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Article

The Nexus of Influencers and Purchase Intention: Does Consumer Brand Co-Creation Behavior Matter?

by
Jerum William Kilumile
1,2,* and
Li Zuo
1
1
School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
2
Mzumbe University, Morogoro, Tanzania
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 3088-3101; https://doi.org/10.3390/jtaer19040149
Submission received: 28 June 2024 / Revised: 16 August 2024 / Accepted: 23 September 2024 / Published: 6 November 2024
(This article belongs to the Topic Digital Marketing Dynamics: From Browsing to Buying)
Browse Figure
Figure 1
<p>Illustration of the research model. Source(s): The authors’ illustration.</p> ">
Versions Notes

Abstract

:
The advancement of social media has led to the rise of influencers who are powerful in shaping consumer purchasing behavior. While influencer attributes play a role in shaping consumer behavior, little attention has been paid to the interplay of the attributes of social presence, influencer congruence with the endorsed brand, and purchasing intention. Thus, the current study investigates the effect of social presence and influencer congruence on purchase intention through consumer brand co-creation behavior. A survey approach was used to collect data from consumers who actively interact with at least one social media influencer in Tanzania. Using a sample size of 422, PLS-SEM was applied to test the hypotheses. The results showed that social presence and congruence affected consumer brand co-creation behavior, which subsequently affected purchase intention. Unlike influencer congruence, the social presence of the influencer did not directly affect purchase intention. Furthermore, the study holds that stimulating consumer brand co-creation behavior catalyzes the effects of social presence and influencer congruence on purchase intention. Therefore, in designing an influencer marketing campaign, selecting an influencer with social presence and congruence attribute is pivotal for the effectiveness of the influencer marketing strategy. Marketers should be relational rather than transaction-focused when designing and implementing the influencer marketing strategy.

1. Introduction

The advancement of social media has significantly transformed the landscape of marketing, with influencers emerging as a new marketing channel capturing the attention of consumers. Unlike traditional media such as TV, radio, print media, etc., consumers are reported to rely on influencers in making purchase decisions [1]. Consequently, brands partner with influencers to foster brand awareness and engagement and ultimately translate into sales conversions. Investment in influencer marketing has been significantly growing. Statista [2] predicts that its market value will grow to more than 22 billion dollars by 2025. While marketers can benefit from the potential of influencer marketing, more attention should be paid to influencer marketing dynamics and its implications for brand performance. The development of digital technology increases influencer marketing dynamism with many possibilities [3] such as influencer–consumer relationships [4]. Such dynamic influencer–consumer interaction may bring favorable and unfavorable implications to brand performance. Therefore, marketers need to monitor such dynamics to have an informed design of influencer marketing campaigns to yield positive results for the brand, including sales.
With the dynamic nature of influencer marketing, scholars’ interest has been growing in researching into influencers and their effect on consumer behavior [1,4,5,6,7]. Although there has been progress in the literature, most studies have focused on influencer attributes such as expertise, homophily, attractiveness, trustworthiness, popularity, likeability, and uniqueness [4,8]. Influencer attributes such as social presence and influencer–brand congruence have received little recognition in the literature [4,8,9]. Thus, understanding how the social presence and congruence aspects of an influencer impact consumer behavior is important in advancing the theoretical understanding of the dynamics of influencers and consumer behavior.
According to the social presence theory [10], the effectiveness and persuasiveness of online communication are improved by the extent to which the medium makes the audience feel like they are in the same physical space as other people [11,12,13,14]. In the influencer marketing context, social presence is found to improve the trustworthiness of the endorsed brand [15]. Social media supports influencers to consolidate their social presence through live video chatting and automated and customized replies. Such perceived presence increases the trustworthiness and persuasive power of an influencer. Therefore, the current study advances knowledge of the relationship between social presence and purchase intention. By doing so, we help marketers know how to strategically collaborate with influencers and optimize the impact of influencer marketing campaigns on sales conversion.
Furthermore, the similarity between influencers and endorsed brands (congruence) potentially predicts consumer attitude and behavioral intention [4]. A study by Koay et al. [16] reports that congruence indirectly influences purchase decisions. Furthermore, Koay et al. [17] confirm that the alignment of influencers with products strengthens purchase intention. Although the congruence factor can predict purchase intention, its relationship mechanism is not significantly established in the influencer marketing literature [4]. In response to a recent call by Han et al. [4], this study progresses the knowledge of influencer marketing by establishing how influencer–product congruence impacts purchase intention. Filling this gap will not only advance our theoretical acquaintance but support marketers in influencer choice, marketing message framing, and overall influencer marketing campaign planning.
Additionally, to advance the theoretical understanding of the interplay of influencers and consumer behavior, service-dominant logic suggests that consumer co-creation behavior can explain the mechanism effect of social presence and influencer congruence on purchase intention. Accordingly, value is co-created through the exchange of resources among stakeholders, especially customers [18]. Consumers possess different resources and competencies. The value is created when they apply their competencies to enhance the development of the brand [19,20]. Through social media platforms, influencers can stimulate consumer brand co-creation behavior (CBCB) [21]. CBCB is a voluntary and interactive process whereby consumers collaborate with brands to define brand identities, meanings, and experiences [22]. Empirical studies show that brand congruence and influencer homophily affect brand co-creation behavior [22]. Subsequently, some studies call for more studies on drivers of brand co-creation [21,23]. Therefore, in response to these research calls, this study asserts that the effect of social presence and congruence on purchase intention is catalyzed by CBCB. Establishing the mediation effect of CBCB advances knowledge in influencer marketing and brand management on how consumers can participate in creating a brand. It also helps marketers consider relational focus rather than transactional focus in designing tailored influencer marketing campaigns.
In addressing the identified multiple research gaps and enriching the understanding of the dynamics of influencer marketing, this study blends social presence theory and self-congruence theory to establish the effect of the perceived social presence of an influencer and influencer–product congruence on CBCB and purchase intention. The study enhances the theoretical advancement by aligning the social presence of an influencer and congruence to explain CBCB and purchase intention. Consequently, it progresses the antecedents of CBCB and the catalyst role of CBCB in influencer marketing. Furthermore, this study offers practical implications on how marketers can strategically collaborate with influencers and set up a tailored influencer marketing campaign to consolidate emotional brand–consumer connections for improved brand value and sales.

