Abstract

This study examined the association between influencer marketing and consumer behavior towards kombucha drinks in Southwestern Uganda, with particular emphasis on the mediating role of brand awareness. A cross-sectional quantitative research design was employed. Data were collected from 346 kombucha consumers using a structured questionnaire and analyzed using SPSS and Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings revealed that influencer marketing was positively associated with both brand awareness and consumer behavior. Brand awareness was found to partially mediate the association between influencer marketing and consumer behavior, suggesting that consumers exposed to influencer marketing tend to exhibit more favorable consumer behavior through higher levels of brand awareness. The cross-sectional design and the study’s focus on one geographical region limit the generalizability of the findings. Future research should employ longitudinal and cross-cultural designs to provide further evidence regarding these relationships. From a practical perspective, marketers should develop influencer marketing strategies that strengthen brand awareness through consistent messaging, enhanced brand visibility and meaningful consumer engagement, particularly for emerging functional beverages such as kombucha. The study contributes to the literature by demonstrating the mediating role of brand awareness in the association between influencer marketing and consumer behavior within a developing market context, thereby extending understanding of the cognitive mechanisms underlying influencer marketing effectiveness.

Keywords

Influencer Marketing, Brand Awareness, Consumer Behavior, Mediation, Kombucha, Uganda

Share and Cite:

1. Introduction

In the digital era, understanding the process of marketing message has become more complex, especially in emerging markets where technology adoption is rapid and consumption patterns are changing. Functional drinks such as kombucha have gained global recognition in the beverage industry because of their association with health, wellness and natural consumption (Jayabalan & Waisundara, 2019; Kim & Adhikari, 2020). These trends are well documented in developed economies; however, recent evidence suggests similar shifts are occurring in developing countries where consumers are becoming more health-conscious and receptive to alternative beverages (Anis et al., 2022). There is a gradual growth of the kombucha market in Uganda in areas with increasing urbanization and exposure to global consumption patterns. The country’s long tradition of drinking fermented beverages also supports the acceptance of kombucha, making consumers more acquainted with probiotic drinks (Mukisa et al., 2012). However, despite the growing demand, kombucha remains a relatively new product category for many consumers and concerns regarding safety, quality and regulatory compliance still exist (NDA, 2022; UNBS, 2022). In these situations, consumers often turn to outside sources of information to decrease uncertainty and to direct their purchase decision.

Influencer marketing (IM) is one of the most powerful sources of such information and has become a key component of digital marketing strategies. Influencers are socially embedded communicators who shape consumer perceptions through credibility, relatability, and engagement with content (Lou & Yuan, 2019; De Veirman et al., 2017). Empirical research has repeatedly demonstrated that IM can impact consumers’ “attitudes” and behavioral “intentions”, especially in online contexts where peer-like communication is highly valued (Casaló et al., 2020; Sokolova & Kefi, 2020). Recent studies also suggest that IM is of critical importance in shaping brand related outcomes such as BA, engagement, and equity (Dewi & Hidayat, 2024). However, the focus of academic interest has shifted from direct effects towards mechanisms of influence. Marketing communication does not directly lead to behavioral outcomes but often works through intermediary cognitive mechanisms (Keller, 2013; Lou & Yuan, 2019). This viewpoint indicates that the impact of IM on CB is largely indirect and requires a deeper investigation into the mediating variables.

BA has been identified as one of the most fundamental constructs in CB and branding literature among these mechanisms. This is the degree to which consumers can “identify and remember” a brand, which makes it more salient in the decision-making process (Keller, 1993; Aaker, 1996). BA, within the Customer-Based Brand Equity (CBBE) framework, is the foundation of consumer responses, influencing perceptions, attitudes and ultimately behavioral outcomes (Keller, 2013). In markets with limited product knowledge, such as emerging beverage categories, BA is especially important for reducing uncertainty and facilitating decision-making (Hoyer & Brown, 1990). Recent empirical studies provide strong evidence of the mediating role of BA in digital marketing. For example, Dewi and Hidayat (2024) found that IM significantly relates BA, which contributes to overall brand equity and consumer response. Similarly, previous studies have identified BA as a mediating factor between digital marketing strategies and consumer purchase decisions, “stressing its role” as a critical cognitive mechanism in consumer decision-making (Huang & Sarigöllü, 2012; Yoo et al., 2000). Prior research indicates that influencer-related characteristics and opinion leadership can shape consumers’ behavioral intentions, including intentions to interact with, recommend, and follow influencers’ advice (Casaló et al., 2020).

