Almana : Jurnal Manajemen dan Bisnis Volume 10 Number 1/ April 2026: 1-15 p-ISSN 2579-4892/ e-ISSN 2655-8327 DOI: 10.
36555/almana.
The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers Yessa Jovita Sugiharto1.
Auditia Setiobudi*1 Universitas Ciputra Surabaya.
Indonesia1 *Corresponding email: auditia.
setiobudi@ciputra.
Abstract: The digital transformation in Indonesia has Article History:
institutionalized influencer marketing as a core strategic Submitted: December 24, 2025 tool, driven by the rapid growth of social media and Revised: January 26, 2026 Accepted: February 9, 2026 Grounded in the StimulusAeOrganismAe Published: April 30, 2026 Response (SOR) framework, this study examines the impact of paid communication .
d recognitio.
, influencer credibility, and consumer attitudes on recommendation Keywords:
intentions within the digital landscape of Surabaya.
This Attitude toward the Influencer research aims at a deeper understanding of how Influencer Credibility sponsored content affects consumer behavior.
Utilizing a Intention to Recommend the quantitative approach, data from 160 purposively Influencer sampled followers of influencer Rachel Vennya were Paid Communication (Ad analyzed via Partial Least SquaresAeStructural Equation Recognitio.
Modeling (PLS-SEM) 3.
The empirical results demonstrate that influencer credibility is the most potent predictor of recommendation intention and a primary driver of positive consumer attitudes.
Crucially, while ad recognition does not directly alter attitudes, it exerts a significant indirect influence on recommendation behavior through the mediating mechanism of perceived credibility.
The studyAos originality lies in establishing ad recognition as a critical antecedent that triggers behavioral responses through an integrated credibility-attitude pathway, offering strategic insights for managing influencer-brand partnerships in emerging digital markets.
These findings suggest that brands should prioritize influencer authenticity and credibility over mere exposure in paid Sugiharto.
, & Setiobudi.
The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers.
Almana Jurnal Manajemen Bisnis.
https://doi.
org/10.
36555/almana.
INTRODUCTION
The rapid advancement of digital technology has generated substantial changes in social interactions and broader societal dynamics (Nur et al.
, 2.
The advancement of information technology and shifting consumer behavior patterns have dramatically transformed the business landscape.
Therefore, to remain relevant and competitive in an increasingly digital market, companies must efficiently adopt information technology (Basid et al.
, 2.
This increasing level of digital adoption is reflected in recent statistics on internet usage in Indonesia.
Data from the Indonesian Internet Service Providers Association (APJII, 2.
shows that internet users in Indonesia reached over 221 million This is a large portion of the total population, which was roughly 278 million in 2023 (Ramdani & Sudarto, 2.
Today, social media is used for much more than just This work is licensed under a Creative Commons Attribution-NonCommercialNoDerivatives 4.
0 International License.
https://creativecommons.
org/licenses/by-nc-nd/4.
Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 it has become one of the most popular ways for people to find and share product The ability of entrepreneurs to leverage digital platforms for marketing their products and services has made business processes more efficient, improved productivity, and provided other significant benefits (S et al.
, 2.
As modern society heavily depends on technologies such as the internet, social media, and digital devices, it is reasonable to refer to todayAos society as a digital society (Fajriah & Ningsih, 2.
Consequently, consumer behavior has evolved, with many individuals now preferring to shop online rather than in physical stores.
This shift allows companies to sell products and services directly to consumers through online platforms, enabling them to reach a broader market at lower costs (Ardiansyah, 2.
Such shifts in consumer behavior have also transformed how businesses conduct promotion and advertising.
The internet has not only changed how people communicate and interact but has also influenced the promotional and advertising aspects of companies in Indonesia and around the world (Larasati et al.
, 2.
In terms of effectiveness, online marketing offers greater convenience, accessibility, and efficiency compared to offline marketing (Ainur et al.
, 2.
Social media has developed into a prominent and influential promotional channel.
In todayAos marketing landscape, companies are increasingly using social media influencers to convey their brand messages to targeted consumers (Susilawati & Solehatun, 2.
In line with this trend, influencers play an essential role in digital marketing by building strong connections between businesses and their audiences (Herman et al.
, 2.
The role of influencers has become a key marketing strategy, as they can present product reviews in an attractive, persuasive way that influences their followers (Syukur & Salsabila, 2.
