The Impact of AI-Personalized Recommendations on Consumer Impulse Buying Behavior: The mediating role of Perceived Usefulness and Urgency to Buy

Abstract

AI recommendation has become an important factor to measure consumer impulse buying behavior over the past years. With increase in e-commerce platforms, AI technology now dominates the domain of understanding customers. The major concern is that the AI personalization systems are not well understood in terms of psychological and emotional influence on consumer choice, especially in emerging digital markets such as Pakistan. Most existing studies are directed at the enhancement of customer satisfaction, trust, or purchase intention, but very few of them explored its direct impact on the impulse buying decision. Therefore, this research study investigated the impact of AI personalized recommendation on impulse buying behavior through mediating role of psychological factors such as perceived usefulness and urgency to buy, with Accuracy as a sub-variable for AI personalized recommendation. The S-O-R model (stimulus-organism-response) such that the AI personalized recommendations as external Stimulus, mediators of PRU and URB as Organism and Impulse buying behavior as Response was used to support this research. Convenience sampling (N = 208) and self-administered structured questionnaires through Likert scale was used for data collection. The results showed insignificant direct relation between AI personalized recommendation and consumer impulse buying in the presence of mediators. However, there is a highly significant relation with mediation of URB (p-value = 0.000) and PRU (p-value = 0.0292). These results highlighted that PRU and URB shows full mediation on impulse buying and strengthens indirect impact, which means that AI recommendations impact consumers not merely through accuracy, but through how consumers feel; pressured, assisted or facilitated during online shopping process in the case of Pakistan’s online platforms.