The results indicate that IM may be more effective as a tool for BA than for influencing behavior. This indirect path is especially important in contexts such as Uganda, where consumers may have limited prior knowledge of kombucha and tend to rely on familiar and recognizable brands when making purchasing decisions. Despite these advances, there is a significant gap in the literature on this topic. Most studies on IM have been conducted in developed markets and have mainly focused on the direct relationship between marketing activities and CB. Research exploring the mediating role of BA in developing countries, particularly in emerging product categories such as functional beverages, is limited. This gap is important because CB in such contexts is often influenced by information asymmetry, cultural influence, and different degrees of market maturity. Thus, our research seeks to address this deficiency by examining the BA on IM and CB towards kombucha drinks in Southwestern Uganda. This study adds to the literature by shifting the focus from direct effects to underlying cognitive processes, thereby offering a more sophisticated understanding of how IM associates to CB in emerging markets. The following sections are literature review, methodology, results, discussion, conclusion, implications, limitations, and suggestions for further research.

2. Literature Review

2.1. Theoretical Foundation

This study is primarily anchored on Keller’s (1993) Customer-Based Brand Equity (CBBE) Model, which explains how marketing communication relates to consumer behavior through cognitive mechanisms. According to the CBBE model, brand awareness represents the foundation of brand equity and influences how consumers recognize, evaluate, and respond to brands (Keller, 1993, 2013). The model suggests that consumers are more likely to develop favorable attitudes and behavioral intentions towards brands they can easily recognize and recall. Consequently, brand awareness serves as a key cognitive mechanism through which marketing activities influence consumer behavior. In the present study, influencer marketing is therefore expected to indirectly influence consumer behavior by enhancing consumers’ brand awareness.

While the CBBE model explains the mediating role of brand awareness, the dimensions of influencer marketing are further supported by complementary communication theories. Source Credibility Theory (Hovland & Weiss, 1951) explains that consumers are more likely to be persuaded by communicators perceived as trustworthy and knowledgeable, providing the theoretical basis for the source credibility dimension. Authenticity Theory (Beverland, 2005) suggests that consumers respond more positively to messages from communicators they perceive as genuine and sincere, thereby underpinning the authenticity dimension of influencer marketing. In addition, Parasocial Interaction Theory (Horton & Wohl, 1956) explains how repeated interactions with media personalities create one-sided psychological relationships that strengthen consumers’ trust, engagement, and responsiveness to influencer recommendations. Collectively, these theories explain how influencer characteristics shape consumer perceptions, while the CBBE model explains how these perceptions translate into consumer behavior through the mediating role of brand awareness.

2.2. Influencer Marketing and Consumer Behavior

IM is an important element of digital marketing tactics, particularly in sectors where consumer trust and product knowledge are crucial. Influencers influence consumer perceptions and behavior through their reputation, expertise and social relationships (Lou & Yuan, 2019). Influencer effectiveness is commonly associated with dimensions such as source credibility, authenticity and parasocial interaction. Source credibility reflects the extent to which influencers are perceived as trustworthy and knowledgeable, thereby increasing consumers’ confidence in promoted products. Authenticity echoes to consumers’ perceptions that influencers provide genuine and honest content aligned with their lifestyles and values. Parasocial interaction refers to the emotional closeness and pseudo-social relationships consumers develop with influencers through repeated online engagement (Sokolova & Kefi, 2020). These dimensions enhance consumers’ trust, engagement and responsiveness toward influencer-generated content.

Unlike traditional advertising, IM relies on peer-to-peer communication, which enhances message credibility and consumer engagement (De Veirman et al., 2017). There is consistent empirical evidence that IM has a significant impact on CB. For example, Casaló et al. (2020) found influencer credibility to have a positive effect on purchase intention. Similarly, Sokolova and Kefi (2020) found that emotional attachment and parasocial interaction with influencers increase the likelihood of consumers adopting recommended products. Meanwhile, recent studies show that IM is also a key driver of consumer decisions in digital and emerging markets, where consumers increasingly use social media to acquire product information (Dewi & Hidayat, 2024). In developing contexts such as Uganda, where consumers may have limited product knowledge and heavily rely on external information sources, IM is expected to have a direct influence on CB by providing product information, reducing uncertainty and enhancing perceived credibility.

H1: IM and CB are positively related.

