interaction to brand identification, 0.114 for the path from opinion leadership to brand trust and 0.089 for the path from parasocial interaction to brand trust. However, the path from brand trust to brand identification was more significant in the male group, with ∆ coefficient being 0.655. Not all path coefficients were statistically significant in the male and female sub-groups. The path from parasocial interaction to brand identification was not statistically significant in the male consumer group. In contrast, the path from opinion leadership to brand identification was not statistically significant in the female consumer group, supporting the importance of the mediating role of brand trust.

 

 

Discussion and conclusion

Using a low-involvement product (i.e., juice) as a stimulus, this study investigated the roles of social influencer opinion leadership and parasocial interaction in the formation of brand trust and brand identification in the Korean context. Specifically, we focused on opinion leadership and parasocial interaction, representing the characteristics of social influencers who play a substantial role as consumer information sources. A summary of the findings is as follows.

Firstly, opinion leadership and parasocial interaction significantly affected brand identification. These results imply that opinion leadership and parasocial interaction (two social influencer characteristics) are essential in brand performance. Opinion leadership and parasocial interaction lead to positive consumer behaviours. These two characteristics positively affect consumer purchase intention (Farivar et al., 2021). Consumers tend to purchase brands highly aligned with their personalities, suggesting that opinion leadership and parasocial interaction are significant factors that can increase a sense of identity with the brand.

Secondly, opinion leadership and parasocial interaction had a statistically significant effect on brand trust. This finding supports Zhang et al. (2011) and Phua et al.'s (2018) studies that followers' perceptions of social influencers are important in forming positive consumer-brand relationships. Notably, brand trust mediates the relationships between brand identification, opinion leadership and parasocial interaction. In other words, consumers' positive perceptions of social influencers strengthen brand trust, ultimately increasing brand identification. In particular, we found the pathway from parasocial interaction to brand identification more significant than the path from opinion leadership to brand identification. Also, the path from parasocial interaction to brand trust was more significant than from opinion leadership to brand trust. The stronger pathway from parasocial interaction to both brand trust and brand identification underscores the vital role of emotional connections between social influencers and their followers in shaping consumers' perceptions of a brand. This may be attributed to parasocial interaction's ability to foster a sense of personal connection with influencers. Consequently, this heightened connection could enhance trust in both the brand and influencers, fostering a sense of closeness and relatability. These emotional bonds, in turn, would lead individuals to align themselves more closely with the brands endorsed by the influencer. Engaging in parasocial interaction with a specific object has been shown to elevate the consumer's level of intimacy and attachment to that object (Zhang et al., 2022). However, it is essential to note that our findings do not undermine the significance of opinion leadership in social influencer marketing. Specifically, interpersonal communication through opinion leadership can exert a substantial influence on purchasing decisions, especially when there is difficulty in evaluating the overall value of a product or service (Song et al., 2017). While the path from opinion leadership to brand trust and identification may be comparatively less significant, opinion leadership still plays a crucial role in shaping followers' perceptions within their social circles. Their influence could be more indirect, operating through interpersonal communication rather than being direct.

Thirdly, we found brand trust to have a statistically significant relationship with brand identification, demonstrating the power of the consumer-brand relationship (Becerra & Badrinarayanan, 2013). Therefore, garnering the consumers' trust and identity with the brand improves the brand's competitive advantage. In addition, a brand trusted by consumers is easier for them to identify with because an evaluation of the brand is more straightforward and more apparent.

Fourthly, the indirect effects of opinion leadership and parasocial interaction on brand identification through brand trust were more significant than the direct effects of opinion leadership and parasocial interaction on brand identification. Our results comparing the male and female consumer groups showed that parasocial interaction did not significantly affect brand identification in the male consumer group. In addition, opinion leadership did not significantly affect brand identification in the female consumer group. The multigroup analysis of the path coefficient difference between male and female consumers revealed that the relationship between parasocial interaction and brand identification was more significant in women. In contrast, the relationship between brand trust and identification was stronger in men.

Theoretical implications

Firstly, the study employed two social influencer characteristics - opinion leadership emphasising the cognitive aspect and parasocial interaction emphasising the emotional part of social influencers - to empirically investigate their effects on brand relationship formation. Individuals with high opinion leadership handle risks cautiously and possess more extensive product knowledge (Chan & Misra, 1990; Dalman et al., 2020). Thus, social influencers with strong opinion leadership offer specialised and diverse information to followers, influencing their cognitive judgements effectively. Parasocial interactions, on the other hand, allow followers to build intimacy, motivating their product purchases and fostering empathic responses and emotional alignment (Shen et al., 2022; Yuksel & Labrecque, 2016). Therefore, through the simultaneous exploration of two crucial social influencer characteristics, encompassing both cognitive and emotional aspects, our findings make a valuable contribution to the literature on social influencer marketing. Furthermore, by concurrently examining opinion leadership and parasocial interaction, our study establishes a foundational framework for diverse comparative research. Additionally, it provides implications for future studies investigating the interplay between social influencer characteristics and variables related to brands.

