ISSN 2528-2433 .
ISSN 2599-283X .
Volume 10.
Number 2 December 2025, pp.
Perceived Relevance or Perceived Credibility: Which Factor Influences Purchase Intention Through Brand Consciousness on Tiktok? Lisa Dwi Yana.
Nurainun*.
Mariyudi.
Khairina Faculty of Economics and Business.
Malikussaleh University.
Indonesia
Article Info
ABSTRACT
Article History:
This study examines the influence of perceived relevance and perceived credibility of TikTok advertising on purchase intention, with brand consciousness as a mediator.
Using a quantitative approach, data were collected from 119 active TikTok users at the Faculty of Economics and Business.
Malikussaleh University, through purposive sampling and analyzed using SEM-PLS.
The findings revealed that both perceived relevance and perceived credibility significantly affected brand consciousness and purchase intention.
Among the predictors, perceived credibility emerged as the most influential factor in shaping consumer responses to TikTok advertising.
Furthermore, brand consciousness partially mediated the effects of both independent variables on purchase intention.
These results underscore the importance of credible advertising content in strengthening brand consciousness and increasing purchase intention, offering meaningful academic insights into the effectiveness of digital advertising among young consumers.
Received 20 Oct, 2025 Accepted 20 Nov, 2025 Keywords:
Brand Consciousness.
Perceived Credibility.
Purchase Intention.
Perceived Relevance Corresponding Author Nurainun Email: nurainun@unimal.
INTRODUCTION
The rapid development of information and communication technology has significantly transformed business practices, particularly in marketing.
Social media has become a key channel for companies to build interactions with consumers due to its ability to.
Unlike traditional advertising, social media enables users to share and receive information in the form of images, text, videos, and audio, making it an effective medium for strengthening customer engagement (Hosain & Mamun, 2.
Among various platforms.
TikTok has emerged as one of the most influential, especially among younger users.
Since its launch in 2016.
TikTok has enabled users to create and share short videos with strong viral potential, making it widely adopted by industries such as fashion for tutorials, product reviews, and influencer-driven promotions (Hosain Journal homepage http://mebis.
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& Mamun, 2.
However, the effectiveness of TikTok advertising remains challenged by the increasing presence of irrelevant and non-credible content, which may weaken consumer trust (Mathur et al.
, 2.
According to Dataindonesia.
TikTok is among the most widely used social media platforms globally, including in Indonesia, with more than one billion active The following infographic illustrates TikTok user statistics in 2025:
8 Countries With the Most TikTok Users in the World (As of April 2.
Indonesia Amerika Serikat Brazil Meksiko Vietnam Pakistan Filipina Rusia Figure 1.
Countries with the largest TikTok users in the world The report shows that Indonesia has the highest number of TikTok users in the world, 95 million users as of April 2025.
This is followed by the United States .
76 millio.
Brazil .
28 millio.
Mexico .
40 millio.
Vietnam .
Pakistan .
40 millio.
, the Philippines .
86 millio.
, and Russia .
In the context of digital marketing, advertising effectiveness is strongly influenced by perceived relevance and perceived credibility (Alalwan, 2.
Advertising relevance refers to the degree to which consumers view an advertisement as aligning with their individual requirements, preferences, and interests.
The greater the perceived relevance, the more likely consumers are to engage with the message and the stronger their intention to make a purchase (Alalwan, 2018.
Hosain & Mamun, 2.
Meaningless advertising credibility reflects consumer trust in the information conveyed, both in terms of the honesty and professionalism of its presentation, so that credible advertising will build consumer trust, which will ultimately lead to a desire to make a purchase (Mustafi & Hosain, 2.
In addition to perceived relevance and perceived credibility, brand consciousness also plays a crucial role.
Customers with strong brand consciousness tend to prioritise product quality, brand reputation, and overall image before deciding to make a purchase.
Research conducted by Hosain & Mamun .
demonstrated that brand consciousness can serve as a mediating variable linking Perceived Relevance and Perceived Credibility to Purchase Intention.
As a result, brand consciousness may function as an intermediary factor that strengthens the impact of advertising relevance and credibility on consumersAo purchasing intentions.
Based on this gap, the present study aims to analyse the effects of perceived relevance and perceived credibility of TikTok advertising on purchase intention, with brand consciousness serving as a mediating variable.
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LITERATURE REVIEW
Perceived relevance refers to the degree to which consumers evaluate advertisements as aligning with their needs, interests, and personal circumstances.