Influencers tend to inspire a high level of trust among audiences (Anggoroningtyas & Adha, 2.
They build engagement and connection with their followers by sharing inspiring, entertaining, or informative content that strengthens their relationships (Larasati et al.
, 2.
In line with this perspective.
Takdirmin et al.
emphasize that influencer marketing within the digital marketing domain has been shown to expand market reach and boost sales.
Supporting this, surveys indicate that 87% of Indonesian consumers make purchasing decisions based on recommendations from influencers or celebrities (Kompas.
id, 2.
Despite the institutionalization of social media as a primary marketing channel, the efficacy of influencer-based promotions remains inconsistent, necessitating a deeper inquiry into the variables governing consumer response (Afrani et al.
, 2.
consumers develop heightened discernment toward commercial intent and sponsorship disclosures, the role of influencer credibility emerges as a critical, yet highly variable, determinant of promotional success (Wahab, 2.
Advertising serves as a strategic instrument to modulate consumer dispositions toward brands.
however, the activation of persuasion knowledgeAitriggered by the recognition of sponsored contentAifrequently elicits adverse psychological responses and undermines purchase intentions (Dermawan & Barkah, 2022.
Cheawkamolpat, 2.
This erosion of source credibility is particularly pronounced when explicit disclosures highlight commercial motives, thereby challenging the influencerAos perceived authenticity (Belanche et al.
, 2.
Given that influencer efficacy is predicated on high visibility and perceived credibilityAia attractivenessAithe mandatory transparency of modern digital ethics poses a strategic paradox (Deng et al.
, 2020.
Ramadani & Dwita, 2.
Ultimately, while credibility remains the primary driver of persuasive communication, the formal demarcation of paid collaborations can inadvertently trigger consumer resistance, diminishing the overall communicative impact and the fundamental influencer-follower relationship (Putri & Handriana, 2023.
Lee & Kim, 2.
Paradoxically, the contemporary digital landscape exhibits a confluence of paid and organic narratives, where followers frequently demonstrate a propensity to trust sponsored content if perceived credibility is maintained.
The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers Yessa Jovita Sugiharto1.
Auditia Setiobudi*1 Almana : Jurnal Manajemen dan Bisnis Volume 10 No.
1/ April 2026: 1-15 Consequently, the success of these digital strategies hinges on the psychological interplay between credibility and consumer attitude, which collectively drive recommendation intentions.
Within this context, influencer credibility emerges as a crucial factor shaping consumersAo perceptions of promoted products.
Such credibility is associated not only with the influencerAos expertise but also with their trustworthiness and attractiveness (Rohmatun et al.
, 2.
When consumers trust an influencer, they are more likely to believe the products promoted are high-quality and consistent with the claims made (Ramadani & Dwita, 2.
Furthermore.
Belanche et al.
note that product promotions by influencers whose styles align with the brandAos image can shape followersAo attitudes toward the influencer figure and perceived credibility.
This, in turn, generates various behavioral responses such as the intention to continue following, imitating, or recommending the influencer to others.
Attitude toward influencers represents a multifaceted psychological evaluationAicomprising beliefs, experiences, and emotionsAi regarding an influencerAos capacity to modulate consumer behavior (Rodhiah & Patricia.
Wadhwa & Chaihanchanchai, 2.
These evaluative dispositions are significantly bolstered by heightened perceived credibility and positive social validation from a followerAos interpersonal network (Belanche et al.
, 2021.
Ramadani & Dwita, 2.
Diverging from traditional brand-centric research, this investigation pivots toward influencer-oriented outcomes, specifically the "intention to recommend," defined as the follower's proclivity to endorse an influencerAos profile to their broader social network (Casaly et al.
, 2.
Thus, the cultivation of a positive attitude serves as a critical bridge between content consumption and active follower advocacy.
Accordingly, a clear research gap remains in the existing influencer marketing Despite the rapid institutionalization of influencer marketing, a significant research gap exists regarding the tension between the recognition of paid content and the subsequent advocacy behavior of followers.
While existing literature extensively explores how sponsorship disclosures affect brand purchase intentions, there is limited empirical evidence explaining how these commercial stimuli influence the intention to recommend the influencer themselves, particularly within the culturally nuanced digital landscape of Indonesia.
This study addresses this void by examining the psychological pathway from ad recognition to follower advocacy.