2.3. Influencer Marketing and Brand Awareness

BA is an important outcome of marketing communication. BA refers to the degree of consumer’s ability to recognize and recall a brand (Aaker, 1996; Keller, 1993). IM assists BA through increasing brand visibility, enhancing brand recall and embedding brands within social and cultural narratives. The influencer’s content, through repeated exposure and personalized message, increases BA (Lou & Yuan, 2019). Casaló et al. (2020) found that opinion leadership influences consumers’ behavioral intentions, including intentions to interact with and recommend the influencer and to follow the influencer’s advice. Moreover, recent studies have found that IM significantly improves BA in digital contexts, especially with younger consumers who are highly engaged on social media platforms (De Veirman et al., 2017; Sokolova & Kefi, 2020; Dewi & Hidayat, 2024). “BA is limited in emerging markets and IM is critical for the introduction and positioning of brands in consumers’ minds”. This is particularly true for kombucha products in Uganda because consumers may use influencers as a major source of information about new and unfamiliar products.

H2: IM and BA are positively related.

2.4. Brand Awareness and Consumer Behavior

BA is widely considered a fundamental determinant of CB. Based on the CBBE model, awareness affects consumer decision-making by enhancing brand salience and reducing perceived risk (Keller, 1993, 2013). Consumers prefer to choose a known brand, especially in situations of uncertainty or lack of information (Hoyer & Brown, 1990). Based on the research, increasing consumer familiarity with BA has a significant impact on purchase intention and brand choice (Hoyer & Brown, 1990; Huang & Sarigöllü, 2012) based on the research. Furthermore, Miswanto and Patmawati (2022) found that BA is an important factor in customers’ purchasing decisions regarding digital marketing. In food and beverage markets, where product attributes may be difficult to evaluate, BA is a vital heuristic for consumers. The novelty of the product and the scarcity of reliable information mean that BA is expected to be of particular importance in the context of kombucha consumption in Southwestern Uganda. When it comes to purchasing decisions, especially those related to health, consumers may gravitate toward brands they know and recognize.

H3: BA and CB are positively related.

2.5. Mediating Role of Brand Awareness

IM has a direct effect on CB, but recent literature has indicated that these effects are often mediated by cognitive variables such as BA. Consistent with Keller’s (1993) Customer-Based Brand Equity model, marketing communication relates to consumer behavior through brand-related cognitive processes such as brand awareness, recognition, and recall before shaping behavioral responses. Therefore, BA is a key channel through which IM affects CB. Lou and Yuan (2019) stated that IM improves brand-related perceptions that influence purchase intention (Figure 1).

Source: Adapted from Hayes (2018), PROCESS Model 4.

Figure 1. Conceptual model.

Similarly, Dewi and Hidayat (2024) and Miswanto and Patmawati (2022) found that “BA mediates the relationship between IM” and consumer responses. The use of IM is likely to increase BA for kombucha in Uganda by exposing consumers to product information and increasing the visibility of the brand. This awareness reduces uncertainty and increases the likelihood of product adoption. Hence, the mediating role of BA in the effect of IM on CB is anticipated.

H4: BA mediates the relationship between IM and CB.

3. Methodology

This study employed a cross-sectional quantitative research design to examine the association between IM and CB towards kombucha drinks in Southwestern Uganda, with particular emphasis on the mediating role of BA. A cross-sectional design was considered appropriate because it enabled data to be collected from a large number of respondents at a single point in time, thereby facilitating the examination of the proposed relationships among the study constructs (Hair et al., 2019). The study was conducted in Southwestern Uganda, where kombucha consumption has steadily increased owing to growing consumer interest in functional beverages.

The sample size was determined using Cochran’s (1977) formula for an unknown population, yielding a minimum sample of 384 respondents at a 95% confidence level and a 5% margin of error. Since no comprehensive sampling frame of kombucha consumers existed, a combination of stratified and convenience sampling techniques was employed. The fourteen districts of Southwestern Uganda constituted the sampling strata to ensure adequate geographical representation, and the target sample was proportionately allocated across these districts. Within each district, respondents were conveniently recruited from supermarkets, cafés, restaurants, bars, specialty shops, market environments, and producers’ outlets where kombucha products were available. Data collection was undertaken at multiple locations and different times of the day to improve sample diversity and minimize selection bias.

To participate in the study, respondents had to be 18 years or older, reside in Southwestern Uganda, and have consumed kombucha at least once before the survey. Eligibility was confirmed using a screening question administered by trained research assistants before distributing the questionnaire. Individuals who had never consumed kombucha were excluded from the study.

