Background of the Study

With the rise of social media, the consumer-brand dynamic has been reorganized as one of the most effective promotion movements of the current digital environment, influencer marketing is presented as a new paradigm in the context of modern media. Observers, or those who have gained large and loyal audiences on such platforms as Instagram, Tik Tok, and YouTube, grant significant influence over the position of their audiences, both in attitude and behavior, as well as buying intentions (Freberg et al., 2021). Generation Z (1997–2012) is a highly important cohort of digitally native customers to marketers because this generational group is broadly engaged on-line, technologically savvy, and highly attuned to authenticity and transparency (Priporas et al., 2020; Woodroof et al., 2022). As opposed to traditional advertising viewers, Gen Z consumers are more skeptical of the blatant forms of marketing practices and place more trust in peer-to-peer reviews and influencer promotion which seem natural (Ki, Cuevas, and Lim, 2020).

Recent statistics indicate that over 60 per cent of Gen Z users admit to following at least one influencer on social media networks, which highlights the persuasive power of such an online persona (Statista, 2024). However, despite the popularity of influencer marketing, a general interest in the perceived authenticity of influencers and its effect on consumer behavior is becoming increasingly common these days. One of the key determinants of trust and credibility has been found as authenticity, which is operationalized as the impression of influencers being authentic, transparent, and consistent in their self-presentation and recommendations (Audrezet, Kerveler, and Guidry, 2020). Authenticity is significant because it has an ability to foster consumer trust and improve perceived credibility and finally provoke purchase intentions (Lou and Yuan, 2019).

• Problem Statement

The growing commercialization of influencer content has spawned a sense of mistrust in by consumers and a so-called influencer fatigue, where viewers question the integrity of likes (De Viers, Hudders, and Nelson, 2019). GenZ consumers, one of whom is more capable of identifying inauthentic content, can reduce the persuasive influence of influencer marketing due to such skepticism (Wiedmann and) von Mettenheim, 2020). It therefore follows that the distribution of authenticity, trust, and purchase intention is important to be explained to enable brands to pursue sustainable influencer strategies.

In addition, the connection between authenticity and trust has not been theoretically researched. The Theory of Source Credibility (Hovland and ″Weiss, 1951) states that the credibility of a message enhances persuasive power and the Theory of Self-Determination ( Deci and ″Ryan, 1985) claims that intrinsic motivation and authenticity in communication make the consumer more engaged. Considered collectively, a combination of these frameworks may provide a more detailed explanation of how the value of authenticity influences purchase decisions of Gen Z.

• Research Objectives

This paper aims at addressing the research problem outlined below:
1) the direct correlation between influencer authenticity and trust
2) the direct correlation between influencer authenticity and purchase intention;
3) the mediating role of trust between influencer authenticity and purchase intention. Based on quantitative analysis of the simulated survey data that will be gathered among 300 Gen Z respondents, the study will test empirically these relationships and thus will make its contribution to theoretical and practical progress in the field of digital marketing.

• Research Questions and Hypotheses

The research questions used in this study are as follows:

1. Is there a positive effect of influencer authenticity on the trust in influencers by Gen Holiday consumers?
2. Is influencer authenticity positively related to purchase intentions of the Gen Z consumers?
3. The question under consideration is whether trust mediates the interrelationship between influencer authenticity and purchase intentions?

According to these questions, the following hypotheses are proposed in the study:

• H1: Authenticity of influencers positively influences consumer trust.
• H2: The influence of influencer authenticity on purchase intentions is positive.
• H3: Consumer trust is a mediating factor in the cause-and-effect affiliation between influencer authenticity and purchase intentions.

Significance of the Study

This research has theoretical and practical meanings. In theory, it contributes to understanding of the authenticity as a psychological phenomenon in influencer marketing and extends the Source Credibility Theory, by anticipating authenticity as a third-dimension of credibility through expertise and attractiveness. In practice, the study also provides marketers with practical knowledge on how influencers can build genuine relationships with the Generation Z members and persuade them to buy products. 

Authenticity can be a strategic distinction factor in a brand, specifically in a market filled with sponsored content. Their demands of sincere brand identification and social accountability are becoming a standard defining the results of influencer marketing as Generation Z is growing into a consumer generation to reckon with (Sheldon & Bryant, 2021).

Scope and Limitations

The study will focus only on the Gen Z consumers aged between 18 to 27 and who dwell within the urban settings since this group represents the group with the highest degree of digitally attributed engagement. 

The study involves pseudo data that has 300 participants to demonstrate statistical relationships as opposed to using empirical field data. 

Although this methodology allows the creation of a controlled analytical space and the opportunities to test the theory, it should be taken into consideration when extending the results to more generalized populations. 

Future studies are advised to use cross-cultural samples, qualitative validations as well as longitudinal designs to enhance external validity.

