Unlocking the Impact of User Experience on AI-Powered Mobile Advertising Engagement

Yanqing Xia, Zijian Liu, Siqin Wang (), Chenxi Huang and Wenqiang Zhao
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Yanqing Xia: Pukyong University
Zijian Liu: Hanyang University
Siqin Wang: Hongik University
Chenxi Huang: Xinyang University
Wenqiang Zhao: Shenyang University of Technology

Journal of the Knowledge Economy, 2025, vol. 16, issue 1, No 168, 4818-4854

Abstract: Abstract This study ventures into the burgeoning domain of artificial intelligence (AI)–powered advertising within mobile applications, addressing the critical gap in understanding how user experiences influence information interaction behavior. Leveraging the technology acceptance Model (TAM) and the Fogg behavior model (FBM), our research scrutinizes eight determinants — perceived usefulness, privacy, authenticity, experiential value, perceived ease of use, motivation, capability, and triggers — to delineate their impact on user engagement with intelligent advertising. Employing a survey alongside structural equation model analysis, we unveil that these determinants unanimously foster information interaction behavior, with motivation and capability mediating the relationships between user experience factors and information exchange. The findings elucidate the multifaceted nature of user engagement in AI-powered mobile advertising, highlighting the indispensable role of a user-centric approach in crafting effective and engaging advertising strategies. This study advances the intelligent advertising discourse by underscoring the criticality of user experience factors and offers pragmatic insights for advertisers aiming to harness AI for more personalized and immersive ad experiences. By emphasizing the necessity of balancing technological advancements with user experience considerations, our research provides a blueprint for leveraging AI to revolutionize mobile advertising strategies, aligning with the knowledge economy’s focus on innovation, entrepreneurship, technology, and societal advancement.

Keywords: AI-powered advertising; User engagement; Mobile app interaction; Technology acceptance model; Fogg behavior model; Information processing; User experience; Digital marketing (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-02153-y

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