Peran Persepsi Generative Artificial Intelligence dalam Memediasi Pengaruh Digital Presence Terhadap Brand Visibility Mall di Bali pada Konteks Ai-Based Search

Ida Bagus Gede Prabawa Putra Udiyana; I Gusti Ayu Agung Istri Dinda Larasshanti Jelantik; Anak Agung Ayu Rika Putri Supartha; I Gusti Ayu Widya Ari Cahyathi; Ni Putu Dhanan Kumaradewi M

doi:10.55681/sentri.v5i5.6202

Authors

Ida Bagus Gede Prabawa Putra Udiyana Fakultas Ekonomi dan Bisnis, Universitas Pendidikan Nasional
I Gusti Ayu Agung Istri Dinda Larasshanti Jelantik Fakultas Ekonomi dan Bisnis, Universitas Pendidikan Nasional
Anak Agung Ayu Rika Putri Supartha Fakultas Ekonomi dan Bisnis, Universitas Pendidikan Nasional
I Gusti Ayu Widya Ari Cahyathi Fakultas Ekonomi dan Bisnis, Universitas Pendidikan Nasional
Ni Putu Dhanan Kumaradewi M Fakultas Ekonomi dan Bisnis, Universitas Pendidikan Nasional

DOI:

https://doi.org/10.55681/sentri.v5i5.6202

Keywords:

Digital Presence, Brand Visibility, Generative Artificial Intelligence, AI-Based Search, Perceived Usefulness, Perceived Trustworthiness

Abstract

This study aims to analyze the mediating role of perceived generative artificial intelligence in the relationship between digital presence and brand visibility of shopping malls in Bali within the context of AI-based search. The research adopts a quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) with a sample of 130 mall visitors in Bali who have experience using AI-based search tools such as ChatGPT and similar platforms. The findings reveal that digital presence has a positive and significant effect on brand visibility, both directly and indirectly through perceived usefulness and perceived trustworthiness. However, the direct effect of digital presence is relatively weaker compared to the mediated effects, indicating that brand visibility is not formed linearly but through a cognitive information processing mechanism influenced by AI perception. Perceived trustworthiness shows a stronger mediating effect than perceived usefulness, highlighting the importance of trust in AI-generated information. This study contributes to the integration of Information Processing Theory (IPT) and Technology Acceptance Model (TAM) by positioning generative AI perception as a key mechanism in transforming digital presence into brand visibility in the AI-based search ecosystem.

Downloads

Download data is not yet available.

References

Adelakun, N. O. (2024). Exploring the Impact of Artificial Intelligence on Information Retrieval Systems. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4834942

Akashkumar, S., Dhanya, K., Sreevarshini, K., Thirunavukkarasu, D. T., & Sivagnanabharathi, D. . (2025). Digital Marketing Strategies Impact On Brand Visibility. International Journal on Science and Technology.

Brayadi, B., Supriadi, S., & Manora, H. (2022). Information Processing And Cognitive Theories Of Learning. Ej. https://doi.org/10.37092/ej.v4i2.363

Chen, M., Wang, X., Chen, K., & Koudas, N. (2025). Generative Engine Optimization: How to Dominate AI Search. CEUR Workshop Proceedings.

Dabbous, A., & Barakat, K. A. (2020). Bridging the online offline gap: Assessing the impact of brands’ social network content quality on brand awareness and purchase intention. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2019.101966

Fan, Y., Xie, X., Cai, Y., Chen, J., Ma, X., Li, X., Zhang, R., & Guo, J. (2022). Pre-training Methods in Information Retrieval. Foundations and Trends in Information Retrieval. https://doi.org/10.1561/1500000100

Fields, G., Campus, V., District, G., Pradesh, A., & Pradesh, A. (2025). Optimizing for the Artificial Intelligence Driven Search Era : An Integrated Framework for Search Engine Optimization , Generative Engine Optimization , and Answer Engine Optimization. 1–10. https://doi.org/10.55041/IJSREM53069

Gao, X. S., Currim, I. S., & Dewan, S. (2022). Validation of the information processing theory of consumer choice: evidence from travel search engine clickstream data. European Journal of Marketing. https://doi.org/10.1108/EJM-09-2021-0678

Giri, S. R., & Ghimire, S. K. (2020). Factors Affecting the Adoption of Digital Payment Systems. Journal of Innovations in Engineering Education. https://doi.org/10.3126/jiee.v3i1.34340

Guo, J., Fan, Y., Pang, L., Yang, L., Ai, Q., Zamani, H., Wu, C., Croft, W. B., & Cheng, X. (2020). A Deep Look into neural ranking models for information retrieval. Information Processing and Management. https://doi.org/10.1016/j.ipm.2019.102067

Guo, J., He, J., & Wu, X. (2024). Shopping trip recommendations: A novel deep learning-enhanced global planning approach. Decision Support Systems. https://doi.org/10.1016/j.dss.2024.114238

