With AI becoming ubiquitous in digital commerce, online fashion retailers increasingly use AI-powered personalization (AIP) to enhance consumer engagement. However, consumer responses and expectations regarding these technologies remain underspecified for fashion AIP, where shoppers evaluate output credibility, fit realism, and identity alignment in addition to utility/price. This study examines how exploratory value drivers (EVD) and personal value drivers (PVD) as benefits, and perceived complexity and trust deficit as sacrifices—synthesized into the overall shopping experience (SHX)—influence purchase intention and intention to recommend. A theoretical framework integrates the value-based adoption model (VAM) and trust theory to assess how consumers balance AIP’s benefits—such as convenience and engagement—against sacrifices, including privacy concerns and loss of autonomy. The study is operationalized through a structured survey, collecting 375 valid responses from shoppers who experienced AIP in online fashion stores, and analyzed using SEM. Results indicate that EVD and PVD (positive) and perceived complexity and trust deficit (negative) affect intentions with SHX mediating the effects of benefits and sacrifices. Perceived risk also mediates these relationships, with trust concerns negatively impacting purchase intent. Additionally, perceived complexity—interpreted as an interaction/interpretability burden—diminishes willingness to buy, emphasizing the need to refine personalization strategies. This study extends VAM and trust theory by demonstrating the psychological dimensions of AIP adoption. Findings provide insights for online fashion retailers to enhance AI-driven experiences by providing concise on-path explanations, clear data-use notices, and controls that let users steer curation—balancing predictive accuracy with consumer agency to foster trust, drive conversions, and strengthen loyalty.

This study explores the impact of demand-side usage of digital platforms on operational decision-making by supply-side firms. The positive impact of digital platforms on product sales is established in the literature. However, this study focuses on the perspective of supply-side firms, examining the effect of increasing reliance on digital platforms on supply-side firms’ decisions. The study shows that greater demand-side usage of online-to-offline (O2O) digital platforms is associated with more efficient operational decisions of supply-side firms. Benefits of leveraging O2O platforms include information transparency and resource pooling. The study further examines the extent to which benefits from participating in O2O digital platforms are affected by inter-firm relationships in which a supply-side firm is embedded. The study uses a panel data model to test hypotheses with data on China's movie theaters that join O2O platforms. It found that movie theaters with greater demand-side usage of O2O digital platforms see better resource utilization and product concentration. Furthermore, it shows that more vertically integrated firms can better reap the benefits from demand-side usage of digital platforms. In contrast, more horizontally integrated firms can less strategically leverage the benefits from demand-side usage of O2O platforms.