<![CDATA[This study examines the influence of variables within the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Threat Avoidance Theory (TTAT), integrated through an IS Dual Factor approach, on Generative AI usage intention among users in the Jabodetabek region, addressing a gap in prior research that has tended to examine enabling and inhibiting factors along separate trajectories despite users experiencing these dual pulls simultaneously in practice, and thereby demonstrating the relevance of the IS Dual Factor framework, which treats the two sets of determinants as distinct yet concurrently operating constructs. A quantitative survey method was employed involving 200 respondents domiciled in Jabodetabek who possess knowledge of and/or experience using Generative AI technology, with data collected through an online questionnaire from September 2025 to April 2026 and analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) via IBM AMOS, encompassing Confirmatory Factor Analysis and structural model testing. The results indicate that all six hypotheses were supported, with Performance Expectancy (β = 0.564) and Facilitating Conditions (β = 0.566) emerging as the strongest predictors, followed by Effort Expectancy (β = 0.379) and Social Influence (β = 0.243), which also exerted significant positive effects, while on the inhibiting side Perceived Threats (β = −0.277) significantly reduced usage intention and Perceived Avoidability (β = 0.287) functioned as a buffer attenuating this negative effect, collectively demonstrating that integrating UTAUT and TTAT within an IS Dual Factor framework yields a more comprehensive predictive model than unidimensional approaches for explaining Generative AI usage intention among Indonesia's urban population. ]]>
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