Hasan, R. (2025). ENHANCING MARKET COMPETITIVENESS THROUGH AI-POWERED SEO AND DIGITAL MARKETING STRATEGIES IN E-COMMERCE. ASRC Procedia: Global Perspectives in Science and Scholarship. https://doi.org/10.63125/31tpjc54

Hersh, W. (2024). Search still matters: Information retrieval in the era of generative AI. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocae014

Jaszus, K., & Hendijani, R. B. (2025). The Role of E-Commerce in Sustainable Development for Solo Travel: Insights from International Travelers in Bali. 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2025. https://doi.org/10.1109/IRASET64571.2025.11008024

Kannan, P. K., & Li, H. “Alice.” (2017). Digital marketing: A framework, review and research agenda. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2016.11.006

Keller, K. L. (1993). Conceptualizing, Measuring, and Managing Customer-Based Brand Equity. Journal of Marketing. https://doi.org/10.1177/002224299305700101

Kelly, S., Kaye, S. A., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics. https://doi.org/10.1016/j.tele.2022.101925

Li, K. (2023). Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model. Sustainability (Switzerland) . https://doi.org/10.3390/su15065221

Loh, E. (2023). ChatGPT and generative AI chatbots: challenges and opportunities for science, medicine and medical leaders. In BMJ Leader. https://doi.org/10.1136/leader-2023-000797

Malatji, W. R., van Eck, R., & Zuva, T. (2020). Understanding the usage, modifications, limitations and criticisms of technology acceptance model (TAM). Advances in Science, Technology and Engineering Systems. https://doi.org/10.25046/aj050612

Mammassis, C. (2025). The Role of Digital Marketing in Building Brand Awareness in the Modern Era. British Journal of Management and Marketing Studies. https://doi.org/10.52589/bjmms_xg92rnys

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An Integrative Model Of Organizational Trust. Academy of Management Review. https://doi.org/10.5465/amr.1995.9508080335

McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research. https://doi.org/10.1287/isre.13.3.334.81

Nalbant, K. G., & Aydin, S. (2023). Development and Transformation in Digital Marketing and Branding with Artificial Intelligence and Digital Technologies Dynamics in the Metaverse Universe. Journal of Metaverse. https://doi.org/10.57019/jmv.1148015

Nilesh Singh. (2025). Demystifying AI-Enhanced Search Systems: A Technical Deep Dive. Journal of Computer Science and Technology Studies. https://doi.org/10.32996/jcsts.2025.7.2.51

Ponzoa, J. M., Gómez, A., & Mas, J. M. (2023). EU27 and USA institutions in the digital ecosystem: Proposal for a digital presence measurement index. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2022.113354

Qasim, D., & Khalifeh, A. (2025). Implementing digital marketing using artificial intelligence. International Journal of Innovative Research and Scientific Studies. https://doi.org/10.53894/ijirss.v8i3.6993

Quintas-Mendes, A., & Paiva, A. (2023). Digital Presence and Online Identity among Digital Scholars: A Thematic Analysis. Social Sciences. https://doi.org/10.3390/socsci12070379

Rabby, F. (2025). Artificial Intelligence In Digital Marketing Influences Consumer Behaviour: A Review And Theoretical Foundation For Future Research. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5101851

Ramdani, A., & Fietroh, M. N. (2025). The Effect of Digital Marketing Strategies, Social Media, and Influencer Marketing on Brand Awareness. Journal of Educational Management Research. https://doi.org/10.61987/jemr.v4i5.1161

Schmitt, B. (2024). Consumer Information Processing and Decision-Making: Origins, Findings, Applications, and Future Directions. Journal of Consumer Research. https://doi.org/10.1093/jcr/ucae008

Segeda, O. (2025). Building Intelligent Search Systems: Advances in AI-Based Information Retrieval. The American Journal of Applied Sciences. https://doi.org/10.37547/tajas/volume07issue06-02

Sucharitha, G., Matta, A., Dwarakamai, K., & Tannmayee, B. (2020). Theory and Implications of Information Processing. In Emotion and Information Processing: A Practical approach. https://doi.org/10.1007/978-3-030-48849-9_4

Sudarma, I. K., Prabawa, D. G. A. P., & Suartama, I. K. (2022). The Application of Information Processing Theory to Design Digital Content in Learning Message Design Course. International Journal of Information and Education Technology. https://doi.org/10.18178/ijiet.2022.12.10.1718

Sugiyono. (2018). Metode penelitian bisnis / Sugiyono. In Journal of Business Research.

Taherdoost, H. (2018). A review of technology acceptance and adoption models and theories. Procedia Manufacturing. https://doi.org/10.1016/j.promfg.2018.03.137

Varsha, P. S., Akter, S., Kumar, A., Gochhait, S., & Patagundi, B. (2021). The Impact of Artificial Intelligence on Branding: A Bibliometric Analysis (1982-2019). In Journal of Global Information Management. https://doi.org/10.4018/JGIM.20210701.oa10

Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science. https://doi.org/10.1287/mnsc.46.2.186.11926