Interest-Based E-Commerce and Users’ Purchase Intention on Social Network Platforms

Autor: Hang Lee
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Access, Vol 12, Pp 87451-87466 (2024)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3417440
Popis: In the modern era of information overload, e-commerce platforms use recommendation systems to predict purchase behavior based on user interests and past actions. Initially limited to e-commerce websites, these systems now leverage the comprehensive data collection capabilities of social network platforms, giving rise to interest-based e-commerce. This study explores factors influencing purchase intentions within this context, using Instagram as an example and applying the Stimulus-Organism-Response (SOR) theory. Data from 313 Generation Z users reveal that interactions with other users and celebrities, along with visually appealing content, significantly enhance perceived enjoyment, which in turn increases purchase intentions. However, self-indulgence did not moderate this relationship. The study extends the SOR theory and provides practical insights for optimizing social media content and engagement strategies to boost purchase intentions, with discussions on implications, limitations, and future research directions.
Databáze: Directory of Open Access Journals