Secondly, this study presented the direct and indirect effects of multidimensionally measured opinion leadership and parasocial interaction on brand identification, revealing the importance of brand trust. It suggests various implications that can be the basis for future research concerning marketing communication, brand trust and brand performance variables. This differs from existing studies that have primarily explored the direct relationship between social influencers and consumer behaviour, such as purchase intention (Fakhreddin & Foroudi, 2022; Sokolova & Kefi, 2020; Yudha, 2023). Specifically, our findings emphasise that the importance of parasocial interaction closely parallels the significance attributed to opinion leadership in past studies. The stronger the emotional connection consumers establish with social influencers, the more likely they are to depend on them. These results align with the idea that as parasocial relationships intensify, the persuasiveness of product recommendations increases (Hartmann & Goldhoorn, 2011). Thus, our findings provide insight into how both opinion leadership and parasocial interaction are interconnected in the formation of consumer-brand relationships.

Thirdly, this study systematically and empirically investigated how social influencer characteristics, as perceived by consumers, relate to brand identification through brand trust, demonstrating the mediating effect of brand trust providing empirical evidence supporting Haudi et al. (2022). Previous research has overlooked the influence of social influencer characteristics on brand trust. The links between social influencer characteristics, such as opinion leadership and parasocial interaction, brand trust and brand identification were rarely explored. Therefore, our findings fill this gap by empirically testing and demonstrating the mediating role of brand trust, which confirms that social influencer characteristics contribute to brand trust, influencing brand identification.

Fourthly, our study contributes valuable insights to the existing understanding of gender-specific responses in social influencer marketing. Consistent with prior research, our results indicate that males often prioritise goal-oriented cues, while females exhibit a greater affinity for relationship-oriented cues such as affection and intimacy (Meyers-Levy, 1989). Importantly, gender differences become evident in the pathway between social influence characteristics and brand identification. Specifically, the cognitive dimension of social influencer characteristics (i.e., opinion leadership) proves pivotal for males, whereas the emotional dimension (i.e., parasocial interaction) is more important for females. This finding aligns with Riedle, Hubert and Kenning (2010), suggesting a potential discrepancy in emphasis, with males tending to prioritise the cognitive dimension while females assign greater importance to the emotional dimension in online environments. However, the path between parasocial interactions and brand trust was significant in both male and female groups. These outcomes illuminate the nuanced impact of social influencer characteristics on brand identification, underscoring its non-uniformity across genders.

Practical implications

Firstly, our results showed that opinion leadership and parasocial interaction are necessary stimulants for brand trust, suggesting they are vital to achieving successful brand performance. Using social influencers with many followers may lead to little effect for companies. In other words, there may be better strategies than simply relying on the number of followers or the popularity of social influencers. Our findings suggest that marketing professionals should exercise caution and strategic acumen by closely examining social influencers' characteristics, especially opinion leadership and parasocial interaction. Beyond relying solely on popularity metrics, such as the number of followers, marketers should scrutinise the authenticity and substance of influencers' opinions to ensure alignment with brand values. Acknowledging the power of parasocial interaction, marketers can also seamlessly integrate their brand into influencers' narratives, fostering a genuine connection with followers. This nuanced analysis has the potential to enable marketers to facilitate collaborations that not only reach a broad audience but also resonate authentically, cultivating lasting brand affinity and fostering a positive consumer perception within the dynamic landscape of social media marketing.

Secondly, our results comparing male and female consumers provide organisations with insights to develop different marketing strategies by target group (i.e., male or female consumer groups). Our results showed that males reacted more positively to the cognitive aspect (i.e., opinion leadership), while females responded more positively to the emotional aspect (i.e., parasocial interaction). These findings suggest that, while both opinion leadership and parasocial interaction hold significance in social influencer marketing, marketing professionals should be cognisant that their relative importance may vary across target groups, such as males versus females. Specifically, our results indicate that when aiming to reach male consumers, marketing professionals may benefit from selecting a social influencer with high opinion leadership, whereas a social influencer with high parasocial interaction could be more effective when targeting female consumers. Thus, it is important for marketing professionals to take a close look at social influencer characteristics to build trust in their brands according to the target group and elicit significant brand performance.

Limitations and future research

Despite the theoretical and practical implications, this study has the following limitations. Firstly, there is a limitation to this study's generalisability of findings as we only collected data from South Korean consumers. Furthermore, South Korea is a country that uses social media most actively, and it is also notable that South Korea has a strong collectivistic tendency, while the United States has a solid individualistic tendency (Hofstede, 1991). In addition, we limited the study's group analysis to gender. Future research could perform a multigroup model analysis with data from different countries to see how the results compare in other countries.

