Aug 2026· International Conference on Computer Vision and Information Technology· Vol 14321, pp. 143210F - 143210F-14· 0 citations· 43 references
Engineering
TL;DR
This study presents an in-depth synthesis for researchers, policymakers, management educators, and industry practitioners by emphasizing the growing influence of artificial intelligence in redefining commercial practices and strategic orientations.
Abstract
Technological advancements have fundamentally altered digital commerce, with artificial intelligence (AI) undertaking an increasingly influential role. Despite the growing volume of academic work in this area, integrative and comprehensive review studies remain limited, particularly in bibliometric and cluster analysis to synthesize accumulated knowledge. This research aims to fill the literature gap by providing a detailed understanding of the emerging trends and patterns in AI's influence on digital commerce. Using the Scopus database, 3751 documents published between 2015 and 2025 were included, and the PRISMA framework was followed. Only documents classified as articles and conference papers in English were included, whereas document types such as books, reviews, editorials, letters, and notes were excluded to ensure consistency in the analysis. BiblioMagika and VOSviewer were employed to perform a detailed bibliometric analysis, covering trend and citation analyses, main contributors and institutions, as well as keyword co-occurrence examination. The findings indicated that the number of publications increased gradually from 76 in 2015 to 1006 in 2025. Interestingly, Robert D. Cairns from McGill University stands out as a key contributor, with seven publications in AI and digital commerce-related research. Among the listed institutions, Jadara University, Jordan, was recognized as the most prolific contributor, with eight publications, followed by Universitas Padjadjaran, Indonesia, with five publications. The keyword co-occurrence network analysis identified seven primary theme clusters, offering valuable insights into future research on AI's role in the digital commerce literature. This study presents an in-depth synthesis for researchers, policymakers, management educators, and industry practitioners by emphasizing the growing influence of artificial intelligence in redefining commercial practices and strategic orientations.
The aim of this research article is to review the existing literature on the impact of artificial intelligence (AI) on the international business (IB) phenomena. In particular, a comprehensive bibliometric method as well as a literature review is conducted, followed by focused future research directions for scholar...
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It is demonstrated that AI-HRM research is evolving in parallel with technological advances and the expanding integration of AI into HRM practices, and provides a foundation for researchers to identify emerging topics, underexplored areas, and future research opportunities in AI-enabled HRM.
R. Pratama, Edris Santoso, P. Sumantri et al.· Journal multidisciplinary sc...· 0 citations
A bibliometric analysis on Artificial Intelligence for Inclusive Education as an emerging research trend particularly in between the years of 2021–2025 suggests integration of AI technologies in education systems through providing valuable insights for educators, researchers and policymakers.
The results reveal a strong increasing trend in post-2019 publications due to the accelerated progress of natural language processing, machine learning, and generative systems such as ChatGPT, and sheds light on the cognitive framework and world process of AI-driven research communication and implications for future ac...
P. Tyagi, S. Sharma· International Journal of Inf...· 0 citations
A bibliometric analysis of studies dedicated to the application of AI technology and online CX, based on 257 Scopus-indexed works produced in 2015-2024 reveals a shift from effectiveness-based usage of AI to more customer-oriented applications.
Yarramsetti Sumanth, G. Somasekhar· Discover Artificial Intellig...· 0 citations
A five-step framework for implementing AI for tax compliance is suggested: risk concept formulation, data integration, model selection, governance and explainability, and continuous monitoring.
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