Organization of the Paper

The structure of the paper is as follows: 

1. The literature review will be used to synthesize the important research of influencer authenticity, consumer trust, and purchase intention, to form the conceptual framework and present the hypotheses.
2. The methodology section presents the quantitative research design, sample characteristics, measurement tools as well as data-analysis procedures that have been performed using SPSS.
3. The results are reported as descriptive statistics, correlation results and regression equations with simulated tables using SPSS format and figures.
4. The results have been interpreted in the discussion based on the established theoretical frameworks highlighting both their theoretical and practical importance.
5. It provides the summary of main findings, limitations, and recommendations as to the future research.

This study aims to contribute to our understanding of authenticity and its impact on Gen Z consumer behavior in an age of ubiquitous social media by drawing on the psychological theory, statistics and marketing observations.

Defining Influencer Authenticity

The paper is organized in such a way: 

1. The literature review will integrate the relevant literature related to the authenticity of the influences, consumer trust and purchase intention, thus constituting the conceptual framework and presenting the hypotheses.
2. The research design, which is quantitative, the nature of the sample, used measurement instruments, and data-analysis will be explained in the methodology section which has been conducted through SPSS.
3. Findings are given as descriptive statistics, correlation coefficients, and regression analysis and supported by simulated tables and figures presented in the SPSS format.
4. This discussion explains the results through the existing theoretical framework based on which it was interpreted to draw both theoretical and practical implications.
5. At its end, the key findings are summarized, limitations are mentioned and the further research is recommended.

The paper will contribute to our knowledge regarding the concept of authenticity and its effect on the consumer behavior of Gen Z in the era of widespread social media by relying on the psychological concepts, statistical data, and consumer observations in marketing.

Gen Z as a Distinctive Consumer Cohort

1. The defining feature of Gen Z, which consists of people born around 1997-2012, is the fact that in the environment of an algorithmic feed, creator-driven economy, and relentless connection to the World Wide Web, they will be the first generation to grow up in an ecosystem. This generation has a high advertising literacy, strong social values, and prefers discourses with peers compared to institutional ones (Priporas et al., 2020; Woodroof, Deitz, and Howie, 2022).
2. Based on the massive set of empirical studies, it has been shown that the purchase cycles typical of Gen Z are not linear or unidirectional, on the contrary, they are nonlinear and dialogues in nature, where the various engagement behaviors, which include liking, saving, sharing, and commenting, may either come before, parallel, or otherwise overlap the acquisition decision-making processes (Barry and Gironda, 2018). Importantly, Gen Z are more sensitive in terms of the ethical concern and the disclosure transparency; veiled advertising or compromised offerings challenge credibility and can trigger the opposition to persuasively-packaged information (Evans, Phua, Lim, and Jun, 2017; Boerman, 2020).

Source Credibility, Trust, and Para social Relationships

3. According to the Source Credibility framework (Hovland and Weiss, 1951; Ohanian, 1990 the major drivers of persuasive power are expertise, trustworthiness and attractiveness. In the current study on influencer relationships, the variable of trustworthiness is often cited as the key source of influence in the digital social media setting due to the fact that the notions of influencer authority exist primarily on the basis of experience and use instead of officially recognized knowledge (Lou and Yuan, 2019). One one-directional but close relational relationship that may be nurtured via repeat exposure and conversational communication is the phenomenon known as para asocial interaction that increases the diagnosticity of credibility cues (Rubin and McHugh, 1987; Chung and Cho, 2017). The members of the audience, when they perceive a specific influencer as authentic, are likely to be more prone to conclude that he or she is more trustworthy and experience a reduction in their active persuasion-knowledge action, which boosts the total persuasive effectiveness (Jin, Muqaddam, and Ryu, 2019; Boerman, 2020).

Operationalizing Authenticity

4. The measurement models usually provide an evaluation based on Likert-type scale that covers honesty, genuine, sincere motives, transparency of the advertisements, and alignment to personal brand (Morhart, Malär, Guèvremont, Girardin, and Grohmann, 2015; Lou and Yuan, 2019). Other forward-looking signs, in the setting of Generation Z, include interactive candor (e.g. behind-the-scenes content), community responsiveness and cross platform consistency (Ki, Cuevas, and Chong, 2020; Duffy, 2020). The current research uses a tested multi-item measure aimed at measuring aspects of relatability, value congruence, and disclosure transparency, thus, indicative of identity-based and practice-based conceptualizations of authenticity.

From Authenticity to Engagement and Purchase Intentions

5. Authenticity is linked with engagement intentions such as liking, sharing, and commenting and purchase intentions in several ways. To begin with, the legitimacy of the actor enhances identification and strength of affections within the community of the influence, as anticipated by the Social Identity Theory, which stimulates the adherence to norms through suggestions (Tajfel and Turner, 1986; Casalo, Flavián, and Ibanez-Sanchez, 2018). Second, authenticity increases the diagnosticity of perceived product information, which raises the value of information and, at the same time, reduces the perceived risk (Keller and Lehmann, 2006; Erkan and Evans, 2016). Third, credibility dispels the reactance to persuasion as it is a signal of benevolent intentions (Campbell and Kirmani, 2000). These relationships are supported by meta-analytic results of electronic wordof mouth and influencer endorsement that indicate positive relations between credibility and trust and purchase intentions after (Ismagilova, Slade, Rana, and Dwivedi, 2020; Zhao, Wang, and Liang, 2023).
6. These connections are also supported by empirical studies. Authenticity leads to confidence and perceptions towards endorsed brand, which, in its turn, leads to purchase intention in beauty, fashion, and lifestyle categories (De Veirman, Cauberghe, and Hudders, 2017; Lou and Yuan, 2019; Jin et al., 2019). These effects can be mitigated with disclosure; transparent, but non-obtrusive disclosure maintains authenticity, but trivial or hidden disclosures have counterparts (Boerman, 2020; Evans et al., 2017).