If social media ads can customise content based on the audience's preferences and interests, consumers will pay more attention to the advertisement and become emotionally involved, ultimately leading to a purchase decision (Alalwan, 2.
High advertisement relevance is also believed to increase consumer interest because they feel the information provided through TikTok social media advertisements is relevant to their needs (Martins et al.
, 2.
Research by Zhu & Chang .
confirms that content tailored to consumer preferences enhances purchase intention.
Furthermore.
Hosain & Mamun .
demonstrate that perceived relevance significantly affects purchase intention, indicating that consumersAo perception of relevance increases their consciousness of advertisements and makes them more likely to use information from TikTok to inform their purchase decisions.
In light of these results, the hypothesis of this research is:
H1: Perceived relevance influences purchase intention.
Perceived credibility is defined as the extent to which consumers believe that information provided through TikTok social media is valid, transparent, and trustworthy.
Therefore, credible advertisements are more readily accepted by consumers (Zhu & Chang 2.
Advertisements perceived as credible, whether through brands or influencers, encourage consumers to trust products and make purchasing decisions (Tseng et al.
, 2.
Hosain & Mamun .
also showed that the perceived credibility of social media advertisements influences purchase intentions.
Mustafi & Hosain .
emphasised that advertisements perceived as credible can foster consumer trust, making them more confident in making purchasing decisions.
Therefore, advertisements with a high level of credibility will have more potential to increase purchase intentions compared to advertisements that raise doubts.
Based on the results of earlier studies, the hypothesis suggested in this research is as follows:
H2: Perceived credibility has a significant effect on purchase intention.
Besides that, advertisements that align with customer preferences and needs tend to be more successful in attracting attention and forming positive perceptions of a brand (Alalwan, 2.
In addition, a high level of ad relevance also contributes to increased brand consciousness, because consumers will more easily identify and have trust in brands that they consider to be in line with their self-identity (Mustafi & Hosain, 2.
A study conducted by Hosain & Mamun .
also indicated that perceived relevance has an influence on brand consciousness.
The perceived relevance of social media advertising not only captures consumersAo attention but also reinforces their recall of the advertised brand.
Drawing from previous research outcomes, the hypothesis for this study is presented as follows:
H3: Perceived relevance of social media advertising influences brand consciousness.
Besides that, information presented through advertisements on social media originating from trustworthy sources also has the potential to foster consumer confidence in the quality and originality of a brand (Ismail, 2.
Consumers tend to pay greater attention to brands supported by credible advertisements (Mustafi & Hosain, 2.
In addition.
Li & Suh .
suggested that the degree of perceived trustworthiness of a social media ad is vital in influencing consumer views of a brand.
Similarly, a study conducted by Hosain & Mamun .
indicated that perceived credibility impacts brand consciousness, where Vol.
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consumers will more easily recognise and remember brands whose information comes from trusted sources.
Referring to previous findings, the research hypothesis proposed is as follows:
H4: Perceived credibility of social media advertising influences brand Brand consciousness can be defined as the ability of customers to have the potential to recognise a brand due to specific memories associated with that brand, and consumers who have brand consciousness will view a brand as an emblem of status and distinction that they possess (Sharda & Bhat, 2.
Furthermore, high brand consciousness can strengthen customer confidence when making purchasing decisions, especially for products promoted through advertisements on social media platforms like TikTok, as customers will feel more confident about the quality of the brand they recognise (Scotto et al.
, 2.
Earlier research has demonstrated that brand consciousness significantly affects buying intentions.
This is evident in the tendency of consumers with higher levels of brand consciousness to prioritise products from brands they already recognise and trust (Hosain & Mamun, 2.
In line with previous findings, the hypothesis proposed in this study is as follows:
H5: Brand consciousness has an effect on purchase intention.
Furthermore, consumers are more likely to focus on advertisements perceived as relevant to their needs, thereby helping them recognise, remember, and evaluate brands more positively (Zhu & Chang, 2.
According to Park & Yoo .
, relevant advertisements can also create emotions that strengthen consumer attachment to brands, as messages that align with personal needs are perceived as more meaningful.
comparable notion is expressed by (Scotto et al.
, 2.
, who mention that emotional bonds with a brand can develop when consumers perceive the advertising message as aligned with their personal values.
When this engagement is formed, brand consciousness will increase, which then drives purchase intention (Riorini, 2.