2. Literature Review and Hypothesis

2.1. Social Presence Theory

The theory explains how people communicate and form relationships through electronically mediated channels such as telephone and computer-mediated communication [10]. It suggests that the effectiveness of electronic communication depends on the extent to which the communication creates a sense of social presence or the perception of being in the same physical space as other people. Jiang et al. [11] add that the social presence of an electronic medium such as a website articulates the persuasiveness capacity of the communication medium. This means that the persuasiveness of any communication medium is also determined by the social presence portrayed by the channel. Therefore, it is essential to examine the perceived social presence of influencers and its effect on CBCB and purchase intention.
The theory has been applied and shown a significant impact on consumer behavior a variety of contexts, including social commerce [13,24,25]. In influencer marketing, the context and social presence can be consolidated by influencers’ actions such as real-time responses to comments, messages, and live streaming. The social presence cultivated through consumer–influencer interactions and consumer–consumer interaction on the influences’ page may result in consumer brand co-creation behavior and purchase intention. Regardless of its potential to explain brand co-creation and purchase intention, the theory is less utilized in the influencer marketing context [8]. Therefore, this study employs social presence theory to explain consumer brand co-creation and purchase intention.

2.2. Self-Congruence Theory

The theory explains the psychological process and results whereby consumers relate their perception of brand image with their actual self-concept [26]. Accordingly, consumers tend to consider purchasing a product that defines their identity. The theory has been extended in the influencer marketing context to predict purchase intention [3]. Influencers with higher connections with followers increase the chance of inducing purchases [16]. Additionally, the self-congruence theory has been applied to examine the effect of influencer–consumer congruence, influencer–product congruence, and consumer–product congruence on consumer purchasing behavior [16,17,27]. The findings show that both influencer–consumer congruence and influencer–product congruence positively moderate purchase intention [17]. Similarly, influencer–consumer congruence strengthens the effect of influencer experience on purchase intention [28]. Therefore, in this study, we blend social presence and self-congruence theory to explain CBCB and purchase intention. In this study, social presence and influencer congruency are regarded as influencer attributes affecting BC and purchase intention.