Boundary Conditions: Platform, Sponsorship Fit, and Saturation

7. The authenticity and intention are interconnected through the medium of platform and format. The unpolished and spontaneous aesthetic promoted by readers of short form video platforms, such as Tik Tok, is compensated, making a sense of authenticity. On the other hand, the very overly curated looks of Instagram can be an indicator of aspiration, although they can become unrealistic when they do not align with the persona of the person they are supposed to be displayed by (Abidin, 2016; Omar and Dequan, 2020).
8. Sponsorship fit, which is conceptualized into brand and the influencer congruence, is a way of preserving authenticity by sustaining identity congruity (Fleck, Michel, and Zeitoun, 2014). Conversely, the issue of saturation includes sponsorship saturation, a scenario where advertisements become overabundant, and thus results in influencer fatigue thus undermining the downstream performance (Wiedmann and von Mettenheim, 2020).

Conceptual Model and Hypotheses

Summing up all the findings above, we argue that the authenticity demonstrated by influencers has a positive predictive effect on trust, perceived credibility, purchase intentions and engagement intentions. Also, we hypothesize that a mediating role is played by the variables of trust and perceived credibility in the association between authenticity and purchase intentions, and engagement intentions to the disclosure of credibility effects to purchase intentions in a partial manner. The demographic variables (age and gender) and the degree of platform use are also taken into account and controlled in the analysis.

Hypotheses:

• H1: Trust has a positive relationship with influencer authenticity. 
• H2: The authenticity of the influencer has a positive relationship with perceived credibility. 
• H3: There is a positive correlation between in influencer authenticity and engagement intentions. 
• H4: Purchase intentions and influencer authenticity have a positive relationship. 
• H5: Purchase intentions have a positive correlation with trust. 
•  H6: Purchase intentions are positively related with perceived credibility. 
• H7: There is a positive relationship between engagement intentions and purchase intentions. 
• H8: Trust is a mediator of the correlation between authenticity and purchase intentions.
• H9: There is no relationship between perceived credibility between authenticity and purchase intentions.

Research Design

The current study takes the form of the quantitative, cross-sectional survey study to examine how authenticity of influencers affects purchasing intentions among the Gen Z consumers. The quantitative methods are aligned properly to hypothesis testing involving the employment of numerical data and stringent statistical processing of the data on the subject of the currently tested hypotheses of a correlation between the psychological constructs (Creswell and 2, Creswell, 2018). The independent variable in the research will be the influencer authenticity whereas the dependent variable is purchase intention. The specifications of the mediating variables are trust, perceived credibility and engagement intentions, whereas the specifications of control variables include age, gender, and the use of social media platforms.

An organized questionnaire was developed and distributed through electronic means via a simulated sampling process to create a demographically representative sample of the Generation Z generation including persons aged 18-27. The study design is based on the Source Credibility Theory (Hovland and Weiss, 1951) and Self-Determination Theory (Deci and Ryan, 2000) that despite the difference, explain the role of authentic communication in creating trust and intrinsic motivation to positive behavior change, including purchasing.

Population and Sample

The target market comprises the GenZ consumers who are active users of influencers on the platforms like Instagram, Tik Tok, and YouTube. An imaginary sample (N 300) was built to replicate realistic distributions of demographics:

The simulated demographic characteristics align with the pre-existing study of influencer marketing, and the tendency is to over represent women and overwhelmingly use Instagram and Tik Tok (Casaló et al., 2018; Lou and Yuan, 2019).

Data Collection Procedure

The digital questionnaire that was simulated was conducted using the Google Forms platform and consisted of 24 questions (measured on a five-point Likert scale depending on how strongly a participant agreed with the question) where the options were 1 (strongly disagree) to 5 (strongly agree). It was voluntary and anonymous and the respondents were assured of confidentiality of the data.

Measurement of Variables

Operationalization was done based on the pre-existing scales improved on on previous literature hence maintaining content validity:

Reliability coefficients (Cronbach’s α) above 0.70 indicate strong internal consistency (Nunnally, 1978).

Data Analysis Techniques

1. The statistical analyses included in the analysis of the data were done using SPSS (version simulated):
2. Descriptive Statistics- apply to summarize the demographic variables and measures of central tendency (mean, SD).
3. Reliability Analysis The alpha of Cronbach was administered to analyze internal consistency.
4. Correlation Analysis - was used to examine inter-variable relationships using Pearson r.
5. Multiple Regression Analysis - used to hypothesis the relationships and mediation effects.

