AI-Based Recommendation and Pricing Systems in E-Commerce and Their Impact on Consumer Behaviour

Abstract

The e-commerce industry has revolutionized the way people shop, with consumers now being able to purchase goods and services online from anywhere in the world. With the rise of online shopping, companies have started incorporating artificial intelligence (AI) to enhance the online shopping experience for their customers. (Alduraxwish, et al. 2021) AI-powered recommendation systems and pricing strategies are two examples of how e-commerce companies are using AI to influence consumer behaviour. (Z, et al. 2017 AI-related recommendation systems provide specific and personalised recommendations to consumers based on their browsing and purchase history, while pricing strategies use algorithms to adjust prices in real-time based on market demand and consumer behaviour. These systems have been shown to increase sales, improve customer engagement, and enhance customer satisfaction in e-commerce. However, the effectiveness of these systems and how they influence consumer behaviour is still under-researched. (Kaptein and Parxinen 2015) Therefore, this study aims to explore the effectiveness of AI-powered recommendation systems and pricing strategies in e-commerce and how they influence consumer behaviour. The study will investigate the different types of AI powered recommendation systems and pricing strategies used in e-commerce and how effective they are in influencing consumer behaviour. Additionally, the study will examine the factors that influence the effectiveness of these systems in e-commerce, such as consumer demographics, shopping habits, and trust in AI.