2.3. The Social Presence of an Influencer and Consumers’ Brand Co-Creation Behavior

The social presence of an influencer has the potential to drive consumer behavior. The literature indicates a positive relationship between social presence and the perceived trustworthiness of the merchant [11], and consequently develops customer loyalty to the brand [24]. Furthermore, social presence on virtual rooms have a greater impact on influencers’ trustworthiness than live streaming on Instagram [29]. It can be argued that influencers’ trustworthiness is enhanced by the social presence developed by virtual rooms with immersive features. Tsai et al. [30] report that brand chatbots’ social presence communication stimulates consumer engagement. Similarly, Algharabat et al. [31] report that the social presence on Facebook significantly influences consumer engagement with the brand. Therefore, our study argues that social presence can simulate a positive discussion and consumer interaction with the brand on social media platforms. During interactions and discussions on social media, consumers share the brand message, provide feedback, and advocate for the brand, resulting in more value for the brand. Therefore, we propose the following hypothesis:
H1: 
The social presence of an influencer positively affects consumers’ brand co-creation behavior.

2.4. Social Presence of an Influencer and Purchase Intention

Social presence helps consumers build closer relationships with e-commerce sellers and a better understanding of the products they need in an e-commerce context [12,32]. According to Huang et al. [33], social presence influences purchase intention in live video commerce. Equally, Jin et al. [15] report that the relationship between the perceived para-social interaction of an influencer and trust towards the endorsed brand is stronger when the influencer shares a post of an endorsed product with a person’s picture in it than a product post with no picture of a person in it. In the context of influencer marketing, social presence is consolidated through immediate response to comments and messages and engagement with followers through live streams. Such induced social presence may lead to more positive attitudes towards the influencer and the influencer’s trustworthiness, and, in turn, more favorable purchasing intentions are likely to be developed. Therefore, the following hypothesis is suggested:
H2: 
The social presence of an influencer positively affects purchase intention.

2.5. Influencer–Product Congruence and Consumer Brand Co-Creation Behavior

Congruence has the potential to drive brand value creation. According to Zhang and Bloemer [34], congruence affects consumer loyalty to the brand and e-WoM. Furthermore, Roy Bhattacharjee et al. [35] add that the alignment of consumers with brands drives consumer brand engagement. Correspondingly, the connection of consumer self-image with the brand image can foster brand co-creation among consumers [22]. Furthermore, a study by Islam [36] found that symbolic and functional incongruence causes consumers to hate brands. With this assertion, it can be argued that congruence plays a role in enhancing CBCB. Therefore, the following hypothesis is proposed:
H3: 
Influencer–product congruence positively affects consumers’ brand co-creation behavior.

2.6. Influencer–Product Congruence and Purchase Intention

Influencer–product congruence plays a role in strengthening purchase intention [16,17,37]. Correspondingly, it strengthens the relationship between influencer experience, influencer content usefulness, and purchase intention [28]. Some scholars call for more studies on the influence of influencer congruence on purchase intention in an influencer marketing context [4,27,37]. Therefore, this study suggests that influencer–product congruence stimulates consumers’ intention to buy a recommended product. Hence, the following hypothesis is proposed:
H4: 
Influencer–product congruence positively affects purchase intention.

2.7. Consumer Brand Co-Creation Behavior and Purchase Intention

Brand co-creation behavior is a customer-led interaction between the brands and the customer which results in providing more value to the brand and the customers [22,38]. Literature indicates that value co-creation significantly affects attitudinal loyalty, which subsequently affects behavioral loyalty [39]. With the built loyalty to the brand, a consumer becomes an advocate for the brand [40], thereby co-creates more value for the brand. Additionally, co-creation behavior may lead to customer satisfaction and intention to purchase [41]. Recent literature shows that consumers’ participation in value co-creation influences purchase intention [41]. However, the literature still calls for further studies, particularly in the context of developing countries [21,41]. Therefore, the following hypothesis is proposed:
H5: 
Consumers’ brand co-creation behavior positively affects purchase intention.

