<![CDATA[In the context of ChatGPT as a shopping assistant in Indonesia, this research investigates the correlations between satisfaction and factors such as perceived utility, anthropomorphism, ease of use, and navigation, as well as the link between satisfaction and buy intention. Using the Technology Acceptance Model (TAM), the research takes into account functional perceptions in addition to conversational AI's human-like and interaction-related traits. The data were analysed using structural equation modelling (SEM) with AMOS from a quantitative, cross-sectional survey that was administered to 200 participants. The findings show that elements such as perceived utility, anthropomorphism, and navigation are positively and substantially linked to satisfaction. There is a positive correlation between perceived ease of use and satisfaction, however the link is not statistically significant (β = 0.135, p = 0.063). Having a positive and substantial association with purchase intention (β = 0.537, p < 0.001) constitutes satisfaction. It turns out that four out of five possibilities are correct. According to the results, in this particular sample, features connected to interactions and practical utility are linked to satisfaction, although simplicity of use by itself does not show any statistical significance. Caution is required due to the study's cross-sectional methodology and conflicting model-fit results, but it does expand the applicability of TAM to conversational shopping help in Indonesia.]]>
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