The research novelty lies in the integration of the StimulusAeOrganismAeResponse (SOR) framework to position paid communication recognition not merely as a transparency tool, but as a critical antecedent that operates through the dual mechanisms of source credibility and consumer attitude.
By focusing on a high-profile Indonesian megainfluencer, the study provides a unique contextual analysis of how credibility can mitigate the potential negative perceptions of "selling out.
" Accordingly, the research objectives are to analyze the direct and indirect impacts of paid communication and source credibility on recommendation intentions, and to elucidate the pivotal mediating role of consumer attitudes in bridging commercial stimuli with active follower advocacy.
LITERATURE REVIEW
The Stimulus-Organism-Response (SOR) theory explains that external stimuli .
can shape an individual's psychological state .
, which then results in a specific behavioural response .
(Liu et al.
, 2.
Within the scope of digital marketing, using the SAeOAeR framework, an influencerAos promotional post is positioned as the stimulus.
The organism component manifests through followersAo perceptions and evaluations of the influencer's credibility, recognition of sponsored content, and their general attitude toward the influencer.
The response is expressed through followersAo behavioural intention to continue recommending the influencer (Belanche et al.
, 2.
The use of the SOR framework allows for a more comprehensive understanding of how paid communications, influencer credibility, and audience attitudes contribute to the Website: http://journalfeb.
id/index.
php/almana/article/view/2986 Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 formation of recommendation intentions in the influencer marketing ecosystem (Wang et , 2.
Based on this theoretical framework, this study systematically formulates explicit hypotheses (H1AeH.
to examine the relationships among paid communication, influencer credibility, attitude toward the influencer, and intention to recommend the The conceptual framework of The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers is as follows:
Figure 1.
Research Model Source: Processed by the author .
Based on the introduction, theory, and previous research and referring to the research objectives, the following research hypothesis is proposed:
H1: Attitude Toward the Influencer has a positive effect on Intention to Recommend the Influencer.
H2: Influencer Credibility has a positive effect on Attitude Toward the Influencer.
H3: Paid Communication does not affect Attitude Toward the Influencer.
H4: Paid Communication negatively affects Influencer Credibility.
H5: Paid Communication has a significant indirect effect on Attitude Toward the Influencer through Influencer Credibility.
H6: Influencer Credibility has a significant indirect effect on Intention to Recommend the Influencer through Attitude Toward the Influencer.
H7: Paid Communication has a significant indirect effect on Intention to Recommend the Influencer through Influencer Credibility and Attitude Toward the Influencer.
H8: Paid Communication does not have a significant indirect effect on Intention to Recommend the Influencer through Attitude Toward the Influencer.
METHODS
This quantitative research method employs an online survey utilizing a five-point Likert scale to objectively examine the causal relationships between paid communication, influencer credibility, and consumer attitudes toward recommendation intentions (Waruwu et al.
, 2.
The study, conducted in Surabaya in 2025, focuses on followers of Rachel VennyaAia prominent Indonesian megainfluencer whose high engagement and frequent commercial collaborations provide a representative case for analyzing digital marketing dynamics.
A non-probability sampling method, namely purposive sampling, was used, in which respondents were intentionally selected according to predefined inclusion criteria aligned with the research objectives (Subhaktiyasa, 2.
A sample of 160 respondents was recruited, satisfying HairAos methodological criterion of 5 to 10 participants per measurement indicator for the 16 The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers Yessa Jovita Sugiharto1.
Auditia Setiobudi*1 Almana : Jurnal Manajemen dan Bisnis Volume 10 No.
1/ April 2026: 1-15 items analyzed.
With 16 indicators used in this study, an appropriate sample size ranged from 80 to 160 respondents to ensure statistical adequacy and measurement reliability.
Data analysis was executed via Partial Least SquaresAeStructural Equation Modeling (PLS-SEM) using SmartPLS 3.
This method was selected for its superior capacity to evaluate complex, multi-layered variable relationships and its distributional flexibility, making it an ideal instrument for predictive and exploratory behavioral research.
Accordingly, the use of purposive sampling and the determination of the respondent size were methodologically justified to ensure that the selected participants possessed relevant exposure to influencer marketing activities, while PLS-SEM was deemed appropriate given the studyAos emphasis on examining both direct and indirect effects within a predictive research framework.