2.8. Mediation Effect of Consumer Brand Co-Creation Behavior

Influencer marketing significantly shapes consumer behavior such as brand engagement and buying behavior [3]. Empirical evidence shows that the congruence between influencers and products drives consumer brand co-creation behaviour [22]. Additionally, the similarity between influencers and consumers affects value co-creation behavior [41]. Furthermore, in social media, consumers may experience social presence through influencer–consumer and consumer–consumer interactions. Such interactions stimulate value creation [21]. Research shows that value co-creation affects brand attitude and behavioral loyalty [39], and hence increases the likelihood of purchasing a product. However, its relationship is under-examined, and accordingly, scholars call for further studies [41]. In this study, we hold that brand value co-creation catalyzes the effect of influencer congruence and the social presence of an influencer on purchase intention. Figure 1 illustrates the research model. Hence, the following hypotheses are suggested:
H6a: 
Consumer brand co-creation behavior mediates the effect of the social presence of an influencer on purchase intention.
H6b: 
Consumer brand co-creation behavior mediates the effect of influencer–product congruence on purchase intention.

3. Materials and Methods

3.1. Sample and Procedures

The study employed a cross-sectional survey design to study the influence of influencer social presence and influencer congruence on purchase intention through CBCB. Purposive sampling with a snowballing technique was applied, whereby a Google form was circulated on social media platforms. Participants involved Tanzanian consumers who actively interact with social media influencers. Like other countries Tanzania is experiencing growth in its digital landscape, featuring increased social media usage such as Instagram, Facebook, TikTok, X, YouTube, and Snapchat [42]. Also, consumers progressively depend on influencers to make purchase decisions [43].
As recommended by Cheung et al. [44], only consumers who follow at least one Tanzanian influencer were involved in this study. Furthermore, the respondents were asked to mention the name of the Tanzanian social media influencer they follow. Additionally, the respondents were instructed to answer questions by referring to the mentioned influencer. This approach is commonly employed in influencer marketing studies such as Koay et al. [17] and Wang et al. [45]. Those respondents who did not interact with influencers every month were not allowed to proceed to the next questions.
A total of 510 respondents were involved in the study; however, 21 respondents never interacted with influencers’ content every month. Thus, they were not allowed to answer the next questions. Furthermore, during the data-cleaning process, a total of 67 respondents were removed due to misbehaving in providing answers. Finally, 422 respondents were considered for the analysis. Since the study used 19 measurement items to represent the constructs and each item should have at least 10 cases, the sample of 422 respondents was enough for conducting structural equation modelling analysis [46]. A full description of respondents in terms of age, gender, education, and frequency of interaction with influencers on social media platforms is reported in Table 1.

3.2. Measurement Items

With a survey approach, the study used a closed-ended questionnaire to collect data to establish the effect of an influencer’s perceived social presence and influencer congruence on CBCB and purchase intention. The questionnaire was developed based on the measurement items that have been validated and employed in previous empirical studies. The items for influencer–product congruence were adapted from Venciute et al. [28] and Koay et al. [17]. Similarly, items for CBCB were adapted from France et al. [22]. Items of social presence were adapted from Ming et al. [13] and Sun et al. [47], and purchase intention items were adapted from Farivar et al. [48] and Taylor et al. [49].
The adapted items were used to develop a questionnaire, whereby a five-point Likert scale was used. The respondents were required to indicate their level of agreement from 1: strongly disagree to 5: strongly agree. Furthermore, a pilot study was conducted on 150 respondents who actively followed at least one Tanzanian influencer. Lastly, a questionnaire reliability test was conducted, and the obtained value of Cronbach’s α coefficient was above 0.70. Hence, the questionnaire was reliable and deserved to be used for large-scale data collection.

4. Results

4.1. Measurement Model Assessment

Before testing the hypothesis, the validity and reliability of the measurement model was established [50]. Indicator reliability was first assessed using item loadings [46]. All item loadings were above 0.70 (see Table 2). Hence, it was confirmed that all constructs explained the items by more than 50%. Composite reliability (Rho_a) was obtained, and its values were above 0.700 (see Table 2). Hence, the acceptable threshold was met. Furthermore, the average variance extracted (AVE) values were also obtained. The values were above the acceptable threshold of 0.50 (see Table 2). Hence, convergent validity was well established. Lastly, the HTMT and Fornell–Larcker criterion values were also obtained to test the discriminant or divergent validity [51]. All HTMT values were below 0.85 (see Table 3). Similarly, the constructs’ correlations were beyond the squared value of AVE (see Table 4). Hence, it confirmed that all constructs were distinct [52].

