Digital Business Journal (DIGIBIS) Volume 4 No.
Hal: 60 - 68
E-ISSN 2963-8585
DOI:10.
31000/digibis.
The Role of AI-Based Content Marketing and User-Generated Content (UGC) on Brand Equity : The Mediating Effect of Value Co-Creation Meydy Fauziridwan1*.
Rhis Ogie Dewandaru 2.
Muhammad Aufa Fatih F3.
Karunia Lestari4
1,2,3,4
Universitas Muhammadiyah Purwokerto.
Purwokerto.
Indonesia e-mail: meydy.
fauziridwan@gmail.
com, 2rhis.
d@gmail.
com, 3aufaabusiness@gmail.
lestari12@gmail.
Diterima 20-09-2025 Direvisi 13-01-2026 Disetujui 31-01-2026 Abstrak - In the era of digital transformation, small businesses such as local cafys are increasingly leveraging artificial intelligence (AI) and user-generated content (UGC) to enhance brand engagement.
This study investigates the effects of AI-based content marketing and UGC on brand equity, with value co-creation as a mediating variable.
The research was conducted using a quantitative approach, with data collected from 200 customers of a local cafy in Purwokerto.
Indonesia.
The analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM).
The results show that AI-based content marketing has a significant direct effect on brand equity, but does not significantly influence value co-creation.
Conversely.
UGC significantly enhances value co-creation but does not directly affect brand equity.
Moreover, value co-creation is found to mediate the relationship between UGC and brand equity, while no mediation effect is observed in the path from AI-based content marketing.
These findings highlight the importance of participatory and collaborative digital strategies in fostering strong brand equity within micro and small enterprises.
This study contributes to the theoretical understanding of service-dominant logic and brand equity in the digital context and offers practical insights for MSMEs to integrate AI tools with community engagement strategies to build sustainable brand value.
Kata Kunci: AI-based content marketing, user-generated content, value co-creation, brand equity.
PLS-SEM.
MSMEs
INTRODUCTION
Over the past decade, digital transformation has transformed the way brands interact with consumers.
This change has been accelerated by the advent of Artificial Intelligence (AI) technology, which enables automation, personalization, and large-scale distribution of digital For small and medium-sized enterprises (SME.
, particularly micro-enterprises like local cafes, digital platforms have become a vital tool for gaining visibility, building engagement, and maintaining a presence in a competitive marketplace.
Brand evaluations now focus not only on product quality but also on digital narratives, emotional connection, and audience engagement in the brand's online communications (France.
Davcik, & Kazandjian.
Content marketing and User-Generated Content (UGC) are two key approaches driving this shift.
Content marketing refers to the creation and distribution of valuable content aimed at attracting and retaining audiences (Hollebeek & Macky, 2.
Today, content marketing has been enhanced by AI, enabling efficiency and scalability.
On the other hand.
UGC includes content voluntarily created by consumers, such as reviews, photos, or videos related to a brand, which is considered to be highly authentic and builds trust (Ashley & Tuten, 2.
These two strategies reflect a shift from one-way communication to brand-consumer collaboration in shaping shared experiences, as emphasized in the concept of value co-creation (Prahalad & Ramaswamy, 2.
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Hal: 60 - 68
E-ISSN 2963-8585
DOI:10.
31000/digibis.
However, challenges arise when the efficiency of AI can potentially undermine perceptions of brand authenticity.
Bruns & Meibner .
caution that AI-based content, while efficient, can be perceived as less human if it lacks emotional elements.
Therefore.
UGC is increasingly relied upon to balance efficiency with authenticity in digital communications, particularly among SMEs.
Unfortunately, research examining the synergy between AI content marketing and UGC on brand equity, particularly in the context of micro-businesses in developing countries, is still very limited.
This study aims to address this gap by examining the effect of AI-based content marketing and UGC on brand equity, with value co-creation as a mediating variable.
The study focused on a local cafe in Purwokerto.
Indonesia, to provide empirical context for the dynamics of SME digital marketing.
The research's contributions include: .
integrating AI content marketing and UGC into a brand equity formation model, .
exploring value co-creation as a balance between technological efficiency and communication authenticity, and .
providing empirical evidence from the perspective of micro-businesses in emerging markets.
This finding is expected to broaden the understanding that brand equity is now formed collaboratively through interactions between business actors and their communities, not just by companies unilaterally.
Based on the background outlined above, the following research questions emerge: .
How does AI-Based Content Marketing influence brand equity in local cafes? .
How does User-Generated Content (UGC) influence brand equity? .
Does Value Co-Creation mediate the relationship between AI-Based Content Marketing and brand equity? .