RESULTS AND DISCUSSION
Based on research conducted with 160 respondents, respondent characteristics were identified, including name, gender, age, occupation, domicile, and other questions, as outlined in this research.
Table 1.
Characteristics of Respondents Gender Amount Man Woman Age Amount 13 - 20 Year 21 - 28 Year 29 - 36 Year 37 - 44 Year > 44 Year Occupation Amount Entrepreneur Student Civil Servant Private Employee Housewife Domicile Amount West Surabaya Central Surabaya South Surabaya East Surabaya North Surabaya What social media do you use often? Amount Instagram TikTok Youtube Frequency of social media use per day? Amount < 1 Hour 1 - 2 Hour 3 - 4 Hour 5 - 6 Hour > 6 Hour Source: Results of processing by the author .
The demographic analysis reveals a predominantly female cohort .
%), with a primary age concentration in the young adult bracket of 21Ae36 years .
%) and the 13Ae 20 youth category .
%).
Occupationally, the sample is characterized by a high representation of students .
%) and private employees .
%), distributed relatively Website: http://journalfeb.
id/index.
php/almana/article/view/2986 Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 evenly across SurabayaAos West and Central districts .
% eac.
Regarding digital consumption patterns.
TikTok emerged as the most prevalent platform .
%), followed by Instagram .
%), with a significant plurality of respondents maintaining high levels of daily engagement, typically ranging from 3 to 4 hours .
%).
Collectively, these data points reflect a young, urban, and digitally active participant base suitable for investigating modern influencer marketing dynamics.
Outer Loading and AVE Validity Test To evaluate the study's validity, the researchers employed both convergent and discriminant validity.
Convergent validity in the reflective measurement model is assessed by examining the correlations among individual indicators and their corresponding constructs, as reflected in the outr loadings calculated in Smart PLS 3.
Figure 2.
Structural Equation Modelling Source: Results of processing by the author .
In Figure 2, the results of convergent validity testing can be seen using each indicator in each variable, namely PC9.
PC10, and PC11 (Paid Communicatio.
ATI1.
ATI3.
ATI5.
ATI6.
ATI7.
ATI9, and ATI11 (Attitude Toward The Influence.
IC1.
IC3.
IC5.
IC6.
IC8.
IC9.
IC10, and IC11 (Influencer Credibilit.
IR1.
IR3.
IR4.
IR5.
IR6.
IR7, and IR9 (Intention to Recommend the Influence.
The convergent validity of this instrument is assessed through a factor-loading analysis, in which factor loadings must exceed 0.
to be considered valid (Maulana et al.
, 2.
Outer loading > 0.
60 is acceptable in the early stages (Kante & Michel, 2.
The results of the outer loading analysis are elaborated in Table 2.
Table 2.
Outer Loadings Items Paid
Communication PC9
PC10
PC11
ATI1
ATI3
Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Desc Valid Valid Valid Valid Valid The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers Yessa Jovita Sugiharto1.
Auditia Setiobudi*1 Almana : Jurnal Manajemen dan Bisnis Volume 10 No.
1/ April 2026: 1-15
Items Paid
Communication ATI5
ATI6
ATI7
ATI9
ATI11
IC1
IC3
IC5
IC6
IC8
IC9
IC10
IC11
IR1
IR3
IR4
IR5
IR6
IR7
IR9
Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Desc Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Source: Results of processing by the author .
Based on the empirical evidence presented in Table 2, the convergent validity of the measurement model is confirmed.
All reflective indicators for Paid Communication.
Attitude Toward the Influencer.
Influencer Credibility, and Intention to Recommend the Influencer attained outer loadings exceeding the 0.
60 benchmark.
Furthermore, the Average Variance Extracted (AVE) for each construct surpassed the critical threshold of 50, demonstrating that the latent variables account for a majority of the variance in their respective indicators (Fahmi et al.
, 2.
A comprehensive summary of the AVE values is detailed in Table 3.
Table 3.
Average Variance Extracted Construct Average Variance Extracted (AVE) Paid Communication Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Source: Results of processing by the author .
Desc Valid Valid Valid Valid According to Table 3, all constructs.
Paid Communication.
Attitude Toward the Influencer.
Influencer Credibility, and Intention to Recommend the Influencer, demonstrate AVE values greater than 0.