4.2. Structural Model Assessment

After assessing the measurement model, the structural model was assessed. The model’s explanatory power was assessed using R2. The R2 values were 0.415 and 0.352 for CBCB and purchase intention, respectively. Hence, both endogenous variables were moderately explained by the exogenous variables [46]. Lastly, Q2 was obtained to establish the model’s predictive power. The Q2 values for CBCB and purchase intention were 0.406 and 0.276, respectively (see Table 5). This implies that the model had strong prediction relevance [53].

4.3. Hypothesis Testing

A bootstrapping step of about 10,000 re-samples was employed to establish the significance of path coefficients. The results showed that except for hypothesis 2, other hypotheses were accepted. Specifically, the results showed that the social presence of influencers had a significant positive effect on CBCB (β = 0.297, t = 5.709, p = 0.000). As pointed out earlier, social presence did not affect purchase intention (β = 0.078, t = 1.352, p = 0.088), rather it went through CBCB. Influencer congruence had a positive and significant effect on CBCB (β = 0.418, t = 7.744, p = 0.000). Similarly, influencer congruence significantly affected purchase intention (β = 0.253, t = 4.363, p = 0.000). Furthermore, CBCB positively affected purchase intention (β = 0.399, t = 6.802, p = 0.000). Regarding the mediation effect of CBCB, the results showed that there was a total mediation effect on CBCB in the influence of social presence on purchase intention (β = 0.167, t = 4.740, p = 0.000). Lastly, CBCB partially mediated the effect of influencer congruence on purchase intention (β = 0.118, t = 4.321, p = 0.000).

5. Discussion

The current study explains the drivers of brand co-creation and purchase intention in the context of influencer marketing using social presence and self-congruence theoretical lenses. The congruence of influencers with endorsed brands affected CBCB. The findings are coherent with those of a study by Bu et al. [41], which reports that the similarity between influencers and followers stimulates consumer value-creation behavior. Furthermore, our study underscores the synergetic effect of brands, consumers, and influencers in driving CBCB. Brands may foster CBCB by collaborating with influencers who are congruent with both products and consumers. Such influencer congruence enhances the value of alignment, identity, and attitude, which results in CBCB.
The current study also amplifies the relationship between consumers’ buying decisions, influencer congruence, and the social presence of influencers. This study holds that the perceived influencer congruence with endorsed products affects purchase intention. This is in line with the theory of self-congruence, which portrays that consumers prefer purchasing products that align with their image [26,54]. Furthermore, the study extends the established debate in the literature which holds that influencer–product congruence consolidates the effect of parasocial relationships [17] and influencer experience on purchase intention [28]. It is evident that when influencers correspond with both endorsed products, it cultivates more association value and a favorable attitude toward the product and influencer, hence adding the endorsed products into consumers’ baskets.
Furthermore, the study offers a new understanding of the relationship between the social presence of influencers and purchase intention in an influencer marketing context. Unlike influencer congruence, the social presence cultivated by an influencer on social media does not directly affect purchase intention, rather it goes through CBCB. Previous scholars hold that the social presence factor influences purchase intention in social commerce platforms [12,32]. The study extends the established debate on social presence by asserting that in the influencer marketing context, social presence does not directly affect purchase intention for several reasons: First, this could be due to the newness of influencer marketing in developing countries such as Tanzania [55], where consumers are used to traditional marketing channels rather than influencer marketing. Therefore, the influence of social presence might be reduced by the perceived credibility of influencers as a new marketing channel. Hence, it may not have a direct effect on purchase intention. Second, consumers are reported to pay much attention to the usefulness of the influencer’s content [1,28], credibility [8,56,57], and congruence [15,16]. Therefore, if an influencer consolidates trustworthiness and authenticity, social presence may have no substantial impact on purchase intention. This study emphasizes consolidating relatability and credibility elements when interacting with consumers in live video sessions, immediate replies, and close chatting on social media community groups. Along with this, it unveils avenues for further studies to delve into the mechanism conditions under which social presence may trigger purchase intention in an influencer marketing context.
Extending the literature further, our study holds that CBCB could be stimulated by the social presence of an influencer. This corresponds to previous studies that found that social presence affects brand loyalty [24] and brand engagement on social media [8,58]. The study amplifies the power of social presence theory [26,54] in stimulating CBCB by underscoring the importance of collaborating with influencers who consolidate their social presence. Therefore, influencers who resonate with the endorsed product and target market, and cultivate social presence, create a conducive environment for consumers to participate in brand value co-creation.
The study also extends the literature on brand management in digital environments by underscoring the interplay of CBCB and consumer buying intention. The study holds that CBCB drives purchase intention. This is in line with a Bu et al. [59] study which reports that value co-creation behavior affects consumer purchasing intention. Furthermore, the current study extends the established understanding that consumers who actively advocate for a brand [22] add more value to the brand [60], which results in customer satisfaction and intention to buy [41]. The study emphasizes the benefits of empowering consumers and being a relation-centric brand rather than a transaction-focused brand. In this study, consumers demonstrate that creating a better environment that fosters CBCB makes them feel brand ownership, subsequently developing an interest in buying a recommended product.
To extend the literature on influencer marketing and brand management, this study holds that a synergetic effect of brands, influencers, and consumers results in CBCB, which in turn catalyzes the effect of social presence and congruence on consumer purchasing decisions. Our findings correspond to those of previous studies, such as Bu et al. [41], which report that value co-creation behavior mediates the effect of influencer homophily on purchase intention. The current study signifies the benefit of being relational rather than transactional. Brands can enhance a relation-centric approach by establishing strategic collaboration with influencers to stimulate sales. Furthermore, in extending the congruence and social presence theories, the study contends that influencer congruence when aligned with social presence encourages consumers to engage in advocacy, helping, and providing suggestions for brand improvement, and such value co-creation behavior results in buying intentions.