Does value cocreation mediate the relationship between UGC and brand equity? AI-Based Content Marketing The development of Artificial Intelligence (AI) has brought about fundamental changes in the digital content marketing landscape.
This transformation has been made possible through the automation of the creation, personalization, and distribution of promotional content by AIbased systems.
Research by Qin and Jiang .
explained that AI-based content systems enable communication optimization through predictive analysis and adaptive content However, findings by Bryns and Meiyner .
warned that the use of entirely AI-generated content risks diminishing the perception of brand authenticity if not balanced with a human touch.
Therefore, a strategic integration of technology and emotional value in content marketing is necessary.
User-Generated Content (UGC) User-generated content (UGC) has been recognized as a more authentic and trustworthy form of digital promotion than company-produced content.
According to Ashley and Tuten .
UGC plays a crucial role in increasing consumer trust, particularly in social media In service sectors such as cafes and restaurants, visual content in the form of food photos, customer reviews, or interaction videos has been shown to shape brand perceptions positively (Wang et al.
, 2.
Furthermore.
France et al.
explained that UGC directly contributes to the formation of digital brand equity by increasing consumer engagement with the brand.
Because it is voluntarily generated by customers, this content is perceived as more authentic and powerful in generating social proof that expands a brand's reach and credibility.
Value Co-Creation The concept of value co-creation has been positioned as a collaborative approach between companies and customers in shaping brand experiences.
A study by Prahalad and Ramaswamy .
emphasized that value is no longer solely created internally by companies, but is also formed through interactions and dialogue with consumers.
In a digital context, forms of value co-creation can be realized through mechanisms such as interactive polls, re-uploading customer content, or customer involvement in product design.
This concept is reinforced by http://jurnal.
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Vargo and Lusch's .
Service-Dominant Logic approach, which states that value creation is the result of active collaboration between service providers and users.
In the digital context, value co-creation can be realized through mechanisms such as interactive polls, reposting customer content, or customer involvement in product design.
study by Qiao and Liu .
demonstrated that these practices can increase customers' emotional engagement with the brand.
Sarmento et al.
also added that this shared value can drive innovation and long-term loyalty.
Brand Equity Brand equity has traditionally been defined by Aaker .
as the added value a brand provides to a product.
The main dimensions proposed include brand awareness, perceived quality, loyalty, and brand associations.
In the context of digital marketing.
France et al.
proposed that brand equity measurement should be expanded to include digital indicators such as search visibility, online engagement, and consumer digital sentiment.
Research by Oliveira Neto et al.
shows that digital branding strategies combined with the use of AI and customer participation can have a significant impact on business performance, especially in emerging markets.
Therefore, understanding brand equity is no longer sufficient if it is only based on traditional dimensions, but also needs to reflect consumers' digital engagement and Theoretical Framework and Conceptual Model The theoretical foundation of this study integrates perspectives from digital content marketing, consumer engagement, and brand equity literature, particularly within the context of micro-enterprises operating in a digitally mediated environment.
The framework is rooted in Service-Dominant Logic (S-D Logi.
(Vargo & Lusch, 2.
, which emphasizes that value is co-created collaboratively between firms and consumers, rather than delivered unilaterally.
Within this framework.
AI-based content marketing is viewed as a technological enabler that enhances the firm's capacity to deliver relevant and timely content to its audience.
However, as Bryns and Meiyner .
caution, excessive reliance on AI-generated content may lead to perceived inauthenticity unless it is combined with human engagement and emotional To mitigate this risk, firms often complement AI efforts with User-Generated Content (UGC) which, as per Ashley and Tuten .
, increases perceived credibility and trust among consumers.
Value co-creation is posited as a mediating mechanism that bridges firm-generated and consumer-generated content strategies with brand equity outcomes.
When consumers actively contribute through content creation, feedback, or brand interactions, they co-produce value that enhances their emotional attachment to the brand (Prahalad & Ramaswamy, 2004.
Qiao & Liu.
This engagement not only reinforces brand identity but also strengthens key brand equity dimensions, including awareness, perceived quality, and loyalty (Aaker, 1991.
France et al.
The conceptual model therefore assumes that both AI-based content marketing and UGC have direct effects on brand equity, as well as indirect effects mediated by value cocreation.
This model will be empirically tested in the context of Arastas Alpha Coffee Shop, where digital strategies are implemented with limited resources but high consumer interaction.
Hypothesis:
H1: AI-Based Content Marketing has a positive effect on Brand Equity.
H2: User-Generated Content (UGC) has a positive effect on Brand Equity.
H3: AI-Based Content Marketing has a positive effect on Value Co-Creation.