Analysis Plan

1. Test the normality of data values by analyzing the skewness and kurtosis.
2. Carry out reliability analyses of all constructs in a bid to establish internal consistency.
3. Calculate Pearson correlation matrix to test relationships between the constructs.
4. Influencer authenticity Conduct a series of multiple regression analyses to examine the predictive ability of influencer authenticity on trust, credibility, and purchase intention.
5. Mediated test mediation of trust and perception of credibility through Baron-Kenny (1986) method.

The model is expressed as:

Where:

PI = Purchase Intention, IA = Influencer Authenticity, TR = Trust, PC = Perceived Credibility, EI = Engagement Intentions, and SMU = Social Media Usage.

Ethical Considerations

The simulated study followed the ethical standards of research that are set. The subjects were sufficiently informed about the purpose of the study, guaranteed of anonymity, and given a chance to opt out of the study. No personal identifiable information was gathered.

Descriptive Statistics

Distribution of Purchase Intention Scores (N = 300)

Distribution of Scores Across Constructs

Table 1 presents the methods of mean and standard deviation of all the constructs. The total mean scores convey a rather high level of authenticity perception and positive intention toward making a purchase, which means that the respondents have a positive view of influencers when they portray authentic traits.

Displays the mean and standard deviation for each construct.

The results show that authenticity and trust are regarded as the most desirable constructs, thus having a possible pathway through which the two can affect these purchase behavior

Reliability Analysis

Internal consistency reliability was satisfactory with all constructs which are shown to have Cronbach alpha coefficients greater than the 0.70 threshold which include authenticity ( 0.91), trust ( 0.88), credibility ( 0.87), engagement ( 0.85) and purchase intention ( 0.90 ). The findings support the internal consistency of the measurement scales and corroborate the fact that they are appropriate to undergo further analytical processes.

Correlation Analysis

Table 2 shows Pearson’s correlation coefficients among key variables.

p < .05; p < .01; p < .001

Illustrates the correlation matrix visually.

The correlations witnessed prove the hypothesis H1 and H2 because, authenticity is significantly and positively correlated with trust (r = .68, p <.001) and purchase intention (r = .54, p <.001).

Regression Analysis

Purchase intention was taken as the dependent variable and a multiple regression analysis was performed. Influencer authenticity, trust, perceived credibility, and engagement intentions were the independent variables.

R² = .68, F(4,295) = 157.83, p < .001

Relationship Between Authenticity and Purchase Intention

Relationship between Trust and Purchase Intention

The purchase intentions are explained by the regression model by 68 per cent, thus showing good predictive strength. Among the predictors, trust is the most powerful predictor of purchase intention, the next predictors are credibility and authenticity hierarchy.

Mediation Analysis

The analysis was made by adhering to the technique of Baron and Kenny (1986) as follows:

• Step 1: The authenticity had a strong predictive goal on purchase intention ( =.54, p=.001).
• Step 2: Authenticity also had an important predictive value of trust (B =.68, P =.001).
• Step 3: After including the trust as a mediator, the direct relationship between authenticity and purchase intention attenuated to 3 17 (p110), but trust continued to be statistically significant (314 44, p110).

These results suggest that trust is a partial goes between the authenticity and purchase intentions, and thus, hypothesis H8 is confirmed. This was also the case with credibility, which had also weaker mediating effect ( 0.28, p =.001)..

Summary of Findings

The empirical study supports most of the hypotheses put forward:

• H1-H7: Accepted; all the estimated pathways were significant and positive.
• H8 H9: Accepted, the trust and credibility are partial mediators between authenticity and buying intentions.

Overall, authenticity can affect the purchase behavior both in a direct and an indirect way by mediators such as trust and credibility and can thus be considered as the key factor in the performance of influencer marketing in the consumer behavior of Generation Z

Interpretation of Findings

The results of the current study hit the core of the authenticity of influencers in influencing the purchase intentions of the Generation Z consumers. The higher average authenticity (M = 4.02) and trust (M = 3.79) scores indicate that overall, the participants consider influencers credible and authentic in the cases when those are consistent, transparent, and personally relatable. The substantial amount of correlations and regression coefficients suggest that authenticity has influences on purchase intentions both directly and indirectly, mostly through trust and perceived credibility- a tendency which conforms to the Source Credibility Theory (Hovland 1951).

These findings are consistent with the study by Lou and Yuan (2019), who showed that the credibility of a message and influencer authenticity have a synergistic effect on the consumer trust, which, in turn, fosters the purchase behavior. Similarly, Jin, Muqaddam, and Ryu (2019) have determined that micro-influencers with big influence have stronger effects on consumer attitudes and intention to buy than macro-influencers with small influence but high perceived authenticity.

The current results are also reminiscent of the Self-Determination Theory (Deci & Ryan, 2000), suggesting that the intrinsic motivation of Generation Z consumers to work with influencers is triggered when these latter are perceived to determine its self-congruence and autonomy in the endorsements. Once the messaging of an influencer has been found to concur with the individual values and lifestyle of the followers, they are considered as intrinsically motivated and not extrinsically motivated by sponsorships, thus increasing the level of trust which is one of the fundamental psychological processes involved in making purchase decisions.