A total of 384 questionnaires were distributed, of which 346 valid responses were retained for analysis, representing a response rate of 90.1%. Although the final sample was slightly below the target sample, it exceeded the minimum sample size recommended for Partial Least Squares Structural Equation Modelling (PLS-SEM). According to Hair et al. (2019), PLS-SEM is appropriate for studies with moderate sample sizes because it focuses on prediction accuracy and maximizes statistical power. Furthermore, the final sample exceeded the minimum sample size required under the ten-times rule, confirming its adequacy for the subsequent analyses.

Because IM, BA, and CB were measured using self-reported responses collected through a single questionnaire, common method bias (CMB) was assessed using Harman’s single-factor test. All measurement items were entered into an exploratory factor analysis, and the variance explained by the first unrotated factor was examined. Following Fuller et al. (2016), common method bias is considered problematic when a single factor explains more than 50% of the total variance. The first factor accounted for 41.169% of the total variance, indicating that common method bias was not a serious concern in this study.

The measurement scales were adapted from validated instruments reported in previous studies. IM was operationalized as a reflective higher-order construct comprising the lower-order dimensions of source credibility, authenticity, and parasocial interaction, measured using 14 items adapted from Lou and Yuan (2019). BA was modelled as a reflective higher-order construct comprising brand recognition and brand recall, measured using eight items adapted from Aaker (1996) and Keller (1993). CB was also specified as a reflective higher-order construct comprising acquisition, usage, and disposition, measured using 13 items adapted from Hoyer et al. (2018).

The higher-order constructs were estimated in SmartPLS 4 using the disjoint two-stage approach, which is recommended for reflective-reflective hierarchical component models because it produces stable parameter estimates while reducing model complexity (Hair et al., 2019). In the first stage, the lower-order constructs were assessed for indicator reliability, internal consistency reliability, convergent validity, and discriminant validity. In the second stage, the latent variable scores of the validated lower-order constructs were used as indicators of their respective higher-order constructs for estimating the structural model. The structural model was subsequently evaluated using path coefficients, bootstrapped significance tests based on 5000 resamples, coefficients of determination (R²), collinearity diagnostics, and mediation analysis.

4. Results

This section presents the findings of the study. The measurement model was first evaluated to establish the reliability and validity of the constructs before assessing the structural model and testing the proposed hypotheses. Consistent with the recommended PLS-SEM procedure, the measurement model was assessed using indicator loadings, internal consistency reliability, convergent validity, and discriminant validity, after which the structural relationships were examined.

4.1. Measurement Model Assessment

The quality of the measurement model was evaluated by examining indicator reliability, internal consistency reliability, convergent validity, and discriminant validity. Indicator reliability was assessed using factor loadings, while Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) were used to evaluate internal consistency and convergent validity. Discriminant validity was assessed using the Heterotrait-Monotrait (HTMT) ratio. The measurement model was evaluated following the recommendations of Hair et al. (2019).

4.1.1. Indicator Reliability

Table 1 presents the standardized loadings of the measurement items. Hair et al. (2019) recommend retaining indicator loadings of at least 0.708, although indicators with loadings between 0.40 and 0.708 may be retained when their removal does not improve the construct’s reliability or convergent validity. Most items exceeded the recommended threshold, demonstrating satisfactory indicator reliability. One item (SC5) exhibited a loading below the acceptable threshold and was therefore removed from the analysis. The remaining indicators adequately represented their respective lower-order constructs.

Table 1. Indicator loadings.

Source: Primary data.

4.1.2. Internal Consistency Reliability and Convergent Validity

Table 2 presents the reliability and convergent validity results for the lower-order constructs. The Cronbach’s alpha values ranged from 0.787 to 0.877, exceeding the recommended threshold of 0.70 and indicating satisfactory internal consistency reliability. Similarly, the composite reliability values ranged from 0.855 to 0.910, which also surpassed the recommended minimum value of 0.70, confirming that the measurement items consistently measured their respective constructs (Hair et al., 2019). Furthermore, the average variance extracted (AVE) values ranged from 0.546 to 0.676, all above the recommended threshold of 0.50, demonstrating adequate convergent validity. The results indicate that the constructs exhibited satisfactory reliability and convergent validity, thereby confirming the adequacy of the measurement model for subsequent structural model analysis.

Table 2. Reliability and convergent validity results.

Source: Primary data.

4.1.3. Discriminant Validity

Discriminant validity was assessed using the HTMT criterion. According to Hair et al. (2019), HTMT values below 0.85 (or 0.90 in less stringent applications) indicate adequate discriminant validity. As shown in Table 3, all HTMT values were below the recommended threshold, demonstrating that the constructs were empirically distinct. Therefore, the measurement model satisfied the criterion for discriminant validity.