6. Implications

6.1. Theoretical Implications

The study offers significant theoretical contributions to influencer marketing dynamics by integrating social presence theory and self-congruence theory to explain CBCB and purchase intention. Less attention has been paid to social presence theory in influencer marketing literature [3,8]. Therefore, cross-fertilizing the two theories carries nuanced contributions to influencer marketing and brand management literature. The study proposes that social presence and congruence of influencers affect purchase intention through CBCB.
This study extends the debate on the role of consumers in value co-creation [60,61] and brand value co-creation [19,22]. While consumers are potential partners in developing value for the brand [19,22], their participation could be amplified by a strategic synergy between brands, influencers, and consumers. The study holds that brands partnering with influencers who cultivate their social presence and congruence with the endorsed product stimulate the target consumers to participate in brand co-creation. Furthermore, in response to the previous research call on CBCB studies by Bu et al. [41] and Ju et al. [21], this study reports that consumers are likely to buy a product when they participate in co-creating the brand.
The study provides empirical support to the literature on the effects of influencer marketing on purchase intention. While the literature is fragmented with contradictory findings on the effects of influencer marketing on purchase intention and skewed on influencer characteristics such as expertise, trustworthiness, homophily, and attractiveness [3,8], the current study establishes that consumers’ intention to buy is also triggered by influencers who are congruent with the endorsed product. Lastly, the study offers more contributions to the dynamics of influencer marketing by explaining its mechanism effects on purchase intention. The existing empirical studies show that social presence and congruence affect purchase intention. However, its mechanism effect is unfolded. Therefore, in response to the recent call for further research on CBCB [21], this study employs CBCB to explain its mechanism effect. The study holds that consumer participation in development, helping, and advocacy catalyzes the effect of social presence and congruence on purchase intention. This offers a new interesting progression of applicability of social presence and self-congruence theory in the influencer marketing context.

6.2. Practical Implications

The study offers several practical implications. First, when selecting influencers, marketers should pay attention to the social presence and similarity of influencers with products. The study shows that influencers who resonate with the endorsed product drive CBCB and the likelihood of consumers’ buying intention.
Second, the effect of social presence on CBCB and congruence on purchase intention provides signs for marketers to revisit their performance metrics of influencers. Co-creation, social presence, and congruence are suggested new metrics to measure the performance of an influencer. Using machine learning and natural language processing technology, marketers can track consumer conversations about the brand as they engage with influencers and fellow consumers in digital spaces.
The mediation effect of CBCB on purchase intention alerts marketers to emphasize inclusive marketing rather than exclusive and transactional marketing. Marketers should closely collaborate with consumers by capitalizing on the social capital of influencers to drive brand interaction in the digital space. Doing so enhances more chances for brand creation in digital spaces.
Considering that consumers pay attention to social presence when participating in brand value co-creation, brands and influencers may collaboratively cultivate social presence. For example, utilizing dueting features offered by social media such as Instagram and TikTok to invite consumers who actively engage with brands to have a live conversation with the influencers. This may create an emotional brand connection and attract more consumers to participate in value co-creation.