Furthermore, research conducted by Hosain & Mamun .
also stated that advertising relevance contributes to the formation of brand consciousness, which ultimately influences purchase intention.
Thus, it can be said that relevant advertisements not only attract consumers' attention but also build strong brand consciousness, thus eliciting consumer desire to make a purchase.
Drawing on the findings of previous studies, the hypothesis formulated in this research is as follows:
H6:
Perceived relevance influences purchase In addition, the perceived high credibility of an advertisement also plays a role in providing a sense of security and confidence to consumers regarding the information provided, which ultimately plays a role in strengthening emotional bonds and consumer memory of the brand (Ismail, 2.
Furthermore, research findings by Hosain & Mamun .
indicate that that brand consciousness can act as a mediator between advertising credibility and purchase intention.
Consumers who trust the advertising source are more likely to recognise and recall the brand effectively, which in turn increases their purchase Therefore, perceived credibility not only cultivates trust in the product but also enhances brand consciousness, which in turn reinforces consumersAo purchase intention.
Based on prior research findings, the hypothesis of this study is formulated as follows:
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H7: Perceived credibility influences purchase intention through brand Figure 2.
Conceptual Framework
RESEARCH METHODS
This research utilised a quantitative method to examine how perceived relevance and perceived credibility of TikTok ads influence purchase intention, while brand consciousness acted as a mediating factor.
The population included students from the Faculty of Economics and Business at Malikussaleh University who had seen TikTok ads and completed purchases.
The sample was identified using a non-probability sampling method, particularly purposive sampling, where participants were chosen according to specific criteria that matched the research goals.
The information utilised in this research consists of primary data gathered through an online survey with Google Forms and shared via the social media platform WhatsApp.
The research tool was created utilising a 5-point Likert scale, with responses varying from "1 = strongly disagree" to "5 = strongly agree".
The survey included elements associated with perceived importance, perceived trustworthiness, brand consciousness, and purchase intent, amounting to 17 indicators.
Based on Hair et al.
, the necessary sample size was determined to be 7 y 17 = 119 participants.
The analysis of the data was conducted using Partial Least Squares-Structural Equation Modelling (PLS-SEM) version 4.
The study encompassed a validity assessment, which involved evaluating outer loadings, average variance extracted (AVE), the Fornell-Larcker criterion, cross-loadings, and the Heterotrait-Monotrait Ratio of Correlations (HTMT).
Reliability was assessed through Cronbach's Alpha and Composite Reliability measures.
The structural model was analysed using path coefficients, the coefficient of determination (RA), and effect size .
A).
Lastly, the significance of hypotheses was examined via the bootstrapping technique.
RESULTS AND DISCUSSION
Results The data utilized in this research were obtained through an online survey distributed to students of the Faculty of Economics and Business at Malikussaleh University.
The participants were those who actively used TikTok, had previously encountered advertisements on the platform, and had made purchases via TikTok.
In total, 119 valid responses were collected.
The demographic characteristics of the respondents were analyzed based on gender, age, field of study, and academic year.
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The findings from the respondent analysis by gender in this study were primarily influenced by female respondents, totaling 94 individuals, which represents 79.
the same time, the number of male respondents was 25, accounting for 21.
Respondent characteristics indicate that the majority were aged 18-20, with 17 respondents representing 14.
The 21-23 age group comprised 101 respondents, 9%, while individuals aged 23 and above had one respondent representing 8%.
The characteristics of the respondents by their major indicate that most of them were from Management, with 95 respondents making up 79.
The Accounting category had 9 respondents 7.
Development Economics included 6 respondents 5.
Sharia Economics featured 3 respondents 2.
Entrepreneurship had 3 respondents 5%, while the D-3 Secretariat program also consisted of 3 respondents 2.
Most of the respondents were from the 2021 cohort, totaling 79 individuals, which represents The 2022 group included 32 participants, accounting for 26.
9%, while the 2023 group had 8 participants, constituting 6.
Table 1.
Demographic Characteristics of Respondents Criteria
Gender
Age
Major
Force Category Man
Amount
Percentage (%) Woman
>23
Management Accounting Development Economics Sharia Economics Entrepreneurship D-3 Secretariat Validity Test Validity assessment is performed to confirm that a construct is precisely measured by specified indicators.
Within PLS-SEM analysis, validity falls into two primary types:
convergent validity and discriminant validity.