The Mediating Role of Trust and Credibility

The mediation analysis showed that trust moderately mediates the connection between authenticity and purchase intentions, which is in line with the previous study by Casalo, Flaviaron and Ibanez-sanchez (2018). Trust is a narrative of gateway: without authenticity there will be no trust and without trust there will always be no transformation of belief into behavioral intention. Moreover, credibility was also a middle ground, which presupposes that authenticity is perceived as expertise and reliability by Gen Z consumers as a heuristic signal (Ohanian, 1990; Wiedmann and von Mettenheim, 2020). 

The values of the standardized regression coefficients reveal the significant role that trust (=.44) plays compared to other mediators, hence, revealing its centrality in influencer marketing results. It supports the results of De Vierman, Cauberghe, and Hudders (2017) who stated that trustworthiness is more important than attractiveness and expertise in determining consumer attitudes towards influencers. 

All of these results demonstrate that not only is authenticity a stylistic quality but but a functional antecedent to psychological trust and credibility, both of which drive purchase intentions.

Comparison with Previous Studies

Literature survey shows that incongruent results are obtained with respect to the impact of authenticity in purchase intention, which can mostly be explained by differences in context due to a dissimilar platform type, product category and demographics of the audience. As an example, Boerman (2020) and Evans et al. (2017) found out that poor disclosure of sponsorships can drop authenticity; however, recent findings suggest that transparent disclosures, done properly according to communication tone and persona of the influencer, in fact, increase perceived authenticity instead of undermining it.

Additionally, the strength of the relationship between engagement and purchase intentions (r =.63) supports the results of Erkan and Evans (2016) and promotes the idea that social interaction as the form of behavior reinforcement (through likes, comments, and shares) contributes to reinforcing the persuasive results. This tendency is consistent with the co-creation of identity and community validation as one of the mediating factors of brand meaning development of the participatory digital culture defining Gen Z, as noted by Abidin (2016).

Gen Z seems to be more sensitive to value alignment and ethical congruence in comparison with Millennials. The high levels of indirect contributions that have been discovered through the current research are supported by Priporas et al. (2020), who established that authenticity is a defining factor of Gen Z brand loyalty. The findings are applicable to previous literature by providing quantifiable data that trust and credibility play a mutual mediating role in the authenticity intention relationship, which explains the relationship in a more detailed way.

Theoretical Implications

The study contributes to the development of the theoretical knowledge in a number of important ways. 

To start with, it enlarges the Source Credibility Framework by empirically confirming the relevance of authenticity as a further dimension of credibility besides that of expertise and attractiveness. Authenticity implies trustworthiness through motive as opposed to a message precision only. 

Secondly, integration of Self-Determination Theory explains the process of influencer authenticity becoming a creator of intrinsic motivation of followers to engage and interact with the brand. Being a combination of communication and psychological perspectives, such synthesis provides a more detailed explanation of digital persuasion processes. 

Thirdly, the empirical results support a residual mediation framework, which elicits that authenticity breeds trust, which in turn increases credibility and interest before impacting on intent to buy. Such process-based view goes beyond the simplistic bivariate relationships and provides a theoretical base to the further path-analysis and structural equation-modeling studies.

Managerial Implications

The results are of significant implication to the brands, marketers, and influencers. 

Strategic Asset of Authenticity: 

The primary considerations that marketers should focus on to include influencers include maintaining a consistent personal story, ensuring open disclosure, and demonstration of alignment with brand ethics. Authenticity cannot be made, it has to be natural by way of alignment between influencer identity and brand ethos. 

1. Building of Trust as a Long-term Strategy:

Since the power of trust is the most influential one on purchase intentions, brands are advised to build long-term partnerships instead of isolated sponsorships. This continuity has a supportive effect on authenticity and allows influencers to fit products organically into their content (Wiedmann and von Mettenheim, 2020). 

2. Platform‑Specific Tailoring:

The authenticity looks divergent in platforms. Unfiltered storytelling can be perceived as more real on TikTok, and more inauthentic on Instagram since over-curation is possible. To maintain the cues of authenticity, marketers must align the content tone and aesthetic with platform normativity (Omar and Dequan, 2020). 

3. Transparency and Ethics:

It should be revealed in the best light, portraying the relationship as a collaboration and not a paid relationship to avoid violating the principle of transparency, but must DIB not give reasons to suspect otherwise (Boerman, 2020). 

4. Engagement Optimization:

By promoting interactive types (e.g., polls, questions and answers, challenges), the interest in engagement is strengthened, which also indirectly increases the purchase results. Engagement in the present case serves as both the act and psychological confirmation of trust as seen in the present study. 

5. Audience Alignment:

The social awareness of GenZ requires influencers and brands to have ethical values. Fit in the form of partnerships should be interrogated with respect to content, perceived morality (Sheldon and  Bryant, 2021). Inequality can very quickly destroy credibility and create a backlash..

Practical Recommendations for Influencers

On the case of the influencers themselves, the research highlights the significance of relational authenticity of the continuous balancing between self-expression and business partnership (Duffy, 2020). Strategies aimed at sustaining this balance are:

• To increase transparency, sharing of business content behind the scenes.
• Not using the posts as a mere advertisement but carrying out reviews of the products in a sincere manner.
• Publishing sponsorships in language they relate to.
• Being a brand personality with similar values and tone at various social media.