Table 3. HTMT results.

Source: Primary data.

4.2. Descriptive Statistics and Correlation Analysis

Descriptive statistics and correlation analysis were conducted to summarize the study variables and provide preliminary evidence of the proposed relationships. The mean and standard deviation were used to describe respondents’ perceptions of IM, BA, and CB, while Pearson correlation coefficients were used to examine the direction and strength of the associations among the constructs.

Table 4 shows that CB recorded the highest mean score (M = 4.017, SD = 0.824), followed by BA (M = 3.528, SD = 0.906) and IM (M = 3.173, SD = 0.831). The relatively small standard deviations indicate limited variability in respondents’ perceptions, suggesting a reasonable level of agreement among respondents.

The correlation analysis revealed significant positive associations among all study variables. IM was positively associated with BA (r = 0.464, p < 0.01) and CB (r = 0.445, p < 0.01), while BA exhibited the strongest positive association with CB (r = 0.635, p < 0.01). These findings provide preliminary support for the hypothesized relationships and justify proceeding with structural model analysis.

Table 4. Descriptive statistics and correlation results.

**Correlation significant at the 0.01 level (2-tailed). Source: Primary data.

4.3. Structural Model Assessment

Following confirmation of the adequacy of the measurement model, the structural model was evaluated. Prior to hypothesis testing, multicollinearity was assessed using tolerance and variance inflation factor (VIF) values to ensure that collinearity among predictor constructs did not bias the structural model estimates.

Collinearity Assessment

The collinearity statistics presented in Table 5 indicate that multicollinearity was not a concern in the structural model. The tolerance values ranged from 0.779 to 0.785, exceeding the recommended minimum threshold of 0.20, while the corresponding VIF values ranged from 1.274 to 1.284, well below the recommended maximum threshold of 5.0 (Hair et al., 2019). These findings demonstrate that the predictor constructs were sufficiently independent and suitable for structural model estimation.

Table 5. Collinearity statistics.

Source: Primary data.

4.4. Hypothesis Testing

The hypothesized relationships among the study constructs were evaluated using PLS-SEM with a bootstrapping procedure based on 5000 resamples. The significance of the structural paths was assessed using standardized path coefficients (β), t-values, p-values, and bias-corrected bootstrap confidence intervals.

The results presented in Table 6 support all three direct hypotheses. IM was positively associated with CB (β = 0.197, t = 4.346, p < 0.001), indicating that higher levels of IM were associated with more favorable CB. IM was also positively associated with BA (β = 0.468, t = 10.528, p < 0.001), suggesting that IM contributes to stronger BA of kombucha brands. In addition, BA was positively associated with CB (β = 0.556, t = 13.026, p < 0.001). In all cases, the bootstrap confidence intervals excluded zero, confirming the statistical significance of the estimated relationships.

Table 6. Direct effects.

Source: Primary data.

4.5. Mediation Analysis

The mediating role of brand awareness was examined using the bootstrapping procedure in PLS-SEM. Mediation was assessed by evaluating the significance of the indirect effect together with the corresponding bootstrap confidence interval.

Table 7. Mediation results.

Source: Primary data.

Table 7 shows that BA partially mediated the association between IM and CB. The significant indirect effect indicates that IM was positively associated with CB through BA, while the significant direct effect indicates that the association also remained after accounting for the mediating role of BA. The results indicate that BA significantly mediated the association between IM and CB. The indirect effect was positive and statistically significant (β = 0.260, t = 7.496, p < 0.001), with a 95% bootstrap confidence interval ranging from 0.199 to 0.334, which excluded zero. These findings indicate that IM was positively associated with CB both directly and indirectly through BA, thereby supporting the proposed mediation hypothesis.

Figure 2 illustrates the estimated structural model and the standardized path coefficients. The model explained 21.8% of the variance in BA (R² = 0.218) and 43.6% of the variance in CB (R² = 0.436), indicating moderate explanatory power according to the guidelines of Hair et al. (2019). These results suggest that IM explains a meaningful proportion of consumers’ BA, while IM and BA jointly explain a substantial proportion of CB towards kombucha drinks.

Figure 2. Direct and interaction effects path diagram CB, BA, IM.

Table 8. Summary of hypothesis testing.

Source: Primary data.

