Artificial Intelligence Applications in Online Purchase Behaviour Research: A Bibliometric Analysis (2005–2025)

Abstract

Purpose: This paper seeks to provide thorough bibliometric review of Artificial Intelligence (AI) and online purchase behaviour (OPB) over the 2005-2025 period. The aim is to determine the major themes, trends, authors with great influence, and collaboration patterns around the world in terms of this dynamic emerging new academic discipline.

Design/Methodology/Approach: The study is carried out on 1,327 peer-reviewed articles and reviews extracted in the Web of Science Core Collection. A well-designed Boolean search strategy was used to locate pertinent literature between the years 2005 to 2025. Based on this data, the analysis of pattern keywords and co-occurrence was performed as well as the network structure and thematic clusters with the help of Biblioshiny and VOSviewer. The trends in publishing, authors who influence publications, relevant journals, and single-country contributions are some of the aspects that are reflected by the analysis. Co-word mapping was used to define thematic groupings and seven majorties were identified such as recommender systems and the sentiment-driven AI as well as ethical personalization and real-time predictive modeling.

Findings: The review revealed the appearance of the high rate of related OPB AI publications after 2018 with the main characters of recommender systems, sentiment analysis, and chatbots. IEEE Access and Expert Systems with Applications turned out to be dominant sources. China, USA and India top the list of research outputs, and Singapore and Germany have high average cites. The growing domains are generative AI, trust modelling, and recommendations personalisation.

Originality/Value: It is also an early specific bibliometric investigation of the use of AI in OPB. The paper defines an organized thematic map, identifies an untapped area of research such as explainable AI and real-time personalization, and acts as a research proposal to be followed by academia and practitioner planning in AI-based commerce.

Keywords: Online Purchase Behaviour, Artificial Intelligence, Bibliometric Analysis, Consumer Behaviour, VOSviewer, Biblioshiny.

Paper Type: Review of Literature