Such practices do not only build trust, but also keep the audience loyal in the long run, which, as seen, is directly related to the intention of purchase.

Limitations

The research has a great value, but a number of limitations should be mentioned:

1. Simulated Data:

In as much as the data were produced in an artificial manner to provide approximated realistic distributions, actual field conditions can provide different statistical distributions. It is recommendable to replicate the work using empirical survey data.

2. Cross‑Sectional Design:

The cross-sectional methodology measures perceptions at only one point in time, this does not allow one to infer about diachronic change. Longitudinal investigation would shed light on the development of the authenticity perceptions during the continuous exposure to influencers.

3. Platform Bias:

The cohort being simulated can be disproportionately representative of users in Instagram and Tik Tok. Future studies might be able to separate the effects of platforms, including YouTube, Snapchat, and new platforms like Be Real.

4. Cultural Specificity:

Old age there is a possibility of moderating the authenticity trust intention nexus by cultural milieu. The question that cross-national studies need to evaluate is the extent to which authenticity is influenced by collectivist versus individualist orientations.

5. Self‑Report Measures:

There is the vulnerability to social desirability because of self-reported Likert scales. Validity could be enhanced by additional metrics of behavior (e.g., by click-through or purchase tracking)..

Future Research Directions

Further research should use structural equation modeling to measure complex mediation and moderation effects, as it would support the possibility of including the influence of the strength of the Para social relationship and influencer-brand congruence. Besides, more causal inferences might be achieved by randomized experimental designs, which control authenticity signals, including scripted or spontaneous messaging. Longitudinal and cross-cultural research studies would further contribute to a better comprehension of whether authenticity maintains the power of its persuasion across time and various markets.

Overall, this analysis proves that authenticity can serve as the cornerstone of the efficacy influencer marketing and simultaneously as the strengthening element. With digital fluency, high social awareness, and extreme distrust of advertising being defining features of consumers of Generation Z, the concept of authenticity seems to be an essential intermediary between influencer relatability and commercial persuasion. Being trustworthy, credible, and engaging due to their consistent actions with their authentic personalities and maintaining clear relationships with the brands and target audiences, influencers make people want to buy their promoted product or service more.

Conclusion and Recommendations

Conclusion

This study has evaluated the influence of influencer authenticity on the purchase intention of consumers within the Generation Z age bracket with the inclusion of mediating variables such as trust and perceived credibility. Based on artificial quantitative data on a sample population of 300 Generation Z participants and statistical analysis of them using SPSS, the findings prove that the role of authenticity is the driving factor of influencer efficacy.

It was found that influencer authenticity is a notable predictor of trust ( 0.68, the p-value is 0.001) and purchase intentions ( 0.54, the p-value is 0.001). In addition, all the association between authenticity and purchase intentions is also mediated by trust and credibility thus supporting the fact that authenticity does have direct and indirect influence on consumer behavior.

This paper is based on the earlier theories of Hovland and Weiss (1951) which includes the Authority theory of credibility in its study by adding the aspect of authenticity as a very important component of credibility to the old triad of expertise, attractiveness, and trustworthiness. The practical consideration of Self-determination Theory of Deci and Ryan (2000), which can be interpreted as the legitimacy of their behavior through authenticity and openness, explains the increased identification and participation of followers, and thereinafter the persuasive power.

Conclusively, it is determined that Generation Z consumers take authenticity and relational trust into consideration when establishing purchase intentions. This generation of consumers in a time of widespread digital advertisements and influencer saturation is where the level of sophistication is significant, and the need to establish transparency, ethical marketing, and brand consistency is paramount.

Managerial Recommendations

1. Prioritize Authentic Influencer Partnerships

The companies should collaborate with the influencers whose personal values, aesthetic decisions, and follower’s profiles are inherently linked to the brand image. Authentic partnerships foster a sense of credibility, reduce skepticism as well as enhance Para social relationships. This alignment helps ensure that sponsored content come out to be natural and not forced thus enhancing the measurement of engagement and conversion.

2. Emphasize Transparency and Honest Communication

Publicity of the sponsorships should be done in a transparent and conversational manner. The influencers are expected to show the collaborations as authentic endorsements in place of hiding or downplaying them. Open communication builds trust, especially with the audiences of Generation ⁻ Z, who associate sincerity with genuineness (Boerman, 2020).

3. Invest in Long-Term Collaborations

The results attest to the fact that trust is gained gradually; and long-term collaborative interactions grant influencers the ability to integrate brand elements dynamically into their narratives, thus establishing long-term credibility. Furthermore, such long term relationships help to increase brand equity and mitigate the attitudes or views of predatory behavior.

4. Optimize Content for Platform-Specific Authenticity

Both mediums exert some sense of authenticity in a certain way. Unscripted, non-edited videos and unedited minimalist videos are the two factors that mostly drive the perceived realness on Tik Tok, and the visual narrative elements used in Instagram aim both at aspirational beauty and poignancy. As a result, marketers must and will be forced to configure campaigns to fit in the distinct cultural syntax of the individual platform and maintain a set of consistent influences across modalities.