H4: User-Generated Content (UGC) has a positive effect on Value Co-Creation.
H5: Value Co-Creation has a positive effect on brand equity.
H6: Value Co-Creation mediates the effect of AI-Based Content Marketing on Brand Equity.
H7: Value Co-Creation mediates the effect of User-Generated Content (UGC) on Brand Equity.
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METHODOLOGY
Type of Research This study employed quantitative research, which can be defined as a research method based on the philosophy of positivism, used to examine a specific population or sample.
Data collection utilizes research instruments and quantitative/statistical data analysis, with the aim of testing a predetermined hypothesis (Sugiyono, 2.
In this study, the type of research used was explanatory research.
According to Sugiyono .
, explanatory research is research that explains the causal relationship between variables that influence a hypothesis.
In this research, there are at least two variables connected, and this research serves to explain, predict, and control a phenomenon.
Data Collection Sugiyono .
states that a population is a generalized area consisting of objects or subjects with certain qualities and characteristics determined by the researcher to be studied and then conclusions drawn.
Determining the population size can facilitate drawing a sample to be used as a data source.
In this study, the population size could not be precisely determined, so the author chose a non-probability sampling method with an accidental sampling technique.
According to Sugiyono .
, accidental sampling is a sampling technique based on chance.
anyone who happens to meet the researcher can be used as a sample if they are deemed suitable as a data Based on calculations by Hair et al.
, the sample size was 95 respondents.
This was due to time and cost constraints.
Furthermore, the data processing technique used in this study was SEM-PLS, as explained by Yamin & Kurniawan .
who stated that PLS is more moderate in terms of sample size, namely a minimum of 30-100 samples.
RESULT AND DISCUSSION
Description of Data and Respondents This study involved respondents from active consumers of a local cafe in Purwokerto who were exposed to digital content both through social media and direct interactions.
The total number of respondents analyzed was 200 respondent, with the questionnaire distributed through a purposive sampling method.
The collected data were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with the help of SmartPLS 4.
0 software.
Convergent Validity (Outer Loading.
All indicators showed an outer loading value > 0.
70, indicating that each indicator has a sufficient contribution in representing its respective construct.
For example: AI-BCM1 .
BE3 .
UGC2 .
, and VC3 .
showed a high level of correlation with their parent constructs.
Construct Validity and Reliability The results of the Construct Reliability and Validity tests show that all constructs meet the requirements of Cronbach Alpha > 0.
Composite Reliability (CR) > 0.
7, and Average Variance Extracted (AVE) > 0.
Thus, the constructs are declared valid and reliable.
Construct
AI-BCM
UGC
Source : SmartPLS 4.
http://jurnal.
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AVE
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R-Square (RA) and Model Predictive Power The RA results indicate that the Value Co-Creation (VC) construct can be explained by the AI-BCM and UGC variables by 28.
6%, while Brand Equity (BE) is explained by the three constructs by 18.
This indicates the model's predictive power is at a moderate level.
Construct Source : SmartPLS 4.
Results of Direct Hypothesis Testing (Direct Effec.
Hypothesis testing was conducted based on the T-statistic and P-value.
Significance was determined at = 0.
Hypothesis Track Coef.
T-Statistic P-Value Information AI-BCM Ie BE 1,808 Accepted UGC Ie BE Rejected AI-BCM Ie VC
1,368
Rejected UGC Ie VC
2,365
Accepted VC Ie BE Rejected Source : SmartPLS4.
Mediation Test Results (Indirect Effec.
To determine whether a mediation effect occurs, a test is carried out on the indirect effect of the path:
THypothess Mediation Path Coef.
Statistic P-Value Information AI-BCM Ie VC Ie BE Rejected UGC Ie VC Ie BE Accepted Source : SmartPLS 4.
Interpretation of Results H1 (Accepte.
: AI-Based Content Marketing has a significant direct effect on brand equity.
This suggests that automated digital content .
AI-generated captions, visual post.
positively enhances consumersAo perception of the brand.
H2 (Rejecte.
: User-Generated Content (UGC) does not directly impact brand equity, indicating that UGC alone is not sufficient to shape brand perceptions.
H3 (Rejecte.
: AI-based content does not significantly drive value co-creation.
limited consumer interaction despite content automation.
H4 (Accepte.
: UGC positively influences value co-creation, meaning consumer-generated content contributes to customer participation and mutual brand engagement.
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H5 (Rejecte.
: Value co-creation does not have a significant direct impact on brand equity within this model.
H6 (Rejecte.
: Although AI-based content has a direct effect on brand equity, the indirect pathway via value co-creation is not significant, meaning AI content does not meaningfully foster participatory customer experiences.
