<![CDATA[Artificial intelligence–driven personalization increasingly shapes consumers’ online shopping experiences, yet its effects may arise through competing evaluations of value and privacy risk. Drawing on the Stimulus–Organism–Response framework, this study examines the influence of AI algorithm personalization on purchase decisions, with perceived value and perceived privacy risk as mediating mechanisms. A quantitative approach was applied, and the proposed relationships were tested using Partial Least Squares–Structural Equation Modeling. The findings show that AI personalization positively influences purchase decisions, perceived value, and perceived privacy risk. Both mediators significantly affect purchase decisions and transmit the effect of personalization, although perceived value exerts the stronger mediating role. The positive association between privacy risk and purchase decisions also indicates a privacy paradox, whereby consumers remain willing to transact despite heightened privacy concerns. This study extends personalization research by integrating benefit- and risk-based evaluations within a single explanatory model. Managerially, the findings suggest that firms should combine relevant personalization with transparent data practices to strengthen consumer value and trust.]]>
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