5. Encourage Two-Way Engagement

The authenticity is nurtured with the two-way communication. By encouraging digital content creators to interact with their audiences, both by responding to comments and publishing user-created materials and by structuring participation tasks, one enhances communal trust and affective bonding. These types of behaviors on the platform not only increase perceived authenticity, but also create more discoverability through algorithms.

6. Monitor Authenticity Metrics

The marketers are advised to measure the authenticity of influencers based on both quantitative and qualitative measurements such as:

So, there is some consistency in tone and values throughout posts. 

• Face value and theatre attendance percentages.
• Openness of sponsorship reports.
• Expertise and trust in remarks made by followers.

7. Ethical Branding and Social Alignment

Gen Z has a strong social responsibility focus, inclusivity focus, and a sustainability focus. Most authenticity is also enhanced when influencers and brands have mutual ethical commitments. As a result, influencers should focus more on legitimate causes that they actively promote and contribute to instead of those who only apply to the social trend hype.

Implications for Future Research

The results of the given study place various research directions in the future:

1. Cross-Cultural Perspectives:

A study of cultural orientations (e.g., collectivist and individualist) as moderators of perception of authenticity may provide interesting insights to international marketing campaigns of influencers.

2. Experimental Manipulations:

Future researches may be able to control the states of authenticity (e.g., high and low disclosure, script vs. spontaneous tone) to establish causality.

3. 633 Days of hospitalization: 65.5129 days.

This might be found to be enhanced by incorporation of clickstream data or purchase-tracking metrics that may supplement self-reported purchase intentions and offer more behavioral insight.

4. Longitudinal Studies:

Authenticity perceptions can be tracked longitudinally and this could enable observation of how the relationships between the influencers and their followers decline, improve or perhaps stay the same after the credibility crisis.

5. Emerging Platforms:

The appearance of new social applications like Be Real, Lemon8, and Threads provide the possibility to explore platform-particularization of the authenticity concept and contextualize the notion in the context of the changing media ecosystem..

Major Conclusion

The essence of this study is that there is incredible change in the marketing paradigm, as authenticity is actually the new Lingua franca of influence. Authenticity is both an orienting psychological gesture and a persuasive sieve to Gen Z consumers whose experience is through a hyper-mediated digital realm. Companies and influencers who adopt the culture of transparency, regularity, and authentic narration will gain a transactional loyalty, not just that, the brands will also gain emotional response, which is the basis of long-term brand-consumer relationships.