Secondly, this study employed only one variable, brand trust, in examining the consumer-brand relationship. Consumer-brand relationships exist in various forms. Adding variables like brand satisfaction and brand immersion to the model would provide more implications by segmenting the consumer-brand relationship. Therefore, future research should use more variables.

Thirdly, the selection of low-involvement products as stimuli in our study prompts consideration of potential constraints on the generalisability of our findings. Consumer behaviour, inherently diverse and contingent upon the nature of the product, is a phenomenon elucidated by product involvement (Chen & Chaiken, 1999). Nevertheless, our investigation intentionally focused on low-involvement products, distinguished by their easily attainable and straightforward purchase processes. This strategic emphasis allowed us to scrutinise the nuanced effects arising from the distinctive characteristics of social influencers. As such, we encourage future research to take a more comprehensive approach, considering both low and high-involvement products, to enhance our understanding of the heightened intricacies inherent in the purchasing dynamics of the high-involvement product.

Finally, this study selected brand identification as an outcome variable from brand relationships. Forming consumer-brand relationships through social influencer marketing can lead to various brand-related behaviours, such as brand passion, brand commitment and brand evangelism. Therefore, future research with the variables above as outcome variables will contribute to a better understanding of social influencer marketing, consumer-brand relationship and brand performance.

 

Acknowledgements

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors' contributions

J-Y.K. conceived of the presented model and developed the theory. J-Y.K. collected the data. J-Y.K. and S-H.K. analysed the data and wrote the original manuscript with input from all authors. Y.C. aided in interpreting the results and worked on the practical discussion. J-Y.K., S-H.K. and Y.C. discussed the results and commented on the manuscript.

Ethical considerations

This article followed all ethical standards for research without direct contact with human or animal subjects.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

The data that support the findings of this study are available on request from the first author, J-Y.K.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency, or that of the publisher. The authors are responsible for this article's results, findings, and content.

 

References

Aaker, J.L. (1997). Dimensions of brand personality. Journal of Marketing Research, 34(3), 347-356. https://doi.org/10.1177/002224379703400304        [ Links ]

Adegbola, O., Gearhart, S., & Skarda-Mitchell, J. (2018). Using Instagram to engage with(potential) consumers: A study of Forbes' most valuable brands' use of Instagram. The Journal of Social Media in Society, 7(2), 232-251.         [ Links ]

Agnihotri, D., Chaturvedi, P., Kulshreshtha, K., & Tripathi, V. (2023). Investigating the impact of authenticity of social media influencers on followers' purchase behavior: Mediating analysis of parasocial interaction on Instagram. Asia Pacific Journal of Marketing and Logistics, 35(10), 2377-2394. https://doi.org/10.1108/APJML-07-2022-0598        [ Links ]

Akdevelioglu, D., & Kara, S. (2020). An international investigation of opinion leadership and social media. Journal of Research in Interactive Marketing, 14(1), 1-88. https://doi.org/10.1108/JRIM-11-2018-0155        [ Links ]

Araujo, T., Neijens, P., & Vliegenthart, R. (2017). Getting the word out on Twitter: The role of influentials, information brokers, and strong ties in building word-of-mouth for brands. International Journal of Advertising, 36(3), 496-513. https://doi.org/10.1080/02650487.2016.1173765        [ Links ]

Areni, C.S. (2022). Automated text analyses of YouTube comments as field experiments for assessing consumer sentiment towards products and brands. Journal of Product & Brand Management, 31(5), 702-717. https://doi.org/10.1108/JPBM-01-2021-3341        [ Links ]

Ashforth, B.E., & Mael, F. (1989). Social identity theory and the organization. Academy of Management Review, 14(1), 20-39. https://doi.org/10.2307/258189        [ Links ]

Assael, H. (1998). Consumer behavior and marketing action, 6th edn., South-Western College Publishing.

Auter, P.J., & Palmgreen, P. (2000). Development and validation of a parasocial interaction measure: The audience-persona interaction scale. Communication Research Reports, 17(1), 79-89. https://doi.org/10.1080/08824090009388753        [ Links ]

Badrinarayanan, V., & Laverie, D.A. (2011). Brand advocacy and sales effort by retail salespeople: Antecedents and influence of identification with manufacturers' brands. Journal of Personal Selling and Sales Management, 31(2), 123-140. https://doi.org/10.2753/PSS0885-3134310202        [ Links ]

Batra, R., Ahuvia, A., & Bagozzi, R.P. (2012). Brand love. Journal of Marketing, 76(2), 1-16. https://doi.org/10.1509/jm.09.0339        [ Links ]