50, thereby satisfying the convergent validity CronbachAos Alpha and Composite Reliability Test Reliability represents the degree to which a scale produces stable and consistent Higher reliability indicates a lower standard error of measurement (Liu et al.
An instrument is considered reliable when repeated measurements of the same construct yield identical or nearly identical results.
In this research, reliability testing was performed to assess the accuracy and consistency of the measurement instrument across all constructs.
Using the Partial Least Squares (PLS) approach, reliability was Website: http://journalfeb.
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php/almana/article/view/2986 Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 examined through two primary indicators: composite reliability and CronbachAos alpha for each indicator block.
Overall, the reliability assessment suggests that measurement consistency is acceptable when the CronbachAos alpha coefficient () attains a value of 50 or above.
Conversely, composite reliability (CR) is regarded as sufficient when CronbachAos alpha exceeds the minimum threshold of 0.
70 (Fahmi et al.
, 2.
The summary of composite reliability and CronbachAos alpha results is presented in Table 4.
Table 4.
Composite Reliability and CronbachAos Alpha Values Variable CronbachAos Composite Alpha Reliability Paid Communication Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Source: Results of processing by the author .
Desc Reliable Reliable Reliable Reliable Referring to the findings presented in Table 4, the summary of the instrument reliability assessment indicates that every construct within the Paid Communication.
Attitude Toward the Influencer.
Influencer Credibility, and Intention to Recommend the Influencer demonstrates composite reliability values above 0.
70 and CronbachAos alpha coefficients of no less than 0.
Accordingly, all constructs can be considered to possess adequate and robust reliability.
Discriminant Validity Test Table 5.
Cross Loadings Items PC9
PC10
PC11
ATI1
ATI3
ATI5
ATI6
ATI7
ATI9
ATI11
IC1
IC3
IC5
IC6
IC8
IC9
IC10
IC11
IR1
IR3
IR4
IR5
IR6
IR7
IR9
Paid Attitude Toward Influencer Intention To Recommend Communication the Influencer Credibility the Influencer Source: Results of processing by the author .
The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers Yessa Jovita Sugiharto1.
Auditia Setiobudi*1 Almana : Jurnal Manajemen dan Bisnis Volume 10 No.
1/ April 2026: 1-15 Based on Table 5, all indicator items show cross-loading values above 0.
60, and each indicatorAos loading is higher than its cross-loadings on other constructs.
These results demonstrate that the outer model meets the required criteria and that discriminant validity is established correctly.
Table 6.
Heterotrait-Monotrait Ratio (HTMT) Variable Attitude Influencer Intention To Paid Toward the Credibility Recommend the Communication Influencer Influencer Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Paid Communication Source: Results of processing by the author .
Based on the HTMT output, all correlation values between constructs are below the HTMT tolerance limit of <1.
00: Attitude Toward the Influencer and Influencer Credibility .
Attitude Toward the Influencer and Intention to Recommend .
Influencer Credibility and Intention to Recommend .
, and Paid Communication with other constructs .
535Ae0.
Although some values are close to 1, they still meet the requirements for discriminant validity because HTMT is considered valid as long as the value is clearly below 1.
00 and does not exceed the upper limit of its confidence interval, as emphasized by (Mentari & Hendayani, 2.
The HTMT values approaching 1 for several construct relationships, such as Attitude Toward the Influencer.
Influencer Credibility, and Intention to Recommend the Influencer, indicate that these variables are theoretically closely related, making the high correlation values reasonable within the context of this study.
Inner Model Test The structural .
model specifies how latent variables are interconnected within the underlying theoretical framework.
Its evaluation involves examining the Rsquare values of endogenous constructs, assessing predictive capability through the StoneAeGeisser Q-square measure, and analyzing the t-statistics and significance levels of the structural path coefficients (Gunawan et al.
, 2.
Table 7.
R-Square and Adjusted R-Square Variable R-Square R-Square Adjusted Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Source: Results of processing by the author .
The structural model evaluation reveals varying degrees of explanatory power across the endogenous variables.
Attitude Toward the Influencer exhibits the highest predictive accuracy with an RA of 0.
729 (Adjusted RA = 0.
, indicating that the predictors explain 72.
6% of its variance.
Intention to Recommend follows with a moderate RA of 0.
679 (Adjusted RA = 0.
, signifying that 67.
7% of its variability is accounted for by the model.
In contrast.