7. Limitations and Future Research Directions

Although the study profoundly contributes to the literature on influencer marketing, brand management, and consumer behavior, it has some limitations that deserve attention for progressing academic debate. First, the study was conducted using a Tanzanian sample only, and consumer reaction to marketing campaigns varies from one cultural setup to another [61]. Future studies may extend the model to compare Western European, American, and African consumer behavior. Second, the age of consumers plays a role in shaping purchasing behavior [61]; however, the study did not account for the age factor. Therefore, future studies may consider comparing Generation Z and millennials to examine the effect of influencer marketing on purchase intention. Third, our study employed a survey approach, thus, the current study cannot establish the causal effects of social presence and influencer congruence on CBCB and purchase intention. Therefore, future studies may consider testing the proposed model using an experimental design. This will give more insight into how CBCB and purchase intention vary across social presence and congruence situations. Lastly, the established effect of social presence and congruence on CBCB may be further advanced. Considering that consumer participation in brand creation depends on resources in possession [19,20,62], future studies may consider examining the moderation effect of digital literacy or the internet on the impact of social presence and congruence on CBCB. Despite these limitations, our study offers useful insights into the dynamics of influencer marketing and its implication on brand management and purchase intention by emphasizing the pivotal role of social presence and congruence.

Author Contributions

Conceptualization, J.W.K. and L.Z.; methodology, J.W.K. and L.Z.; software, J.W.K.; formal analysis, J.W.K.; investigation, J.W.K. and L.Z.; resources, L.Z.; data curation, J.W.K.; writing—original draft preparation, J.W.K.; writing—review and editing, J.W.K. and L.Z.; visualization, J.W.K.; supervision, L.Z.; project administration, L.Z.; funding acquisition, L.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was supported by Humanities and Social Science Fund of Ministry of Education of China, Grant/Award Number: 21YJA630131.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. The respondents were informed through the survey.

Data Availability Statement

The data used to support the findings of this study are available from the first author upon request.

Acknowledgments

The authors give thanks to Angel Mwoleka, Johakim Katekele, Baraka Mtebe, Sadick Mchia, Samuel Mrisha, Julia Johaness, Krantz Mwantepele, Gillsant Mlaseko, Michael Mwampashe, and Wandera Joseph for their unconditional support.

Conflicts of Interest

The authors declare no conflicts of interest.