Becerra, E.P., & Badrinarayanan, V. (2013). The influence of brand trust and brand identification on brand evangelism. Journal of Product and Brand Management, 22(5/6), 371-383. https://doi.org/10.1108/JPBM-09-2013-0394        [ Links ]

Bergami, M., & Bagozzi, R.P. (2000). Self-categorization, affective commitment and group self-esteem as distinct aspects of social identity in the organization. British Journal of Social Psychology, 39(4), 555-577. https://doi.org/10.1348/014466600164633        [ Links ]

Bobkowski, P.S. (2015). Sharing the news: Effects of informational utility and opinion leadership on online news sharing. Journalism & Mass Communication Quarterly, 92(2), 320-345. https://doi.org/10.1177/1077699015573194        [ Links ]

Boerman, S.C. (2020). The effects of the standardized Instagram disclosure for micro and meso influencers. Computers in Human Behavior, 103, 199-207. https://doi.org/10.1016/j.chb.2019.09.015        [ Links ]

Casaló, L.V., Flavi´an, C., & Ib´a˜nez-S´anchez, S. (2018). Influencers on Instagram: Antecedents and consequences of opinion leadership. Journal of Business Research, 117, 510-519. https://doi.org/10.1016/j.jbusres.2018.07.005        [ Links ]

Casaló, L.V., Flavián, C., & Ibáñez-Sánchez, S. (2020). Influencers on Instagram: Antecedents and consequences of opinion leadership. Journal of Business Research, 117, 510-519. https://doi.org/10.1016/j.jbusres.2018.07.005        [ Links ]

Chan, K.K., & Misra, S. (1990). Characteristics of the opinion leader: A new dimension. Journal of Advertising, 19(3), 53-60. https://doi.org/10.1080/00913367.1990.10673192        [ Links ]

Chaudhuri, A., & Holbrook, M.B. (2001). The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. Journal of Marketing, 65(2), 81-93. https://doi.org/10.1509/jmkg.65.2.81.18255        [ Links ]

Chaudhuri, A., & Holbrook, M.B. (2002). Product-class effects on brand commitment and brand outcomes: The role of brand trust and brand affect. Journal of Brand Management, 10(1), 33-58. https://doi.org/10.1057/palgrave.bm.2540100        [ Links ]

Chen, S., & Chaiken, S. (1999). The heuristic-systematic model in its broader context. In S. Chaiken & Y. Trope (Eds.), Dual-process theories in social psychology (pp. 73-96). The Guilford Press.

Childers, C.C., Lemon, L.L., & Hoy, M.G. (2019). #Sponsored# Ad: Agency perspective on influencer marketing campaigns. Journal of Current Issues & Research in Advertising, 40(3), 258-274. https://doi.org/10.1080/10641734.2018.1521113        [ Links ]

Chinomona, R. (2016). Brand communication, brand image, & brand trust as antecedents of brand loyalty in Gauteng Province of South Africa. African Journal of Economic and Management Studies, 7(1), 124-139. https://doi.org/10.1108/AJEMS-03-2013-0031        [ Links ]

Chitturi, R., Londono, J.C., & Amezquita, C.A. (2019). The influence of color and shape of package design on consumer preference: The case of orange juice. International Journal of Innovation and Economic Development, 5(2), 42-56. https://doi.org/10.18775/ijied.1849-7551-7020.2015.52.2003        [ Links ]

Cohen, J. (2003). Parasocial breakups: Measuring individual differences in responses to the dissolution of parasocial relationships. Mass Communication & Society, 6(2), 191-202. https://doi.org/10.1207/S15327825MCS0602_5        [ Links ]

Dalman, M.D., Chatterjee, S., & Min, J. (2020). Negative word of mouth for a failed innovation from higher/lower equity brands: Moderating roles of opinion leadership and consumer testimonials. Journal of Business Research, 115, 1-13. https://doi.org/10.1016/j.jbusres.2020.04.041        [ Links ]

De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: The impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798-828. https://doi.org/10.1080/02650487.2017.1348035        [ Links ]

Del Rio, A.B., Vazquez, R., & Iglesias, V. (2001). The effects of brand associations on consumer response. Journal of Consumer Marketing, 18(5), 410-425. https://doi.org/10.1108/07363760110398808        [ Links ]

Delgado-Ballester, E. (2004). Applicability of a brand trust scale across product categories: A multigroup invariance analysis. European Journal of Marketing, 38(5/6), 573-592. https://doi.org/10.1108/03090560410529222        [ Links ]

Dibble, J.L., Hartmann, T., & Rosaen, S.F. (2016). Parasocial interaction and parasocial relationship: Conceptual clarification and a critical assessment of measures. Human Communication Research, 42(1), 21-44. https://doi.org/10.1111/hcre.12063        [ Links ]

