A Study on AI Recommendations and Impulse: Impact on Post-Purchase Emotions in Fashion E-Commerce

Abstract

Artificial intelligence (AI) in fashion e-commerce has drastically changed how consumers make decisions by offering highly tailored product recommendations. This study looks into how consumers' impulsive purchasing behaviour is affected by AI-powered personalised recommendations. It also looks at how this activity affects post-purchase evaluation outcomes, particularly satisfaction and cognitive dissonance. The study takes a quantitative method, employing a structured questionnaire to gather information from fashion e-commerce customers. It is based on the Stimulus–Organism–Response (S–O–R) theory. According to the research, AI-generated personalised recommendations serve as a powerful inducement that frequently results in impulsive purchases. The findings also show that impulsive purchases might have two effects in the post-purchase phase: either they cause dissonance because of unfulfilled expectations or they cause satisfaction because of a chance discovery. These observations add to the body of knowledge on AI in consumer behaviour and have applications for e-commerce platforms looking to maximise recommendation systems to minimise post-purchase regret and increase customer pleasure. The study highlights the necessity of designing AI with ethics in mind in order to strike a balance between persuasiveness and the welfare of consumers in the digital marketplace.