Influencer Credibility demonstrates weak explanatory power (RA = 0.
Adjusted RA = 0.
, suggesting that 87.
3% of its variance is influenced by external factors beyond the current study's scope.
Overall, the model provides substantial insights into attitude and recommendation intentions, while Website: http://journalfeb.
id/index.
php/almana/article/view/2986 Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 the low RA for credibility indicates a need for additional antecedents in future research.
Gunawan et al.
explained that the assessment of a PLS structural model utilizes the R-Square (RA) values of endogenous constructs to evaluate predictive capability and the substantive effects of exogenous variables.
RA values of 0.
75, 0.
50, and 0.
represent strong, moderate, and weak levels of model accuracy, respectively, indicating the proportion of variance explained by the model.
Table 8.
F Square Variable Attitude Influencer Toward the Credibility Influencer Intention To Recommend the Influencer Paid Communication Attitude Toward the Influencer Influencer Credibility Intention To Recommend the Influencer Paid Communication Source: Results of processing by the author .
Based on the effect sizes .
A) shown in the table 8.
Influencer Credibility makes a substantial contribution to Attitude Toward the Influencer .
A = 2.
and to Intention to Recommend .
A = 2.
, confirming its dominant role in the model.
In contrast.
Paid Communication has a negligible effect on Attitude Toward the Influencer .
A = 0.
and a small to moderate effect on Influencer Credibility .
A = 0.
Referring to the fA criteria proposed by Guenther et al.
, namely small .
, medium .
, and large .
or mor.
, these findings indicate that Influencer Credibility plays a substantive role in shaping endogenous variables, while the contribution of Paid Communication is relatively limited.
This means that the higher the fA value, the greater the construct's influence on the structural model.
The fA test is employed to evaluate the magnitude of a constructAos influence on another construct by examining changes in the RA value, thereby indicating the extent to which predictor variables affect the dependent variable within the research model (Leonardo & Wijoyo, 2.
Table 9.
Path Coefficients Hypothesis Original Sample Standard T Statistics P Values Sample Mean (M) Deviation (|O/STDEV|) (O) (STDEV) Attitude Toward the Influencer -> Intention to Recommend the Influencer Influencer Credibility -> Attitude Toward the Influencer Paid Communication -> Attitude Toward the Influencer Paid Communication -> Influencer Credibility Source: Results of processing by the author .
Result Supported Supported Rejected Supported The path coefficient indicates the strength of the relationship or influence among latent constructs (Fathonah & Zulganef, 2.
The structural model assessment, as detailed in Table 9, reveals varying degrees of influence among the hypothesized The results indicate that the association between Attitude Toward the The Mediating Role of Attitude: How Paid Communication and Source Credibility Influence the Intention to Recommend Digital Influencers Yessa Jovita Sugiharto1.
Auditia Setiobudi*1 Almana : Jurnal Manajemen dan Bisnis Volume 10 No.
1/ April 2026: 1-15 Influencer and Intention to Recommend the Influencer represents the most substantial relationship within the model, yielding a predominant path coefficient of beta = 0.
Conversely, the influence of Paid Communication on Attitude Toward the Influencer was identified as the weakest structural linkage, characterized by a marginal coefficient of beta = 0.
These findings suggest that internal follower dispositions exert a significantly higher relative impact on recommendation intentions than external communication efforts.
Saskara & Achmad .
stated that a relationship is considered statistically significant when the P-Value is below 0.
05, and the T-Statistic exceeds 1.
Consistent with this view.
Belanche et al.
highlight that favorable attitudes toward influencers are likely to enhance individualsAo intentions to recommend them to others.
The results of the partial effect analysis indicate that Attitude Toward the Influencer has a significant impact on the Intention to Recommend the Influencer (H.
This is evidenced by a TStatistic value of 27.
666 and a P-Value of 0.
000, which meets the required significance thresholds, thereby confirming that H1 is supported.
Furthermore, findings from Bakar et .
demonstrate that the credibility dimension, namely Influencer Credibility, positively influences attitudes towards Influencers.
Based on Table 9.
Influencer Credibility significantly affects Attitude Toward the Influencer (H.
, with a T-Statistic of 102 and a P-Value of 0.
000, supporting H2.
Research by Putri & Handriana .
suggests that when influencers are perceived as credible and trustworthy, a stronger relationship forms, leading to a more positive consumer attitude toward the influencer.
