The Role of Algorithmic Anthropomorphism, Transparency, and Fairness in Shaping Consumer Purchase Intentions in E-Commerce

Artificial intelligence (AI) is often employed in various sectors of e-commerce. Conse-quently, it becomes necessary to identify the impact of various parameters of the algorithm on buyer behavior. This study aims to investigate the impact of algorithmic anthropomor-phism, algorithmic transparency and perceived algorithmic fairness on buyer purchase intentions. In addition, this study has endeavored to establish the role of Technology Ac-ceptance Model as a moderating variable. A structured questionnaire was dispersed among 384 online buyers via Qualtrics. The proposed model was tested using PROCESS macro (Hayes, 2022) for mediation and moderation analyses. The results reveal that: (1) algorithmic anthropomorphism positively affects both algorithmic transparency and per-ceived algorithmic fairness; (2) algorithmic transparency has a significant positive effect on both perceived fairness and purchase intention; (3) perceived algorithmic fairness me-diates the relationships between algorithmic anthropomorphism and purchase intention, as well as between algorithmic transparency and purchase intention; and (4) TAM posi-tively influences purchase intention, though its moderating effect on the anthropomor-phism–purchase intention link is only marginally significant. These findings offer theo-retical contributions to AI-driven consumer behavior research and practical implications for the design of algorithmic e-commerce systems.