H7 (Accepte.
: UGC positively influences brand equity through the mediation of value cocreation.
This supports the idea that user-driven content becomes impactful only when it fosters active consumer-brand interaction.
Discussion The findings of this study indicate that AI-Based Content Marketing has a positive and direct effect on consumersAo brand equity.
This result aligns with previous studies by Hollebeek and Macky .
and Feuerriegel et al.
, which highlight that digital content that is relevant, scheduled, and personalized can enhance perceived quality and the clarity of brand In the context of MSMEs such as local cafys.
AI-based content allows businesses to deliver consistent messaging without requiring extensive resources, thereby supporting efficient brand recognition and trust.
However, the effect of AI-Based Content Marketing on value co-creation was found to be statistically insignificant.
This can be explained by the Service-Dominant Logic (Vargo & Lusch, 2.
, which emphasizes that value is not created solely by the firm but emerges from interaction between providers and consumers.
Highly automated AI content, although efficient, tends to be one-directional and lacks the interactive elements that enable consumer This finding echoes Bryns and MeiynerAos .
argument that the use of AIgenerated content should be balanced with elements that foster emotional connection and a human touch to preserve brand authenticity.
In contrast.
User-Generated Content (UGC) does not directly affect brand equity, but it has a significant influence on value co-creation.
UGC in the form of reviews, photos, or testimonials creates a collaborative space between consumers and brands.
This supports findings by Ashley and Tuten .
and France et al.
, who argue that organic content created by customers enhances authenticity and emotional engagement.
Through co-creation mechanisms, consumers feel as though they are part of the brand narrative, meaning that brand value is shaped not only by company-led messages but also by the contributions of the The significant mediating effect of value co-creation in the relationship between UGC and brand equity reinforces the notion that active consumer participation is crucial in shaping brand perception in the digital era.
As noted by Sarmento et al.
, co-creation not only enhances loyalty but also enriches the brand experience through processes of sharing, creating, and co-building.
Conversely, because AI-based content is more passive and driven by the company, its contribution to co-creation is limited.
Thus, although AI content can strengthen brand perception directly, the mediating pathway through value co-creation is not supported in this In conclusion, the study suggests that community-driven and collaborative strategies (UGC Ie VC Ie BE) offer more sustainable long-term impacts compared to fully automated content strategies.
CONCLUSION
Conclusion Based on the analysis and discussion conducted in this study, several key findings can be summarized as follows: .
AI-Based Content Marketing has a positive effect on Brand Equity.
These results indicate that the use of strategically designed content supported http://jurnal.
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by artificial intelligence can improve consumer perceptions of local cafe brands.
UserGenerated Content (UGC) does not directly impact Brand Equity.
However.
UGC has a significant influence on Value Co-Creation, which ultimately influences the formation of Brand Equity indirectly.
Value co-creation has not been shown to mediate the relationship between AI-based content marketing and brand equity.
This means that while AI-based content can improve brand perception, it does not do so through the mechanism of active customer .
Value co-creation has been shown to be a significant mediator in the relationship between UGC and brand equity.
This suggests that UGC only impacts a brand if customers feel actively involved in co-creating experiences or value with the brand.
These findings provide insight that, in the context of local cafe marketing, a communitybased approach and customer participation .
hrough UGC and value co-creatio.
play a stronger role in shaping brand perception than a purely content-automated approach.
Implications The results of this study offer several practical implications:
MSMEs or local cafe owners should develop content strategies that encourage customer participation, such as inviting them to share experiences, offering testimonials, and uploading AI-Based Content Marketing strategies remain important for maintaining visual and informational consistency, but need to be integrated with interactive elements to spark two-way Customer engagement through value co-creation should be a primary focus in building long-term brand loyalty and value.
Research Limitations This study has several limitations that should be considered:
The research was limited to one geographic area (Purwokert.
and two local cafes, so the results cannot necessarily be broadly generalized.
Data was collected using a nonprobability sampling technique, which could potentially introduce respondent bias.
The use of a single mediating variable (Value Co-Creatio.
opens up opportunities for exploration of multiple mediation or moderation of external variables such as customer involvement or trust.
Recommendation Involve a broader and more varied audience, such as various types of MSMEs in the F&B sector or the creative industry.
Add moderating variables such as Customer Engagement.
Digital Trust, or Customer Satisfaction.
Combine quantitative and qualitative approaches .
ixed-method.
to delve deeper into customer perceptions of co-creation and digital content.
By refining this approach, further research is expected to provide a stronger contribution to developing effective and sustainable digital-based marketing strategies for MSMEs.
REFERENCES