As summarized in Table 8, all four hypotheses were supported. Specifically, IM was positively associated with CB (H1) and BA (H2), BA was positively associated with CB (H3), and BA significantly mediated the association between IM and CB (H4). Collectively, these findings provide empirical support for the proposed conceptual model.

5. Discussion

These results confirm that IM was positively associated with CB, consistent with previous research that shows that influencers affect consumer attitudes and purchase decisions through credibility, authenticity and engagement (Lou & Yuan, 2019; Casaló et al., 2020). However, rather than a purely direct and persuasive effect as traditional interpretations have suggested, the present study finds that the effect is partially indirect via cognitive mechanisms. This finding aligns with the existing literature that influencer-generated content contributes to brand salience via repeated exposure and contextualized messaging (De Veirman et al., 2017; Lou & Yuan, 2019). This function is especially important in emerging markets such as Uganda, where product knowledge may be low and consumers look to influencers for key information regarding unfamiliar products such as kombucha.

Furthermore, BA has a significant relationship to CB, confirming the central role of BA in consumer decision-making. This is in agreement with the Customer-Based Brand Equity (CBBE) model, which considers BA as a basic component of consumer response which relates to how consumers perceive and evaluate products (Keller, 1993; Keller, 2013). Consumers with BA are more inclined to that brand when making purchase decisions, especially in situations involving perceived uncertainty or risk. For kombucha consumers who are not necessarily experienced or knowledgeable, BA is a heuristic that reduces decision-making complexity.

Importantly, results furnish that BA mediates the relationship between IM and CB, suggesting that IM indirectly impacts CB through its effect on consumers’ brand-related cognition and recognition. Partial mediation implies that IM has a direct persuasive effect on CB, but a large part of its effect is through the increase in BA. This result agrees with the previous literature emphasizing the role of BA as an important cognitive mechanism that links marketing communication with behavioral outcomes (Keller, 1993; Yoo et al., 2000). The results also support the growing literature emphasizing the importance of indirect pathways and mediating mechanisms in explaining marketing effectiveness beyond simple direct relationships (Lou & Yuan, 2019; Joshi & Rahman, 2015).

6. Conclusion

This study examined the association between IM and CB towards kombucha drinks in Southwestern Uganda, with particular emphasis on the mediating role of BA. The findings indicate that IM was positively associated with CB both directly and indirectly through BA. The results further suggest that BA plays an important role in the observed association between IM and CB by strengthening consumers’ recognition and familiarity with kombucha brands. The partial mediation findings indicate that the positive association between IM and CB is linked not only to direct promotional efforts but also to consumers’ cognitive responses, particularly brand recognition and recall. The findings highlight the importance of integrating IM with brand-building strategies that strengthen BA and consumer engagement, particularly in emerging product categories such as kombucha drinks. While the observed relationships provide valuable insights for theory and practice, they should be interpreted as associations rather than causal effects because the study employed a cross-sectional research design.

7. Implications

These findings imply that functional beverage managers should focus on IM that enhances BA, as BA partially mediates the relationship between IM and CB. Hence, managers must focus on consistent brand messaging, repeated brand exposure, and long-term collaborations with influencers to increase consumers’ familiarity with and recall of kombucha brands. This approach is especially relevant in developing economies, where consumer awareness of the product and knowledge of kombucha drinks are still being developed.

The findings further suggest that policymakers and regulatory bodies should scrutinize IM practices associated with health-oriented products, such as kombucha drinks. IM was positively associated with CB through greater BA. It is imperative to ensure that the promotional content shared by influencers is accurate, transparent, and complies with established advertising and consumer protection standards. This would help protect consumers from misleading health claims and promote responsible marketing.

8. Limitations and Areas for Further Studies

Cross-sectional nature of the study limited the capacity to form causal linkages and look at variations in CB over time. Future research could use a longitudinal method to investigate the impact of ongoing exposure to IM on BA and CB. Secondly, the study was conducted in Southwestern Uganda which may restrict generalizability of the results to other contexts. Therefore, upcoming studies should investigate alike relations in other geographic and cultural contexts. Third, the study used BA as the mediating mechanism between IM and CB. Future studies can extend the model by incorporating other mediating variables like trust, perceived value and risk to get a wider view of customer responses to IM.

Data Availability

Supporting data can be obtained upon request from the respective author.

Author Contributions

Kabasinguzi, B.: Conceptualization, methodology, data collection, data analysis, and manuscript preparation. Kamukama, N.: Supervision, review and editing, and validation. Nabachwa, S.: Literature review, data collection, and review of the manuscript. All authors read and approved the final manuscript.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References