The appraisal of convergent validity involves examining the outer loading values and the Average Variance Extracted (AVE) According to the guidelines by Hair et al.
an indicator is deemed valid when its correlation coefficient surpasses 0.
Those indicators falling short of this benchmark are advised to be removed.
The outcomes from the initial phase of convergent validity evaluation are presented in the table below:
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Table 2.
Outer loading Variables Latent
Perceived Relevance Perceived Credibility Brand
Consciousness Purchase Intention
Instruments PR1
PR2
PR3
PR4
PC1
PC2
PC3
PC4
BC1
BC2
BC3
BC4
PI1
PI2
PI3
PI4
PI5
Perceived Relevance Perceived Credibility Brand Consciousness Purchase Intention According to the data analysis presented in Table 2, the outer loading values range from 5 to 0.
However, there are five indicators that have values less than 0.
7, namely PR 1 .
PR2 .
BC1 .
PI2 .
, and PI4 .
, which according to Hair et al.
can be considered for elimination.
Therefore, the researchers decided to remove these five indicators and reprocess the data.
Table 3.
Outer Loading 2
Latent
Variables Perceived Relevance Perceived Brand
Consciousness Purchase Intention
Instrument
PR3
PR4
PC1
PC2
PC3
PC4
BC2
BC3
BC4
PI1
PI3
PI5
Perceived Relevance Perceived Credibility Brand Consciousness Purchase Intention As shown in Table 3, which presents the findings from the second phase of the outer loading analysis, the perceived relevance variable recorded an outer loading value of 868 for indicator PR3 and 0.
917 for indicator PR4.
The outer loading value for the perceived credentials variable for indicator PC1 was 0.
PC2 was 0.
PC3 was 0.
and PC4 was 0.
The outer loading value for the brand consciousness variable for indicator BC2 was 0.
BC3 was 0.
866, and BC4 was 0.
Finally, the outer loading value for the purchase intention variable for indicator PI 1 was 0.
PI3 was 0.
858, and PI5 was 0.
Thus, all indicators can be categorized as valid.
All indicators for the Vol.
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variables perceived relevance, perceived credentials, brand consciousness, and purchase intention had values above 0.
These results indicate that the statements used effectively reflect the constructs or variables being measured.
Average Variance Extracted (AVE) Value The Average Variance Extracted (AVE) value is an average score that displays the level of indicator variance that can be attributed to a construct or latent variable.
A higher AVE score indicates that the construct is effective in explaining the indicator variance.
An AVE value exceeding 0.
5 indicates that the construct can account for over half of the variance in its indicators.
As a result.
Hair et al.
5 as the lowest acceptable level for AVE.
The subsequent table presents the results of the AVE calculations obtained from the PLS-SEM analysis:
Table.
4 Average Variance Extracted (AVE) Value Variable Brand Consciousness Perceived Credibility Perceived Relevance Purchase Intention Critical Value AVE Based on Table 4.
Brand consciousness shows an AVE of 0.
Perceived Credibility has an AVE of 0.
Perceived Relevance has an AVE of 0.
797, and Purchase Intention has an AVE of 0.
Therefore, all constructs can be deemed valid, as each Average Variance Extracted (AVE) value surpasses the minimum benchmark of 0.
demonstrating a high level of convergent validity.
Fornell-Larcker Value Fornell Larcker is used to test whether a construct in a PLS model has good discriminant validity, a construct is considered valid when the square root of its AVE exceeds the correlations with other constructs in the relevant row.
Conversely, if the OoAVE value is lower than the correlation coefficients, the construct is deemed invalid, then the construct is considered invalid, meaning, the measurement model can clearly distinguish between one construct and another Hair et al.
Table 5.
Fornell Larcker
Variabel
Brand
Consciousness Perceived Credibility Perceived Relevance Purchase Intention
Brand
Consciousness Perceived Credibility Perceived Relevance Purchase Intention
0,831
0,583
0,795
0,531
0,673
0,893
0,620
0,657
0,649
0,841
According to the Fornell Larcker Criterion outcomes detailed in Table 5, the square roots of the AVE values .
ighlighted in bold on the diagona.
for each construct namely.
Brand Consciousness .
Perceived Credibility .
Perceived Relevance .
, and Buy Intention .
exceed the inter construct correlations in their corresponding rows Vol.
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and columns.
This result indicates robust discriminant validity for each construct, meaning that the latent Cross-Loading A cross-loading value is considered valid when the correlation between an indicator and its associated variable is higher than its correlation with other variables.