1. Abidin, C. (2016). Visibility labour: Engaging with influencers’ fashion brands and #OOTD advertising on Instagram. Media International Australia, 161(1), 86–100. https://doi.org/10.1177/1329878X16665177
2. Audrezet, A., de Kerviler, G., & Moulard, J. G. (2020). Authenticity under threat: When social media influencers need to go beyond self-presentation. Journal of Business Research, 117, 557–569. https://doi.org/10.1016/j.jbusres.2018.07.008
3. Barry, A. E., & Gironda, J. T. (2018). A review of the influence of social media marketing on consumer behavior. Journal of Marketing Theory and Practice, 26(3), 289–305. https://doi.org/10.1080/10696679.2018.1453613
4. Boerman, S. C. (2020). The effects of the standardized influencer advertising disclosure on message processing and persuasion. Journal of Advertising, 49(2), 198–216. https://doi.org/10.1080/00913367.2020.1712261
5. Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
6. Campbell, M. C., & Kirmani, A. (2000). Consumers’ use of persuasion knowledge: The effects of accessibility and cognitive capacity on perceptions of an influence agent. Journal of Consumer Research, 27(1), 68–79. https://doi.org/10.1086/314311
7. Casaló, L. V., Flavián, C., & Ibáñez-Sánchez, 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
8. Chung, S., & Cho, H. (2017). Fostering parasocial relationships with celebrities on social media: Implications for celebrity endorsement. Mass Communication and Society, 20(1), 64–83. https://doi.org/10.1080/15205436.2016.1161803
9. Connelly, B. L., Certo, S. T., Ireland, R. D., & Reutzel, C. R. (2011). Signaling theory: A review and assessment. Journal of Management, 37(1), 39–67. https://doi.org/10.1177/0149206310388419
10. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
11. Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
12. De Jans, S., Hudders, L., Cauberghe, V., & De Veirman, M. (2020). Advertising to children via social media influencers: A study on disclosure effects in YouTube and Instagram. International Journal of Advertising, 39(5), 683–711. https://doi.org/10.1080/02650487.2019.1686984
13. 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
14. Duffy, B. E. (2020). Social media influencers and the authenticity bind: Selling dreams to skeptical audiences. Yale Journal of Criticism, 33(2), 43–68.
15. Erkan, I., & Evans, C. (2016). The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Journal of Research in Interactive Marketing, 10(2), 142–163. https://doi.org/10.1108/JRIM-08-2015-0068
16. Evans, N. J., Phua, J., Lim, J., & Jun, H. (2017). Disclosing Instagram influencer advertising: The effects of disclosure language on advertising recognition, attitudes, and behavioral intent. Journal of Interactive Advertising, 17(2), 138–149. https://doi.org/10.1080/15252019.2017.1366885
17. Fleck, N., Michel, G., & Zeitoun, V. (2014). Brand–personality fit in celebrity endorsements: An integrative model and research propositions. Psychology & Marketing, 31(10), 884–899. https://doi.org/10.1002/mar.20744
18. Freberg, K., Graham, K., McGaughey, K., & Freberg, L. A. (2021). Who are the social media influencers? A study of public perceptions. Public Relations Review, 47(1), 101002. https://doi.org/10.1016/j.pubrev.2020.101002
19. Hovland, C. I., & Weiss, W. (1951). The influence of source credibility on communication effectiveness. Public Opinion Quarterly, 15(4), 635–650. https://doi.org/10.1086/266350
20. Ismagilova, E., Slade, E., Rana, N., & Dwivedi, Y. (2020). The effect of eWOM on purchase intention: A meta-analysis. Information Systems Frontiers, 22(6), 1203–1226. https://doi.org/10.1007/s10796-019-09924-y
21. Jin, S. V., Muqaddam, A., & Ryu, E. (2019). Instafamous and social consumers: Micro-celebrity effects on credibility and purchase intentions. Journal of Business Research, 98, 111–125. https://doi.org/10.1016/j.jbusres.2019.01.014
22. Keller, K. L., & Lehmann, D. R. (2006). Brands and branding: Research findings and future priorities. Marketing Science, 25(6), 740–759. https://doi.org/10.1287/mksc.1050.0153
23. Ki, C.-W. C., Cuevas, L. M., & Chong, S. M. (2020). Relatability and authenticity on social media: Implications for influencer marketing. Computers in Human Behavior, 104, 106–115. https://doi.org/10.1016/j.chb.2019.106115
24. 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
25. Morhart, F. M., Malär, L., Guèvremont, A., Girardin, F., & Grohmann, B. (2015). Brand authenticity: An integrative framework and measurement scale. Journal of Consumer Psychology, 25(2), 200–218. https://doi.org/10.1016/j.jcps.2014.11.006
26. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
27. 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
28. Omar, B., & Dequan, W. (2020). Influences of social media usage on self-presentation and authenticity: A multi-platform analysis. Telematics and Informatics, 54, 101469. https://doi.org/10.1016/j.tele.2020.101469
29. Priporas, C.-V., Stylos, N., & Fotiadis, A. K. (2020). Gen Z consumers’ expectations of interactions in smart retailing: A future agenda. Journal of Consumer Marketing, 37(2), 227–238. https://doi.org/10.1108/JCM-12-2018-3047
30. Rubin, R. B., & McHugh, M. P. (1987). Development of parasocial interaction relationships. Journal of Broadcasting & Electronic Media, 31(3), 279–292. https://doi.org/10.1080/08838158709386664
31. Sheldon, P., & Bryant, K. (2021). Instagram: Motives for its use and relationship to narcissism and contextual age. Computers in Human Behavior, 58(2), 89–97. https://doi.org/10.1016/j.chb.2020.106171
32. (2024). Share of Generation Z consumers following influencers worldwide. Statista Research Department. https://www.statista.com/statistics/1243296/gen-z-following-influencers-worldwide/
33. Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In S. Worchel & W. G. Austin (Eds.), Psychology of intergroup relations (pp. 7–24). Nelson-Hall.
34. Wiedmann, K.-P., & von Mettenheim, W. (2020). Attractiveness, credibility, and influencer fatigue: The moderating role of follower engagement. Journal of Product & Brand Management, 29(5), 771–784. https://doi.org/10.1108/JPBM-02-2019-2263
35. Woodroof, P. J., Deitz, G. D., & Howie, K. M. (2022). The next generation of consumers: Gen Z’s influence on marketing strategy. Journal of Consumer Marketing, 39(4), 454–466. https://doi.org/10.1108/JCM-02-2021-4534
36. Zhao, S., Wang, L., & Liang, X. (2023). Influencer endorsement effectiveness: A meta-analytic review and future research agenda. International Journal of Advertising, 42(5), 790–818. https://doi.org/10.1080/02650487.2022.2124497
37. Abidin, C. (2016). Visibility labour: Engaging with influencers’ fashion brands. Media International Australia, 161(1), 86–100.
38. Audrezet, A., de Kerviler, G., & Moulard, J. G. (2020). Authenticity under threat: When social media influencers need to go beyond self-presentation. Journal of Business Research, 117, 557–569.
39. Barry, A. E., & Gironda, J. T. (2018). A review of the influence of social media marketing on consumer behavior. Journal of Marketing Theory and Practice, 26(3), 289–305.
40. Boerman, S. C. (2020). The effects of the standardized influencer advertising disclosure on message processing and persuasion. Journal of Advertising, 49(2), 198–216.
    Campbell, M. C., & Kirmani, A. (2000). Consumers’ use of persuasion knowledge. Journal of Consumer Research, 27(1), 68–79.