From learning to Informed decision-making: The role of recommender systems on e-commerce platforms : Exploring User-Recommender System-Mediated Interactions

Sammanfattning

Digitalization and the rise of e-commerce have led people to shift from purchasing products or services in traditional physical stores toward e-commerce platforms. E-commerce platforms offer a wide range of products and services, and the information can often be overwhelming for users. To reduce information overload, businesses have now adopted recommender systems that operate on artificial intelligence. Integrating these systems into e-commerce platforms has transformed the product search and evaluation process. The study aims to explore how users learn through interaction on e-commerce platforms mediated by recommender systems. Learning here goes beyond simple exposure to information and involves cognitive changes such as developing new understanding, comparing alternatives, refining preferences, and applying knowledge in future situations. A qualitative research approach was adopted to gain an in-depth understanding of users’ experiences with recommender systems. Semi-structured interviews were conducted with 20 participants who often use e-commerce platforms to purchase and have experienced product or service-related recommendations. The collected data were analysed using thematic analysis. The findings identified four interconnected themes that explain the learning processes within user-system interactions: Incidental learning, Exploratory learning, Reflective learning, and guided learning. The study also reveals that learning outcomes in recommender system-mediated environments vary depending on individual characteristics, personal needs, and contextual factors. The study proposed a framework for learning processes on e-commerce platforms mediated by recommender systems. The study contributes to the existing literature by extending the understanding of recommender systems beyond consumer behaviour and sales-oriented perspectives towards their role as digital learning environments. The findings provide practical implications for businesses in designing transparent, informative, and user-centred recommender systems that support meaningful learning experiences and informed decisions on e-commerce platforms.