This condition confirms that all indicators are valid and appropriately represent their respective constructs (Hair et al.
,2.
Table 6.
Cross Loading PR3
PR4
PC1
PC2
PC3
PI1
PI3
PI5
BC2
BC3
BC4
Table 6 shows the cross-loading value for the perceived relevance variable (X.
with PR3 indicators of 0.
868 and PR4 of 0.
917, the perceived credibility variable (X.
with PC1 indicators of 0.
PC2 of 0.
811, and PC3 of 0.
792, the purchase intention (Y) with PI1 indicators of 0.
PI3 of 0.
858, and PI5 of 0.
brand consciousness variable (Z) with BC2 indicators of 0.
BC3 of 0.
BC4 of 0.
854, and brand consciousness variable (Z) with BC2 indicators of 0.
BC3 of 0.
BC4 of 0.
All variables exhibit correlation values between each indicator .
and its corresponding construct that are greater than the correlations with other constructs.
The outcomes of both the convergent validity and discriminant validity tests demonstrate consistency, confirming that all indicators are valid.
Heterotrait-Monotrait Ratio of Correlations (HTMT) Discriminant validity is regarded as strong when the Heterotrait Monotrait Ratio of Correlations (HTMT) value is less than 0.
85, a conservative limit.
If there is a possibility of similarity between indicators between constructs, researchers can still use a looser limit, namely below 0.
90, which still indicates acceptable discriminant validity.
This means that as long as the HTMT correlation value between two constructs does not 85, then the construct has good discriminant validity (Hair & Alamer, 2.
Table 7.
Heterotrait-Monotrait Ratio of Correlations (HTMT) Brand Consciousness Perceived Credibility Perceived Relevance Purchase Intention Brand Consciousness Perceived Credibility Perceived Relevance Purchase Intention Vol.
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The analysis results indicate that all HTMT values fall below the recommended upper limit of 0.
Specifically, the HTMT value between Perceived Credibility and Brand Consciousness was found to be 0.
689, while that between perceived relevance and brand consciousness was recorded at 0.
On the other hand, the HTMT value between brand consciousness and purchase intention was 0.
The value obtained between perceived credibility and perceived relevance was 0.
Meanwhile, the HTMT value between Perceived Credibility and Purchase Intention reached 0.
792, and the value between Perceived Relevance and Purchase Intention was recorded at 0.
Reliability Test Reliability testing serves to determine how effectively a measurement instrument can generate accurate, consistent, and precise data when assessing a construct.
The reliability of a construct is evaluated using one or both of the following criteria: CronbachAos alpha and Composite Reliability.
A Composite Reliability value above 0.
7 is deemed acceptable, and a CronbachAos alpha value exceeding 0.
7 likewise indicates good reliability (Hair et al.
, 2.
Table 8.
Reliability Test
Variables Brand consciousness Perceived credibility Perceived relevance Purchase Intention
Cronbach's alpha
0,777
0,811
0,748
0,792
Composite reliability 0,870 0,873 0,887 0,878 The reliability test results revealed that the Composite Reliability values for each variable were as follows: Brand Consciousness .
Perceived Credibility .
Perceived Relevance .
, and Purchase Intention .
Since all values exceed the minimum threshold of 0.
70, each variable demonstrates an acceptable level of reliability.
Moreover, the CronbachAos Alpha value for the Brand Consciousness variable was recorded at 0.
perceived credibility 0.
811, perceived relevance 0.
748, and purchase intention 0.
Since all values are above 0.
70, it can be stated that all variables are reliable.
Square (RA) The coefficient of determination (RA) is utilized to assess the degree to which exogenous variables affect endogenous variables.
The RA value reflects the overall influence of both exogenous and endogenous variables on the endogenous construct.
According to conventional benchmarks.
RA values of 0.
75, 0.
50, and 0.
25 represent strong, moderate, and weak model explanatory power, respectively.
In essence, a higher RA value signifies greater predictive capability and a more robust research model (Hair et al.
,2.
Table 9.
R-Square (R.
Dependent Variable Purchase Intention Brand Consciousness R-Square 0,564 0,375 R-Square Adjusted 0,553 0,364 According to Table 9, the R-Square for Purchase Intention is 0.
564, which means that 4% of the variation in this variable is accounted for by the predictors in the model, while the remaining 43.
6% is due to factors not included.