Diehl, D., & Spinler, S. (2013). Defining a common ground for supply chain risk management-A case study in the fast-moving consumer goods industry. International Journal of Logistics Research and Applications, 16(4), 311-327. https://doi.org/10.1080/13675567.2013.813443        [ Links ]

Djafarova, E., & Bowes, T. (2021). 'Instagram made Me buy it': Generation Z impulse purchases in the fashion industry. Journal of Retailing and Consumer Services, 59, 102345. https://doi.org/10.1016/j.jretconser.2020.102345        [ Links ]

Dommeyer, C.J., & Gross, B.L. (2003). What consumers know and what they do: An investigation of consumer knowledge, awareness, and use of privacy protection strategies. Journal of Interactive Marketing, 17(2), 34-51. https://doi.org/10.1002/dir.10053        [ Links ]

Doney, P.M., & Cannon, P.J. (1997). An examination of the nature of trust in buyer-seller relationships. Journal of Marketing, 62(2), 35-51. https://doi.org/10.1177/002224299706100203        [ Links ]

Erdem, T., & Swait, J. (2004). Brand credibility, brand consideration, & choice. Journal of consumer Research, 31(1), 191-198. https://doi.org/10.1086/383434        [ Links ]

Erdem, T., Swait, J., & Valenzuela, A. (2006). Brands as signals: A cross-country validation study. Journal of Marketing, 70(1), 34-49. https://doi.org/10.1509/jmkg.70.1.034.qxd        [ Links ]

Evans, M. (2019), Five key traits defining connected consumers in 2019. Forbes. Retrieved from https://www.forbes.com/sites/michelleevans1/2019/09/23/five-key-traits-defining-connected-consumers-in-2019/#6b1b97e622df

Fakhreddin, F., & Foroudi, P. (2022). Instagram influencers: The role of opinion leadership in consumers' purchase behavior. Journal of Promotion Management, 28(6), 795-825. https://doi.org/10.1080/10496491.2021.2015515        [ Links ]

Farivar, S., Wang, F., & Yuan, Y. (2021). Opinion leadership vs. parasocial relationship: Key factors in influencer marketing. Journal of Retailing and Consumer Services, 59, 102371. https://doi.org/10.1016/j.jretconser.2020.102371        [ Links ]

Fisher, R.J., & Dubé, L. (2005). Gender differences in responses to emotional advertising: A social desirability perspective. Journal of Consumer Research, 31, 850-858. https://doi.org/10.1086/426621        [ Links ]

Flynn, L.R., Goldsmith, R.E., & Eastman, J.K. (1996). Opinion leaders and opinion seekers: Two new measurement scales. Journal of the Academy of Marketing Science, 24(2), 137-147. https://doi.org/10.1177/0092070396242004        [ Links ]

Gamage, T.C., & Ashill, N.J. (2023). # Sponsored-influencer marketing: Effects of the commercial orientation of influencer-created content on followers' willingness to search for information. Journal of Product & Brand Management, 32(2), 316-329. https://doi.org/10.1108/JPBM-10-2021-3681        [ Links ]

Hakim, C. (2010). Erotic capital. European Sociological Review, 26(5), 499-518. https://doi.org/10.1093/esr/jcq014        [ Links ]

Harris, L.C., & Goode, M.M. (2010). Online servicescapes, trust, & purchase intentions. Journal of Services Marketing, 24(3), 230-243. https://doi.org/10.1108/08876041011040631        [ Links ]

Hartmann, T., & Goldhoorn, C. (2011). Horton and Wohl revisited: Exploring viewers' experience of parasocial interaction. Journal of Communication, 61(6), 1104-1121. https://doi.org/10.1111/j.1460-2466.2011.01595.x        [ Links ]

Haudi, H., Handayani, W., Musnaini, M., Suyoto, Y., Prasetio, T., Pitaloka, E., Wijoyo, H., Yonata, H., Koho, I.R., & Cahyono, Y. (2022). The effect of social media marketing on brand trust, brand equity and brand loyalty. International Journal of Data and Network Science, 6(3), 961-972. https://doi.org/10.5267/j.ijdns.2022.1.015        [ Links ]

Hofstede, G. (1991). Cultures and organizations: Software of the mind. McGraw-Hill.

Horton, D., & Wohl, R. (1956). Mass communication and parasocial interaction: Observations on intimacy at a distance. Journal of Psychiatry, 19(3), 215-229. https://doi.org/10.1080/00332747.1956.11023049        [ Links ]

Hovland, C.I., Janis, I.L., & Kelley, H.H. (1953). Communication and persuasion. Yale University Press.

