The proliferation of AI-driven retail platforms in Indonesia has outpaced empirical understanding of how cultural factors shape their adoption and effectiveness. This study addresses a specific gap: existing hybrid TAM–SERVQUAL models treat cultural variables as contextual background rather than structural moderators, limiting their explanatory power in high-context, collectivist markets. Specifically, this research examines whether interpersonal trust, collectivism orientation, and relation-based communication preferences significantly moderate the relationships between AI-based marketing information systems and customer satisfaction, and whether these moderation effects differ between large retailers and micro, small, and medium enterprises (UMKM) in Indonesia. To fill this gap, we develop and formally validate the Culturally-Moderated AI Adoption Framework (CMAAF), which extends TAM and SERVQUAL beyond additive integration by formally specifying cultural boundary conditions that amplify or attenuate AI’s effect on satisfaction. Unlike prior hybrid models, CMAAF is validated here using confirmatory factor analysis (CFA) and structural equation modeling via SmartPLS 4.0 with a sample of 347 respondents across five major Indonesian cities. Reliability ranged from α = 0.782 to 0.891. Results confirm that AI personalization (β = 0.421), recommendation systems (β = 0.318), and chatbots (β = 0.267) significantly predict customer satisfaction (R² = 0.637), with cultural variables acting as significant structural moderators, particularly in the UMKM segment. These findings demonstrate that CMAAF provides a more precise and culture-sensitive predictive framework than existing hybrid models, with direct implications for AI deployment strategies in emerging economies.
Fordiana Ekawati, Emi Sita Eriana· bit-Tech· 0 citations
This study evaluates the feasibility of integrating Gemini AI to counteract declining student motivation driven by conventional teaching methodologies at Pamulang University, South Tangerang. Utilizing an integrated SWOT and TELOS (Technical, Economic, Legal, Operational, and Schedule) framework, the research analyzes empirical survey data from Information Systems students. The findings reveal that 97.6% of respondents belong to Generation Z, a demographic natively receptive to digital tools. Furthermore, 78.6% had independently adopted Gemini AI for academic purposes prior to institutional intervention, while 87.8% agree that diverse digital materials significantly enhance classroom interaction. The SWOT analysis highlights critical internal strengths, including heightened motivation and broader knowledge access, alongside interactive learning environments. Conversely, a severe internal weakness is the university's infrastructure, with 54.8% of students reporting unstable internet connectivity. While high independent adoption presents a strong external opportunity, the primary external threat stems from an overreliance on AI that could compromise critical thinking and analytical problem-solving skills. From a TELOS perspective, implementing Gemini AI is both economically and legally viable, aligning with Indonesian frameworks such as the Ministry of Communication Circular No. 9/2023 and Law No. 27/2022 on Personal Data Protection. Nevertheless, the institution's technical readiness falls below the required threshold and demands substantial enhancement. To ensure a responsible transition to AI-assisted education, this study recommends a phased strategy: upgrading IT infrastructure, providing regular AI literacy training for educators, and establishing structured faculty supervision protocols to mitigate student dependency.
Raihand Ramadhani Abdul Sayeed, Emi Sita Eriana, Afrizal Zein· bit-Tech· 0 citations
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