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Jtaer 19 00149 g001
Figure 1. Illustration of the research model. Source(s): The authors’ illustration.
Figure 1. Illustration of the research model. Source(s): The authors’ illustration.
Jtaer 19 00149 g001
Table 1. Demographic data of the respondents.
Table 1. Demographic data of the respondents.
VariableCategoryFrequencyPercentage
GenderMale20548.58%
Female21751.42%
Age18–2424157.11%
25–3412629.86%
35–44368.53%
45–54153.55%
Above 5440.95%
Education levelBasic163.79%
Ordinary secondary5312.56%
Advanced secondary255.92%
Diploma9121.56%
Bachelor’s degree20348.10%
Master’s degree307.11%
PhD40.95%
Frequency of interaction with influencer’s contentDaily24357.58%
Weekly12629.86%
Monthly5312.56%
Social media platformSocial media
Instagram23154.74%
Facebook7918.72%
TikTok8018.96%
X (formerly Twitter)153.55%
YouTube122.84%
Snapchat51.18%
Table 2. Validity and reliability of constructs.
Table 2. Validity and reliability of constructs.
Construct ItemsLoadingsVIF
Social Presence of an Influencer (SPI) (Items adapted from Ming et al. [13] and Sun et al. [47])
(Cronbach Alpha = 0.727, CR (rho_a) = 0.735 and AVE = 0.547)
SPI1: I can understand my favorite influencer’s attitude better by interacting with his or her content;0.7121.467
SPI2: I sometimes feel that the influencer is posting content targeting me; 0.7001.549
SPI3: I could vividly imagine him or her as I interact with content on social media;0.7871.539
SPI4: There is a sense of human touch when communicating with my favorite influencer streamers via live video sessions;0.7561.425
Influencer–Product Congruence (IPC) (Items adapted from Venciute et al. [28] and Koay et al. [17])
(Cronbach Alpha = 0.879, CR (rho_a) = 0.881 and AVE = 0.735)
IPC1: My favorite influencer’s personality fits well with the product he/she recommends;0.8252.042
IPC2: I feel that my favorite influencer likes the product he/she recommends;0.8772.579
IPC3: My favorite influencer’s image resembles a product she/he recommends;0.8902.655
IPC4: My favorite influencer’s lifestyle matches the product he/she recommends.0.8362.103
Consumer Brand Co-Creation Behavior (CBCB) (Items adapted from France et al. [22])
(Cronbach Alpha = 0.813, CR (rho_a) = 0.915 and AVE = 0.623)
CBCB1: I recommend this influencer and his/her recommendations to others;0.7572.500
CBCB2: I encourage my friends to participate in contests related to the recommended product; 0.7672.887
CBCB3: I share/repost his content shared about a product he/she recommends;0.8102.819
CBCB4: I encourage my friend to consider buying a product recommended by my favorite influencer;0.8062.378
CBCB5: I sometimes explain to my friends/followers the benefits of a recommended product;0.7642.670
CBCB6: I help other followers if they have difficulties with the recommended product;0.8023.199
CBCB7: I help other followers/friends buy a product;0.8022.519
CBCB8: I tell others about new things and the recommendations made by the influencer.0.8022.530
Purchase Intention (PI) (Items adapted from Farivar et al. [48] and Taylor et al. [49])
(Cronbach Alpha = 0.883, CR (rho_a) = 0.888 and AVE = 0.811)
PI1: I then plan to buy the product that my favorite influencer recommends;0.8882.540
PI2: I am interested in buying the product that my favorite influencer recommends;0.9403.568
PI3: I will likely buy the product that my favorite influencer recommends.0.8712.299
Table 3. HTMT values.
Table 3. HTMT values.
CBCBIPCPISP
CBCB
IPC0.662
PI0.6570.610
SPI0.6570.7500.555
Table 4. Fornell–Larcker criterion values.
Table 4. Fornell–Larcker criterion values.
CBCBIPCPISP
CBCB0.789
IPC0.5970.857
PI0.5930.5390.900
SP0.5490.6020.4500.740
Table 5. Established direct and indirect relationships.
Table 5. Established direct and indirect relationships.
RelationshipsβTp ValuesDecision
H1: SPI -> CBCB0.2975.7090.000Accepted
H2: SPI -> PI0.0781.3520.088Rejected
H3: IPC -> CBCB0.4187.7440.000Accepted
H4: IPC -> PI0.2534.3630.000Accepted
H5: CBCB -> PI0.3996.8020.000Accepted
H6a: SP -> CBCB -> PI0.1674.7400.000Accepted
H6b: IPC -> CBCB -> PI0.1184.3210.000Accepted
Note: Relationships are significant at p < 0.05, β = Beta Coefficient, T = t—Statistics, p = Probability (p) value. Q2: CBCB (0.406); PI (0.276) R2: CBCB (0.415); PI (0.352).
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Kilumile, J.W.; Zuo, L. The Nexus of Influencers and Purchase Intention: Does Consumer Brand Co-Creation Behavior Matter? J. Theor. Appl. Electron. Commer. Res. 2024, 19, 3088-3101. https://doi.org/10.3390/jtaer19040149

AMA Style

Kilumile JW, Zuo L. The Nexus of Influencers and Purchase Intention: Does Consumer Brand Co-Creation Behavior Matter? Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(4):3088-3101. https://doi.org/10.3390/jtaer19040149

Chicago/Turabian Style

Kilumile, Jerum William, and Li Zuo. 2024. "The Nexus of Influencers and Purchase Intention: Does Consumer Brand Co-Creation Behavior Matter?" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 4: 3088-3101. https://doi.org/10.3390/jtaer19040149

APA Style

Kilumile, J. W., & Zuo, L. (2024). The Nexus of Influencers and Purchase Intention: Does Consumer Brand Co-Creation Behavior Matter? Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 3088-3101. https://doi.org/10.3390/jtaer19040149

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