Jacoby, J. (2002). Stimulus-organism-response reconsidered: An evolutionary step in modeling(consumer) behavior. Journal of Consumer Psychology, 12(1), 51-57. https://doi.org/10.1207/S15327663JCP1201_05        [ Links ]

Jin, S.V., Ryu, E., & Muqaddam, A. (2021). I trust what she's# endorsing on Instagram: Moderating effects of parasocial interaction and social presence in fashion influencer marketing. Journal of Fashion Marketing and Management: An International Journal, 25(4), 665-681. https://doi.org/10.1108/JFMM-04-2020-0059        [ Links ]

Johnson, D., & Grayson, K. (2005). Cognitive and affective trust in service relationships. Journal of Business Research, 58(4), 500-507. https://doi.org/10.1016/S0148-2963(03)00140-1        [ Links ]

Kamboj, S., Sarmah, B., Gupta, S., & Dwivedi, Y. (2018). Examining branding co-creation in brand communities on social media: Applying the paradigm of stimulus-organism-response. International Journal of Information Management, 39, 169-185. https://doi.org/10.1016/j.ijinfomgt.2017.12.001        [ Links ]

Kim, D.Y., & Kim, H.Y. (2021). Influencer advertising on social media: The multiple inference model on influencer-product congruence and sponsorship disclosure. Journal of Business Research, 130, 405-415. https://doi.org/10.1016/j.jbusres.2020.02.020        [ Links ]

Kim, H. (2022). Keeping up with influencers: Exploring the impact of social presence and parasocial interactions on Instagram. International Journal of Advertising, 41(3), 414-434. https://doi.org/10.1080/02650487.2021.1886477        [ Links ]

King, C.W., & Summers, J.O. (1970). Overlap of opinion leadership across consumer product categories. Journal of Marketing Research, 7(1), 43-50. https://doi.org/10.1177/002224377000700104        [ Links ]

Knoll, J., Schramm, H., Schallhorn, C., & Wynistorf, S. (2015). Good guy vs. bad guy: The influence of parasocial interactions with media characters on brand placement effects. International Journal of Advertising, 34(5), 720-743. https://doi.org/10.1080/02650487.2015.1009350        [ Links ]

Kuenzel, J., & Musters, P. (2007). Social interaction and low involvement products. Journal of Business Research, 60(8), 876-883. https://doi.org/10.1016/j.jbusres.2007.02.008        [ Links ]

Kuenzel, S., & Vaux Halliday, S. (2008). Investigating antecedents and consequences of brand. Journal of Product & Brand Management, 17(5), 293-304. https://doi.org/10.1108/10610420810896059        [ Links ]

Leahy, R. (2011). Relationships in fast moving consumer goods markets: The consumers' perspective. European Journal of Marketing, 45(4), 651-672. https://doi.org/10.1108/03090561111111370        [ Links ]

Leal, G.P.A., Hor-Meyll, L.F., & De Paula Pessôa, L.A.G. (2014). Influence of virtual communities in purchasing decisions: The participants' perspective. Journal of Business Research, 67(5), 882-890. https://doi.org/10.1016/j.jbusres.2013.07.007        [ Links ]

Lee, J.E., & Watkins, B. (2016). YouTube vloggers' influence on consumer luxury brand perceptions and intentions. Journal of Business Research, 69(12), 5753-5760. https://doi.org/10.1016/j.jbusres.2016.04.171        [ Links ]

Ling, X., Shahzad, M.F., Abrar, Z.U., & Khattak, J.K. (2021). Determinants of the intention to purchase branded meat: Mediation of brand trust. SAGE Open, 11(3), 21582440211032669. https://doi.org/10.1177/21582440211032669        [ Links ]

Lou, C., & Kim, H.K. (2019). Fancying the new rich and famous? Explicating the roles of influencer content, credibility, and parental mediation in adolescents' parasocial relationship, materialism, and purchase intentions. Frontiers in Psychology, 10, 2567. https://doi.org/10.3389/fpsyg.2019.02567        [ Links ]

Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58-73. https://doi.org/10.1080/15252019.2018.1533501        [ Links ]

Manthiou, A., Ayadi, K., Lee, S., Chiang, L., & Tang, L. (2017). Exploring the roles of self-concept and future memory at consumer events: The application of an extended Mehrabian-Russell model. Journal of Travel and Tourism Marketing, 34(4), 531-543. https://doi.org/10.1080/10548408.2016.1208786        [ Links ]

Mayer, R.C., Davis, J., & Schoorman, D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734. https://doi.org/10.2307/258792        [ Links ]

McCracken, G. (1989). Who is the celebrity endorser? Cultural foundations of the endorsement process. Journal of Consumer Research, 16(3), 310-321. https://doi.org/10.1086/209217        [ Links ]

Mehrabian, A., & Russell, J.A. (1974). A verbal measure of information rate for studies in environmental psychology. Environment and Behavior, 16(2), 233. https://doi.org/10.1177/001391657400600205        [ Links ]

Meyers-Levy, J. (1989). The influence of a brand name's association set size and word frequency on brand memory. Journal of Consumer Research, 16(2), 197-207. https://doi.org/10.1086/209208        [ Links ]