Conversely, the empirical results indicate that Paid Communication does not exert a statistically significant influence on Attitude Toward the Influencer, leading to the rejection of H3.
This lack of significance is evidenced by a T-statistic of 1.
361 and a Pvalue of 0.
174, both of which fail to meet the conventional critical thresholds .
pecifically, t > 1.
96 and p < 0.
Consequently, the data fail to provide sufficient evidence to support the hypothesized relationship, suggesting that promotional stimuli may not be the primary driver of follower attitudes in this context.
Finally, the analysis reveals that Paid Communication exerts a statistically significant positive influence on Influencer Credibility, thereby providing robust empirical support for H4.
This relationship is substantiated by a T-statistic of 5.
296 and a P-value of 0.
< 0.
, both of which comfortably surpass the established significance thresholds.
Paradoxically, this finding diverges from the scholarship of Belanche et al.
, who contended that the overt nature of promotional content might undermine the perceived trustworthiness and expertise of an influencer.
The current results suggest that, in this specific context, paid disclosures may not necessarily trigger skepticism but could instead be viewed as a signal of professional legitimacy.
Table 10.
Specific Indirect Effects Hypothesis Paid Communication -> Influencer Credibility -> Attitude Toward the Influencer Influencer Credibility -> Attitude Toward the Influencer -> Intention to Recommend the Influencer Paid Communication -> Influencer Credibility -> Attitude Toward the Original Sample Standard T Statistics P Values Sample Mean Deviation (|O/STDEV|) (O) (M) (STDEV) Result Supported Supported Supported Website: http://journalfeb.
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php/almana/article/view/2986 Almana : Jurnal Manajemen dan Bisnis Hypothesis p-ISSN: 2579-4892 e-ISSN: 2655-8327 Original Sample Standard T Statistics P Values Sample Mean Deviation (|O/STDEV|) (O) (M) (STDEV) Influencer -> Intention to Recommend the Influencer Paid Communication -> Attitude Toward the Influencer -> Intention to Recommend the Influencer Source: Results of processing by the author .
Result Rejected Referring to Table 10, the analysis reveals multiple forms of indirect relationships among the variables.
The first indirect pathway shows that Paid Communication influences Attitude Toward the Influencer via Influencer Credibility, as reflected by a TStatistic of 5.
428 and a P-Value of 0.
000, which is below the 0.
05 significance level, thereby confirming H5.
In addition.
Influencer Credibility exerts an indirect effect on Intention to Recommend the Influencer through Attitude Toward the Influencer, as evidenced by a T-Statistic of 13.
077 and a P-Value of 0.
000, supporting H6.
Furthermore.
Paid Communication demonstrates a serial mediation effect on Intention to Recommend the Influencer via Influencer Credibility and Attitude Toward the Influencer, with a TStatistic of 5.
455 and a P-Value of 0.
000, supporting H7.
In contrast, the indirect effect of Paid Communication on Intention to Recommend the Influencer, mediated solely by Attitude Toward the Influencer, is not statistically significant, as indicated by a T-Statistic 380 and a P-Value of 0.
168, leading to the rejection of H8.
Overall, these results suggest that most indirect effects are statistically meaningful, particularly those involving Influencer Credibility and Attitude Toward the Influencer as mediating variables, underscoring their pivotal role in influencing followersAo intentions to recommend an CONCLUSION The Structural Equation Model (SEM) results demonstrate robust relationships across the latent variables.
Influencer Credibility emerges as a significant predictor of Attitude Toward the Influencer.
This finding underscores that the perceived quality, trustworthiness, and expertise attributed to the influencer are the primary drivers of favorable consumer attitudes, accounting for a large proportion of variability in the outcome variable.
Conversely, the direct path from Paid Communication to Attitude Toward the Influencer exhibits a negligible coefficient, suggesting that the mere fact that the communication is paid has limited direct explanatory power for attitude formation compared to the underlying credibility factor.
Crucially, the model reveals that Attitude Toward the Influencer is the most powerful antecedent for Intention to Recommend the Influencer, evidenced by the exceptionally high path coefficient.
This indicates that a positive affective evaluation of the influencer effectively translates into a firm behavioral intention to advocate and recommend among consumers.
However, these findings cannot be fully generalized and may yield different results when applied to other influencers or research contexts.
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