Enhancing Product Availability Perception in Small-Scale E-Commerce Through Consumer Behavior-Informed AI Predictions

The present study is trying to conduct a study on the impact of AI-based product availability systems on customer trust and loyalty on seasonal retail microenterprises. Based on the common attributes, the study uses structural equation modelling (SEM) on the data gathered on 300-400 customers who used AI to shop in seasonal retail chains and identify six latent variables that forecasting, communication, preparedness, stability, trust and loyalty. The analysis shows that the positive effect of AI-driven predictive analytics and open communication on the customer trust is high, and the readiness and site stability are the mediating variables that contribute to this effect. The factor of trust comes out as one of the predictors of consumer loyalty, affirming to the fact that reliability in the technological aspect of the availability management is a precursor to long-term dedication. Based on the literature on the service quality and use of AI as means of operational aid and impression-forming elements, the given work suggests that the retailers should combine predictive AI with customer-centered open communication channels to become more loyal and competitive in the seasonal markets.