Mohsin, M. (2020). 10 Instagram stats every marketer should know in 2020. Oberlo. Retrieved from https://www.oberlo.com/blog/instagram-stats-every-marketer-should-know

Montandon, A.C., Ogonowski, A., & Botha, E. (2017). Product involvement and the relative importance of health endorsements. Journal of Food Products Marketing, 23(6), 649-667. https://doi.org/10.1080/10454446.2015.1048031        [ Links ]

Moorman, R.H., & Blakely, G.L. (1995). Individualism-collectivism as an individual difference predictor of organizational citizenship behavior. Journal of Organizational Behavior, 16(2), 127-142. https://doi.org/10.1002/job.4030160204        [ Links ]

Morgan-Thomas, A., & Veloutsou, C. (2013). Beyond technology acceptance: Brand relationships and online brand experience. Journal of Business Research, 66(1), 21-27. https://doi.org/10.1016/j.jbusres.2011.07.019        [ Links ]

Moschis, G.P., & Churchill Jr, G.A. (1978). Consumer socialization: A theoretical and empirical analysis. Journal of Marketing Research, 15(4), 599-609. https://doi.org/10.1177/002224377801500409        [ Links ]

Munnukka, J., Maity, D., Reinikainen, H., & Luoma-aho, V. (2019). Thanks for watching. The effectiveness of YouTube vlog endorsements. Computers in Human Behavior, 93, 226-234. https://doi.org/10.1016/j.chb.2018.12.014        [ Links ]

Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers' perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39-52. https://doi.org/10.1080/00913367.1990.10673191        [ Links ]

Phua, J., Lin, J.S.E., & Lim, D.J. (2018). Understanding consumer engagement with celebrity-endorsed E-cigarette advertising on Instagram. Computers in Human Behavior, 84, 93-102.         [ Links ]

Reichheld, F.F., Markey Jr. R.G., & Hopton, C. (2000). E-customer loyalty applying the traditional rules of business of online success. European Business Journal, 12(4), 173-179.         [ Links ]

Rempel, J.K., Holmes, J.G., & Zanna, M.P. (1985). Trust in close relations. Journal of Personality and Social Psychology, 49(1), 95-112. https://doi.org/10.1037/0022-3514.49.1.95        [ Links ]

Riedl, R., Hubert, M., & Kenning, P. (2010). Are there neural gender differences in online trust? An fMRI study on the perceived trustworthiness of eBay offers. MIS Quarterly, 34(2), 397-428. https://doi.org/10.2307/20721434        [ Links ]

Rossiter, J.R., & Percy, L. (1991). Emotions and motivations in advertising. Advances in Consumer Research, 18(1), 100-110.         [ Links ]

Rubin, A.M., & Perse, E.M. (1987). Audience activity and television news gratifications. Journal of Communication Research, 14(1), 58-84. https://doi.org/10.1177/009365087014001004        [ Links ]

Saima & Khan, M.A. (2020). Effect of social media influencer marketing on consumers' purchase intention and the mediating role of credibility. Journal of Promotion Management, 27(4), 503-523. https://doi.org/10.1080/10496491.2020.1851847        [ Links ]

Shen, H., Zhao, C., Fan, D.X., & Buhalis, D. (2022). The effect of hotel livestreaming on viewers' purchase intention: Exploring the role of parasocial interaction and emotional engagement. International Journal of Hospitality Management, 107, 103348. https://doi.org/10.1016/j.ijhm.2022.103348        [ Links ]

Schiappa, E., Allen, M., & Gregg, P.B. (2007). Parasocial relationships and television: A meta-analysis of the effects. R.W. Preiss (Ed.), Mass media effects research: Advances through meta-analysis (pp. 301-314). Routledge.

Schouten, A.P., Janssen, L., & Verspaget, M. (2020). Celebrity vs. Influencer endorsements in advertising: The role of identification, credibility, and product-endorser fit. International Journal of Advertising, 39(2), 258-281. https://doi.org/10.1080/02650487.2019.1634898        [ Links ]

Scott, J., & Craig-Lees, M. (2010). Audience engagement and its effects on product placement recognition. Journal of Promotion Management, 16(1-2), 39-58. https://doi.org/10.1080/10496490903571803        [ Links ]

Simon, F., & Tossan, V. (2018). Does brand-consumer social sharing matter? A relational framework of customer engagement to brand-hosted social media. Journal of Business Research, 85, 175-184. https://doi.org/10.1016/j.jbusres.2017.12.050        [ Links ]

Sokolova, K., & Kefi, H. (2020). Instagram and YouTube bloggers promote it; why should I buy? How credibility and parasocial interaction influence purchase intentions. Journal of Retailing and Consumer Services, 53, 101742. https://doi.org/10.1016/j.jretconser.2019.01.011        [ Links ]