This implies a fairly robust association between the predictors and Purchase Intention.
In contrast, the R-Square for Vol.
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Brand Consciousness is 0.
375, indicating that 37.
5% of its variation is explained by the model's predictors, with the other 62.
5% influenced by external elements.
This value reflects a moderately strong relationship, implying that while the model can account for a substantial portion of the factors affecting Brand Consciousness, there are still notable external influences impacting the construct.
Effect Size (FA) The effect size FA, is utilized to gauge the extent to which each predictor variable impacts the variability in the outcome variable.
This assessment involves examining shifts in the RA value upon removing a specific predictor from the model.
Typically, an FA of 0.
signifies a minor impact, 0.
15 indicates a medium influence, and 0.
35 suggests a substantial effect.
Such an approach assists researchers in pinpointing which predictors have the most significant role in shaping the outcome, thus enhancing the comprehension of interconnections between latent factors (Hair & Alamer, 2.
Table 10.
Effect Size(F.
Brand
Consciousness (Z) Purchase Intention
(Y)
Perceived Relevance (X.
Perceived Credibility (X.
Brand Consciousness (Z) Purchase Intention (Y) As indicated in Table 10, the value of Perceived Relevance (X.
on Brand Consciousness (Z) is 0.
056, which falls into the low influence category.
The value of Perceived Credibility (X.
on Brand Consciousness (Z) is 0.
149, which falls into the medium influence category.
The impact of Perceived Relevance (X .
on Purchase Intention (Y) is measured at 0.
109, which is considered as a medium level of influence.
The influence of Perceived Credibility (X.
on Purchase Intention (Y) is recorded at 0.
085, which indicates a very small impact.
Meanwhile, the influence of Brand Consciousness (Z) on Purchase Intention (Y) is identified at 0.
126, which falls into the medium influence category.
Figure 3.
Path Diagram Construction Vol.
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Hypothesis Testing Results Table 11.
Direct Effect Path Coefficient Perceived Relevance -> Purchase Intention Perceived Credibility -> Purchase Intention Perceived Relevance -> Brand Consciousness Perceived Credibility -> Brand Consciousness Brand Consciousness -> Purchase Intention Original Sample (O) Sample Mean (M) Standard Deviation (STDEV) T Statistics P Values 0,303 0,305 0,093 3,254 0,001 0,280 0,277 0,088 3,180 0,002 0,253 0,249 0,074 3,436 0,001 0,413 0,413 0,075 5,503 0,000 0,297 0,302 0,087 3,393 0,001 Based on the data presented in Table 11, the Perceived Relevance variable has a coefficient value of 0.
303, a T-value of 3.
254 (> 1.
, and a p-value of 0.
001 (< 0.
These results indicate that Perceived Relevance significantly affects Purchase Intention, thus supporting the proposed hypothesis.
In addition.
Perceived Credibility shows a coefficient of 0.
280, with a T-value of 3.
180 (> 1.
and a p-value of 0.
002 (<0.
confirming that Perceived Credibility has a significant effect on Purchase Intention.
therefore, the hypothesis is accepted.
Lastly.
Perceived Relevance demonstrates a coefficient of 0.
253, accompanied by a T-value of 3.
436 (> 1.
and a p-value of 0.
(< 0.
, further validating that this variable significantly influences Purchase Intention.
Table 12.
Indirect Effect
Path Coefficient Perceived Relevance -> Brand
Consciousness -> Purchase Perceived Credibility -> Brand
Consciousness -> Purchase Intention
Original sample (O) Sample mean (M) Standard
(STDEV)
2,319
2,789
Based on the findings outlined in Table 12.
Perceived Relevance exerts a notable indirect impact on Purchase Intention via Brand Consciousness, as indicated by a coefficient of 075, a T-statistic of 2.
319 (> 1.
, and a P-value of 0.
022 (< 0.
Given that the direct link between Perceived Relevance and Purchase Intention is also statistically significant.
Brand Consciousness operates as a partial mediator, thus validating the hypothesis.
Likewise.
Perceived Credibility exhibits a substantial indirect effect on Purchase Intention through Brand Consciousness, with a coefficient value of 0.
122, a T-statistic of 789 (> 1.
, and a P-value of 0.
006 (< 0.
Since the direct connection between Perceived Credibility and Purchase Intention remains significant.
Brand Consciousness acts as a partial mediator in this context, resulting in the hypothesis being upheld.
DISCUSSION