Song, S.Y., Cho, E., & Kim, Y.K. (2017). Personality factors and flow affecting opinion leadership in social media. Personality and Individual Differences, 114, 16-23. https://doi.org/10.1016/j.paid.2017.03.058        [ Links ]

Stern, B.B., & Gould, S.J. (1988). The consumer as financial opinion leader. Journal of Retail Banking, 10(2), 43-52.         [ Links ]

Stewart, K.L. (2003). Trust transfer on the world wide web. Organization Science, 14(1), 1-106. https://doi.org/10.1287/orsc.14.1.5.12810        [ Links ]

Stokburger-Sauer, N., Ratneshwar, S., & Sen, S. (2012). Drivers of consumer-brand identification. International Journal of Research in Marketing, 29(4), 406-418. https://doi.org/10.1016/j.ijresmar.2012.06.001        [ Links ]

Tassiello, V., Tillotson, J.S., & Rome, A.S. (2021). Alexa, order me a pizza!': The mediating role of psychological power in the consumer-voice assistant interaction. Psychology & Marketing, 38(7), 1069-1080. https://doi.org/10.1002/mar.21488        [ Links ]

Taylor, C.R. (2020). The urgent need for more research on influencer marketing. International Journal of Advertising, 39(7), 889-891. https://doi.org/10.1080/02650487.2020.1822104        [ Links ]

Thakur, R., Angriawan, A., & Summey, J.H. (2016). Technological opinion leadership: The role of personal innovativeness, gadget love, & technological innovativeness. Journal of Business Research, 69(8), 2764-2773. https://doi.org/10.1016/j.jbusres.2015.11.012        [ Links ]

Tsai, W.H.S., & Men, L.R. (2017). Social CEOs: The effects of CEOs' communication styles and parasocial interaction on social networking sites. New Media & Society, 19(11), 1848-1867. https://doi.org/10.1177/1461444816643922        [ Links ]

Turcotte, J., York, C., Irving, J., Scholl, R.M., & Pingree, R.J. (2015). News recommendations from social media opinion leaders: Effects on media trust and information seeking. Journal of Computer-Mediated Communication, 20(5), 520-535. https://doi.org/10.1111/jcc4.12127        [ Links ]

Weeks, B.E., Ardèvol-Abreu, A., & Gil de Zúñiga, H. (2017). Online influence? Social media use, opinion leadership, and political persuasion. International Journal of Public Opinion Research, 29(2), 214-239.         [ Links ]

Weimann, G. (1991). The influentials: Back to the concept of opinion leaders?. The Public Opinion Quarterly, 55(2), 267-279. https://doi.org/10.1086/269257        [ Links ]

Yang, J., Zhang, D., Liu, X., Li, Z., & Liang, Y. (2022). Reflecting the convergence or divergence of Chinese outbound solo travellers based on the stimulus-organism-response model: A gender comparison perspective. Tourism Management Perspectives, 43, 100982. https://doi.org/10.1016/j.tmp.2022.100982        [ Links ]

Yudha, A. (2023). A source effect theory perspective on how opinion leadership, parasocial relationship, and credibility influencers affect purchase intention. Journal of Theoretical and Applied Management, 16(2), 240-253. https://doi.org/10.20473/jmtt.v16i2.48099        [ Links ]

Yuksel, M., & Labrecque, L.I. (2016). 'Digital buddies': Parasocial interactions in social media. Journal of Research in Interactive Marketing, 10(4), 305-320. https://doi.org/10.20473/jmtt.v16i2.48099        [ Links ]

Zehir, C., Şahin, A., Kitapçı, H., & Özşahin, M. (2011). The effects of brand communication and service quality in building brand loyalty through brand trust: The empirical research on global bsrands. Procedia-Social and Behavioral Sciences, 24, 1218-1231. https://doi.org/10.1016/j.sbspro.2011.09.142

Zhang, C.B., Zhang, Z.P., Chang, Y., Li, T.G., & Hou, R.J. (2022). Effect of WeChat interaction on brand evaluation: A moderated mediation model of para-social interaction and affiliative tendency. Journal of Retailing and Consumer Services, 64, 102812. https://doi.org/10.1016/j.jretconser.2021.102812        [ Links ]

Zhang, Y., Fang, Y., Wei, K.K., Ramsey, E., McCole, P., & Chen, H. (2011). Repurchase intention in B2C e-commerce - A relationship quality perspective. Information and Management, 48(6), 192-200. https://doi.org/10.1016/j.im.2011.05.003        [ Links ]

 

 

Correspondence:
Sung-Hoon Ko
baumhoffnung@kyonggi.ac.kr

Received: 19 May 2023
Accepted: 13 Dec. 2023
Published: 21 Feb. 2024